CMSA

Big Data Conference 2021
2021-08-24 | Virtual
On August 24, 2021, the CMSA hosted our seventh annual Conference on Big Data. The Conference features many speakers from the Harvard community as well as scholars from across the globe, with talks focusing on computer science, statistics, math and physics, and economics.
The 2021 Big Data Conference took place virtually on Zoom.
Organizers:

Shing-Tung Yau, William Caspar Graustein Professor of Mathematics, Harvard University
Scott Duke Kominers, MBA Class of 1960 Associate Professor, Harvard Business
Horng-Tzer Yau, Professor of Mathematics, Harvard University
Sergiy Verstyuk, CMSA, Harvard University

Speakers:

Andrew Blumberg, University of Texas at Austin
Moran Koren, Harvard CMSA
Hima Lakkaraju, Harvard University
Katrina Ligett, The Hebrew University of Jerusalem

Time (ET; Boston time)
Speaker
Title/Abstract

9:00AM
Conference Organizers
Introduction and Welcome

9:10AM – 9:55AM
Andrew Blumberg, University of Texas at Austin
Title: Robustness and stability for multidimensional persistent homology
Abstract: A basic principle in topological data analysis is to study the shape of data by looking at multiscale homological invariants. The idea is to filter the data using a scale parameter that reflects feature size. However, for many data sets, it is very natural to consider multiple filtrations, for example coming from feature scale and density. A key question that arises is how such invariants behave with respect to noise and outliers. This talk will describe a framework for understanding those questions and explore open problems in the area.

10:00AM – 10:45AM
Katrina Ligett, The Hebrew University of Jerusalem
Title: Privacy as Stability, for Generalization
Abstract: Many data analysis pipelines are adaptive: the choice of which analysis to run next depends on the outcome of previous analyses. Common examples include variable selection for regression problems and hyper-parameter optimization in large-scale machine learning problems: in both cases, common practice involves repeatedly evaluating a series of models on the same dataset. Unfortunately, this kind of adaptive re-use of data invalidates many traditional methods of avoiding overfitting and false discovery, and has been blamed in part for the recent flood of non-reproducible findings in the empirical sciences. An exciting line of work beginning with Dwork et al. in 2015 establishes the first formal model and first algorithmic results providing a general approach to mitigating the harms of adaptivity, via a connection to the notion of differential privacy. In this talk, we’ll explore the notion of differential privacy and gain some understanding of how and why it provides protection against adaptivity-driven overfitting. Many interesting questions in this space remain open.
Joint work with: Christopher Jung (UPenn), Seth Neel (Harvard), Aaron Roth (UPenn), Saeed Sharifi-Malvajerdi (UPenn), and Moshe Shenfeld (HUJI). This talk will draw on work that appeared at NeurIPS 2019 and ITCS 2020

10:50AM – 11:35AM
Hima Lakkaraju, Harvard University
Title: Towards Reliable and Robust Model Explanations
Abstract: As machine learning black boxes are increasingly being deployed in domains such as healthcare and criminal justice, there is growing emphasis on building tools and techniques for explaining these black boxes in an interpretable manner. Such explanations are being leveraged by domain experts to diagnose systematic errors and underlying biases of black boxes. In this talk, I will present some of our recent research that sheds light on the vulnerabilities of popular post hoc explanation techniques such as LIME and SHAP, and also introduce novel methods to address some of these vulnerabilities. More specifically, I will first demonstrate that these methods are brittle, unstable, and are vulnerable to a variety of adversarial attacks. Then, I will discuss two solutions to address some of the vulnerabilities of these methods – (i) a framework based on adversarial training that is designed to make post hoc explanations more stable and robust to shifts in the underlying data; (ii) a Bayesian framework that captures the uncertainty associated with post hoc explanations and in turn allows us to generate explanations with user specified levels of confidences. I will conclude the talk by discussing results from real world datasets to both demonstrate the vulnerabilities in post hoc explanation techniques as well as the efficacy of our aforementioned solutions.

11:40AM – 12:25PM
Moran Koren, Harvard CMSA
Title: A Gatekeeper’s Conundrum
Abstract: Many selection processes contain a “gatekeeper”. The gatekeeper’s goal is to examine an applicant’s suitability to a proposed position before both parties endure substantial costs. Intuitively, the introduction of a gatekeeper should reduce selection costs as unlikely applicants are sifted out. However, we show that this is not always the case as the gatekeeper’s introduction inadvertently reduces the applicant’s expected costs and thus interferes with her self-selection. We study the conditions under which the gatekeeper’s presence improves the system’s efficiency and those conditions under which the gatekeeper’s presence induces inefficiency. Additionally, we show that the gatekeeper can sometimes improve selection correctness by behaving strategically (i.e., ignore her private information with some probability).

12:25PM
Conference Organizers
Closing Remarks

Math Science Lectures in Honor of Raoul Bott
2021-10-04 02:51 - 2021-10-05 02:51 (America/New_York) | CMSA, 20 Garden Street, Cambridge, MA, 02138, United States
On October 4th and October 5th, 2021, Harvard CMSA will host its annual Math Science Lectures in Honor of Raoul Bott. This year’s speaker will be Michael Freedman (Microsoft). The lectures will take place from 11:00am – 12:15pm (ET) on Zoom.
This will be the third annual lecture series held in honor of Raoul Bott.

Lecture 1
October 4th, 11:00am (Boston time)
Title: The Universe from a single Particle
Abstract: I will explore a toy model for our universe in which spontaneous symmetry breaking – acting on the level of operators (not states) – can produce the interacting physics we see about us from the simpler, single particle, quantum mechanics we study as undergraduates. Based on joint work with Modj Shokrian Zini, see arXiv:2011.05917 and arXiv:2108.12709.
Video

Lecture 2
October 5th, 11:00am (Boston time)
Title: Controlled Mather Thurston Theorems.
Abstract: The “c-principle” is a cousin of Gromov’s h-principle in which cobordism rather than homotopy is required to (canonically) solve a problem. We show that in certain well-known c-principle contexts only the mildest cobordisms, semi-s-cobordisms, are required. In physical applications, the extra topology (a perfect fundamental group) these cobordisms introduce could easily be hidden in the UV. This leads to a proposal to recast gauge theories such as EM and the standard model in terms of flat connections rather than curvature. See arXiv:2006.00374
Video

Math Science Lectures in Honor of Raoul Bott: Michael Freedman
2021-10-04 11:00 - 12:30 | Virtual
On October 4th and October 5th, 2021, Harvard CMSA hosted the annual Math Science Lectures in Honor of Raoul Bott. This year’s speaker was Michael Freedman (Microsoft). The lectures took place on Zoom.
This will be the third annual lecture series held in honor of Raoul Bott.

Lecture 1
October 4th, 11:00am (Boston time)
Title: The Universe from a single Particle
Abstract: I will explore a toy model for our universe in which spontaneous symmetry breaking – acting on the level of operators (not states) – can produce the interacting physics we see about us from the simpler, single particle, quantum mechanics we study as undergraduates. Based on joint work with Modj Shokrian Zini, see arXiv:2011.05917 and arXiv:2108.12709.
Video

Lecture 2
October 5th, 11:00am (Boston time)
Title: Controlled Mather Thurston Theorems.
Abstract: The “c-principle” is a cousin of Gromov’s h-principle in which cobordism rather than homotopy is required to (canonically) solve a problem. We show that in certain well-known c-principle contexts only the mildest cobordisms, semi-s-cobordisms, are required. In physical applications, the extra topology (a perfect fundamental group) these cobordisms introduce could easily be hidden in the UV. This leads to a proposal to recast gauge theories such as EM and the standard model in terms of flat connections rather than curvature. See arXiv:2006.00374
Video

CMSA Math-Science Literature Lecture - Karen Uhlenbeck
2021-12-09 09:30 - 14:30 | Virtual
Karen Uhlenbeck (Institute for Advanced Study)
Title: The Noether Theorems in Geometry: Then and Now
Abstract: The 1918 Noether theorems were a product of the general search for energy and momentum conservation in Einstein’s newly formulated theory of general relativity. Although widely referred to as the connection between symmetry and conservation laws, the theorems themselves are often not understood properly and hence have not been as widely used as they might be. In the first part of the talk, I outline a brief history of the theorems, explain a bit of the language, translate the first theorem into coordinate invariant language and give a few examples. I will mention only briefly their importance in physics and integrable systems. In the second part of the talk, I describe why they are still relevant in geometric analysis: how they underlie standard techniques and why George Daskalopoulos and I came to be interested in them for our investigation into the best Lipschitz maps of Bill Thurston. Some applications to integrals on a domain a hyperbolic surface leave open possibilities for applications to integrals on domains which are locally symmetric spaces of higher dimension. The talk finishes with an example or two from the literature.
Talk Chair: Laura DeMarco
VIDEO

General Relativity Program
2022-01-24 09:00 - 2022-05-21 17:00 | CMSA Room G10, CMSA, 20 Garden Street, Cambridge, MA, 02138, United States
During the Spring 2022 semester, the CMSA hosted a program on General Relativity.
This semester-long program included four minicourses, a conference, and a workshop.
General Relativity Mincourses: March–May, 2022
General Relativity Conference: April 4–8, 2022
General Relativity Workshop: May 2–5, 2022

Program Visitors

Dan Lee, CMSA/CUNY, 1/24/22 – 5/20/22
Stefan Czimek, Brown, 2/27/22 – 3/3/22
Lan-Hsuan Huang, University of Connecticut, 3/13/22 – 3/19/222, 3/21/22 – 3/25/22, 4/17 /22– 4/23/22
Mu-Tao Wang, Columbia, 3/21/22 – 3/25/22, 5/7/22 – 5/9/22
Po-Ning Chen, University of California, Riverside, 3/21/22 – 3/25/22, 5/7/22–5/9/22
Marnie Smith, Imperial College London, 3/27/22 – 4/11/22
Christopher Stith, University of Michigan, 3/27/22 – 4/23/22
Martin Taylor, Imperial College London, 3/27/22 – 4/11/22
Marcelo Disconzi, Vanderbilt, 5/9/22 – 5/21/22
Lydia Bieri, University of Michigan, 5/5/22 – 5/9/22

General Relativity Program Minicourses
2022-03-01 10:00 - 2022-05-17 13:00 | CMSA Room G10, CMSA, 20 Garden Street, Cambridge, MA, 02138, United States
Minicourses
General Relativity Program Minicourses

During the Spring 2022 semester, the CMSA hosted a program on General Relativity.
This semester-long program included four minicourses running in March, April, and May; a conference April 4–8, 2022; and a workshop from May 2–5, 2022.

Schedule
Speaker
Title
Abstract

March 1 – 3, 2022
10:00 am – 12:00 pm ET, each dayLocation: Hybrid. CMSA main seminar room, G-10.
Dr. Stefan Czimek
Characteristic Gluing for the Einstein Equations
Abstract: This course serves as an introduction to characteristic gluing for the Einstein equations (developed by the lecturer in collaboration with S. Aretakis and I. Rodnianski). First we set up and analyze the characteristic gluing problem along one outgoing null hypersurface. Then we turn to bifurcate characteristic gluing (i.e. gluing along two null hypersurfaces bifurcating from a spacelike 2-sphere) and show how to localize characteristic initial data. Subsequently we turn to applications for spacelike initial data. Specifically, we discuss in detail our alternative proofs of the celebrated Corvino-Schoen gluing to Kerr and the Carlotto-Schoen localization of spacelike initial data (with improved decay).

March 22 – 25, 2022
22nd & 23rd, 10:00 am – 11:30am ET
24th & 25th, 11:00 am – 12:30pm ETLocation: Hybrid. CMSA main seminar room, G-10.
Prof. Lan-Hsuan Huang
Existence of Static Metrics with Prescribed Bartnik Boundary Data
Abstract: The study of static Riemannian metrics arises naturally in general relativity and differential geometry. A static metric produces a special Einstein manifold, and it interconnects with scalar curvature deformation and gluing. The well-known Uniqueness Theorem of Static Black Holes says that an asymptotically flat, static metric with black hole boundary must belong to the Schwarzschild family. In the same vein, most efforts have been made to classify static metrics as known exact solutions. In contrast to the rigidity phenomena and classification efforts, Robert Bartnik proposed the Static Vacuum Extension Conjecture (originating from his other conjectures about quasi-local masses in the 80’s) that there is always a unique, asymptotically flat, static vacuum metric with quite arbitrarily prescribed Bartnik boundary data. In this course, I will discuss some recent progress confirming this conjecture for large classes of boundary data. The course is based on joint work with Zhongshan An, and the tentative plan is
1. The conjecture and an overview of the results
2. Static regular: a sufficient condition for existence and local uniqueness
3. Convex boundary, isometric embedding, and static regular
4. Perturbations of any hypersurface are static regular
Video on Youtube: March 22, 2022

March 29 – April 1, 2022 10:00am – 12:00pm ET, each day
Location: Hybrid. CMSA main seminar room, G-10.
Prof. Martin Taylor
The nonlinear stability of the Schwarzschild family of black holes
Abstract: I will present aspects of a theorem, joint with Mihalis Dafermos, Gustav Holzegel and Igor Rodnianski, on the full finite codimension nonlinear asymptotic stability of the Schwarzschild family of black holes.

April 19 & 21, 2022
10 am – 12 pm ET, each dayZoom only
Prof. Håkan Andréasson
Two topics for the Einstein-Vlasov system: Gravitational collapse and properties of static and stationary solutions.
Abstract: In these lectures I will discuss the Einstein-Vlasov system in the asymptotically flat case. I will focus on two topics; gravitational collapse and properties of static and stationary solutions. In the former case I will present results in the spherically symmetric case that give criteria on initial data which guarantee the formation of black holes in the evolution. I will also discuss the relation between gravitational collapse for the Einstein-Vlasov system and the Einstein-dust system. I will then discuss properties of static and stationary solutions in the spherically symmetric case and the axisymmetric case. In particular I will present a recent result on the existence of massless steady states surrounding a Schwarzschild black hole.
Video 4/19/2022
Video 4/22/2022

May 16 – 17, 2022
10:00 am – 1:00 pm ET, each dayLocation: Hybrid. CMSA main seminar room, G-10.
Prof. Marcelo Disconzi
A brief overview of recent developments in relativistic fluids
Abstract: In this series of lectures, we will discuss some recent developments in the field of relativistic fluids, considering both the motion of relativistic fluids in a fixed background or coupled to Einstein’s equations. The topics to be discussed will include: the relativistic free-boundary Euler equations with a physical vacuum boundary, a new formulation of the relativistic Euler equations tailored to applications to shock formation, and formulations of relativistic fluids with viscosity.
1. Set-up, review of standard results, physical motivation.
2. The relativistic Euler equations: null structures and the problem of shocks.
3. The free-boundary relativistic Euler equations with a physical vacuum boundary.
4. Relativistic viscous fluids.
Video 5/16/2022
Video 5/17/2022

General Relativity Conference
2022-04-04 09:30 - 2022-04-08 17:00 | CMSA, 20 Garden Street, Cambridge, MA, 02138, United States
Schedule | April 4–8, 2022
Monday, April 4, 2022

Time (ET)
Speaker
Title/Abstract

9:30 am–10:30 am
Pieter Blue, University of Edinburgh, UK
(virtual)
Title: Linear stability of the Kerr spacetime in the outgoing radiation gauge
Abstract: This talk will discuss a new gauge condition (i.e. coordinate condition) for the Einstein equation, the linearisation of the Einstein equation in this gauge, and the decay of solutions to the linearised Einstein equation around Kerr black holes in this gauge. The stability of the family of Kerr black holes under the evolution generated by the Einstein equation is a long-standing problem in mathematical relativity. In 1972, Teukolsky discovered equations governing certain components of the linearised curvature that are invariant under linearised gague transformations. In 1975, Chrzanowski introduced the “outgoing radiation gauge”, a condition on the linearised metric that allows for the construction of the linearised metric from the linearised curvature. In 2019, we proved decay for the metric constructed using Chrzanowski’s outgoing radiation gauge. Recently, using a flow along null geodesics, we have constructed a new gauge such that, in this gauge, the Einstein equation is well posed and such that the linearisation is Chrzanowski’s outgoing radiation gauge.
This is joint work with Lars Andersson, Thomas Backdahl, and Siyuan Ma.

10:30 am–11:30 am
Peter Hintz, ETH Zürich
(virtual)
Title: Mode stability and shallow quasinormal modes of Kerr-de Sitter
black holesAbstract: The Kerr-de Sitter metric describes a rotating black hole with mass $m$ and specific angular momentum $a$ in a universe, such as our own, with cosmological constant $Lambda>0$. I will explain a proof of mode stability for the scalar wave equation on Kerr-de Sitter spacetimes in the following setting: fixing $Lambda$ and the ratio $|a/m|<1$ (related to the subextremality of the black hole in question), mode stability holds for sufficiently small black hole mass $m$. We also obtain estimates for the location of quasinormal modes (resonances) $sigma$ in any fixed half space $Imsigma>-C$. Our results imply that solutions of the wave equation decay exponentially in time to constants, with an explicit exponential rate. The proof is based on careful uniform estimates for the spectral family in the singular limit $mto 0$ in which, depending on the scaling, the Kerr-de Sitter spacetime limits to a Kerr or the de Sitter spacetime.

11:30 am–12:30 pm
Lars Andersson, Albert Einstein Institute, Germany
(virtual)
Title: Gravitational instantons and special geometry
Abstract: Gravitational instantons are Ricci flat complete Riemannian 4-manifolds with at least quadratic curvature decay. In this talk, I will introduce some notions of special geometry, discuss known examples, and mention some open questions. The Chen-Teo gravitational instanton is an asymptotically flat, toric, Ricci flat family of metrics on $mathrm{CP}^2 setminus mathrm{S}^1$, that provides a counterexample to the classical Euclidean Black Hole Uniqueness conjecture. I will sketch a proof that the Chen-Teo Instanton is Hermitian and non-Kähler. Thus, all known examples of gravitational instantons are Hermitian. This talks is based on joint work with Steffen Aksteiner, cf. https://arxiv.org/abs/2112.11863.

12:30 pm–1:30 pm
break

1:30 pm–2:30 pm
Martin Taylor, Imperial College London
(virtual)
Title: The nonlinear stability of the Schwarzschild family of black holes
Abstract: I will present a theorem on the full finite codimension nonlinear asymptotic stability of the Schwarzschild family of black holes. The proof employs a double null gauge, is expressed entirely in physical space, and utilises the analysis of Dafermos–Holzegel–Rodnianski on the linear stability of the Schwarzschild family. This is joint work with M. Dafermos, G. Holzegel and I. Rodnianski.

2:30 pm–3:30 pm
Po-Ning Chen, University of California, Riverside
(virtual)
Title: Angular momentum in general relativity

Abstract: The definition of angular momentum in general relativity has been a subtle issue since the 1960s, due to the ‘supertranslation ambiguity’. In this talk, we will discuss how the mathematical theory of quasilocal mass and angular momentum leads to a new definition of angular momentum at null infinity that is free of any supertranslation ambiguity.This is based on joint work with Jordan Keller, Mu-Tao Wang, Ye-Kai Wang, and Shing-Tung Yau.

3:30 pm–4:00 pm
break

4:00 pm–5:00 pm
Dan Lee, Queens College (CUNY)
(hybrid: in person & virtual)
Title: Stability of the positive mass theorem
Abstract: We will discuss the problem of stability for the rigidity part of the Riemannian positive mass theorem, focusing on recent work with Kazaras and Khuri, in which we proved that if one assumes a lower Ricci curvature bound, then stability holds with respect to pointed Gromov-Hausdorff convergence.

Tuesday, April 5, 2022

Time (ET)
Speaker
Title/Abstract

9:30 am–10:30 am
Xinliang An, National University of Singapore
(virtual)
Title: Anisotropic dynamical horizons arising in gravitational collapse
Abstract: Black holes are predicted by Einstein’s theory of general relativity, and now we have ample observational evidence for their existence. However theoretically there are many unanswered questions about how black holes come into being and about the structures of their inner spacetime singularities. In this talk, we will present several results in these directions. First, in a joint work with Qing Han, with tools from scale-critical hyperbolic method and non-perturbative elliptic techniques, with anisotropic characteristic initial data we prove that: in the process of gravitational collapse, a smooth and spacelike apparent horizon (dynamical horizon) emerges from general (both isotropic and anisotropic) initial data. This result extends the 2008 Christodoulou’s monumental work and it connects to black hole thermodynamics along the apparent horizon. Second, in joint works with Dejan Gajic and Ruixiang Zhang, for the spherically symmetric Einstein-scalar field system, we derive precise blow-up rates for various geometric quantities along the inner spacelike singularities. These rates obey polynomial blow-up upper bounds; and when it is close to timelike infinity, these rates are not limited to discrete finite choices and they are related to the Price’s law along the event horizon. This indicates a new blow-up phenomenon, driven by a PDE mechanism, rather than an ODE mechanism. If time permits, some results on fluid dynamics will also be addressed.

10:30 am–11:30 am
Sergiu Klainerman, Princeton
(virtual)
Title: Nonlinear stability of slowly rotating Kerr solutions
Abstract: I will talk about the status of the stability of Kerr conjecture in General Relativity based on recent results obtained in collaboration with Jeremie Szeftel and Elena Giorgi.

11:30 am–12:30 pm
Siyuan Ma, Sorbonne University
(virtual)
Title: Sharp decay for Teukolsky master equation
Abstract: I will talk about joint work with L. Zhang on deriving the late time dynamics of the spin $s$ components that satisfy the Teukolsky master equation in Kerr spacetimes.

12:30 pm–1:30 pm
Break

1:30 pm–2:30 pm
Jonathan Luk, Stanford
(virtual)
Title: A tale of two tails
Abstract: Motivated by the strong cosmic censorship conjecture, we introduce a general method for understanding the late-time tail for solutions to wave equations on asymptotically flat spacetimes in odd spatial dimensions. A particular consequence of the method is a re-proof of Price’s law-type results, which concern the sharp decay rate of the late-time tails on stationary spacetimes. Moreover, we show that the late-time tails are in general different from the stationary case in the presence of dynamical and/or nonlinear perturbations. This is a joint work with Sung-Jin Oh (Berkeley).

2:30 pm–3:30 pm
Gary Horowitz, University of California Santa Barbara
(virtual)
Title: A new type of extremal black hole
Abstract: I describe a family of four-dimensional, asymptotically flat, charged black holes that develop (charged) scalar hair as one increases their charge at fixed mass. Surprisingly, the maximum charge for given mass is a nonsingular hairy black hole with a nondegenerate event horizon. Since the surface gravity is nonzero, if quantum matter is added, Hawking radiation does not appear to stop when this new extremal limit is reached. This raises the question of whether Hawking radiation will cause the black hole to turn into a naked singularity. I will argue that does not occur.

3:30 pm–4:00 pm
Break

4:00 pm–5:00 pm
Lydia Bieri, University of Michigan
(virtual)
Title: Gravitational radiation in general spacetimes
Abstract: Studies of gravitational waves have been devoted mostly to sources such as binary black hole mergers or neutron star mergers, or generally sources that are stationary outside of a compact set. These systems are described by asymptotically-flat manifolds solving the Einstein equations with sufficiently fast decay of the gravitational field towards Minkowski spacetime far away from the source. Waves from such sources have been recorded by the LIGO/VIRGO collaboration since 2015. In this talk, I will present new results on gravitational radiation for sources that are not stationary outside of a compact set, but whose gravitational fields decay more slowly towards infinity. A panorama of new gravitational effects opens up when delving deeper into these more general spacetimes. In particular, whereas the former sources produce memory effects that are finite and of purely electric parity, the latter in addition generate memory of magnetic type, and both types grow. These new effects emerge naturally from the Einstein equations both in the Einstein vacuum case and for neutrino radiation. The latter results are important for sources with extended neutrino halos.

Wednesday, April 6, 2022

Time (ET)
Speaker
Title/Abstract

9:30 am–10:30 am
Gerhard Huisken, Mathematisches Forschungsinstitut Oberwolfach
(virtual)
Title: Space-time versions of inverse mean curvature flow
Abstract: In order to extend the Penrose inequality from a time-symmetric setting to general asymptotically flat initial data sets several anisotropic generalisations of inverse mean curvature flow have been suggested that take the full space-time geometry into account. The lecture describes the properties of such flows and reports on recent joint work with Markus Wolff on inverse flow along the space-time mean curvature.

10:30 am–11:30 am
Carla Cederbaum, Universität Tübingen, Germany
(virtual)
Title: Coordinates are messy
Abstract: Asymptotically Euclidean initial data sets $(M,g,K)$ are characterized by the existence of asymptotic coordinates in which the Riemannian metric $g$ and second fundamental form $K$ decay to the Euclidean metric $delta$ and to $0$ suitably fast, respectively. Provided their matter densities satisfy suitable integrability conditions, they have well-defined (ADM-)energy, (ADM-)linear momentum, and (ADM-)mass. This was proven by Bartnik using harmonic coordinates. To study their (ADM-)angular momentum and (BORT-)center of mass, one usually assumes the existence of Regge—Teitelboim coordinates on the initial data set $(M,g,K)$ in question. We will give examples of asymptotically Euclidean initial data sets which do not possess any Regge—Teitelboim coordinates We will also show that harmonic coordinates can be used as a tool in checking whether a given asymptotically Euclidean initial data set possesses Regge—Teitelboim coordinates. This is joint work with Melanie Graf and Jan Metzger. We will also explain the consequences these findings have for the definition of the center of mass, relying on joint work with Nerz and with Sakovich.

11:30 am–12:30 pm
Stefanos Aretakis, University of Toronto
(virtual)
Title: Observational signatures for extremal black holes
Abstract: We will present results regarding the asymptotics of scalar perturbations on black hole backgrounds. We will then derive observational signatures for extremal black holes that are based on global or localized measurements on null infinity. This is based on joint work with Gajic-Angelopoulos and ongoing work with Khanna-Sabharwal.

12:30 pm–1:30 pm
Break

1:30 pm–2:30 pm
Jared Speck, Vanderbilt University
(virtual)
Title: The mathematical theory of shock waves in multi-dimensional relativistic and non-relativistic compressible Euler flow
Abstract: In the last two decades, there have been dramatic advances in the rigorous mathematical theory of shock waves in solutions to the relativistic Euler equations and their non-relativistic analog, the compressible Euler equations. A lot of the progress has relied on techniques that were developed to study Einstein’s equations. In this talk, I will provide an overview of the field and highlight some recent progress on problems without symmetry or irrotationality assumptions. I will focus on results that reveal various aspects of the structure of the maximal development of the data and the corresponding implications for the shock development problem, which is the problem of continuing the solution weakly after a shock. I will also describe various open problems, some of which are tied to the Einstein–Euler equations. Various aspects of this program are joint with L. Abbrescia, M. Disconzi, and J. Luk.

2:30 pm–3:30 pm
Lan-Hsuan Huang, University of Connecticut
(virtual)
Title: Null perfect fluids, improvability of dominant energy scalar, and Bartnik mass minimizers
Abstract: We introduce the concept of improvability of the dominant energy scalar, and we derive strong consequences of non-improvability. In particular, we prove that a non-improvable initial data set without local symmetries must sit inside a null perfect fluid spacetime carrying a global Killing vector field. We also show that the dominant energy scalar is always almost improvable in a precise sense. Using these main results, we provide a characterization of Bartnik mass minimizing initial data sets which makes substantial progress toward Bartnik’s stationary conjecture.
Along the way we observe that in dimensions greater than eight there exist pp-wave counterexamples (without the optimal decay rate for asymptotically flatness) to the equality case of the spacetime positive mass theorem. As a consequence, we find counterexamples to Bartnik’s stationary and strict positivity conjectures in those dimensions. This talk is based on joint work with Dan A. Lee.

3:30 pm–4:00 pm
Break

4:00 pm–5:00 pm
Demetre Kazaras, Duke University
(virtual)
Title: Comparison geometry for scalar curvature and spacetime harmonic functions
Abstract: Comparison theorems are the basis for our geometric understanding of Riemannian manifolds satisfying a given curvature condition. A remarkable example is the Gromov-Lawson toric band inequality, which bounds the distance between the two sides of a Riemannian torus-cross-interval with positive scalar curvature by a sharp constant inversely proportional to the scalar curvature’s minimum. We will give a new qualitative version of this and similar band-type inequalities in dimension 3 using the notion of spacetime harmonic functions, which recently played the lead role in our recent proof of the positive mass theorem. This is joint work with Sven Hirsch, Marcus Khuri, and Yiyue Zhang.

Thursday, April 7, 2022

Time (ET)
Speaker
Title/Abstract

9:30 am–10:30 am
Piotr Chrusciel, Universitat Wien
(virtual)
Title: Maskit gluing and hyperbolic mass
Abstract: “Maskit gluing” is a gluing construction for asymptotically locally hyperbolic (ALH) manifolds with negative cosmological constant. I will present a formula for the mass of Maskit-glued ALH manifolds and describe how it can be used to construct general relativistic initial data with negative mass.

10:30 am–11:30 am
Greg Galloway, University of Miami (virtual)
Title: Initial data rigidity and applications
Abstract: We present a result from our work with Michael Eichmair and Abraão Mendes concerning initial data rigidity results (CMP, 2021), and look at some consequences. In a note with Piotr Chruściel (CQG 2021), we showed how to use this result, together with arguments from Chruściel and Delay’s proof of the their hyperbolic PMT result, to obtain a hyperbolic PMT result with boundary. This will also be discussed.

11:30 am–12:30 pm
Pengzi Miao, University of Miami
(virtual)
Title: Some remarks on mass and quasi-local mass
Abstract: In the first part of this talk, I will describe how to detect the mass of asymptotically flat and asymptotically hyperbolic manifolds via large Riemannian polyhedra. In the second part, I will discuss an estimate of the Bartnik quasi-local mass and its geometric implications. This talk is based on several joint works with A. Piubello, and with H.C. Jang.

12:30 pm–1:30 pm
Break

1:30 pm–2:30 pm
Yakov Shlapentokh Rothman, Princeton
(hybrid: in person & virtual)
Title: Self-Similarity and Naked Singularities for the Einstein Vacuum Equations
Abstract: We will start with an introduction to the problem of constructing naked singularities for the Einstein vacuum equations, and then explain our discovery of a fundamentally new type of self-similarity and show how this allows us to construct solutions corresponding to a naked singularity. This is joint work with Igor Rodnianski.

2:30 pm–3:30 pm
Marcelo Disconzi, Vanderbilt University
(virtual)
Title: General-relativistic viscous fluids.
Abstract: The discovery of the quark-gluon plasma that forms in heavy-ion collision experiments provides a unique opportunity to study the properties of matter under extreme conditions, as the quark-gluon plasma is the hottest, smallest, and densest fluid known to humanity. Studying the quark-gluon plasma also provides a window into the earliest moments of the universe, since microseconds after the Big Bang the universe was filled with matter in the form of the quark-gluon plasma. For more than two decades, the community has intensely studied the quark-gluon plasma with the help of a rich interaction between experiments, theory, phenomenology, and numerical simulations. From these investigations, a coherent picture has emerged, indicating that the quark-gluon plasma behaves essentially like a relativistic liquid with viscosity. More recently, state-of-the-art numerical simulations strongly suggested that viscous and dissipative effects can also have non-negligible effects on gravitational waves produced by binary neutron star mergers. But despite the importance of viscous effects for the study of such systems, a robust and mathematically sound theory of relativistic fluids with viscosity is still lacking. This is due, in part, to difficulties to preserve causality upon the inclusion of viscous and dissipative effects into theories of relativistic fluids. In this talk, we will survey the history of the problem and report on a new approach to relativistic viscous fluids that addresses these issues.

3:30 pm–4:00 pm
Break

4:00 pm–5:00 pm
Maxime van de Moortel, Princeton
(hybrid: in person & virtual)
Title: Black holes: the inside story of gravitational collapse
Abstract: What is inside a dynamical black hole? While the local region near time-like infinity is understood for various models, the global structure of the black hole interior has largely remained unexplored.
These questions are deeply connected to the nature of singularities in General Relativity and celebrated problems such as Penrose’s Strong Cosmic Censorship Conjecture.
I will present my recent resolution of these problems in spherical gravitational collapse, based on the discovery of a novel phenomenon: the breakdown of weak singularities and the dynamical formation of a strong singularity.

Friday, April 8, 2022

Time (ET)
Speaker
Title/Abstract

9:30 am–10:30 am
Ye-Kai Wang, National Cheng Kun University, Taiwan
(virtual)
Title: Supertranslation invariance of angular momentum at null infinity in double null gauge
Abstract: This talk accompanies Po-Ning Chen’s talk on Monday with the results described in the double null gauge rather than Bondi-Sachs coordinates. Besides discussing
how Chen-Wang-Yau angular momentum resolves the supertranslation ambiguity, we also review the definition of angular momentum defined by A. Rizzi. The talk is based on the joint work with Po-Ning Chen, Jordan Keller, Mu-Tao Wang, and Shing-Tung Yau.

10:30 am–11:30 am
Zoe Wyatt, King’s College London
(virtual)
Title: Global Stability of Spacetimes with Supersymmetric Compactifications
Abstract: Spacetimes with compact directions which have special holonomy, such as Calabi-Yau spaces, play an important role in
supergravity and string theory. In this talk I will discuss a recent work with Lars Andersson, Pieter Blue and Shing-Tung Yau, where we show the global, nonlinear stability a spacetime which is a cartesian product of a high dimensional Minkowski space with a compact Ricci flat internal space with special holonomy. This stability result is related to a conjecture of Penrose concerning the validity of string theory. Our proof uses the intersection of methods for quasilinear wave and Klein-Gordon equations, and so towards the end of the talk I will also comment more generally on coupled wave–Klein-Gordon equations.

11:30 am–12:30 pm
Elena Giorgi, Columbia University
(hybrid: in person & virtual)
Title: The stability of charged black holes
Abstract: Black hole solutions in General Relativity are parametrized by their mass, spin and charge. In this talk, I will motivate why the charge of black holes adds interesting dynamics to solutions of the Einstein equation thanks to the interaction between gravitational and electromagnetic radiation. Such radiations are solutions of a system of coupled wave equations with a symmetric structure which allows to define a combined energy-momentum tensor for the system. Finally, I will show how this physical-space approach is resolutive in the most general case of Kerr-Newman black hole, where the interaction between the radiations prevents the separability in modes.

12:30 pm–1:30 pm
Break

1:30 pm–2:30 pm
Marcus Khuri, Stony Brook University
(virtual)
Title: The mass-angular momentum inequality for multiple black holes

Abstract: Consider a complete 3-dimensional initial data set for the Einstein equations which has multiple asymptotically flat or asymptotically cylindrical ends. If it is simply connected, axisymmetric, maximal, and satisfies the appropriate energy condition then the ADM mass of any of the asymptotically flat ends is bounded below by the square root of the total angular momentum. This generalizes previous work of Dain, Chrusciel-Li-Weinstein, and Schoen-Zhou which treated either the single black hole case or the multiple black hole case without an explicit lower bound. The proof relies on an analysis of the asymptotics of singular harmonic maps from
R^3 Gamma –>H^2 where Gamma is a coordinate axis. This is joint work with Q. Han, G. Weinstein, and J. Xiong.

2:30 pm–3:30 pm
Martin Lesourd, Harvard
(hybrid: in person & virtual)
Title: A Snippet on Mass and the Topology and Geometry of Positive Scalar Curvature
Abstract: I will talk about a small corner of the study of Positive Scalar Curvature (PSC) and questions which are most closely related to the Positive Mass Theorem. The classic questions are ”which topologies allow for PSC?” and ”what is the geometry of manifolds with PSC?”. This is based on joint work with Prof. S-T. Yau, Prof. D. A. Lee, and R. Unger.

3:30 pm–4:00 pm
Break

4:00 pm–5:00 pm
Georgios Moschidis, Princeton
(virtual)
Title: Weak turbulence for the Einstein–scalar field system.
Abstract: In the presence of confinement, the Einstein field equations are expected to exhibit turbulent dynamics. In the presence of a negative cosmological constant, the AdS instability conjecture claims the existence of arbitrarily small perturbations to the initial data of Anti-de Sitter spacetime which, under evolution by the vacuum Einstein equations with reflecting boundary conditions at conformal infinity, lead to the formation of black holes after sufficiently long time.
In this talk, I will present a rigorous proof of the AdS instability conjecture in the setting of the spherically symmetric Einstein-scalar field system. The construction of the unstable initial data will require carefully designing a family of initial configurations of localized matter beams and estimating the exchange of energy taking place between interacting beams over long periods of time, as well as estimating the decoherence rate of those beams.

Second Annual Yip Lecture: Extraterrestrial Life
2022-04-04 19:00 - 20:00 | Harvard Science Center, 1 Oxford Street, Cambridge, MA, 02138
Harvard CMSA hosted the second annual Yip Lecture on April 4, 2022.
The Yip Lecture takes place thanks to the support of Dr. Shing-Yiu Yip.
This year’s speaker was Avi Loeb (Harvard).

Extraterrestrial Life
Abstract: Are we alone? It would be arrogant to think that we are, given that a quarter of all stars host a habitable Earth-size planet. Upcoming searches will aim to detect markers of life in the atmospheres of planets outside the Solar System. We also have unprecedented technologies to detect signs of intelligent civilizations through industrial pollution of planetary atmospheres, space archaeology of debris from dead civilizations or artifacts such as photovoltaic cells that are used to re-distribute light and heat on the surface of a planet or giant megastructures. Our own civilization is starting to explore interstellar travel. Essential information may also arrive as a “message in a bottle”, implying that we should examine carefully any unusual object that arrives to our vicinity from outside the Solar System, such as `Oumuamua.

Abraham (Avi) Loeb is the Frank B. Baird, Jr., Professor of Science at Harvard University and a bestselling author (in lists of the New York Times, Wall Street Journal, Publishers Weekly, Die Zeit, Der Spiegel, L’Express and more). He received a PhD in Physics from the Hebrew University of Jerusalem in Israel at age 24 (1980–1986), led the first international project supported by the Strategic Defense Initiative (1983–1988), and was subsequently a long-term member of the Institute for Advanced Study at Princeton (1988–1993). Loeb has written 8 books, including most recently, Extraterrestrial (Houghton Mifflin Harcourt, 2021), and nearly a thousand papers (with an h-index of 118) on a wide range of topics, including black holes, the first stars, the search for extraterrestrial life, and the future of the Universe. Loeb is the head of the Galileo Project in search for extraterrestrial intelligence, the Director of the Institute for Theory and Computation (2007–present) within the Harvard-Smithsonian Center for Astrophysics, and also serves as the Head of the Galileo Project (2021–present). He had been the longest serving Chair of Harvard’s Department of Astronomy (2011–2020) and the Founding Director of Harvard’s Black Hole Initiative (2016–2021). He is an elected fellow of the American Academy of Arts & Sciences, the American Physical Society, and the International Academy of Astronautics. Loeb is a former member of the President’s Council of Advisors on Science and Technology (PCAST) at the White House, a former chair of the Board on Physics and Astronomy of the National Academies (2018–2021) and a current member of the Advisory Board for “Einstein: Visualize the Impossible” of the Hebrew University. He also chairs the Advisory Committee for the Breakthrough Starshot Initiative (2016–present) and serves as the Science Theory Director for all Initiatives of the Breakthrough Prize Foundation. In 2012, TIME magazine selected Loeb as one of the 25 most influential people in space and in 2020 Loeb was selected among the 14 most inspiring Israelis of the last decade.
Click here for Loeb’s commentaries on innovation and diversity.
Website: https://www.cfa.harvard.edu/~loeb/
See the Harvard Gazette article featuring Avi Loeb: “Oh, if I could talk to the aliens” published March 8, 2022.
Prof. Loeb’s books:
Extraterrestrial: The First Sign of Intelligent Life Beyond Earth (2021)
Life in the Cosmos: From Biosignatures to Technosignatures (2021)
Avil Loeb is the head of the Galileo Project at Harvard.

The previous Yip Lecture featured Peter Galison (Harvard), who spoke on the EHT’s hunt for an objective image of a black hole.

Workshop on Machine Learning and Mathematical Conjecture
2022-04-15 09:00 - 13:00 | CMSA Room G10, CMSA, 20 Garden Street, Cambridge, MA, 02138, United States
On April 15, 2022, the CMSA will hold a one-day workshop, Machine Learning and Mathematical Conjecture, related to the New Technologies in Mathematics Seminar Series.
Location: Room G10, 20 Garden Street, Cambridge, MA 02138.
Organizers: Michael R. Douglas (CMSA/Stony Brook/IAIFI) and Peter Chin (CMSA/BU).
Machine learning has driven many exciting recent scientific advances. It has enabled progress on long-standing challenges such as protein folding, and it has helped mathematicians and mathematical physicists create new conjectures and theorems in knot theory, algebraic geometry, and representation theory.
At this workshop, we will bring together mathematicians, theoretical physicists, and machine learning researchers to review the state of the art in machine learning, discuss how ML results can be used to inspire, test and refine precise conjectures, and identify mathematical questions which may be suitable for this approach.
Speakers:

James Halverson, Northeastern University Dept. of Physics and IAIFI
Fabian Ruehle, Northeastern University Dept. of Physics and Mathematics and IAIFI
Andrew Sutherland, MIT Department of Mathematics

CMSA/Tsinghua Math-Science Literature Lecture: Three Introductory Lectures on Game Theory for Mathematicians: Game Theory Basics and Classical Existence Theorems
2022-04-18 09:30 - 11:00 | Virtual
Eric Maskin (Harvard University) Three Introductory Lectures on Game Theory for Mathematicians
April 18, 2022 | 9:30 – 11:00 am ET
Title: Game Theory Basics and Classical Existence Theorems
Abstract: Games in extensive and normal form. Equilibrium existence theorems by Nash, von Neumann, and Zermelo
Talk chairs: Scott Kominers, Sergiy Verstyuk
SLIDES | VIDEO

CMSA/Tsinghua Math-Science Literature Lecture: Three Introductory Lectures on Game Theory for Mathematicians: Mechanism Design
2022-04-20 09:30 - 11:00 | Virtual
Eric Maskin (Harvard University) Three Introductory Lectures on Game Theory for Mathematicians
April 20, 2022 | 9:30 – 11:00 am ET
Title: Mechanism Design
Abstract: Given a social goal, under what circumstances can we design a game to achieve that goal?
Talk chairs: Scott Kominers, Sergiy Verstyuk
SLIDES | VIDEO

CMSA/Tsinghua Math-Science Literature Lecture: Three Introductory Lectures on Game Theory for Mathematicians: Auction Theory
2022-04-22 09:30 - 23:00 | Virtual
Eric Maskin (Harvard University) Three Introductory Lectures on Game Theory for Mathematicians
April 22, 2022 | 9:30 – 11:00 am ET
Title: Auction Theory
Abstract: Equivalences among four standard auctions: the high-bid auction (the high bidder wins and pays her bid); the second-bid auction (the high bidder wins and pays the second-highest bid); the Dutch auction (the auctioneer lowers the price successively until some bidder is willing to pay); and the English auction (bidders raise their bids successively until no one wants to bid higher).
Talk chairs: Scott Kominers, Sergiy Verstyuk
SLIDES | VIDEO Answers to Questions from Talks 2 and 3

Workshop on Nonlinear Algebra and Combinatorics from Physics
2022-04-27 09:00 - 2022-04-29 17:00 | CMSA, 20 Garden Street, Cambridge, MA, 02138, United States
On April 27–29, 2022, the CMSA hosted a workshop on Nonlinear Algebra and Combinatorics.
Organizers: Bernd Sturmfels (MPI Leipzig) and Lauren Williams (Harvard).
In recent years, ideas from integrable systems and scattering amplitudes have led to advances in nonlinear algebra and combinatorics. In this short workshop, aimed at younger participants in the field, we will explore some of the interactions between the above topics.
Speakers:

Federico Ardila (San Francisco State)
Nima Arkani-Hamed (IAS)
Madeline Brandt (Brown)
Nick Early (Max Planck Institute)
Chris Eur (Harvard)
Claudia Fevola (Max Planck Institute)
Christian Gaetz (Harvard)
Yuji Kodama (Ohio State University)
Yelena Mandelshtam (Berkeley)
Sebastian Mizera (IAS)
Matteo Parisi (Harvard CMSA)
Emma Previato (Boston University)
Anna Seigal (Harvard)
Melissa Sherman-Bennett (University of Michigan)
Simon Telen (Max Planck Institute)
Charles Wang (Harvard)

Schedule
Wednesday, April 27, 2022

9:30 am–10:30 am
Federico Ardila
Title: Nonlinear spaces from linear spaces
Abstract: Matroid theory provides a combinatorial model for linearity, but it plays useful roles beyond linearity. In the classical setup, a linear subspace V of an n-dimensional vector space gives rise to a matroid M(V) on {1,…,n}. However, the matroid M(V) also knows about some nonlinear geometric spaces related to V. Conversely, those nonlinear spaces teach us things we didn’t know about matroids. My talk will discuss some examples.

10:30 am–11:00 am
COFFEE BREAK

11:00 am–11:45 am
Chris Eur
Title: Tautological classes of matroids
Abstract: Algebraic geometry has furnished fruitful tools for studying matroids, which are combinatorial abstractions of hyperplane arrangements. We first survey some recent developments, pointing out how these developments remained partially disjoint. We then introduce certain vector bundles (K-classes) on permutohedral varieties, which we call “tautological bundles (classes)” of matroids, as a new framework that unifies, recovers, and extends these recent developments. Our framework leads to new questions that further probe the boundary between combinatorics and geometry. Joint work with Andrew Berget, Hunter Spink, and Dennis Tseng.

11:45 am–2:00 pm
LUNCH BREAK

2:00 pm–2:45 pm
Nick Early
Title: Biadjoint Scalars and Associahedra from Residues of Generalized Amplitudes
Abstract: The associahedron is known to encapsulate physical properties such as the notion of tree-level factorization for one of the simplest Quantum Field Theories, the biadjoint scalar, which has only cubic interactions. I will discuss novel instances of the associahedron and the biadjoint scalar in a class of generalized amplitudes, discovered by Cachazo, Early, Guevara and Mizera, by taking certain limits thereof. This connection leads to a simple proof of a new realization of the associahedron involving a Minkowski sum of certain positroid polytopes in the second hypersimplex.

2:45 pm–3:30 pm
Anna Seigal
Title: Invariant theory for maximum likelihood estimation
Abstract: I will talk about work to uncover connections between invariant theory and maximum likelihood estimation. I will describe how norm minimization over a torus orbit is equivalent to maximum likelihood estimation in log-linear models. We will see the role played by polytopes and discuss connections to scaling algorithms. Based on joint work with Carlos Améndola, Kathlén Kohn, and Philipp Reichenbach.

3:30 pm–4:00 pm
COFFEE BREAK

4:00 pm–4:45 pm
Matteo Parisi
Title: Amplituhedra, Scattering Amplitudes, and Triangulations
Abstract: In this talk I will discuss about Amplituhedra – generalizations of polytopes inside the Grassmannian – introduced by physicists to encode interactions of elementary particles in certain Quantum Field Theories. In particular, I will explain how the problem of finding triangulations of Amplituhedra is connected to computing scattering amplitudes of N=4 super Yang-Mills theory.
Triangulations of polygons are encoded in the associahedron, studied by Stasheff in the sixties; in the case of polytopes, triangulations are captured by secondary polytopes, constructed by Gelfand et al. in the nineties. Whereas a “secondary” geometry describing triangulations of Amplituhedra is still not known, and we pave the way for such studies. I will discuss how the combinatorics of triangulations interplays with T-duality from String Theory, in connection with the Momentum Amplituhedron. A generalization of T-duality led us to discover a striking duality between Amplituhedra of “m=2” type and a seemingly unrelated object – the Hypersimplex. The latter is a polytope which appears in many contexts, from matroid theory to tropical geometry.
Based on joint works with Lauren Williams, Melissa Sherman-Bennett, Tomasz Lukowski.

4:45 pm–5:30 pm
Melissa Sherman-Bennett
Title: The hypersimplex and the m=2 amplituhedron
Abstract: In this talk, I’ll continue where Matteo left off. I’ll give some more details about the curious correspondence between the m=2 amplituhedron, a 2k-dimensional subset of Gr(k, k+2), and the hypersimplex, an (n-1)-dimensional polytope in R^n. The amplituhedron and hypersimplex are both images of the totally nonnegative Grassmannian under some map (the amplituhedron map and the moment map, respectively), but are different dimensions and live in very different ambient spaces. I’ll talk about joint work with Matteo Parisi and Lauren Williams in which we give a bijection between decompositions of the amplituhedron and decompositions of the hypersimplex (originally conjectured by Lukowski–Parisi–Williams). The hypersimplex decompositions are closely related to matroidal subdivisions. Along the way, we prove a nice description of the m=2 amplituhedron conjectured by Arkani-Hamed–Thomas–Trnka and give a new decomposition of the m=2 amplituhedron into Eulerian-number-many chambers, inspired by an analogous triangulation of the hypersimplex into Eulerian-number-many simplices.

Thursday, April 28, 2022

9:30 am–10:30 am
Claudia Fevola
Title: Nonlinear Algebra meets Feynman integrals
Abstract: Feynman integrals play a central role in particle physics in the theory of scattering amplitudes. They form a finite-dimensional vector space and the elements of a basis are named “master integrals” in the physics literature. The number of master integrals has been interpreted in different ways: it equals the dimension of a twisted de Rham cohomology group, the Euler characteristic of a very affine variety, and the holonomic rank of a D-module. In this talk, we are interested in a more general family of integrals that contains Feynman integrals as a special case. We explore this setting using tools coming from nonlinear algebra. This is an ongoing project with Daniele Agostini, Anna-Laura Sattelberger, and Simon Telen.

10:30 am–11:00 am
COFFEE BREAK

11:00 am–11:45 am
Simon Telen
Title: Landau discriminants
Abstract: The Landau discriminant is a projective variety containing kinematic parameters for which a Feynman integral can have singularities. We present a definition and geometric properties. We discuss how to compute Landau discriminants using symbolic and numerical methods. Our methods can be used, for instance, to compute the Landau discriminant of the pentabox diagram, which is a degree 12 hypersurface in 6-space. This is joint work with Sebastian Mizera.

11:45 am–2:00 pm
LUNCH BREAK

2:00 pm–2:45 pm
Christian Gaetz
Title: 1-skeleton posets of Bruhat interval polytopes
Abstract: Bruhat interval polytopes are a well-studied class of generalized permutohedra which arise as moment map images of various toric varieties and totally positive spaces in the flag variety. I will describe work in progress in which I study the 1-skeleta of these polytopes, viewed as posets interpolating between weak order and Bruhat order. In many cases these posets are lattices and the polytopes, despite not being simple, have interesting h-vectors. In a special case, work of Williams shows that Bruhat interval polytopes are isomorphic to bridge polytopes, so that chains in the 1-skeleton poset correspond to BCFW-bridge decompositions of plabic graphs.

2:45 pm–3:30 pm
Madeleine Brandt
Title: Top Weight Cohomology of $A_g$
Abstract: I will discuss a recent project in computing the top weight cohomology of the moduli space $A_g$ of principally polarized abelian varieties of dimension $g$ for small values of $g$. This piece of the cohomology is controlled by the combinatorics of the boundary strata of a compactification of $A_g$. Thus, it can be computed combinatorially. This is joint work with Juliette Bruce, Melody Chan, Margarida Melo, Gwyneth Moreland, and Corey Wolfe.

3:30 pm–4:00 pm
COFFEE BREAK

4:00 pm–5:00 pm
Emma Previato
Title: Sigma function on curves with non-symmetric semigroup
Abstract: We start with an overview of the correspondence between spectral curves and commutative rings of differential operators, integrable hierarchies of non-linear PDEs and Jacobian vector fields. The coefficients of the operators can be written explicitly in terms of the Kleinian sigma function: Weierstrass’ sigma function was generalized to genus greater than one by Klein, and is a ubiquitous tool in integrability. The most accessible case is the sigma function of telescopic curves. In joint work with J. Komeda and S. Matsutani, we construct a curve with non-symmetric Weierstrass semigroup (equivalently, Young tableau), consequently non-telescopic, and its sigma function. We conclude with possible applications to commutative rings of differential operators.

6:00 pm

Dinner Banquet, Gran Gusto Trattoria

Friday, April 29, 2022

9:00 am–10:00 am
Yuji Kodama
Title: KP solitons and algebraic curves
Abstract: It is well-known that soliton solutions of the KdV hierarchy are obtained by singular limits of hyper-elliptic curves. However, there is no general results for soliton solutions of the KP hierarchy, KP solitons. In this talk, I will show that some of the KP solitons are related to the singular space curves associated with certain class of numerical semigroups.

10:00 am–10:30 am
COFFEE BREAK

10:30 am–11:15 am
Yelena Mandelshtam
Title: Curves, degenerations, and Hirota varieties
Abstract: The Kadomtsev-Petviashvili (KP) equation is a differential equation whose study yields interesting connections between integrable systems and algebraic geometry. In this talk I will discuss solutions to the KP equation whose underlying algebraic curves undergo tropical degenerations. In these cases, Riemann’s theta function becomes a finite exponential sum that is supported on a Delaunay polytope. I will introduce the Hirota variety which parametrizes all KP solutions arising from such a sum. I will then discuss a special case, studying the Hirota variety of a rational nodal curve. Of particular interest is an irreducible subvariety that is the image of a parameterization map. Proving that this is a component of the Hirota variety entails solving a weak Schottky problem for rational nodal curves. This talk is based on joint work with Daniele Agostini, Claudia Fevola, and Bernd Sturmfels.

11:15 am–12:00 pm
Charles Wang
Title: Differential Algebra of Commuting Operators
Abstract: In this talk, we will give an overview of the problem of finding the centralizer of a fixed differential operator in a ring of differential operators, along with connections to integrable hierarchies and soliton solutions to e.g. the KdV or KP equations. Given these interesting connections, it is important to be able to compute centralizers of differential operators, and we discuss how to use techniques from differential algebra to approach this question, as well as how having these computational tools can help in understanding the structure of soliton solutions to these equations.

12:00 pm–2:00 pm
LUNCH BREAK

2:00 pm–3:00 pm
Sebastian Mizera
Title: Feynman Polytopes
Abstract: I will give an introduction to a class of polytopes that recently emerged in the study of scattering amplitudes in quantum field theory.

3:00 pm–3:30 pm
COFFEE BREAK

3:30 pm–4:30 pm
Nima Arkani-Hamed
Title: Spacetime, Quantum Mechanics and Combinatorial Geometries at Infinity

General Relativity Workshop
2022-05-02 09:00 - 2022-05-05 17:00 | CMSA, 20 Garden Street, Cambridge, MA, 02138, United States
General Relativity Workshop on scalar curvature, minimal surfaces, and initial data sets
Dates: May 2–5, 2022
Location: Room G10, CMSA, 20 Garden Street, Cambridge MA 02138 and via Zoom webinar.
Advanced registration for in-person components is required.
Organizers: Dan Lee (CMSA/CUNY), Martin Lesourd (CMSA/BHI), and Lan-Hsuan Huang (University of Connecticut).
Speakers:

Zhongshan An, University of Connecticut
Paula Burkhardt-Guim, NYU
Hyun Chul Jang, University of Miami
Chao Li, NYU
Christos Mantoulidis, Rice University
Robin Neumayer, Carnegie Mellon University
Andre Neves, University of Chicago
Tristan Ozuch, MIT
Annachiara Piubello, University of Miami
Antoine Song, UC Berkeley
Tin-Yau Tsang, UC Irvine
Ryan Unger, Princeton
Zhizhang Xie, Texas A & M
Xin Zhou, Cornell University
Jonathan Zhu, Princeton University

Schedule
Monday, May 2, 2022

9:30–10:30 am
Hyun Chul Jang
Title: Mass rigidity for asymptotically locally hyperbolic manifolds with boundary
Abstract: Asymptotically locally hyperbolic (ALH) manifolds are a class of manifolds whose sectional curvature converges to −1 at infinity. If a given ALH manifold is asymptotic to a static reference manifold, the Wang-Chruściel-Herzlich mass integrals are well-defined, which is a geometric invariant that essentially measure the difference from the reference manifold. In this talk, I will present the result that an ALH manifold which minimize the mass integrals admits a static potential. To show this, we proved the scalar curvature map is locally surjective when it is defined on (1) the space of ALH metrics that coincide exponentially toward the boundary or (2) the space of ALH metrics with arbitrarily prescribed nearby Bartnik boundary data. And then, we establish the rigidity of the known positive mass theorems by studying the static uniqueness. This talk is based on joint work with L.-H. Huang.

10:40–11:40 am
Annachiara Piubello
Title: Estimates on the Bartnik mass and their geometric implications.
Abstract: In this talk, we will discuss some recent estimates on the Bartnik mass for data with non-negative Gauss curvature and positive mean curvature. In particular, if the metric is round the estimate reduces to an estimate found by Miao and if the total mean curvature approaches 0, the estimate tends to 1/2 the area radius, which is the bound found by Mantoulidis and Schoen in the blackhole horizon case. We will then discuss some geometric implications. This is joint work with Pengzi Miao.

LUNCH BREAK

1:30–2:30 pm
Ryan Unger
Title: Density and positive mass theorems for black holes and incomplete manifolds
Abstract: We generalize the density theorems for the Einstein constraint equations of Corvino-Schoen and Eichmair-Huang-Lee-Schoen to allow for marginally outer trapped boundaries (which correspond physically to apparent horizons). As an application, we resolve the spacetime positive mass theorem in the presence of MOTS boundary in the non-spin case. This also has a surprising application to the Riemannian setting, including a non-filling result for manifolds with negative mass. This is joint work with Martin Lesourd and Dan Lee.

2:40–3:40 pm
Zhizhang Xie
Title: Gromov’s dihedral extremality/rigidity conjectures and their applications I
Abstract: Gromov’s dihedral extremality and rigidity conjectures concern comparisons of scalar curvature, mean curvature and dihedral angle for compact manifolds with corners. They have very interesting consequences in geometry and mathematical physics. The conjectures themselves can in some sense be viewed as “localizations” of the positive mass theorem. I will explain some recent work on positive solutions to these conjectures and some related applications (such as a positive solution to the Stoker conjecture). The talks are based on my joint works with Jinmin Wang and Guoliang Yu.

TEA BREAK

4:10–5:10 pm
Antoine Song (virtual)
Title: The spherical Plateau problem
Abstract: For any closed oriented manifold with fundamental group G, or more generally any group homology class for a group G, I will discuss an infinite codimension Plateau problem in a Hilbert classifying space for G. For instance, for a closed oriented 3-manifold M, the intrinsic geometry of any Plateau solution is given by the hyperbolic part of M.

Tuesday, May 3, 2022

9:30–10:30 am
Chao Li
Title: Stable minimal hypersurfaces in 4-manifolds
Abstract: There have been a classical theory for complete minimal surfaces in 3-manifolds, including the stable Bernstein conjecture in R^3 and rigidity results in 3-manifolds with positive Ricci curvature. In this talk, I will discuss how one may extend these results in four dimensions. This leads to new comparison theorems for positively curved 4-manifolds.

10:40–11:40 am
Robin Neumayer
Title: An Introduction to $d_p$ Convergence of Riemannian Manifolds I
Abstract: What can you say about the structure or a-priori regularity of a Riemannian manifold if you know certain bounds on its curvature? To understand this question, it is often important to understand in what sense a sequence of Riemannian manifolds (possessing a given curvature constraint) will converge, and what the limiting objects look like. In this mini-course, we introduce the notions of $d_p$ convergence of Riemannian manifolds and of rectifiable Riemannian spaces, the objects that arise as $d_p$ limits. This type of convergence can be useful in contexts when the distance functions of the Riemannian manifolds are not uniformly controlled. This course is based on joint work with Man Chun Lee and Aaron Naber.

LUNCH BREAK

1:30–2:30 pm
Zhongshan An
Title: Local existence and uniqueness of static vacuum extensions of Bartnik boundary data
Abstract: The study of static vacuum Riemannian metrics arises naturally in differential geometry and general relativity. It plays an important role in scalar curvature deformation, as well as in constructing Einstein spacetimes. Existence of static vacuum Riemannian metrics with prescribed Bartnik data — the induced metric and mean curvature of the boundary — is one of the most fundamental problems in Riemannian geometry related to general relativity. It is also a very interesting problem on the global solvability of a natural geometric boundary value problem. In this talk I will first discuss some basic properties of the nonlinear and linearized static vacuum equations and the geometric boundary conditions. Then I will present some recent progress towards the existence problem of static vacuum metrics based on joint works with Lan-Hsuan Huang.

2:40–3:40 pm
Zhizhang Xie
Title: Gromov’s dihedral extremality/rigidity conjectures and their applications II
Abstract: Gromov’s dihedral extremality and rigidity conjectures concern comparisons of scalar curvature, mean curvature and dihedral angle for compact manifolds with corners. They have very interesting consequences in geometry and mathematical physics. The conjectures themselves can in some sense be viewed as “localizations” of the positive mass theorem. I will explain some recent work on positive solutions to these conjectures and some related applications (such as a positive solution to the Stoker conjecture). The talks are based on my joint works with Jinmin Wang and Guoliang Yu.

TEA BREAK

4:10–5:10 pm
Tin-Yau Tsang
Title: Dihedral rigidity, fill-in and spacetime positive mass theorem
Abstract: For compact manifolds with boundary, to characterise the relation between scalar curvature and boundary geometry, Gromov proposed dihedral rigidity conjecture and fill-in conjecture. In this talk, we will see the role of spacetime positive mass theorem in answering the corresponding questions for initial data sets.

Speakers Banquet

Wednesday, May 4, 2022

9:30–10:30 am
Tristan Ozuch
Title: Weighted versions of scalar curvature, mass and spin geometry for Ricci flows
Abstract: With A. Deruelle, we define a Perelman-like functional for ALE metrics which lets us study the (in)stability of Ricci-flat ALE metrics. With J. Baldauf, we extend some classical objects and formulas from the study of scalar curvature, spin geometry and general relativity to manifolds with densities. We surprisingly find that the extension of ADM mass is the opposite of the above functional introduced with A. Deruelle. Through a weighted Witten’s formula, this functional also equals a weighted spinorial Dirichlet energy on spin manifolds. Ricci flow is the gradient flow of all of these quantities.

10:40–11:40 am
Robin Neumayer
Title: An Introduction to $d_p$ Convergence of Riemannian Manifolds II
Abstract: What can you say about the structure or a-priori regularity of a Riemannian manifold if you know certain bounds on its curvature? To understand this question, it is often important to understand in what sense a sequence of Riemannian manifolds (possessing a given curvature constraint) will converge, and what the limiting objects look like. In this mini-course, we introduce the notions of $d_p$ convergence of Riemannian manifolds and of rectifiable Riemannian spaces, the objects that arise as $d_p$ limits. This type of convergence can be useful in contexts when the distance functions of the Riemannian manifolds are not uniformly controlled. This course is based on joint work with Man Chun Lee and Aaron Naber.

LUNCH BREAK

1:30–2:30 pm
Christos Mantoulidis
Title: Metrics with lambda_1(-Delta+kR) > 0 and applications to the Riemannian Penrose Inequality
Abstract: On a closed n-dimensional manifold, consider the space of all Riemannian metrics for which -Delta+kR is positive (nonnegative) definite, where k > 0 and R is the scalar curvature. This spectral generalization of positive (nonnegative) scalar curvature arises naturally, for different values of k, in the study of scalar curvature in dimension n + 1 via minimal surfaces, the Yamabe problem in dimension n, and Perelman’s surgery for Ricci flow in dimension n = 3. We study these spaces in unison and generalize, as appropriate, scalar curvature results that we eventually apply to k = 1/2, where the space above models apparent horizons in time-symmetric initial data sets to the Einstein equations and whose flexibility properties are intimately tied with the instability of the Riemannian Penrose Inequality. This is joint work with Chao Li.

2:40–3:40 pm
Zhizhang Xie
Title: Gromov’s dihedral extremality/rigidity conjectures and their applications III
Abstract: Gromov’s dihedral extremality and rigidity conjectures concern comparisons of scalar curvature, mean curvature and dihedral angle for compact manifolds with corners. They have very interesting consequences in geometry and mathematical physics. The conjectures themselves can in some sense be viewed as “localizations” of the positive mass theorem. I will explain some recent work on positive solutions to these conjectures and some related applications (such as a positive solution to the Stoker conjecture). The talks are based on my joint works with Jinmin Wang and Guoliang Yu.

TEA BREAK

4:10–5:10 pm
Xin Zhou
(Virtual)
Title: Min-max minimal hypersurfaces with higher multiplicity
Abstract: It is well known that minimal hypersurfaces produced by the Almgren-Pitts min-max theory are counted with integer multiplicities. For bumpy metrics (which form a generic set), the multiplicities are one thanks to the resolution of the Marques-Neves Multiplicity One Conjecture. In this talk, we will exhibit a set of non-bumpy metrics on the standard (n+1)-sphere, in which the min-max varifold associated with the second volume spectrum is a multiplicity two n-sphere. Such non-bumpy metrics form the first set of examples where the min-max theory must produce higher multiplicity minimal hypersurfaces. The talk is based on a joint work with Zhichao Wang (UBC).

May 5, 2022

9:00–10:00 am
Andre Neves
Title: Metrics on spheres where all the equators are minimal
Abstract: I will talk about joint work with Lucas Ambrozio and Fernando Marques where we study the space of metrics where all the equators are minimal.

10:10–11:10 am
Robin Neumayer
Title: An Introduction to $d_p$ Convergence of Riemannian Manifolds III
Abstract: What can you say about the structure or a-priori regularity of a Riemannian manifold if you know certain bounds on its curvature? To understand this question, it is often important to understand in what sense a sequence of Riemannian manifolds (possessing a given curvature constraint) will converge, and what the limiting objects look like. In this mini-course, we introduce the notions of $d_p$ convergence of Riemannian manifolds and of rectifiable Riemannian spaces, the objects that arise as $d_p$ limits. This type of convergence can be useful in contexts when the distance functions of the Riemannian manifolds are not uniformly controlled. This course is based on joint work with Man Chun Lee and Aaron Naber.

11:20–12:20 pm
Paula Burkhardt-Guim
Title: Lower scalar curvature bounds for C^0 metrics: a Ricci flow approach
Abstract: We describe some recent work that has been done to generalize the notion of lower scalar curvature bounds to C^0 metrics, including a localized Ricci flow approach. In particular, we show the following: that there is a Ricci flow definition which is stable under greater-than-second-order perturbation of the metric, that there exists a reasonable notion of a Ricci flow starting from C^0 initial data which is smooth for positive times, and that the weak lower scalar curvature bounds are preserved under evolution by the Ricci flow from C^0 initial data.

LUNCH BREAK

1:30–2:30 pm
Jonathan Zhu
Title: Widths, minimal submanifolds and symplectic embeddings
Abstract: Width or waist inequalities measure the size of a manifold with respect to measures of families of submanifolds. We’ll discuss related area estimates for minimal submanifolds, as well as applications to quantitative symplectic camels.

2022 NSF FRG Workshop on Discrete Shapes
2022-05-06 10:00 - 2022-05-08 17:00 | CMSA, 20 Garden Street, Cambridge, MA, 02138, United States
On May 6–8, 2022, the CMSA hosted a second NSF FRG Workshop.
This project brings together a community of researchers who develop theoretical and computational models to characterize shapes. Their combined interests span Mathematics (Geometry and Topology), Computer Science (Scientific Computing and Complexity Theory), and domain sciences, from Data Sciences to Computational Biology.
Scientific research benefits from the development of an ever-growing number of sensors that are able to capture details of the world at increasingly fine resolutions. The seemingly unlimited breadth and depth of these sources provide the means to study complex systems in a more comprehensive way. At the same time, however, these sensors are generating a huge amount of data that comes with a high level of complexity and heterogeneity, providing indirect measurements of hidden processes that provide keys to the systems under study. This has led to new challenges and opportunities in data analysis. Our focus is on image data and the shapes they represent. Advances in geometry and topology have led to powerful new tools that can be applied to geometric methods for representing, searching, simulating, analyzing, and comparing shapes. These methods and tools can be applied in a wide range of fields, including computer vision, biological imaging, brain mapping, target recognition, and satellite image analysis.
This workshop is part of the NSF FRG project: Geometric and Topological Methods for Analyzing Shapes.
The workshop was held in room G10 of the CMSA, located at 20 Garden Street, Cambridge, MA.

Workshop on Discrete Shapes
May 6–8, 2022
Organizers:

David Glickenstein (University of Arizona)
Joel Hass (University of California, Davis)
Patrice Koehl (University of California, Davis)
Feng Luo (Rutgers University, New Brunswick)
Maria Trnkova (University of California, Davis)
Shing-Tung Yau (Harvard)

Speakers:

Miri Ben-Chen (Technion)
Alexander Bobenko (TU Berlin)
John Bowers (James Madison)
Steven Gortler (Harvard)
David Gu (Stony Brook)
Anil Hirani (UIUC)
Yanwen Luo (Rutgers)
Peter Schroeder (Caltech)
Justin Solomon (MIT)
Tianqi Wu (Clark University)

Contributed Talk Speakers:

Oded Stein (MIT)
Bohan Zhou (Dartmouth)

Schedule
Schedule (PDF)
Friday, May 6, 2022

10:00–10:05 am

Welcome Opening

10:05–10:55 am
Anil N. Hirani
Title: Discrete vector bundles with connection
Abstract: We have recently initiated a generalization of discrete exterior calculus to differential forms with values in a vector bundle. A discrete vector bundle with connection over a simplicial complex has fibers at vertices and transport maps on edges, just as in lattice gauge theory. The first part of this work involves defining and examining properties of a combinatorial exterior covariant derivative and wedge product. We find that these operators commute with pullback under simplicial maps of the base space. From these definitions emerges a combinatorial curvature. In the second part of this work we showed that the curvature behaves as one expects: it measures failure of parallel transport to be independent of the path, and is the local obstruction to a trivialization. For a bundle with metric, metric compatibility of the discrete connection is equivalent to a Leibniz rule. Vanishing curvature is indeed equivalent to an appropriately defined discrete flat connection, and curvature obstructs trivializability. In this talk I will focus on just the first part, and talk about naturality of the discrete exterior covariant derivative and discrete wedge product using simple examples. Joint work with Daniel Berwick-Evans (UIUC) and Mark Schubel (Apple, Inc.).

11:10–12:00 pm
David Gu
Title: Surface Quadrilateral Meshing Based on Abel-Jacobi Theory
Abstract: Surface quadrilateral meshing plays an important role in many fields. For example, in CAD (computer-aided design), all shapes are represented as Spline surfaces, which requires structured quad-meshing; in CAE (computer-aided engineering), the surface tessellation greatly affects the accuracy and efficiency of numerical simulations. Although the research on mesh generation has a long history, it remains a great challenge to automatically generate structured quad-meshes with high qualities. The key is to find the governing equation for the singularities of the global structured quad-meshes.
In this talk, we introduce our recent discovery: the singularities of a quad-mesh are governed by the Abel theorem. We show that each quad-mesh determines a conformal structure and a meromorphic quadratic differential, the configuration of the mesh singularities can be described as the divisor of the differential. The quad-mesh divisor minus four times of the divisor of a holomorphic one-form is principal and satisfies the Abel theorem: its image under the Jacobi map is zero in the Jacobi variety.
This leads to a rigorous and efficient algorithm for surface structured quadrilateral meshing. After determining the singularities, the metric induced by the quad-mesh can be computed using the discrete Yambe flow, and the meromorphic quartic differential can be constructed, the trajectories of the differentials give the quad-mesh. The method can be applied directly for geometric modeling and computational mechanics.

12:00–2:00 pm
Lunch Break

2:00–2:50 pm
Justin Solomon
Title: Geometry Processing with Volumes
Abstract: Many algorithms in geometry processing are restricted to two-dimensional surfaces represented as triangle meshes. Drawing inspiration from simulation, medical imaging, and other application domains, however, there is a substantial demand for geometry processing algorithms targeted to volumes represented as tetrahedral meshes or grids. In this talk, I will summarize some efforts in our group to develop a geometry processing toolkit specifically for volumes. Specifically, I will cover our recent work on hexahedral remeshing via cuboid decomposition, volumetric correspondence, and minimal surface computation via geometric measure theory.

3:00–3:20 pm
Oded Stein
Title: Optimization for flip-free parametrization
Abstract: Parametrizations without flipped elements are desirable in a variety of applications such as UV mapping and surface/volume correspondence. Computing flip-free parametrizations can be challenging, and there are many different approaches to the problem. In this talk we will look at multiple strategies for flip-free parametrizations that are based on the optimization of continuous energies. Due to the nature of the problem, these energies are often nonconvex and unbounded, which is a challenge for optimization methods. We will also take a closer look at our recently developed method for computing flip-free parametrizations using the Alternating Direction Method of Multipliers (ADMM).

3:20–4:00 pm
Break

4:00–4:50 pm
John Bowers
Title: Koebe-Andre’ev-Thurston Packings via Flow
Abstract: Recently, Connelly and Gortler gave a novel proof of the circle packing theorem for tangency packings by introducing a hybrid combinatorial-geometric operation, flip-and-flow, that allows two tangency packings whose contact graphs differ by a combinatorial edge flip to be continuously deformed from one to the other while maintaining tangencies across all of their common edges. Starting from a canonical tangency circle packing with the desired number of circles a finite sequence of flip-and-flow operations may be applied to obtain a circle packing for any desired (proper) contact graph with the same number of circles.
The full Koebe-Andre’ev-Thurston theorem generalizes the circle packing theorem to allow for neighboring circles to overlap by angles up to $pi/2$. In this talk I will show that the Connelly-Gortler method can be extended to allow for circles to overlap to angles up to $pi/2$. This results in a new proof of the general Koebe-Andre’ev-Thurston theorem for disk patterns on $mathbb{S}^2$ as well as a numerical algorithm for computing them. The proof involves generalizing a notion of convexity for circle polyhedra that was recently used to prove the global rigidity of certain circle packings, which is then used to show that all convex circle polyhedra are infinitesimally rigid, a result of independent interest.

5:00–5:30 pm
Movies
“conform!” & ”Koebe polyhedra”

Saturday, May 7, 2022

9:30–10:20 am
Alexander Bobenko
Title: The Bonnet problem: Is a surface characterized by its metric and curvatures?
Abstract: We consider a classical problem in differential geometry, known as the Bonnet problem, whether a surface is characterized by a metric and mean curvature function. Generically, the answer is yes. Special cases when it is not the case are classified. In particular, we explicitly construct a pair of immersed tori that are related by a mean curvature preserving isometry. This resolves a longstanding open problem on whether the metric and mean curvature function determine a unique compact surface. Discrete differential geometry is used to find crucial geometric properties of surfaces. This is a joint work with Tim Hoffmann and Andrew Sageman-Furnas

10:20–11:00 am
Break

11:00–11:50 am
Miri Ben Chen
Title: Surface Multigrid via Intrinsic Prolongation
Abstract: The solution of a linear system is a required ingredient in many geometry processing applications, and multigrid methods are among the most efficient solution techniques. However, due to the unstructured nature of triangle meshes, mapping functions between different multigrid levels is challenging. In this talk I will present our recent work that uses an intrinsic prolongation operator as the main building block in a multigrid solver for curved triangle meshes. Our solver can be used as a black-box in any triangle-mesh based system that requires a linear solve, and leads to order of magnitude time-efficiency improvement compared to direct solvers.

12:00–2:00 pm
Lunch Break

2:00–2:50 pm
Steven Gortler
Title: Reconstructing configurations and graphs from unlabeled distance measurements
Abstract: Place a configuration of n points (vertices) generically in R^d. Measure the Euclidean lengths of m point-pairs (edges). When is the underlying graph determined by these $m$ numbers (up to isomorphism)? When is the point configuration determined by these $m$ numbers (up to congruence)? This question is motivated by a number of inverse problem applications. In this talk, I will review what is known about this question.

3:00–3:20 pm
Bohan Zhou
Title: Efficient and Exact Multimarginal Optimal Transport with Pairwise Costs
Abstract: Optimal transport has profound and wide applications since its introduction in 1781 by Monge. Thanks to the Benamou-Brenier formulation, it provides a meaningful functional in the image science like image and shape registrations. However, exact computation through LP or PDE is in general not practical in large scale, while the popular entropy-regularized method introduces additional diffusion noise, deteriorating shapes and boundaries. Until the recent work [Jacobs and Leger, A Fast Approach to Optimal Transport: the back-and-forth method, Numerische Mathematik, 2020], solving OT in a both accurate and fast fashion finally becomes possible. Multiple marginal optimal transport is a natural extension from OT but has its own interest and is in general more computationally expensive. The entropy method suffers from both diffusion noise and high dimensional computational issues. In this work with Matthew Parno, we extend from two marginals to multiple marginals, on a wide class of cost functions when those marginals have a graph structure. This new method is fast and does not introduce diffusion. As a result, the new proposed method can be used in many fields those require sharp boundaries. If time allows, we will illustrate by examples the faithful joint recover via MMOT of images with sharp boundaries, with applications on sea ice prediction.

3:20–4:00 pm
Break

4:00–4:50 pm
Peter Schroeder
Title: Constrained Willmore Surfaces
Abstract: The Willmore energy of a surface is a canonical example of a squared curvature bending energy. Its minimizers are therefore of interest both in the theory of surfaces and in practical applications from physical and geometric modeling. Minimizing the bending energy alone however is insufficient. Taking a cue from univariate splines which incorporate an isometry constraint we consider Willmore minimizers subject to a conformality constraint. In this talk I will report on a numerical algorithm to find such constrained minimizers for triangle meshes.
Joint work with Yousuf Soliman (Caltech), Olga Diamanti (UGraz), Albert Chern (UCSD), Felix Knöppel (TU Berlin), Ulrich Pinkall (TU Berlin).

5:00–5:50 pm

Problems and Application discussions

Sunday, May 8, 2022

9:00–9:50 am
Tianqi Wu
Title: Convergence of discrete uniformizations
Abstract: The theory of discrete conformality, based on the notion of vertex scaling, has been implemented in computing conformal maps or uniformizations of surfaces. We will show that if a Delaunay triangle mesh approximates a smooth surface, then the related discrete uniformization will converge to the smooth uniformization, with an error bounded linearly by the size of the triangles in the mesh.

10:10–11:00 am
Yanwen Luo
Title: Recent Progress in Spaces of Geodesic Triangulations of Surfaces

Abstract: Spaces of geodesic triangulations of surfaces are natural discretization of the groups of surface diffeomorphisms isotopy to the identity. It has been conjectured that these spaces have the same homotopy type as their smooth counterparts. In this talk, we will report the recent progress in this problem. The key ingredient is the idea in Tutte’s embedding theorem. We will explain how to use it to identify the homotopy types of spaces of geodesic triangulations. This is joint work with Tianqi Wu and Xiaoping Zhu.

11:10–12:00 pm

Problems and Application discussions

12:00–1:00 pm
Movie
“The Discrete Charm of Geometry”

Conference in Memory of Professor Masatake Kuranishi
2022-05-09 09:00 - 2022-05-12 12:30 | Science and Engineering Complex (SEC), 150 Western Ave, Allston, MA 02134, MA
On May 9–12, 2022, the CMSA hosted the conference Deformations of structures and moduli in geometry and analysis: A Memorial in honor of Professor Masatake Kuranishi.
Organizers: Tristan Collins (MIT) and Shing-Tung Yau (Harvard and Tsinghua)
Videos are available on the conference playlist.

Speakers:
Charles Fefferman (Princeton University)
Teng Fei (Rutgers University)
Robert Friedman (Columbia University)
Kenji Fukaya (Simons Center, Stony Brook)
Akito Futaki (Tsinghua University)
Victor Guillemin (Massachusetts Institute of Technology)
Nigel Hitchin (Oxford University)
Blaine Lawson (Stony Brook University)
Yu-Shen Lin (Boston University)
Melissa C.C. Liu (Columbia University)
Takeo Ohsawa (Nagoya University)
Duong H. Phong (Columbia University)
Sebastien Picard (University of British Columbia)
Paul Seidel (Massachusetts Institute of Technology)
Gabor Szekelyhidi (University of Notre Dame)
Claire Voisin (Institut de Mathematiques, Jussieu, France)
Shing-Tung Yau (Harvard University)

Schedule (download pdf)

Monday, May 9, 2022

8:15 am
Light breakfast & coffee/tea

8:45–9:00 am
Opening Remarks

9:00–10:00 am
Kenji Fukaya
Title: Gromov Hausdorff convergence of filtered A infinity category
Abstract: In mirror symmetry a mirror to a symplectic manifold is actually believed to be a family of complex manifold parametrized by a disk (of radius 0). The coordinate ring of the parameter space is a kind of formal power series ring the Novikov ring. Novikov ring is a coefficient ring of Floer homology. Most of the works on homological Mirror symmetry so far studies A infinity category over Novikov field, which corresponds to the study of generic fiber. The study of A infinity category over Novikov ring is related to several interesting phenomenon of Hamiltonian dynamics. In this talk I will explain a notion which I believe is useful to study mirror symmetry.
Video

10:15–11:15 am
Nigel Hitchin (Zoom)
Title: Deformations: A personal perspective
Abstract: The talk, largely historical, will focus on different deformation complexes I have encountered in my work, starting with instantons on 4-manifolds, but also monopoles, Higgs bundles and generalized complex structures. I will also discuss some speculative ideas related to surfaces of negative curvature.
Video

11:30–12:30 pm
H. Blaine Lawson
Title: Projective Hulls, Projective Linking, and Boundaries of Varieties
Abstract: In 1958 John Wermer proved that the polynomial hull of a compact real analytic curve γ ⊂ Cn was a 1-dim’l complex subvariety of Cn − γ. This result engendered much subsequent activity, and was related to Gelfand’s spectrum of a Banach algebra. In the early 2000’s Reese Harvey and I found a projective analogue of these concepts and wondered whether Wermer’s Theorem could be generalized to the projective setting. This question turned out to be more subtle and quite intriguing, with unexpected consequences. We now know a great deal, a highpoint of which s a result with Harvey and Wermer. It led to conjectures (for Cω-curves in P2C) which imply several results. One says, roughly, that a (2p − 1)-cycle Γ in Pn bounds a positive holomorphic p-chain of mass ≤ Λ ⇐⇒ its normalized linking number with all positive (n − p)-cycles in Pn − |Γ| is ≥ −Λ. Another says that a class τ ∈ H2p(Pn,|Γ|;Z) with ∂τ = Γ contains a positive holomorphic p-chain ⇐⇒ τ•[Z]≥0 for all positive holomorphic (n−p)-cycles Z in Pn−|Γ|
Video

12:30–2:30 pm
Lunch Break

2:30–3:30 pm
Gabor Szekelyhidi
Title: Singularities along the Lagrangian mean curvature flow.
Abstract: We study singularity formation along the Lagrangian mean curvature flow of surfaces. On the one hand we show that if a tangent flow at a singularity is the special Lagrangian union of two transverse planes, then the flow undergoes a “neck pinch”, and can be continued past the flow. This can be related to the Thomas-Yau conjecture on stability conditions along the Lagrangian mean curvature flow. In a different direction we show that ancient solutions of the flow, whose blow-down is given by two planes meeting along a line, must be translators. These are joint works with Jason Lotay and Felix Schulze.
Video

3:30–4:00 pm
Coffee Break

4:00–5:00 pm
Takeo Ohsawa
Title: Glimpses of embeddings and deformations of CR manifolds
Abstract: Basic results on the embeddings and the deformations of CR manifolds will be reviewed with emphasis on the reminiscences of impressive moments with Kuranishi since his visit to Kyoto in 1975.
Video

Tuesday, May 10, 2022

8:15 am
Light breakfast & coffee/tea

9:00–10:00 am
Charles Fefferman (Zoom)
Title: Interpolation of Data by Smooth Functions
Abstract: Let X be your favorite Banach space of continuous functions on R^n. Given an (arbitrary) set E in R^n and an arbitrary function f:E->R, we ask: How can we tell whether f extends to a function F in X? If such an F exists, then how small can we take its norm? What can we say about its derivatives (assuming functions in X have derivatives)? Can we take F to depend linearly on f? Suppose E is finite. Can we compute an F as above with norm nearly as small as possible? How many computer operations does it take? What if F is required to agree only approximately with f on E? What if we are allowed to discard a few data points (x, f(x)) as “outliers”? Which points should we discard?
The results were obtained jointly with A. Israel, B. Klartag, G.K. Luli and P. Shvartsman over many years.
Video

10:15–11:15 am
Claire Voisin
Title: Deformations of K-trivial manifolds and applications to hyper-Kähler geometry
Summary: I will explain the Ran approach via the T^1-lifting principle to the BTT theorem stating that deformations of K-trivial compact Kähler manifolds are unobstructed. I will explain a similar unobstructedness result for Lagrangian submanifolds of hyper-Kähler manifolds and I will describe important consequences on the topology and geometry of hyper-Kähler manifolds.
Video

11:30– 2:30 pm
Victor Guillemin
Title: Semi-Classical Functions of Isotropic Type
Abstract: The world of semiclassical analysis is populated by objects of “Lagrangian type.” The topic of this talk however will be objects in semi-classical analysis that live instead on isotropic submanifolds. I will describe in my talk a lot of interesting examples of such objects.
Video

12:30–2:30 pm
Lunch Break

2:30–3:30 pm
Teng Fei
Title: Symplectic deformations and the Type IIA flow
Abstract: The equations of flux compactification of Type IIA superstrings were written down by Tomasiello and Tseng-Yau. To study these equations, we introduce a natural geometric flow known as the Type IIA flow on symplectic Calabi-Yau 6-manifolds. We prove the wellposedness of this flow and establish the basic estimates. We show that the Type IIA flow can be applied to find optimal almost complex structures on certain symplectic manifolds. We prove the dynamical stability of the Type IIA flow, which leads to a proof of stability of Kahler property for Calabi-Yau 3-folds under symplectic deformations. This is based on joint work with Phong, Picard and Zhang.
Video

Speakers Banquet

Wednesday, May 11, 2022

8:15 am
Light breakfast & coffee/tea

9:00–10:00 am
Shing-Tung Yau (Zoom)
Title: Canonical metrics and stability in mirror symmetry
Abstract: I will discuss the deformed Hermitian-Yang-Mills equation, its role in mirror symmetry and its connections to notions of stability. I will review what is known, and pose some questions for the future.
Video

10:15–11:15 am
Duong H. Phong
Title: $L^infty$ estimates for the Monge-Ampere and other fully non-linear equations in complex geometry
Abstract: A priori estimates are essential for the understanding of partial differential equations, and of these, $L^infty$ estimates are particularly important as they are also needed for other estimates. The key $L^infty$ estimates were obtained by S.T. Yau in 1976 for the Monge-Ampere equation for the Calabi conjecture, and sharp estimates obtained later in 1998 by Kolodziej using pluripotential theory. It had been a long-standing question whether a PDE proof of these estimates was possible. We provide a positive answer to this question, and derive as a consequence sharp estimates for general classes of fully non-linear equations. This is joint work with B. Guo and F. Tong.
Video

11:30–2:30 pm
Paul Seidel
Title: The quantum connection: familiar yet puzzling
Abstract: The small quantum connection on a Fano variety is possibly the most basic piece of enumerative geometry. In spite of being really easy to write down, it is the subject of far-reaching conjectures (Dubrovin, Galkin, Iritani), which challenge our understanding of mirror symmetry. I will give a gentle introduction to the simplest of these questions.
Video

12:30–2:30 pm
Lunch Break

2:30–3:30 pm
Melissa C.C. Liu
Title: Higgs-Coulumb correspondence for abelian gauged linear sigma models
Abstract: The underlying geometry of a gauged linear sigma model (GLSM) consists of a GIT quotient of a complex vector space by the linear action of a reductive algebraic group G (the gauge group) and a polynomial function (the superpotential) on the GIT quotient. The Higgs-Coulomb correspondence relates (1) GLSM invariants which are virtual counts of curves in the critical locus of the superpotential (Higgs branch), and (2) Mellin-Barnes type integrals on the Lie algebra of G (Coulomb branch). In this talk, I will describe the correspondence when G is an algebraic torus, and explain how to use the correspondence to study dependence of GLSM invariants on the stability condition. This is based on joint work with Konstantin Aleshkin.
Video

3:30–4:00 pm
Coffee Break

4:00–5:00 pm
Sebastien Picard
Title: Topological Transitions of Calabi-Yau Threefolds
Abstract: Conifold transitions were proposed in the works of Clemens, Reid and Friedman as a way to travel in the parameter space of Calabi-Yau threefolds with different Hodge numbers. This process may deform a Kahler Calabi-Yau threefold into a non-Kahler complex manifold with trivial canonical bundle. We will discuss the propagation of differential geometric structures such as balanced hermitian metrics, Yang-Mills connections, and special submanifolds through conifold transitions. This is joint work with T. Collins, S. Gukov and S.-T. Yau.
Video

Thursday, May 12, 2022

8:15 am
Light breakfast & coffee/tea

9:00 am–10:00 am
Akito Futaki (Zoom)
Title: Transverse coupled Kähler-Einstein metrics and volume minimization

Abstract: We show that transverse coupled Kähler-Einstein metrics on toric Sasaki manifolds arise as a critical point of a volume functional. As a preparation for the proof, we re-visit the transverse moment polytopes and contact moment polytopes under the change of Reeb vector fields. Then we apply it to a coupled version of the volume minimization by Martelli-Sparks-Yau. This is done assuming the Calabi-Yau condition of the Kählercone, and the non-coupled case leads to a known existence result of a transverse Kähler-Einstein metric and a Sasaki-Einstein metric, but the coupled case requires an assumption related to Minkowski sum to obtain transverse coupled Kähler-Einstein metrics.Video

10:15 am–11:15 am
Yu-Shen Lin
Title: SYZ Mirror Symmetry of Log Calabi-Yau Surfaces
Abstract: Strominger-Yau-Zaslow conjecture predicts Calabi-Yau manifolds admits special Lagrangian fibrations. The conjecture serves as one of the guiding principles in mirror symmetry. In this talk, I will explain the existence of the special Lagrangian fibrations in some log Calabi-Yau surfaces and their dual fibrations in their expected mirrors. The journey leads us to the study of the moduli space of Ricci-flat metrics with certain asymptotics on these geometries and the discovery of new semi-flat metrics. If time permits, I will explain the application to the Torelli theorem of ALH^* gravitational instantons. The talk is based on joint works with T. Collins and A. Jacob.
Video

11:30 am – 12:30 pm
Robert Friedman
Title: Deformations of singular Fano and Calabi-Yau varieties
Abstract: This talk will describe recent joint work with Radu Laza on deformations of generalized Fano and Calabi-Yau varieties, i.e. compact analytic spaces whose dualizing sheaves are either duals of ample line bundles or are trivial. Under the assumption of isolated hypersurface canonical singularities, we extend results of Namikawa and Steenbrink in dimension three and discuss various generalizations to higher dimensions.
Video

12:30 pm
Concluding Remarks

SMaSH: Symposium for Mathematical Sciences at Harvard
2022-05-17 09:00 - 18:00 | Science and Engineering Complex (SEC), 150 Western Ave, Allston, MA 02134, MA
SMaSH: Symposium for Mathematical Sciences at Harvard
On Tuesday, May 17, 2022, from 9:00 am – 5:30 pm, the Harvard John A Paulson School of Engineering and Applied Sciences (SEAS) and the Harvard Center of Mathematical Sciences and Applications (CMSA) held a Symposium for Mathematical Sciences for the mathematical sciences community at Harvard.
Organizing Committee

Michael Brenner, Applied Mathematics (SEAS)
Michael Desai, Organismic and Evolutionary Biology (FAS)
Sam Gershman, Psychology (FAS)
Michael Hopkins, Mathematics (FAS)
Gary King, Government (FAS)
Peter Koellner, Philosophy (FAS)
Scott Kominers, Economics (FAS) & Entrepreneurial Management (HBS)
Xihong Lin, Biostatistics (HSPH) & Statistics (FAS)
Yue Lu, Electrical Engineering (SEAS)
Susan Murphy, Statistics (FAS) & Computer Science (SEAS)
Lisa Randall, Physics (SEAS)
Eugene Shakhnovich, Chemistry (FAS)
Salil Vadhan, Computer Science (SEAS)
Horng-Tzer Yau, Mathematics (FAS)

This event was held in-person at the Science and Engineering Complex (SEC) at 150 Western Ave, Allston, MA 02134, and streamed on Zoom.
Harvard graduate students and postdocs presented Poster Sessions.

Venue: Science and Engineering Complex (SEC)

Speakers

Anurag Anshu, Computer Science (SEAS)
Morgane Austern, Statistics (FAS)
Demba Ba, Electrical Engineering & Bioengineering (SEAS)
Michael Brenner, Applied Mathematics (SEAS)
Rui Duan, Biostatistics (HSPH)
Yannai A. Gonczarowski, Economics (FAS) & Computer Science (SEAS)
Kosuke Imai, Government & Statistics (FAS)
Sham M. Kakade, Computer Science (SEAS) & Statistics (FAS)
Seth Neel, Technology & Operations Management (HBS)
Melanie Matchett Wood, Mathematics (FAS)

Schedule PDF
Schedule

9:00–9:30 am
Coffee and Breakfast
West Atrium (ground floor of the SEC)

9:30–10:30 am
Faculty Talks
Winokur Family Hall Classroom (Room 1.321) located just off of the West AtriumKosuke Imai, Government & Statistics (FAS): Use of Simulation Algorithms for Legislative Redistricting Analysis and EvaluationYannai A. Gonczarowski, Economics (FAS) & Computer Science (SEAS): The Sample Complexity of Up-to-ε Multi-Dimensional Revenue Maximization

10:30–11:00 am
Coffee Break
West Atrium (ground floor of the SEC)

11:00–12:00 pm
Faculty Talks
Winokur Family Hall Classroom (Room 1.321) located just off of the West AtriumSeth Neel, Technology & Operations Management (HBS): “Machine (Un)Learning” or Why Your Deployed Model Might Violate Existing Privacy LawDemba Ba, Electrical Engineering & Bioengineering (SEAS): Geometry, AI, and the Brain

12:00–1:00 pm
Lunch Break
Engineering Yard Tent

1:00–2:30 pm
Faculty Talks
Winokur Family Hall Classroom (Room 1.321) located just off of the West AtriumMelanie Matchett Wood, Mathematics (FAS): Understanding distributions of algebraic structures through their momentsMorgane Austern, Statistics (FAS): Limit theorems for structured random objectsAnurag Anshu, Computer Science (SEAS): Operator-valued polynomial approximations and their use.

2:30–3:00 pm
Coffee Break
West Atrium (ground floor of the SEC)

3:00–4:30 pm
Faculty Talks
Winokur Family Hall Classroom (Room 1.321) located just off of the West AtriumMichael Brenner, Applied Mathematics (SEAS): Towards living synthetic materialsRui Duan, Biostatistics (HSPH): Federated and transfer learning for healthcare data integrationSham M. Kakade, Computer Science (SEAS) & Statistics (FAS): What is the Statistical Complexity of Reinforcement Learning?

4:30–5:30 pm
Reception with Jazz musicians
& Poster Session
Engineering Yard Tent

Faculty Talks

Speaker
Title / Abstract / Bio

Anurag Anshu, Computer Science (SEAS)
Title: Operator-valued polynomial approximations and their use.
Abstract: Approximation of complicated functions with low degree polynomials is an indispensable tool in mathematics. This becomes particularly relevant in computer science, where the complexity of interesting functions is often captured by the degree of the approximating polynomials. This talk concerns the approximation of operator-valued functions (such as the exponential of a hermitian matrix, or the intersection of two projectors) with low-degree operator-valued polynomials. We will highlight the challenges that arise in achieving similarly good approximations as real-valued functions, as well as recent methods to overcome them. We will discuss applications to the ground states in physics and quantum complexity theory: correlation lengths, area laws and concentration bounds.
Bio: Anurag Anshu is an Assistant Professor of computer science at Harvard University. He spends a lot of time exploring the rich structure of quantum many-body systems from the viewpoint of quantum complexity theory, quantum learning theory and quantum information theory. He held postdoctoral positions at University of California, Berkeley and University of Waterloo and received his PhD from National University of Singapore, focusing on quantum communication complexity.

Morgane Austern, Statistics (FAS)
Title: Limit theorems for structured random objects
Abstract: Statistical inference relies on numerous tools from probability theory to study the properties of estimators. Some of the most central ones are the central limit theorem and the free central limit theorem. However, these same tools are often inadequate to study modern machine problems that frequently involve structured data (e.g networks) or complicated dependence structures (e.g dependent random matrices). In this talk, we extend universal limit theorems beyond the classical setting. We consider distributionally “structured’ and dependent random object i.e random objects whose distribution is invariant under the action of an amenable group. We show, under mild moment and mixing conditions, a series of universal second and third order limit theorems: central-limit theorems, concentration inequalities, Wigner semi-circular law and Berry-Esseen bounds. The utility of these will be illustrated by a series of examples in machine learning, network and information theory.
Bio: Morgane Austern is an assistant professor in the Statistics Department of Harvard University. Broadly, she is interested in developing probability tools for modern machine learning and in establishing the properties of learning algorithms in structured and dependent data contexts. She graduated with a PhD in statistics from Columbia University in 2019 where she worked in collaboration with Peter Orbanz and Arian Maleki on limit theorems for dependent and structured data. She was a postdoctoral researcher at Microsoft Research New England from 2019 to 2021.

Demba Ba, Electrical Engineering & Bioengineering (SEAS)
Title: Geometry, AI, and the Brain
Abstract: A large body of experiments suggests that neural computations reflect, in some sense, the geometry of “the world”. How do artificial and neural systems learn representations of “the world” that reflect its geometry? How, for instance, do we, as humans, learn representations of objects, e.g. fruits, that reflect the geometry of object space? Developing artificial systems that can capture/understand the geometry of the data they process may enable them to learn representations useful in many different contexts and tasks. My talk will describe an artificial neural-network architecture that, starting from a simple union-of-manifold model of data comprising objects from different categories, mimics some aspects of how primates learn, organize, and retrieve concepts, in a manner that respects the geometry of object space.
Bio: Demba Ba serves as an Associate Professor of electrical engineering and bioengineering in Harvard University’s School of Engineering and Applied Sciences, where he directs the CRISP group. Recently, he has taken a keen interest in the connection between artificial neural networks and sparse signal processing. His group leverages this connection to solve data-driven unsupervised learning problems in neuroscience, to understand the principles of hierarchical representations of sensory signals in the brain, and to develop explainable AI. In 2016, he received a Research Fellowship in Neuroscience from the Alfred P. Sloan Foundation. In 2021, Harvard’s Faculty of Arts and Sciences awarded him the Roslyn Abramson award for outstanding undergraduate teaching.

Michael Brenner, Applied Mathematics (SEAS)
Title: Towards living synthetic materials
Abstract: Biological materials are much more complicated and functional than synthetic ones. Over the past several years we have been trying to figure out why. A sensible hypothesis is that biological materials are programmable. But we are very far from being able to program materials we create with this level of sophistication. I will discuss our (largely unsuccessful) efforts to bridge this gap, though as of today I’m somewhat optimistic that we are arriving at a set of theoretical models that is rich enough to produce relevant emergent behavior.
Bio: I’ve been at Harvard for a long time. My favorite part of Harvard is the students.

Rui Duan, Biostatistics (HSPH)
Title: Federated and transfer learning for healthcare data integration
Abstract: The growth of availability and variety of healthcare data sources has provided unique opportunities for data integration and evidence synthesis, which can potentially accelerate knowledge discovery and improve clinical decision-making. However, many practical and technical challenges, such as data privacy, high dimensionality, and heterogeneity across different datasets, remain to be addressed. In this talk, I will introduce several methods for the effective and efficient integration of multiple healthcare datasets in order to train statistical or machine learning models with improved generalizability and transferability. Specifically, we develop communication-efficient federated learning algorithms for jointly analyzing multiple datasets without the need of sharing patient-level data, as well as transfer learning approaches that leverage shared knowledge learned across multiple datasets to improve the performance of statistical models in target populations of interest. We will discuss both the theoretical properties and examples of implementation of our methods in real-world research networks and data consortia.
Bio: Rui Duan is an Assistant Professor of Biostatistics at the Harvard T.H. Chan School of Public Health. She received her Ph.D. in Biostatistics in May 2020 from the University of Pennsylvania. Her research interests focus on developing statistical, machine learning, and informatics tools for (1) efficient data integration in biomedical research, (2) understanding and accounting for the heterogeneity of biomedical data, and improving the generalizability and transferability of models across populations (3) advancing precision medicine research on rare diseases and underrepresented populations.

Yannai A. Gonczarowski, Economics (FAS) & Computer Science (SEAS)
Title: The Sample Complexity of Up-to-ε Multi-Dimensional Revenue Maximization
Abstract: We consider the sample complexity of revenue maximization for multiple bidders in unrestricted multi-dimensional settings. Specifically, we study the standard model of n additive bidders whose values for m heterogeneous items are drawn independently. For any such instance and any ε > 0, we show that it is possible to learn an ε-Bayesian Incentive Compatible auction whose expected revenue is within ε of the optimal ε-BIC auction from only polynomially many samples.
Our fully nonparametric approach is based on ideas that hold quite generally, and completely sidestep the difficulty of characterizing optimal (or near-optimal) auctions for these settings. Therefore, our results easily extend to general multi-dimensional settings, including valuations that are not necessarily even subadditive, and arbitrary allocation constraints. For the cases of a single bidder and many goods, or a single parameter (good) and many bidders, our analysis yields exact incentive compatibility (and for the latter also computational efficiency). Although the single-parameter case is already well-understood, our corollary for this case extends slightly the state-of-the-art.
Joint work with S. Matthew Weinberg
Bio: Yannai A. Gonczarowski is an Assistant Professor of Economics and of Computer Science at Harvard University—the first faculty member at Harvard to have been appointed to both of these departments. Interested in both economic theory and theoretical computer science, Yannai explores computer-science-inspired economics: he harnesses approaches, aesthetics, and techniques traditionally originating in computer science to derive economically meaningful insights. Yannai received his PhD from the Departments of Math and CS, and the Center for the Study of Rationality, at the Hebrew University of Jerusalem, where he was advised by Sergiu Hart and Noam Nisan. Yannai is also a professionally-trained opera singer, having acquired a bachelor’s degree and a master’s degree in Classical Singing at the Jerusalem Academy of Music and Dance. Yannai’s doctoral dissertation was recognized with several awards, including the 2018 Michael B. Maschler Prize of the Israeli Chapter of the Game Theory Society, and the ACM SIGecom Doctoral Dissertation Award for 2018. For the design and implementation of the National Matching System for Gap-Year Programs in Israel, he was awarded the Best Paper Award at MATCH-UP’19 and the inaugural INFORMS AMD Michael H. Rothkopf Junior Researcher Paper Prize (first place) for 2020. Yannai is also the recipient of the inaugural ACM SIGecom Award for Best Presentation by a Student or Postdoctoral Researcher at EC’18. His first textbook, “Mathematical Logic through Python” (Gonczarowski and Nisan), which introduces a new approach to teaching the material of a basic Logic course to Computer Science students, tailored to the unique intuitions and strengths of this cohort of students, is forthcoming in Cambridge University Press.

Kosuke Imai, Government & Statistics (FAS)
Title: Use of Simulation Algorithms for Legislative Redistricting Analysis and Evaluation
Abstract: After the 2020 Census, many states have been redrawing the boundaries of Congressional and state legislative districts. To evaluate the partisan and racial bias of redistricting plans, scholars have developed Monte Carlo simulation algorithms. The idea is to generate a representative sample of redistricting plans under a specified set of criteria and conduct a statistical hypothesis test by comparing a proposed plan with these simulated plans. I will give a brief overview of these redistricting simulation algorithms and discuss how they are used in real-world court cases.
Bio: Kosuke Imai is Professor in the Department of Government and Department of Statistics at Harvard University. Before moving to Harvard in 2018, Imai taught at Princeton University for 15 years where he was the founding director of the Program in Statistics and Machine Learning. Imai specializes in the development of statistical methods and machine learning algorithms and their applications to social science research. His areas of expertise include causal inference, computational social science, program evaluation, and survey methodology.

Sham M. Kakade, Computer Science (SEAS) & Statistics (FAS)
Title: What is the Statistical Complexity of Reinforcement Learning?
Abstract: This talk will highlight much of the recent progress on the following fundamental question in the theory of reinforcement learning: what (representational or structural) conditions govern our ability to generalize and avoid the curse of dimensionality? With regards to supervised learning, these questions are reasonably well understood, both practically and theoretically: practically, we have overwhelming evidence on the value of representational learning (say through modern deep networks) as a means for sample efficient learning, and, theoretically, there are well-known complexity measures (e.g. the VC dimension and Rademacher complexity) that govern the statistical complexity of learning. Providing an analogous theory for reinforcement learning is far more challenging, where even characterizing structural conditions which support sample efficient generalization has been far less well understood, until recently.
This talk will survey recent advances towards characterizing when generalization is possible in RL, focusing on both necessary and sufficient conditions. In particular, we will introduce a new complexity measure, the Decision-Estimation Coefficient, that is proven to be necessary (and, essentially, sufficient) for sample-efficient interactive learning.
Bio: Sham Kakade is a professor at Harvard University and a co-director of the Kempner Institute for the Study of Artificial and Natural Intelligence. He works on the mathematical foundations of machine learning and AI. Sham’s thesis helped lay the statistical foundations of reinforcement learning. With his collaborators, his additional contributions include foundational results on: policy gradient methods in reinforcement learning; regret bounds for linear bandit and Gaussian process bandit models; the tensor and spectral methods for latent variable models; and a number of convergence analyses for convex and non-convex algorithms. He is the recipient of the ICML Test of Time Award, the IBM Pat Goldberg best paper award, and INFORMS Revenue Management and Pricing Prize. He has been program chair for COLT 2011.
Sham was an undergraduate at Caltech, where he studied physics and worked under the guidance of John Preskill in quantum computing. He completed his Ph.D. with Peter Dayan in computational neuroscience at the Gatsby Computational Neuroscience Unit. He was a postdoc with Michael Kearns at the University of Pennsylvania.

Seth Neel, Technology & Operations Management (HBS)
Title: “Machine (Un)Learning” or Why Your Deployed Model Might Violate Existing Privacy Law
Abstract: Businesses like Facebook and Google depend on training sophisticated models on user data. Increasingly—in part because of regulations like the European Union’s General Data Protection Act and the California Consumer Privacy Act—these organizations are receiving requests to delete the data of particular users. But what should that mean? It is straightforward to delete a customer’s data from a database and stop using it to train future models. But what about models that have already been trained using an individual’s data? These are not necessarily safe; it is known that individual training data can be exfiltrated from models trained in standard ways via model inversion attacks. In a series of papers we help formalize a rigorous notion of data-deletion and propose algorithms to efficiently delete user data from trained models with provable guarantees in both convex and non-convex settings.
Bio: Seth Neel is a first-year Assistant Professor in the TOM Unit at Harvard Business School, and Co-PI of the SAFR ML Lab in the D3 Institute, which develops methodology to incorporate privacy and fairness guarantees into techniques for machine learning and data analysis, while balancing other critical considerations like accuracy, efficiency, and interpretability. He obtained his Ph.D. from the University of Pennsylvania in 2020 where he was an NSF graduate fellow. His work has focused primarily on differential privacy, notions of fairness in a variety of machine learning settings, and adaptive data analysis.

Melanie Matchett Wood, Mathematics (FAS)
Title: Understanding distributions of algebraic structures through their moments
Abstract: A classical tool of probability and analysis is to use the moments (mean, variance, etc.) of a distribution to recognize an unknown distribution of real numbers. In recent work, we are interested in distributions of algebraic structures that can’t be captured in a single number. We will explain one example, the fundamental group, that captures something about the shapes of possibly complicated or high dimensional spaces. We are developing a new theory of the moment problem for random algebraic structures which helps to to identify distributions of such, such as fundamental groups of random three dimensional spaces. This talk is based partly on joint work with Will Sawin.
Bio: Melanie Matchett Wood is a professor of mathematics at Harvard University and a Radcliffe Alumnae Professor at the Radcliffe Institute for Advanced Study. Her work spans number theory, algebraic geometry, algebraic topology, additive combinatorics, and probability. Wood has been awarded a CAREER grant, a Sloan Research Fellowship, a Packard Fellowship for Science and Engineering, and the AWM-Microsoft Research Prize in Algebra and Number Theory, and she is a Fellow of the American Mathematical Society. In 2021, Wood received the National Science Foundation’s Alan T. Waterman Award, the nation’s highest honor for early-career scientists and engineers.

2022 Summer Introduction to Mathematical Research
2022-05-21 09:00 - 2022-06-12 17:00 | Virtual
The Math Department and Harvard’s Center of Mathematical Sciences and Applications (CMSA) will be running a math program/course for mathematically minded undergraduates this summer. The course will be run by Dr. Yingying Wu from CMSA. Here is a description:
Summer Introduction to Mathematical Research (sponsored by CMSA and the Harvard Math Department)
In this course, we will start with an introduction to computer programming, algorithms, and scientific computing. Then we will discuss topics in topology, classical geometry, projective geometry, and differential geometry, and see how they can be applied to machine learning. We will go on to discuss fundamental concepts of deep learning, different deep neural network models, and mathematical interpretations of why deep neural networks are effective from a calculus viewpoint. We will conclude the course with a gentle introduction to cryptography, introducing some of the iconic topics: Yao’s Millionaires’ problem, zero-knowledge proof, the multi-party computation algorithm, and its proof.
The program hopes to provide several research mentors from various disciplines who will give some of the course lectures. Students will have the opportunity to work with one of the research mentors offered by the program.
Prerequisites: Basic coding ability in some programming language (C/Python/Matlab or CS50 experience). Some background in calculus and linear algebra is needed too. If you wish to work with a research mentor on differential geometry, more background in geometry such as from Math 132 or 136 will be useful. If you wish to work with a research mentor on computer science, coding experience mentioned above will be very useful. If you wish to work with a medical scientist, some background in life science or basic organic chemistry is recommended.
The course will meet 3 hours per week for 7 weeks via Zoom on days and times that will be scheduled for the convenience of the participants. There may be other times to be arranged for special events.
This program is only open to current Harvard undergraduates; both Mathematics concentrators and non-math concentrators are invited to apply. People already enrolled in a Math Department summer tutorial are welcome to partake in this program also. As with the summer tutorials, there is no association with the Harvard Summer School; and neither Math concentration credit nor Harvard College credit will be given for completing this course. This course has no official Harvard status and enrollment does not qualify you for any Harvard-related perks (such as a place to live if you are in Boston over the summer.)
However: As with the summer tutorials, those enrolled are eligible* to receive a stipend of $700, and if you are a Mathematics concentrator, any written paper for the course can be submitted to fulfill the Math Concentration third-year paper requirement. (*The stipend is not available for people already receiving a stipend via the Math Department’s summer tutorial program, nor is it available for PRISE participants or participants in the Herchel Smith program.)
If you wish to join this program, please email Cliff Taubes (chtaubes@math.harvard.edu). The enrollment is limited, so don’t wait too long to apply.

Symposium on Foundations of Responsible Computing (FORC)
2022-06-06 09:00 - 2022-06-08 17:00 | CMSA Room G10, CMSA, 20 Garden Street, Cambridge, MA, 02138, United States
On June 6-8, 2022, the CMSA hosted the 3rd annual Symposium on Foundations of Responsible Computing (FORC).
The Symposium on Foundations of Responsible Computing (FORC) is a forum for mathematical research in computation and society writ large. The Symposium aims to catalyze the formation of a community supportive of the application of theoretical computer science, statistics, economics and other relevant analytical fields to problems of pressing and anticipated societal concern.
Organizers: Cynthia Dwork, Harvard SEAS | Omer Reingold, Stanford | Elisa Celis, Yale
Schedule
June 6, 2022

9:15 am–10:15 am
Opening Remarks
Keynote Speaker: Caroline Nobo, Yale University
Title: From Theory to Impact: Why Better Data Systems are Necessary for Criminal Legal Reform
Abstract: This talk will dive into the messy, archaic, and siloed world of local criminal justice data in America. We will start with a 30,000 foot discussion about the current state of criminal legal data systems, then transition to the challenges of this broken paradigm, and conclude with a call to measure new things – and to measure them better! This talk will leave you with an understanding of criminal justice data infrastructure and transparency in the US, and will discuss how expensive case management software and other technology are built on outdated normative values which impede efforts to reform the system. The result is an infuriating paradox: an abundance of tech products built without theoretical grounding, in a space rich with research and evidence.

10:15 am–10:45 am
Coffee Break

10:45 am–12:15 pm
Paper Session 1
Session Chair: Ruth Urner

Georgy Noarov, University of Pennsylvania
Title: Online Minimax Multiobjective Optimization
Abstract: We introduce a simple but general online learning framework in which a learner plays against an adversary in a vector-valued game that changes every round. The learner’s objective is to minimize the maximum cumulative loss over all coordinates. We give a simple algorithm that lets the learner do almost as well as if she knew the adversary’s actions in advance. We demonstrate the power of our framework by using it to (re)derive optimal bounds and efficient algorithms across a variety of domains, ranging from multicalibration to a large set of no-regret algorithms, to a variant of Blackwell’s approachability theorem for polytopes with fast convergence rates. As a new application, we show how to “(multi)calibeat” an arbitrary collection of forecasters — achieving an exponentially improved dependence on the number of models we are competing against, compared to prior work.

Matthew Eichhorn, Cornell University
Title: Mind your Ps and Qs: Allocation with Priorities and Quotas
Abstract: In many settings, such as university admissions, the rationing of medical supplies, and the assignment of public housing, decision-makers use normative criteria (ethical, financial, legal, etc.) to justify who gets an allocation. These criteria can often be translated into quotas for the number of units available to particular demographics and priorities over agents who qualify in each demographic. Each agent may qualify in multiple categories at different priority levels, so many allocations may conform to a given set of quotas and priorities. Which of these allocations should be chosen? In this talk, I’ll formalize this reserve allocation problem and motivate Pareto efficiency as a natural desideratum. I’ll present an algorithm to locate efficient allocations that conform to the quota and priority constraints. This algorithm relies on beautiful techniques from integer and linear programming, and it is both faster and more straightforward than existing techniques in this space. Moreover, its clean formulation allows for further refinement, such as the secondary optimization of some heuristics for fairness.

Haewon Jeong, Harvard University
Title: Fairness without Imputation: A Decision Tree Approach for Fair Prediction with Missing Values
Abstract: We investigate the fairness concerns of training a machine learning model using data with missing values. Even though there are a number of fairness intervention methods in the literature, most of them require a complete training set as input. In practice, data can have missing values, and data missing patterns can depend on group attributes (e.g. gender or race). Simply applying off-the-shelf fair learning algorithms to an imputed dataset may lead to an unfair model. In this paper, we first theoretically analyze different sources of discrimination risks when training with an imputed dataset. Then, we propose an integrated approach based on decision trees that does not require a separate process of imputation and learning. Instead, we train a tree with missing incorporated as attribute (MIA), which does not require explicit imputation, and we optimize a fairness-regularized objective function. We demonstrate that our approach outperforms existing fairness intervention methods applied to an imputed dataset, through several experiments on real-world datasets.

Emily Diana, University of Pennsylvania
Title: Multiaccurate Proxies for Downstream Fairness
Abstract: We study the problem of training a model that must obey demographic fairness conditions when the sensitive features are not available at training time — in other words, how can we train a model to be fair by race when we don’t have data about race? We adopt a fairness pipeline perspective, in which an “upstream” learner that does have access to the sensitive features will learn a proxy model for these features from the other attributes. The goal of the proxy is to allow a general “downstream” learner — with minimal assumptions on their prediction task — to be able to use the proxy to train a model that is fair with respect to the true sensitive features. We show that obeying multiaccuracy constraints with respect to the downstream model class suffices for this purpose, provide sample- and oracle efficient-algorithms and generalization bounds for learning such proxies, and conduct an experimental evaluation. In general, multiaccuracy is much easier to satisfy than classification accuracy, and can be satisfied even when the sensitive features are hard to predict.

12:15 pm–1:45 pm
Lunch Break

1:45–3:15 pm
Paper Session 2
Session Chair: Guy Rothblum

Elbert Du, Harvard University
Title: Improved Generalization Guarantees in Restricted Data Models
Abstract: Differential privacy is known to protect against threats to validity incurred due to adaptive, or exploratory, data analysis — even when the analyst adversarially searches for a statistical estimate that diverges from the true value of the quantity of interest on the underlying population. The cost of this protection is the accuracy loss incurred by differential privacy. In this work, inspired by standard models in the genomics literature, we consider data models in which individuals are represented by a sequence of attributes with the property that where distant attributes are only weakly correlated. We show that, under this assumption, it is possible to “re-use” privacy budget on different portions of the data, significantly improving accuracy without increasing the risk of overfitting.

Ruth Urner, York University
Title: Robustness Should not be at Odds with Accuracy
Abstract: The phenomenon of adversarial examples in deep learning models has caused substantial concern over their reliability and trustworthiness: in many instances an imperceptible perturbation can falsely flip a neural network’s prediction. Applied research in this area has mostly focused on developing novel adversarial attack strategies or building better defenses against such. It has repeatedly been pointed out that adversarial robustness may be in conflict with requirements for high accuracy. In this work, we take a more principled look at modeling the phenomenon of adversarial examples. We argue that deciding whether a model’s label change under a small perturbation is justified, should be done in compliance with the underlying data-generating process. Through a series of formal constructions, systematically analyzing the the relation between standard Bayes classifiers and robust-Bayes classifiers, we make the case for adversarial robustness as a locally adaptive measure. We propose a novel way defining such a locally adaptive robust loss, show that it has a natural empirical counterpart, and develop resulting algorithmic guidance in form of data-informed adaptive robustness radius. We prove that our adaptive robust data-augmentation maintains consistency of 1-nearest neighbor classification under deterministic labels and thereby argue that robustness should not be at odds with accuracy.

Sushant Agarwal, University of Waterloo
Title: Towards the Unification and Robustness of Perturbation and Gradient Based Explanations
Abstract: As machine learning black boxes are increasingly being deployed in critical domains such as healthcare and criminal justice, there has been a growing emphasis on developing techniques for explaining these black boxes in a post hoc manner. In this work, we analyze two popular post hoc interpretation techniques: SmoothGrad which is a gradient based method, and a variant of LIME which is a perturbation based method. More specifically, we derive explicit closed form expressions for the explanations output by these two methods and show that they both converge to the same explanation in expectation, i.e., when the number of perturbed samples used by these methods is large. We then leverage this connection to establish other desirable properties, such as robustness and linearity, for these techniques. We also derive finite sample complexity bounds for the number of perturbations required for these methods to converge to their expected explanation. Finally, we empirically validate our theory using extensive experimentation on both synthetic and real world datasets.

Tijana Zrnic, University of California, Berkeley
Title: Regret Minimization with Performative Feedback
Abstract: In performative prediction, the deployment of a predictive model triggers a shift in the data distribution. As these shifts are typically unknown ahead of time, the learner needs to deploy a model to get feedback about the distribution it induces. We study the problem of finding near-optimal models under performativity while maintaining low regret. On the surface, this problem might seem equivalent to a bandit problem. However, it exhibits a fundamentally richer feedback structure that we refer to as performative feedback: after every deployment, the learner receives samples from the shifted distribution rather than only bandit feedback about the reward. Our main contribution is regret bounds that scale only with the complexity of the distribution shifts and not that of the reward function. The key algorithmic idea is careful exploration of the distribution shifts that informs a novel construction of confidence bounds on the risk of unexplored models. The construction only relies on smoothness of the shifts and does not assume convexity. More broadly, our work establishes a conceptual approach for leveraging tools from the bandits literature for the purpose of regret minimization with performative feedback.

3:15 pm–3:45 pm
Coffee Break

3:45 pm–5:00 pm
Panel Discussion
Title: What is Responsible Computing?
Panelists: Jiahao Chen, Cynthia Dwork, Kobbi Nissim, Ruth Urner
Moderator: Elisa Celis

June 7, 2022

9:15 am–10:15 am
Keynote Speaker: Isaac Kohane, Harvard Medical School
Title: What’s in a label? The case for and against monolithic group/ethnic/race labeling for machine learning
Abstract: Populations and group labels have been used and abused for thousands of years. The scale at which AI can incorporate such labels into its models and the ways in which such models can be misused are cause for significant concern. I will describe, with examples drawn from experiments in precision medicine, the task dependence of how underserved and oppressed populations can be both harmed and helped by the use of group labels. The source of the labels and the utility models underlying their use will be particularly emphasized.

10:15 am–10:45 am
Coffee Break

10:45 am–12:15 pm
Paper Session 3
Session Chair: Ruth Urner

Rojin Rezvan, University of Texas at Austin
Title: Individually-Fair Auctions for Multi-Slot Sponsored Search
Abstract: We design fair-sponsored search auctions that achieve a near-optimal tradeoff between fairness and quality. Our work builds upon the model and auction design of Chawla and Jagadeesan, who considered the special case of a single slot. We consider sponsored search settings with multiple slots and the standard model of click-through rates that are multiplicatively separable into an advertiser-specific component and a slot-specific component. When similar users have similar advertiser-specific click-through rates, our auctions achieve the same near-optimal tradeoff between fairness and quality. When similar users can have different advertiser-specific preferences, we show that a preference-based fairness guarantee holds. Finally, we provide a computationally efficient algorithm for computing payments for our auctions as well as those in previous work, resolving another open direction from Chawla and Jagadeesan.

Judy Hanwen Shen, Stanford
Title: Leximax Approximations and Representative Cohort Selection
Abstract: Finding a representative cohort from a broad pool of candidates is a goal that arises in many contexts such as choosing governing committees and consumer panels. While there are many ways to define the degree to which a cohort represents a population, a very appealing solution concept is lexicographic maximality (leximax) which offers a natural (pareto-optimal like) interpretation that the utility of no population can be increased without decreasing the utility of a population that is already worse off. However, finding a leximax solution can be highly dependent on small variations in the utility of certain groups. In this work, we explore new notions of approximate leximax solutions with three distinct motivations: better algorithmic efficiency, exploiting significant utility improvements, and robustness to noise. Among other definitional contributions, we give a new notion of an approximate leximax that satisfies a similarly appealing semantic interpretation and relate it to algorithmically-feasible approximate leximax notions. When group utilities are linear over cohort candidates, we give an efficient polynomial-time algorithm for finding a leximax distribution over cohort candidates in the exact as well as in the approximate setting. Furthermore, we show that finding an integer solution to leximax cohort selection with linear utilities is NP-Hard.

Jiayuan Ye,
National University of Singapore
Title: Differentially Private Learning Needs Hidden State (or Much Faster Convergence)
Abstract: Differential privacy analysis of randomized learning algorithms typically relies on composition theorems, where the implicit assumption is that the internal state of the iterative algorithm is revealed to the adversary. However, by assuming hidden states for DP algorithms (when only the last-iterate is observable), recent works prove a converging privacy bound for noisy gradient descent (on strongly convex smooth loss function) that is significantly smaller than composition bounds after a few epochs. In this talk, we extend this hidden-state analysis to various stochastic minibatch gradient descent schemes (such as under “shuffle and partition” and “sample without replacement”), by deriving novel bounds for the privacy amplification by random post-processing and subsampling. We prove that, in these settings, our privacy bound is much smaller than composition for training with a large number of iterations (which is the case for learning from high-dimensional data). Our converging privacy analysis, thus, shows that differentially private learning, with a tight bound, needs hidden state privacy analysis or a fast convergence. To complement our theoretical results, we present experiments for training classification models on MNIST, FMNIST and CIFAR-10 datasets, and observe a better accuracy given fixed privacy budgets, under the hidden-state analysis.

Mahbod Majid, University of Waterloo
Title: Efficient Mean Estimation with Pure Differential Privacy via a Sum-of-Squares Exponential Mechanism
Abstract: We give the first polynomial-time algorithm to estimate the mean of a d-variate probability distribution from O(d) independent samples (up to logarithmic factors) subject to pure differential privacy.
Our main technique is a new approach to use the powerful Sum of Squares method (SoS) to design differentially private algorithms. SoS proofs to algorithms is a key theme in numerous recent works in high-dimensional algorithmic statistics – estimators which apparently require exponential running time but whose analysis can be captured by low-degree Sum of Squares proofs can be automatically turned into polynomial-time algorithms with the same provable guarantees. We demonstrate a similar proofs to private algorithms phenomenon: instances of the workhorse exponential mechanism which apparently require exponential time but which can be analyzed with low-degree SoS proofs can be automatically turned into polynomial-time differentially private algorithms. We prove a meta-theorem capturing this phenomenon, which we expect to be of broad use in private algorithm design.

12:15 pm–1:45 pm
Lunch Break

1:45–3:15 pm
Paper Session 4
Session Chair: Kunal Talwar

Kunal Talwar,
Apple
Title: Differential Secrecy for Distributed Data and Applications to Robust Differentially Secure Vector Summation
Abstract: Computing the noisy sum of real-valued vectors is an important primitive in differentially private learning and statistics. In private federated learning applications, these vectors are held by client devices, leading to a distributed summation problem. Standard Secure Multiparty Computation (SMC) protocols for this problem are susceptible to poisoning attacks, where a client may have a large influence on the sum, without being detected.
In this work, we propose a poisoning-robust private summation protocol in the multiple-server setting, recently studied in PRIO. We present a protocol for vector summation that verifies that the Euclidean norm of each contribution is approximately bounded. We show that by relaxing the security constraint in SMC to a differential privacy like guarantee, one can improve over PRIO in terms of communication requirements as well as the client-side computation. Unlike SMC algorithms that inevitably cast integers to elements of a large finite field, our algorithms work over integers/reals, which may allow for additional efficiencies.

Giuseppe Vietri, University of Minnesota
Title: Improved Regret for Differentially Private Exploration in Linear MDP
Abstract: We study privacy-preserving exploration in sequential decision-making for environments that rely on sensitive data such as medical records. In particular, we focus on solving the problem of reinforcement learning (RL) subject to the constraint of (joint) differential privacy in the linear MDP setting, where both dynamics and rewards are given by linear functions. Prior work on this problem due to Luyo et al. (2021) achieves a regret rate that has a dependence of O(K^{3/5}) on the number of episodes K. We provide a private algorithm with an improved regret rate with an optimal dependence of O(K^{1/2}) on the number of episodes. The key recipe for our stronger regret guarantee is the adaptivity in the policy update schedule, in which an update only occurs when sufficient changes in the data are detected. As a result, our algorithm benefits from low switching cost and only performs O(log(K)) updates, which greatly reduces the amount of privacy noise. Finally, in the most prevalent privacy regimes where the privacy parameter ? is a constant, our algorithm incurs negligible privacy cost — in comparison with the existing non-private regret bounds, the additional regret due to privacy appears in lower-order terms.

Mingxun Zhou,
Carnegie Mellon University
Title: The Power of the Differentially Oblivious Shuffle in Distributed Privacy MechanismsAbstract: The shuffle model has been extensively investigated in the distributed differential privacy (DP) literature. For a class of useful computational tasks, the shuffle model allows us to achieve privacy-utility tradeoff similar to those in the central model, while shifting the trust from a central data curator to a “trusted shuffle” which can be implemented through either trusted hardware or cryptography. Very recently, several works explored cryptographic instantiations of a new type of shuffle with relaxed security, called differentially oblivious (DO) shuffles. These works demonstrate that by relaxing the shuffler’s security from simulation-style secrecy to differential privacy, we can achieve asymptotical efficiency improvements. A natural question arises, can we replace the shuffler in distributed DP mechanisms with a DO-shuffle while retaining a similar privacy-utility tradeoff?
In this paper, we prove an optimal privacy amplification theorem by composing any locally differentially private (LDP) mechanism with a DO-shuffler, achieving parameters that tightly match the shuffle model. Moreover, we explore multi-message protocols in the DO-shuffle model, and construct mechanisms for the real summation and histograph problems. Our error bounds approximate the best known results in the multi-message shuffle-model up to sub-logarithmic factors. Our results also suggest that just like in the shuffle model, allowing each client to send multiple messages is fundamentally more powerful than restricting to a single message.

Badih Ghazi,
Google Research
Title: Differentially Private Ad Conversion Measurement
Abstract: In this work, we study conversion measurement, a central functionality in the digital advertising space, where an advertiser seeks to estimate advertiser site conversions attributed to ad impressions that users have interacted with on various publisher sites. We consider differential privacy (DP), a notion that has gained in popularity due to its strong and rigorous guarantees, and suggest a formal framework for DP conversion measurement, uncovering a subtle interplay between attribution and privacy. We define the notion of an operationally valid configuration of the attribution logic, DP adjacency relation, privacy
budget scope and enforcement point, and provide, for a natural space of configurations, a complete characterization.

3:15 pm–3:45 pm
Coffee Break

3:45 pm–5:00 pm
Open Poster Session

June 8, 2022

9:15 am–10:15 am
Keynote Speaker: Nuria Oliver, Data-Pop Alliance
Title: Data Science against COVID-19
Abstract: In my talk, I will describe the work that I have been doing since March 2020, leading a multi-disciplinary team of 20+ volunteer scientists working very closely with the Presidency of the Valencian Government in Spain on 4 large areas: (1) human mobility modeling; (2) computational epidemiological models (both metapopulation, individual and LSTM-based models); (3) predictive models; and (4) citizen surveys via the COVID19impactsurvey with over 600,000 answers worldwide.
I will describe the results that we have produced in each of these areas, including winning the 500K XPRIZE Pandemic Response Challenge and best paper award at ECML-PKDD 2021. I will share the lessons learned in this very special initiative of collaboration between the civil society at large (through the survey), the scientific community (through the Expert Group) and a public administration (through the Commissioner at the Presidency level). WIRED magazine just published an article describing our story.

10:15 am–10:45 am
Coffee Break

10:45 am–12:15 pm
Paper Session 5
Session Chair: Kunal Talwar

Shengyuan Hu, Carnegie Mellon University
Title: Private Multi-Task Learning: Formulation and Applications to Federated Learning
Abstract: Many problems in machine learning rely on multi-task learning (MTL), in which the goal is to solve multiple related machine learning tasks simultaneously. MTL is particularly relevant for privacy-sensitive applications in areas such as healthcare, finance, and IoT computing, where sensitive data from multiple, varied sources are shared for the purpose of learning. In this work, we formalize notions of task-level privacy for MTL via joint differential privacy (JDP), a relaxation of differential privacy for mechanism design and distributed optimization. We then propose an algorithm for mean-regularized MTL, an objective commonly used for applications in personalized federated learning, subject to JDP. We analyze our objective and solver, providing certifiable guarantees on both privacy and utility. Empirically, our method allows for improved privacy/utility trade-offs relative to global baselines across common federated learning benchmarks

Christina Yu,
Cornell University
Title: Sequential Fair Allocation: Achieving the Optimal Envy-Efficiency Tradeoff Curve
Abstract: We consider the problem of dividing limited resources to individuals arriving over T rounds with a goal of achieving fairness across individuals. In general there may be multiple resources and multiple types of individuals with different utilities. A standard definition of `fairness’ requires an allocation to simultaneously satisfy envy-freeness and Pareto efficiency. However, in the online sequential setting, the social planner must decide on a current allocation before the downstream demand is realized, such that no policy can guarantee these desiderata simultaneously with probability 1, requiring a modified metric of measuring fairness for online policies. We show that in the online setting, the two desired properties (envy-freeness and efficiency) are in direct contention, in that any algorithm achieving additive counterfactual envy-freeness up to L_T necessarily suffers an efficiency loss of at least 1 / L_T. We complement this uncertainty principle with a simple algorithm, HopeGuardrail, which allocates resources based on an adaptive threshold policy and is able to achieve any fairness-efficiency point on this frontier. Our result is the first to provide guarantees for fair online resource allocation with high probability for multiple resource and multiple type settings. In simulation results, our algorithm provides allocations close to the optimal fair solution in hindsight, motivating its use in practical applications as the algorithm is able to adapt to any desired fairness efficiency trade-off.

Hedyeh Beyhaghi, Carnegie Mellon University
Title: On classification of strategic agents who can both game and improve
Abstract: In this work, we consider classification of agents who can both game and improve. For example, people wishing to get a loan may be able to take some actions that increase their perceived credit-worthiness and others that also increase their true credit-worthiness. A decision-maker would like to define a classification rule with few false-positives (does not give out many bad loans) while yielding many true positives (giving out many good loans), which includes encouraging agents to improve to become true positives if possible. We consider two models for this problem, a general discrete model and a linear model, and prove algorithmic, learning, and hardness results for each. For the general discrete model, we give an efficient algorithm for the problem of maximizing the number of true positives subject to no false positives, and show how to extend this to a partial-information learning setting. We also show hardness for the problem of maximizing the number of true positives subject to a nonzero bound on the number of false positives, and that this hardness holds even for a finite-point version of our linear model. We also show that maximizing the number of true positives subject to no false positive is NP-hard in our full linear model. We additionally provide an algorithm that determines whether there exists a linear classifier that classifies all agents accurately and causes all improvable agents to become qualified, and give additional results for low-dimensional data.

Keegan Harris, Carnegie Mellon University
Title: Bayesian Persuasion for Algorithmic Recourse
Abstract: When subjected to automated decision-making, decision subjects may strategically modify their observable features in ways they believe will maximize their chances of receiving a favorable decision. In many practical situations, the underlying assessment rule is deliberately kept secret to avoid gaming and maintain competitive advantage. The resulting opacity forces the decision subjects to rely on incomplete information when making strategic feature modifications. We capture such settings as a game of Bayesian persuasion, in which the decision maker offers a form of recourse to the decision subject by providing them with an action recommendation (or signal) to incentivize them to modify their features in desirable ways. We show that when using persuasion, both the decision maker and decision subject are never worse off in expectation, while the decision maker can be significantly better off. While the decision maker’s problem of finding the optimal Bayesian incentive-compatible (BIC) signaling policy takes the form of optimization over infinitely-many variables, we show that this optimization can be cast as a linear program over finitely-many regions of the space of possible assessment rules. While this reformulation simplifies the problem dramatically, solving the linear program requires reasoning about exponentially-many variables, even under relatively simple settings. Motivated by this observation, we provide a polynomial-time approximation scheme that recovers a near-optimal signaling policy. Finally, our numerical simulations on semi-synthetic data empirically illustrate the benefits of using persuasion in the algorithmic recourse setting.

12:15 pm–1:45 pm
Lunch Break

1:45–3:15 pm
Paper Session 6
Session Chair: Elisa Celis

Mark Bun, Boston University
Title: Controlling Privacy Loss in Sampling Schemes: An Analysis of Stratified and Cluster Sampling
Abstract: Sampling schemes are fundamental tools in statistics, survey design, and algorithm design. A fundamental result in differential privacy is that a differentially private mechanism run on a simple random sample of a population provides stronger privacy guarantees than the same algorithm run on the entire population. However, in practice, sampling designs are often more complex than the simple, data-independent sampling schemes that are addressed in prior work. In this work, we extend the study of privacy amplification results to more complex, data-dependent sampling schemes. We find that not only do these sampling schemes often fail to amplify privacy, they can actually result in privacy degradation. We analyze the privacy implications of the pervasive cluster sampling and stratified sampling paradigms, as well as provide some insight into the study of more general sampling designs.

Samson Zhou, Carnegie Mellon University
Title: Private Data Stream Analysis for Universal Symmetric Norm Estimation
Abstract: We study how to release summary statistics on a data stream subject to the constraint of differential privacy. In particular, we focus on releasing the family of symmetric norms, which are invariant under sign-flips and coordinate-wise permutations on an input data stream and include L_p norms, k-support norms, top-k norms, and the box norm as special cases. Although it may be possible to design and analyze a separate mechanism for each symmetric norm, we propose a general parametrizable framework that differentially privately releases a number of sufficient statistics from which the approximation of all symmetric norms can be simultaneously computed. Our framework partitions the coordinates of the underlying frequency vector into different levels based on their magnitude and releases approximate frequencies for the “heavy” coordinates in important levels and releases approximate level sizes for the “light” coordinates in important levels. Surprisingly, our mechanism allows for the release of an arbitrary number of symmetric norm approximations without any overhead or additional loss in privacy. Moreover, our mechanism permits (1+alpha)-approximation to each of the symmetric norms and can be implemented using sublinear space in the streaming model for many regimes of the accuracy and privacy parameters.

Aloni Cohen, University of Chicago
Title: Attacks on Deidentification’s Defenses
Abstract: Quasi-identifier-based deidentification techniques (QI-deidentification) are widely used in practice, including k-anonymity, ?-diversity, and t-closeness. We present three new attacks on QI-deidentification: two theoretical attacks and one practical attack on a real dataset. In contrast to prior work, our theoretical attacks work even if every attribute is a quasi-identifier. Hence, they apply to k-anonymity, ?-diversity, t-closeness, and most other QI-deidentification techniques.
First, we introduce a new class of privacy attacks called downcoding attacks, and prove that every QI-deidentification scheme is vulnerable to downcoding attacks if it is minimal and hierarchical. Second, we convert the downcoding attacks into powerful predicate singling-out (PSO) attacks, which were recently proposed as a way to demonstrate that a privacy mechanism fails to legally anonymize under Europe’s General Data Protection Regulation. Third, we use LinkedIn.com to reidentify 3 students in a k-anonymized dataset published by EdX (and show thousands are potentially vulnerable), undermining EdX’s claimed compliance with the Family Educational Rights and Privacy Act.
The significance of this work is both scientific and political. Our theoretical attacks demonstrate that QI-deidentification may offer no protection even if every attribute is treated as a quasi-identifier. Our practical attack demonstrates that even deidentification experts acting in accordance with strict privacy regulations fail to prevent real-world reidentification. Together, they rebut a foundational tenet of QI-deidentification and challenge the actual arguments made to justify the continued use of k-anonymity and other QI-deidentification techniques.

Steven Wu,
Carnegie Mellon University
Title: Fully Adaptive Composition in Differential Privacy
Abstract: Composition is a key feature of differential privacy. Well-known advanced composition theorems allow one to query a private database quadratically more times than basic privacy composition would permit. However, these results require that the privacy parameters of all algorithms be fixed before interacting with the data. To address this, Rogers et al. introduced fully adaptive composition, wherein both algorithms and their privacy parameters can be selected adaptively. The authors introduce two probabilistic objects to measure privacy in adaptive composition: privacy filters, which provide differential privacy guarantees for composed interactions, and privacy odometers, time-uniform bounds on privacy loss. There are substantial gaps between advanced composition and existing filters and odometers. First, existing filters place stronger assumptions on the algorithms being composed. Second, these odometers and filters suffer from large constants, making them impractical. We construct filters that match the tightness of advanced composition, including constants, despite allowing for adaptively chosen privacy parameters. We also construct several general families of odometers. These odometers can match the tightness of advanced composition at an arbitrary, preselected point in time, or at all points in time simultaneously, up to a doubly-logarithmic factor. We obtain our results by leveraging recent advances in time-uniform martingale concentration. In sum, we show that fully adaptive privacy is obtainable at almost no loss, and conjecture that our results are essentially not improvable (even in constants) in general.

3:15 pm–3:45 pm
FORC Reception

3:45 pm–5:00 pm
Social Hour

Joint BHI/CMSA Conference on Flat Holography
2022-06-21 09:00 - 2022-06-24 17:00 | CMSA Room G10, CMSA, 20 Garden Street, Cambridge, MA, 02138, United States
On June 21–24, 2022, the Harvard Black Hole Initiative and the CMSA hosted the Joint BHI/CMSA Conference on Flat Holography (and related topics).
The recent discovery of infinitely-many soft symmetries for all quantum theories of gravity in asymptotically flat space has provided a promising starting point for a bottom-up construction of a holographic dual for the real world. Recent developments have brought together previously disparate studies of soft theorems, asymptotic symmetries, twistor theory, asymptotically flat black holes and their microscopic duals, self-dual gravity, and celestial scattering amplitudes, and link directly to AdS/CFT.
The conference was held in room G10 of the CMSA, 20 Garden Street, Cambridge, MA.
Organizers:

Daniel Kapec, CMSA
Andrew Strominger, BHI
Shing-Tung Yau, Harvard & Tsinghua

Confirmed Speakers:

Nima Arkani-Hamed, IAS
Shamik Banerjee, Bhubaneswar, Inst. Phys.
Miguel Campiglia, Republica U., Montevido
Geoffrey Compere, Brussels
Laura Donnay, Vienna
Netta Engelhardt, MIT
Laurent Freidel, Perimeter
Alex Lupsasca, Princeton
Juan Maldacena, IAS
Lionel Mason, Oxford
Natalie Paquette, U. Washington
Sabrina Pasterski, Princeton/Perimeter
Andrea Puhm, Ecole Polytechnique
Ana-Maria Raclariu, Perimeter
Marcus Spradlin, Brown
Tomasz Taylor, Northeastern
Herman Verlinde, Princeton
Anastasia Volovich, Brown
Bin Zhu, Northeastern

Short talks by: Gonçalo Araujo-Regado (Cambridge), Adam Ball (Harvard), Eduardo Casali (Harvard), Jordan Cotler (Harvard), Erin Crawley (Harvard), Stéphane Detournay (Brussels), Alfredo Guevara (Harvard), Temple He (UC Davis), Elizabeth Himwich (Harvard), Yangrui Hu (Brown), Daniel Kapec (Harvard), Rifath Khan (Cambridge), Albert Law (Harvard), Luke Lippstreu (Brown), Noah Miller (Harvard), Sruthi Narayanan (Harvard), Lecheng Ren (Brown), Francisco Rojas (UAI), Romain Ruzziconi (Vienna), Andrew Strominger (Harvard), Adam Tropper (Harvard), Tianli Wang (Harvard), Walker Melton (Harvard)

Schedule
Monday, June 20, 2022

Arrival

7:00–9:00 pm
Welcome Reception at Andy’s residence

Tuesday, June 21, 2022

9:00–9:30 am
Breakfast
light breakfast provided

Morning Session
Chair: Dan Kapec

9:30–10:00 am
Herman Verlinde
Title: Comments on Celestial Dynamics

10:00–10:30 am
Juan Maldacena
Title: What happens when you spend too much time looking at supersymmetric
black holes?

10:30–11:00
Coffee break

11:00–11:30 am
Miguel Campiglia
Title: Asymptotic symmetries and loop corrections to soft theorems

11:30–12:00 pm
Geoffrey Compere
Title: Metric reconstruction from $Lw_{1+infty}$ multipoles
Abstract: The most general vacuum solution to Einstein’s field equations with no incoming radiation can be constructed perturbatively from two infinite sets of canonical multipole moments, which are found to be exchanged under gravitational electric-magnetic duality at the non-linear level. We demonstrate that in non-radiative regions such spacetimes are completely determined by a set of conserved celestial charges, which uniquely label transitions among non-radiative regions caused by radiative processes. The algebra of the conserved celestial charges is derived from the real $Lw_{1+infty}$ algebra. The celestial charges are expressed in terms of multipole moments, which allows to holographically reconstruct the metric in de Donder, Newman-Unti or Bondi gauge outside of sources.

12:00–2:00 pm
Lunch break

Afternoon Session
Chair: Eduardo Casali

2:00–2:30 pm
Natalie Paquette
Title: New thoughts on old gauge amplitudes

2:30–3:00 pm
Lionel Mason
Title: An open sigma model for celestial gravity
Abstract: A global twistor construction for conformally self-dual split signature metrics on $S2times S2$ was developed 15 years ago by Claude LeBrun and the speaker. This encodes the conformal metric into the location of a finite deformation of the real twistor space inside the flat complex twistor space, $mathbb{CP}3$. This talk adapts the construction to construct global SD Einstein metrics from conformal boundary data and perturbations around the self-dual sector. The construction entails determining a family of holomorphic discs in $mathbb{CP}3$ whose boundaries lie on the deformed real slice and the (chiral) sigma model controls these discs in the Einstein case and provides amplitude formulae.

3:00–3:30 pm
Coffee break

3:30–4:30 pm
Short Talks
Daniel Kapec: Soft Scalars and the Geometry of the Space of Celestial CFTs
Albert Law: Soft Scalars and the Geometry of the Space of Celestial CFTs
Sruthi Narayanan: Soft Scalars and the Geometry of the Space of Celestial CFTs
Stéphane Detournay: Non-conformal symmetries and near-extremal black holes
Francisco Rojas: Celestial string amplitudes beyond tree level
Temple He: An effective description of energy transport from holography

4:30–5:00 pm
Nima Arkani-Hamed
(Dual) surfacehedra and flow particles know about strings

Wednesday, June 22, 2022

9:00–9:30 am
Breakfast
light breakfast provided

Morning Session
Chair: Alfredo Guevara

9:30–10:00 am
Laurent Freidel
Title: Higher spin symmetry in gravity
Abstract: In this talk, I will review how the gravitational conservation laws at infinity reveal a tower of symmetry charges in an asymptotically flat spacetime.
I will show how the conservation laws, at spacelike infinity, give a tower of soft theorems that connect to the ones revealed by celestial holography.
I’ll present the expression for the symmetry charges in the radiative phase space, which opens the way to reveal the structure of the algebra beyond the positive helicity sector. Then, if time permits I’ll browse through many questions that these results raise:
such as the nature of the spacetime symmetry these charges represent, the nature of the relationship with multipole moments, and the insights their presence provides for quantum gravity.

10:00–10:30 am
Ana-Maria Raclariu
Title: Eikonal approximation in celestial CFT

10:30–11:00 am
Coffee break

11:00–11:30 am
Anastasia Volovich
Title: Effective Field Theories with Celestial Duals

11:30–12:00 pm
Marcus Spradlin
Title: Loop level gluon OPE’s in celestial holography

12:00–2:00 pm
Lunch break

Afternoon Session
Chair: Chiara Toldo

2:00–2:30 pm
Netta Engelhardt
Title: Wormholes from entanglement: true or false?

2:30–3:00 pm
Short Talks
Luke Lippstreu: Loop corrections to the OPE of celestial gluons
Yangrui Hu: Light transforms of celestial amplitudes
Lecheng Ren: All-order OPE expansion of celestial gluon and graviton primaries from MHV amplitudes

3:00–3:30 pm
Coffee break

3:30–4:30 pm
Short Talks
Noah Miller: C Metric Thermodynamics
Erin Crawley: Kleinian black holes
Rifath Khan: Cauchy Slice Holography: A New AdS/CFT Dictionary
Gonçalo Araujo-Regado: Cauchy Slice Holography: A New AdS/CFT Dictionary
Tianli Wang: Soft Theorem in the BFSS Matrix Model
Adam Tropper: Soft Theorem in the BFSS Matrix Model

7:00–9:00 pm
Banquet
Maharaja Restaurant, 57 JFK Street, Cambridge, MA

Thursday, June 23, 2022

9:00–9:30 am
Breakfast
light breakfast provided

Morning Session
Chair: Jordan Cotler

9:30–10:00 am
Laura Donnay
Title: A Carrollian road to flat space holography

10:00–10:30 am
Andrea Puhm
Title: Celestial wave scattering on Kerr-Schild backgrounds

10:30–11:00 am
Coffee break

11:00–11:30 am
Sabrina Pasterski
Title: Mining Celestial Symmetries
Abstract: The aim of this talk is to delve into the common thread that ties together recent work with H. Verlinde, L. Donnay, A. Puhm, and S. Banerjee exploring, explaining, and exploiting the symmetries encoded in the conformally soft sector.
Come prepared to debate the central charge, loop corrections, contour prescriptions, and orders of limits!

11:30–12:00 pm
Shamik Banerjee
Title: Virasoro and other symmetries in CCFT
Abstract: In this talk I will briefly describe my ongoing work with Sabrina Pasterski. In this work we revisit the standard construction of the celestial stress tensor as a shadow of the subleading conformally soft graviton. In its original formulation, we find that there is an obstruction to reproducing the expected $TT$ OPE in the double soft limit. This obstruction is related to the existence of the $SL_2$ current algebra symmetry of the CCFT. We propose a modification to the definition of the stress tensor which circumvents this obstruction and also discuss its implications for the existence of other current algebra (w_{1+infty}) symmetries in CCFT.

12:00–2:00 pm
Lunch break

Afternoon Session
Chair: Albert Law

2:00–2:30 pm
Tomasz Taylor
Title: Celestial Yang-Mills amplitudes and D=4 conformal blocks

2:30–3:00 pm
Bin Zhu
Title: Single-valued correlators and Banerjee-Ghosh equations
Abstract: Low-point celestial amplitudes are plagued with singularities resulting from spacetime translation. We consider a marginal deformation of the celestial CFT which is realized by coupling Yang-Mills theory to a background dilaton field, with the (complex) dilaton source localized on the celestial sphere. This picture emerges from the physical interpretation of the solutions of the system of differential equations discovered by Banerjee and Ghosh. We show that the solutions can be written as Mellin transforms of the amplitudes evaluated in such a dilaton background. The resultant three-gluon and four-gluon amplitudes are single-valued functions of celestial coordinates enjoying crossing symmetry and all other properties expected from standard CFT correlators.

3:00–3:30 pm
Coffee break

3:30–4:00 pm
Alex Lupsasca
Title: Holography of the Photon Ring

4:00–5:30 pm
Short Talks
Elizabeth Himwich: Celestial OPEs and w(1+infinity) symmetry of massless and massive amplitudes
Adam Ball: Perturbatively exact $w_{1+infty}$ asymptotic symmetry of quantum self-dual gravity
Romain Ruzziconi: A Carrollian Perspective on Celestial Holography
Jordan Cotler: Soft Gravitons in 3D
Alfredo Guevara: Comments on w_1+inf
Andrew Strominger: Top-down celestial holograms
Eduardo Casali: Celestial amplitudes as AdS-Witten diagrams
Walker Melton: Top-down celestial holograms

Friday, June 24, 2022

9:00–9:30 am
Breakfast

9:30–12:30 pm
Open Discussion

12:30–2:30 pm
Lunch provided at the BHI

Departure

Advances in Mathematical Physics
2022-07-30 09:00 - 2022-08-01 13:45 | Harvard Science Center, 1 Oxford Street, Cambridge, MA, 02138
A Conference in Honor of Elliott H. Lieb on his 90th Birthday
On July 30 – Aug 1, 2022 the Harvard Mathematics Department and the CMSA co-hosted a birthday conference in honor of Elliott Lieb.
This meeting highlights Elliott’s vast contribution to math and physics. Additionally, this meeting features Prof. Lieb’s more recent impact in strong subadditivity of entropy and integrable systems (ice model, Temperley-Lieb algebra etc.).
Venue:
July 30–31, 2022: Hall B, Science Center, 1 Oxford Street, Cambridge, MA, 02138
August 1, 2022: Hall C, Science Center, 1 Oxford Street, Cambridge, MA, 02138
Schedule (pdf)
Organizers:
Michael Aizenman, Princeton University
Joel Lebowitz, Rutgers University
Ruedi Seiler, Technische Universität Berlin
Herbert Spohn, Technical University of Munich
Horng-Tzer Yau, Harvard University
Shing-Tung Yau, Harvard University
Jakob Yngvason, University of Vienna
SPEAKERS:
Rafael Benguria, Pontificia Universidad Catolica de Chile
Eric Carlen, Rutgers University
Philippe Di Francesco, University of Illinois
Hugo Duminil-Copin, IHES
László Erdös, Institute of Science and Technology Austria
Rupert Frank, Ludwig Maximilian University of Munich
Jürg Fröhlich, ETH Zurich
Alessandro Giuliani, Università degli Studi Roma Tre
Bertrand Halperin, Harvard University
Klaus Hepp, Institute for Theoretical Physics, ETH Zurich
Sabine Jansen, Ludwig Maximilian University of Munich
Mathieu Lewin, Université Paris-Dauphine
Bruno Nachtergaele, The University of California, Davis
Yoshiko Ogata, University of Tokyo
Ron Peled, Tel Aviv University
Benjamin Schlein, University of Zurich
Robert Seiringer, Institute of Science and Technology Austria
Jan Philip Solovej, University of Copenhagen
Hal Tasaki, Gakushuin University
Simone Warzel, Technical University of Munich
Jun Yin, The University of California, Los Angeles

Phase Transitions and Topological Defects in the Early Universe
2022-08-02 09:00 - 2022-08-05 17:00 | CMSA Room G10, CMSA, 20 Garden Street, Cambridge, MA, 02138, United States
On August 2–5, the CMSA hosted a workshop on Phase Transitions and Topological Defects in the Early Universe.
The workshop was held in room G10 of the CMSA, located at 20 Garden Street, Cambridge, MA and online via Zoom webinar.
The next decade will see a wealth of new cosmological data, which can lead to new insights into fundamental physics. Upcoming facilities (such as LISA) will be able to probe signals of fascinating phenomena in the early universe. These include signals from “Phase Transitions and Topological Defects,” which are ubiquitously given rise to in well-motivated UV models. In-depth studies of such signals requires cross-talks between experts from a wide spectrum of fields.
The workshop aims to provide a platform for efficient exchange of new ideas related to these topics. It will start with an overview of some of the past and future experimental efforts. Next, there will be a substantial number of talks probing different aspects of phenomenology of phase transitions and topological defects in the early universe. It will finally close with discussions on recent formal development in the field.
Scientific Advisory: Julian B. Muñoz, Lisa Randall, Matthew Reece, Tracy Slatyer, Shing-Tung Yau
Organizers:
Harvard: Nick DePorzio, Katie Fraser, Sam Homiller, Rashmish Mishra, & Aditya Parikh
MIT: Pouya Asadi, Marianne Moore, & Yitian Sun
Schedule/Format
There will be 20+ 10 minute talks, ample discussion time, and lightning chalkboard talks.
Speakers:

Nancy Aggarwal (Northwestern)
Jae Hyeok Chang (UMD – JHU)
Yanou Cui (UC Riverside)
David Dunsky (UC Berkeley)
Isabel Garcia-Garcia (KITP – UCSB)
Oliver Gould (Nottingham)
Yann Gouttenoire (Tel Aviv)
Eleanor Hall (UC Berkeley)
Sungwoo Hong (Chicago)
Anson Hook (UMD)
Jessica Howard (UC Irvine)
Seth Koren (Chicago)
Mrunal Korwar (Wisconsin)
Soubhik Kumar (UC Berkeley)
Vuk Mandic (Minnesota)
Yuto Minami (Osaka)
Michael Nee (Oxford)
Kai Schmitz (CERN)
Stephen R. Taylor (Vanderbilt)
Ofri Telem (UC Berkeley)
Juven Wang (Harvard)
Yikun Wang (Caltech)

Participants:

Manuel Buen Abad (UMD)
Pouya Asadi (MIT)
Sean Benevedes (MIT)
Sandipan Bhattacherjee (Birla Institute of Technology Mesra Ranchi India)
Xingang Chen (Harvard University)
Nicholas DePorzio (Harvard University)
Peizhi Du (Stony Brook University)
Nicolas Fernandez (University of Illinois Urbana-Champaign)
Joshua Foster (MIT)
Katherine Fraser (Harvard University)
Sarah Geller (MIT)
Aurora Ireland (University of Chicago)
Marius Kongsore (New York University)
Ho Tat Lam (Massachusetts Institute of Technology)
Lingfeng Li (Brown University)
Yingying Li (Fermilab)
Gustavo Marques-Tavares (UMD)
Rashmish Mishra (Harvard University)
Siddharth Mishra-Sharma (MIT/Harvard University)
Toby Opferkuch (UC Berkeley)
Tong Ou (University of Chicago)
Aditya Parikh (Harvard University)
Yitian Sun (MIT)
Juan Sebastian Valbuena-Bermudez (Ludwig Maximilian University of Munich and Max Planck Institute for Physics)
Isaac Wang (Rutgers)
Wei Xue (University of Florida)
Winston Yin (UC Berkeley)
Quratulain Zahoor (The Islamia University of Bahwalpur Punjab (Pakistan)

Schedule
Tuesday, August 2, 2022

9:00–9:20 am
Breakfast

9:20–9:30 am
Rashmish Mishra
Opening Remarks

9:30–10:00 am
Vuk Mandic
Title: Searching for the Stochastic Gravitational Wave Background with LISA
Abstract: The upcoming space-borne gravitational wave detector Laser Interferometer Space Antenna (LISA) will open a window into the milliHertz band of the gravitational wave spectrum. Among the many sources in this band is the stochastic gravitational wave background (SGWB), arising as an incoherent superposition of many uncorrelated gravitational wave sources. The SGWB could be of cosmological origin, carrying unique information about the physical processes that took place within the first minute after the big bang, including possible phase transitions and topological defects. LISA therefore has the potential to illuminate particle physics at very high energy scales that may be inaccessible in laboratories. I will discuss how LISA can be used to search for the SGWB, highlighting a new pipeline developed for this purpose as well as several challenges and limitations that such a search will encounter.

10:00–10:30 am
Nancy Aggarwal
Title: Gravitational waves at frequencies above 10 kHz
Abstract: Gravitational waves (GWs) at frequencies higher than the LIGO band can bring us completely new information about the universe. Besides being the most-interesting frequency region for looking at cosmological phenomena, they can also convey signatures of ultralight bosons through blackhole superradiance and light primordial blackholes (PBHs). I will introduce a new global initiative to study GW sources and detectors at ultra-high-frequencies (MHz-GHz), as well as a new experiment at Northwestern University to look for GWs in the frequency band of 10 kHz to 300 kHz using levitated optomechanical sensors. I will summarize the design, the current experimental progress, as well as a path forward for future improvements.

10:30–11:00 am
Yuto Minami
Title: New measurements of the cosmic birefringence
Abstract: Polarised light of the cosmic microwave background, the remnant light of the Big Bang, is sensitive to parity-violating physics, cosmic birefringence. In this presentation I report on a new measurement of cosmic birefringence from polarisation data of the European Space Agency (ESA)’s Planck satellite released in 2018. The statistical significance of the measured signal is 2.4 sigma. Recently, we found a signal with 3.3 sigma statistical significance when we use the latest Planck data and consider an effect of polarised foreground emission. If confirmed with higher statistical significance in future, it would have important implications for the elusive nature of dark matter and dark energy.

11:00–1:30 pm
Break

1:30–3:00 pm
Lighting Talks 1
Lingfeng Li
Winston Yin
Marius Kongsore
Nick DePorzio

3:00–3:30 pm
Jae Hyeok Chang
Title: Correlating gravitational wave and gamma-ray signals from primordial black holes
Abstract: Asteroid-mass primordial black holes (PBHs) can explain the observed dark matter abundance while being consistent with the current indirect detection constraints. These PBHs can produce gamma-ray signals from Hawking radiation that are within the sensitivity of future measurements by the AMEGO and e-ASTROGAM experiments. PBHs which give rise to such observable gamma-ray signals have a cosmic origin from large primordial curvature fluctuations. There must then be a companion, stochastic gravitational wave (GW) background produced by the same curvature fluctuations. I will demonstrate that the resulting GW signals will be well within the sensitivity of future detectors such as LISA, DECIGO, BBO, and the Einstein Telescope. The multimessenger signal from the observed gamma-rays and GWs will allow a precise measurement of the primordial curvature perturbation that produces the PBH. I will also argue that the resulting correlation between the two types of observations can provide a smoking-gun signal of PBHs.

3:30–4:00 pm
Anson Hook
(Virtual via Zoom)
Title: Early Universe Cosmology from Stochastic Gravitational Waves
Abstract: The causal tail of stochastic gravitational waves can be used to probe the energy density in free streaming relativistic species as well as measure gstar and beta functions as a function of temperature. In the event of the discovery of loud stochastic gravitational waves, we demonstrate that LISA can measure the free streaming fraction of the universe down to the 10^-3 level, 100 times more sensitive than current constraints. Additionally, it would be sensitive to O(1) deviations of gstar and the QCD beta function from their Standard Model value at temperatures ~ 10^5 GeV. In this case, many motivated models such as split SUSY and other solutions to the Electroweak Hierarchy problem would be tested. Future detectors, such as DECIGO, would be 100 times more sensitive than LISA to these effects and be capable of testing other motivated scenarios such as WIMPs and axions. The amazing prospect of using precision gravitational wave measurements to test such well motivated theories provides a benchmark to aim for when developing a precise understanding of the gravitational wave spectrum both experimentally and theoretically.

Wednesday, August 3, 2022

9:00–9:30 am
Breakfast

9:30–10:00 am
Kai Schmitz
(Virtual via Zoom)
Title: Gravitational waves from metastable cosmic strings
Abstract: Cosmic strings are predicted by many Standard Model extensions involving the cosmological breaking of an Abelian symmetry and represent a potential source of primordial gravitational waves (GWs). In many Grand Unified Theories (GUTs), cosmic strings especially turn out to be metastable, as the nucleation of GUT monopoles along strings after a finite lifetime eventually leads to the collapse of the entire string network. In this talk, I will discuss the theoretical description of such a network and its individual components as well as the consequences for the emitted GW spectrum. Remarkably, the GW signal from metastable strings may well explain the common-spectrum process recently observed in pulsar timing data, while at the same time and in contrast to stable cosmic strings predicting a signal at higher frequencies that is still within the reach of current-generation ground-based interferometers. On their way to design sensitivity, existing GW experiments will thus have a realistic chance to probe particle physics processes at energies close to the GUT scale via the observation of GWs from metastable strings. This talk is based on 2107.04578 in collaboration with Wilfried Buchmüller and Valerie Domcke.

10:00–10:30 am
Oliver Gould
(Virtual via Zoom)
Title: Effective field theory for cosmological phase transitions
Abstract: Phase transitions are driven by thermal loop fluctuations, which modify background fields at leading order. This breaks the loop expansion and leads to large theoretical uncertainties in typical calculations, especially for gravitational wave predictions. I will give an overview of our present understanding of these uncertainties, and of the tools that have been developed to overcome them. Effective field theory has been at the forefront of this development, and I will outline how it can be used to solve a number of decades-long-standing theoretical problems.

10:30–11:00 am
Isabel Garcia-Garcia
Title: The Rocket Science of Expanding Bubbles

11:00–1:30 pm
Break

1:30–3:00 pm
Lightning Talks 2
Sarah Geller
Peizhi Du
Tong Ou
Isaac Wang
Katie Fraser

3:00–3:30 pm
David Dunsky
(Virtual via Zoom)
Title: Gravitational Wave Gastronomy
Abstract: The symmetry breaking of grand unified gauge groups in the early universe often leaves behind relic topological defects such as cosmic strings, domain walls, or monopoles. For some symmetry breaking chains, hybrid defects can form where cosmic strings attach to domain walls or monopoles attach to strings. In general, such hybrid defects are unstable and can leave behind unique gravitational wave fingerprints. In this talk, I will discuss the gravitational wave spectrum from 1) the destruction of a cosmic string network by the nucleation of monopoles which cut up and “eat” the strings, 2) the collapse and decay of a monopole-string network by strings that “eat” the monopoles, 3) the destruction of a domain wall network by the nucleation of string-bounded holes on the wall that expand and “eat” the wall, and 4) the collapse and decay of a string-bounded wall network by walls that “eat” the strings. We call the gravitational wave signals produced from the “eating” of one topological defect by another “gravitational wave gastronomy”. The gravitational wave gastronomy signals considered yield unique spectra that can be used to narrow down the SO(10) symmetry breaking chain to the Standard Model and the scales of symmetry breaking associated with the consumed topological defects.

3:30–4:00 pm
Yanou Cui
(Virtual via Zoom)
Title: Cosmic Archaeology with gravitational waves from (axion) cosmic strings
Abstract: In this talk I will discuss important aspects of cosmology and particle physics that can be probed with GW signals from cosmic strings: probing the pre-BBN primordial dark age and axion physics. Gravitational waves (GWs) originating from the dynamics of a cosmic string network have the ability to probe many otherwise inaccessible properties of the early universe. In particular, I will discuss how the frequency spectrum of a stochastic GW background (SGWB) from a cosmic string network can be used to probe Hubble expansion rate of the early universe prior to Big Bang Nucleosynthesis (BBN), during the “primordial dark age”. Furthermore I will show that in contrast to the standard expectation, cosmic strings formed before inflation could regrow back into the horizon and leave imprints, with GW bursts potentially being the leading signal. In relation to axion physics I will also demonstrate the detection prospect for SGWB from global/axion strings which may provide a new probe for axion-like dark matter models, considering various scenarios of cosmic history.

4:00–4:30 pm
Michael Nee
Title: The Boring Monopole
Abstract: First order phase transitions play an important role in the cosmology of many theories of BSM physics. In this talk I will discuss how a population of magnetic monopoles present in the early universe can seed first order phase transitions, causing them to proceed much more rapidly than in the usual case. The field profiles describing the decay do not have the typically assumed O(3)/O(4) symmetry, thus requiring an extension of the usual decay rate calculation. To numerically determine the saddle point solutions which describe the decay we use a new algorithm based on the mountain pass theorem. Our results show that monopole-catalysed tunnelling can dominate over the homogeneous decay for a wide range of parameters.

Thursday, August 4, 2022

9:00–9:30 am
Breakfast

9:30–10:00 am
Yikun Wang
Title: A New Approach to Electroweak Symmetry Non-Restoration
Abstract: Electroweak symmetry non-restoration up to high temperatures well above the electroweak scale has intriguing implications for (electroweak) baryogenesis and early universe thermal histories. In this talk, I will discuss such a possible fate of the electroweak symmetry in the early universe and a new approach to realize it, via an inert Higgs sector that couples to the Standard Model Higgs as well as an extended scalar singlet sector. Examples of benchmark scenarios that allow for electroweak symmetry non-restoration all the way up to hundreds of TeV temperatures, at the same time featuring suppressed sphaleron washout factors down to the electroweak scale, will be presented. Renormalization group improvements and thermal resummation, necessary to evaluate the effective potential spanning over a broad range of energy scales and temperatures, have been implemented calculating the thermal history. This method for transmitting the Standard Model broken electroweak symmetry to an inert Higgs sector can be scrutinized through Higgs physics phenomenology and electroweak precision measurements at the HL-LHC.

10:00–10:30 am
Soubhik Kumar
Title: Probing primordial fluctuations through stochastic gravitational wave background anisotropies
Abstract: Stochastic gravitational wave backgrounds are expected to be anisotropic. While such anisotropies can be of astrophysical origin, a cosmological component of such anisotropies can carry rich information about primordial perturbations. Focusing on the case of a cosmological phase transition, I will talk about how such anisotropies can give us a powerful probe of primordial non-Gaussianities, complementary to current and future CMB and LSS searches. In the scenario where astrophysical foregrounds are also present, I will then discuss some strategies using which we can extract the cosmological signal, focusing on the case of LISA, Taiji and BBO, in particular.

10:30–11:00 am
Jessica Howard
(Virtual via Zoom)
Title: Dark Matter Freeze-out during SU(2)_L Confinement
Abstract: We explore the possibility that dark matter is a pair of SU(2)_L doublets and propose a novel mechanism of dark matter production that proceeds through the confinement of the weak sector of the Standard Model. This phase of confinement causes the Standard Model doublets and dark matter to confine into pion-like objects. Before the weak sector deconfines, the dark pions freezeout and generate a relic abundance of dark matter. We solve the Boltzmann equations for this scenario to determine the scale of confinement and constituent dark matter mass required to produce the observed relic density. We determine which regions of this parameter space evade direct detection and collider bounds.

11:00–11:30 am
Juven Wang
Title: Quantum Matter Adventure to Beyond the Standard Model Prediction
Abstract: Ideas developed from the quantum matter and quantum field theory frontier may guide us to explore new physics beyond the 4d Standard Model. I propose a few such ideas. First, new physics for neutrinos: right-handed neutrinos carry a Z_{16} class mixed gauge-gravitational global anomaly index, which could be replaced by 4d or 5d topological quantum field theory, or 4d interacting conformal field theory. These theories provide possible new neutrino mass mechanisms [arXiv:2012.15860]. Second, deconfined quantum criticality between Grand Unified Theories: dictated by a Z_2 class global anomaly, a gapless quantum critical region can happen between Georgi-Glashow and Pati-Salam models as deformation of the Standard Model, where Beyond the Standard Model physics and Dark Gauge sector occur as neighbor phases [arXiv:2106.16248, arXiv:2112.14765, arXiv:2204.08393]. Third, the Strong CP problem can be solved by a new solution involving Symmetric Mass Generation [arXiv:2204.14271].

11:30–1:30 pm
Break

1:30–4:00 pm
Stephen R. Taylor
Title: Pulsar Timing Arrays: The Next Window onto the Low-frequency Gravitational-wave Universe
Abstract: The nanohertz-frequency band of gravitational waves should be awash with signals from supermassive black-hole binaries, as well as cosmological signatures of phase transitions, cosmic strings, and other relics of the early Universe. Pulsar-timing arrays (PTAs) like the North American Nanohertz Observatory for Gravitational waves (NANOGrav) and the International Pulsar Timing Array are poised to chart this new frontier of gravitational wave discovery within the next several years. I will present exciting new results from recent cutting-edge searches, discuss some milestones on the road to the next decade of PTA discovery, and take workshop attendees through a guided tutorial of how the broader community can use our production-level analysis pipeline to extract new science with ease.

Friday, August 5, 2022

9:00–9:30 am
Breakfast

9:30–10:00 am
Ofri Telem
Title: Charge-Monopole Pairwise Phases from Dressed Quantum States

10:00–10:30 am
Sungwoo Hong
Title: Coupling a Cosmic String to a TQFT
Abstract: In the last few years, the notion of symmetry has been enlarged to “generalized symmetry” or “higher-form symmetry” and these more generalized symmetries have played a critical role in deepening our understanding of QFT, notably IR phases of QFT. In this talk, I will discuss a various ways of coupling the axion-Maxwell theory to a topological field theory (TQFT). Contrary to a common wisdom, I will show that such topological modifications can lead to direct changes in the local physics with possible observable consequences. This surprise can be realized by a dimensional reduction, namely, a coupling to a TQFT in 4d leads to a non-trivial and local impact on the 2d string world-sheet QFT. There also exists a topological modification of the theory, i.e. gauging a discrete subgroup of 0-form shift symmetry, and this time it results in a alteration of spectrum of cosmic strings. If time permits, I will also discuss generalized symmetries and associated higher-groups of these theories.

10:30–11:00 am
Eleanor Hall
(Virtual via Zoom)
Title: Non-perturbative methods for false vacuum decay
Abstract: Gravitational waves from phase transitions in the early universe are one of our most promising signal channels of BSM physics; however, existing methods for predicting these signals are limited to weakly-coupled theories. In this talk, I present the quasi-stationary effective action, a new non-perturbative formalism for false vacuum decay that integrates over local fluctuations in field space using the functional renormalization group. This method opens the door to reliable calculation of gravitational wave signals and false vacuum decay rates for strongly-interacting theories. I will also discuss recent developments and ongoing extensions of the QSEA.

11:00–1:30 pm
Break

1:30–2:00 pm
Mrunal Korwar
Title: Electroweak Symmetric Balls
Abstract: Electroweak symmetric balls are macroscopic objects with electroweak symmetry restored inside. Such an object can arise in models where dark sectors contain monopole or non-topological soliton with a Higgs portal interaction to the Standard Model. It could be produced in the early universe via phase transition or parametric resonance, accounting for all dark matter. In a scenario where the balls are allowed to evaporate, the observed baryon asymmetry in our universe could be explained by a mechanism of “catalyzed baryogenesis.” In this mechanism, the motion of a ball-like catalyst provides the necessary out-of-equilibrium condition, its outer wall has CP-violating interactions with the Standard Model particles, and its interior has baryon number violating interactions via electroweak Sphaleron. Because of electroweak symmetric cores, such objects have a large geometric cross-section off a nucleus, generating a multi-hit signature in large volume detectors. These objects could radiatively capture a nucleus and release GeV-scale energy for each interaction. The IceCube detector can probe dark matter balls with masses up to a gram.

2:00–2:30 pm
Seth Koren
Title: Discrete Gauged Baryon Minus Lepton Number and the Cosmological Lithium Problem
Abstract: We study the baryon minus lepton number gauge theory broken by a scalar with charge six. The infrared discrete vestige of the gauge symmetry demands the existence of cosmic string solutions, and their production as dynamical objects in the early universe is guaranteed by causality. These topological defects can support interactions which convert three protons into three positrons, and we argue an `electric’-`magnetic’ interplay can lead to an amplified, strong-scale cross-section in an analogue of the Callan-Rubakov effect.
The cosmological lithium problem—that theory predicts a primordial abundance thrice as high as that observed—has resisted decades of attempts by cosmologists, nuclear physicists, and astronomers alike to root out systematics. We suggest cosmic strings have disintegrated O(1) of the primordial lithium nuclei and estimate the rate in a benchmark scenario. To our knowledge this is the first new physics mechanism with microphysical justification for the abundance of lithium uniquely to be modified after Big Bang Nucleosynthesis.

2:30–3:00 pm
Yann Gouttenoire
Title: Supercool Composite Dark Matter beyond 100 TeV

Big Data Conference 2022
2022-08-26 09:00 - 13:00 | Virtual
On August 26, 2022 the CMSA hosted our eighth annual Conference on Big Data. The Big Data Conference features speakers from the Harvard community as well as scholars from across the globe, with talks focusing on computer science, statistics, math and physics, and economics.
The 2022 Big Data Conference took place virtually on Zoom.
Organizers:

Scott Duke Kominers, MBA Class of 1960 Associate Professor, Harvard Business
Horng-Tzer Yau, Professor of Mathematics, Harvard University
Sergiy Verstyuk, CMSA, Harvard University

Speakers:

Xiaohong Chen, Yale
Miles Cranmer, Princeton
Jessica Jeffers, University of Chicago
Dan Roberts, MIT

Schedule

9:00 am
Conference Organizers
Introduction and Welcome

9:10 am – 9:55 am
Xiaohong Chen
Title: On ANN optimal estimation and inference for policy functionals of nonparametric conditional moment restrictions
Abstract: Many causal/policy parameters of interest are expectation functionals of unknown infinite-dimensional structural functions identified via conditional moment restrictions. Artificial Neural Networks (ANNs) can be viewed as nonlinear sieves that can approximate complex functions of high dimensional covariates more effectively than linear sieves. In this talk we present ANN optimal estimation and inference on policy functionals, such as average elasticities or value functions, of unknown structural functions of endogenous covariates. We provide ANN efficient estimation and optimal t based confidence interval for regular policy functionals such as average derivatives in nonparametric instrumental variables regressions. We also present ANN quasi likelihood ratio based inference for possibly irregular policy functionals of general nonparametric conditional moment restrictions (such as quantile instrumental variables models or Bellman equations) for time series data. We conduct intensive Monte Carlo studies to investigate computational issues with ANN based optimal estimation and inference in economic structural models with endogeneity. For economic data sets that do not have very high signal to noise ratios, there are current gaps between theoretical advantage of ANN approximation theory vs inferential performance in finite samples.
Some of the results are applied to efficient estimation and optimal inference for average price elasticity in consumer demand and BLP type demand.
The talk is based on two co-authored papers:
(1) Efficient Estimation of Average Derivatives in NPIV Models: Simulation Comparisons of Neural Network Estimators
(Authors: Jiafeng Chen, Xiaohong Chen and Elie Tamer)
https://arxiv.org/abs/2110.06763
(2) Neural network Inference on Nonparametric conditional moment restrictions with weakly dependent data
(Authors: Xiaohong Chen, Yuan Liao and Weichen Wang).
View/Download Lecture Slides (pdf)

10:00 am – 10:45 am
Jessica Jeffers
Title: Labor Reactions to Credit Deterioration: Evidence from LinkedIn Activity
Abstract: We analyze worker reactions to their firms’ credit deterioration. Using weekly networking activity on LinkedIn, we show workers initiate more connections immediately following a negative credit event, even at firms far from bankruptcy. Our results suggest that workers are driven by concerns about both unemployment and future prospects at their firm. Heightened networking activity is associated with contemporaneous and future departures, especially at financially healthy firms. Other negative events like missed earnings and equity downgrades do not trigger similar reactions. Overall, our results indicate that the build-up of connections triggered by credit deterioration represents a source of fragility for firms.

10:50 am – 11:35 am
Miles Cranmer
Title: Interpretable Machine Learning for Physics
Abstract: Would Kepler have discovered his laws if machine learning had been around in 1609? Or would he have been satisfied with the accuracy of some black box regression model, leaving Newton without the inspiration to discover the law of gravitation? In this talk I will explore the compatibility of industry-oriented machine learning algorithms with discovery in the natural sciences. I will describe recent approaches developed with collaborators for addressing this, based on a strategy of “translating” neural networks into symbolic models via evolutionary algorithms. I will discuss the inner workings of the open-source symbolic regression library PySR (github.com/MilesCranmer/PySR), which forms a central part of this interpretable learning toolkit. Finally, I will present examples of how these methods have been used in the past two years in scientific discovery, and outline some current efforts.
View/Download Lecture Slides (pdf)

11:40 am – 12:25 pm
Dan Roberts
Title: A Statistical Model of Neural Scaling Laws
Abstract: Large language models of a huge number of parameters and trained on near internet-sized number of tokens have been empirically shown to obey “neural scaling laws” for which their performance behaves predictably as a power law in either parameters or dataset size until bottlenecked by the other resource. To understand this better, we first identify the necessary properties allowing such scaling laws to arise and then propose a statistical model — a joint generative data model and random feature model — that captures this neural scaling phenomenology. By solving this model using tools from random matrix theory, we gain insight into (i) the statistical structure of datasets and tasks that lead to scaling laws (ii) how nonlinear feature maps, i.e the role played by the deep neural network, enable scaling laws when trained on these datasets, and (iii) how such scaling laws can break down, and what their behavior is when they do. A key feature is the manner in which the power laws that occur in the statistics of natural datasets are translated into power law scalings of the test loss, and how the finite extent of such power laws leads to both bottlenecks and breakdowns.
View/Download Lecture Slides (pdf)

12:30 pm
Conference Organizers
Closing Remarks

Information about last year’s conference can be found here.

CMSA/MATH Fall Gathering
2022-09-23 04:30 - 18:00 | Harvard Science Center, 1 Oxford Street, Cambridge, MA, 02138
CMSA/MATH Fall Gathering
Friday, Sep 23, 2022
4:30–6:00 pm

All CMSA and Math affiliates are invited.

CMSA/Tsinghua Math-Science Literature Lecture: Large cardinals and small sets: The AD+ Duality Program
2022-11-09 09:30 - 11:00 | CMSA Room G10, CMSA, 20 Garden Street, Cambridge, MA, 02138, United States
CMSA/Tsinghua Math-Science Literature Lecture

Prof. Hugh Woodin will present a lecture in the CMSA/Tsinghua Math-Science Literature Lecture Series.
Date: Wednesday, November 9, 2022
Time: 9:30 – 11:00 am ET
Location: Via Zoom Webinar and Room G10, CMSA, 20 Garden Street, Cambridge MA 02138

Title: Large cardinals and small sets: The AD+ Duality Program
Abstract: The determinacy axiom, AD, was introduced by Mycielski and Steinhaus over 60 years ago as an alternative to the Axiom of Choice for the study of arbitrary sets of real numbers. The modern view is that determinacy axioms concern generalizations of the borel sets, and deep connections with large cardinal axioms have emerged.
The study of determinacy axioms has led to a specific technical refinement of AD, this is the axiom AD+. The further connections with large axioms have in turn implicitly led to a duality program, this is the AD+ Duality Program.
The main open problems here are intertwined with those of the Inner Model Program, which is the central program in the study of large cardinal axioms.
This has now all been distilled into a series of specific conjectures.

Talk chair: Horng-Tzer Yau (Harvard Mathematics & CMSA)
Moderator: Alejandro Poveda Ruzafa (Harvard CMSA)

Beginning in Spring 2020, the CMSA began hosting a lecture series on literature in the mathematical sciences, with a focus on significant developments in mathematics that have influenced the discipline, and the lifetime accomplishments of significant scholars.

CMSA COVID-19 Policies

Representation Theory, Calabi–Yau Manifolds, and Mirror Symmetry
2022-11-28 09:00 - 2022-12-01 15:30 | CMSA Room G10, CMSA, 20 Garden Street, Cambridge, MA, 02138, United States
Videos are available on the CMSA Youtube Playlist.
On November 28 – Dec 1, 2022, the CMSA hosted a Workshop on Representation Theory, Calabi-Yau Manifolds, and Mirror Symmetry.
Organizers: An Huang (Brandeis University) | Siu-Cheong Lau (Boston University) | Tsung-Ju Lee (CMSA, Harvard) | Andrew Linshaw (University of Denver)
Scientific Advisor: Shing-Tung Yau (Harvard, Tsinghua)
Location: Room G10, CMSA, 20 Garden Street, Cambridge MA 02138

The conference was held in hybrid format, both in-person and online.
The workshop was partially supported by Simons and NSF Grant DMS-2227199.

Speakers:

Tomoyuki Arakawa (Kyoto)
Thomas Creutzig (Edmonton)
Jonathan Mboyo Esole (Northeastern)
Fei Han (National University of Singapore)
Shinobu Hosono (Gakushuin University)
Flor Orosz Hunziker (Colorado)
Cuipo Jiang (Shanghai)
Shashank Kanade (Denver)
Matt Kerr (Washington University in St. Louis)
Carl Lian (Humboldt-Universität zu Berlin)
Nai-Chung Conan Leung (CUHK)
Ivan Loseu (Yale)
Robert McRae (Tsinghua University)
Anne Moreau (Université Paris-Saclay, Orsay)
Tony Pantev (University of Pennsylvania)
Mauricio Romo (Tsinghua University)
Bailin Song (USTC)
Cumrun Vafa (Harvard University)
Chin-Lung Wang (National Taiwan University)
Weiqiang Wang (Virginia)
Yaping Yang (University of Melbourne)
Shing-Tung Yau (Tsinghua University)
Chenglong Yu (Tsinghua University)
Gufang Zhao (University of Melbourne)

Schedule (Eastern Time)
Schedule (pdf)
11/28 (Monday)

08:30am – 08:55am
Refreshments

08:55am – 09:00am
Opening remarks by Horng-Tzer Yau

09:00am – 09:45am
Shing-Tung Yau*
Title: The Hull-Strominger system through conifold transitions
Abstract: In this talk I discuss the geometry of C-Y manifolds outside of the Kähler regime and especially describe the Hull-Strominger system through the conifold transitions.

10:00am – 10:45am
Chenglong Yu*
Title: Commensurabilities among Lattices in PU(1,n)
Abstract: In joint work with Zhiwei Zheng, we study commensurabilities among certain subgroups in PU(1,n). Those groups arise from the monodromy of hypergeometric functions. Their discreteness and arithmeticity are classified by Deligne and Mostow. Thurston also obtained similar results via flat conic metrics. However, the classification of the lattices among them up to conjugation and finite index (commensurability) is not completed. When n=1, it is the commensurabilities of hyperbolic triangles. The cases of n=2 are almost resolved by Deligne-Mostow and Sauter’s commensurability pairs, and commensurability invariants by Kappes-Möller and McMullen. Our approach relies on the study of some higher dimensional Calabi-Yau type varieties instead of complex reflection groups. We obtain some relations and commensurability indices for higher n and also give new proofs for existing pairs in n=2.

11:00am – 11:45am
Thomas Creutzig*
Title: Shifted equivariant W-algebras
Abstract: The CDO of a compact Lie group is a family of VOAs whose top level is the space of functions on the Lie group. Similar structures appear at the intersections of boundary conditions in 4-dimensional gauge theories, I will call these new families of VOAs shifted equivariant W-algebras. I will introduce these algebras, construct them and explain how they can be used to quickly prove the GKO-coset realization of principal W-algebras.

11:45am – 1:30 pm
Lunch

01:30pm – 02:15pm
Cumrun Vafa
Title: Reflections on Mirror Symmetry
Abstract: In this talk I review some of the motivations leading to the search and discovery of mirror symmetry as well as some of the applications it has had.

02:30pm – 03:15pm
Jonathan Mboyo Esole
Title: Algebraic topology and matter representations in F-theory
Abstract: Recently, it was observed that representations appearing in geometric engineering in F-theory all satisfy a unique property: they correspond to characteristic representations of embedding of Dynkin index one between Lie algebras. However, the reason why that is the case is still being understood. In this talk, I will present new insights, giving a geometric explanation for this fact using K-theory and the topology of Lie groups and their classifying spaces. In physics, this will be interpreted as conditions on the charge of instantons and the classifications of Wess-Zumino-Witten terms.

03:15pm – 03:45 pm
Break

03:45pm – 04:30pm
Weiqiang Wang
Title: A Drinfeld presentation of affine i-quantum groups
Abstract: A quantum symmetric pair of affine type (U, U^i) consists of a Drinfeld-Jimbo affine quantum group (a quantum deformation of a loop algebra) U and its coideal subalgebra U^i (called i-quantum group). A loop presentation for U was formulated by Drinfeld and proved by Beck. In this talk, we explain how i-quantum groups can be viewed as a generalization of quantum groups, and then we give a Drinfeld type presentation for the affine quasi-split i-quantum group U^i. This is based on joint work with Ming Lu (Sichuan) and Weinan Zhang (Virginia).

04:45pm – 05:30pm
Tony Pantev
Title: Decomposition, anomalies, and quantum symmetries
Abstract: Decomposition is a phenomenon in quantum physics which converts quantum field theories with non-effectively acting gauge symmetries into equivalent more tractable theories in which the fields live on a disconnected space. I will explain the mathematical content of decomposition which turns out to be a higher categorical version of Pontryagin duality. I will examine how this duality interacts with quantum anomalies and secondary quantum symmetries and will show how the anomalies can be canceled by homotopy coherent actions of diagrams of groups. I will discuss in detail the case of 2-groupoids which plays a central role in anomaly cancellation, and will describe a new duality operation that yields decomposition in the presence of anomalies. The talk is based on joint works with Robbins, Sharpe, and Vandermeulen.

11/29 (Tuesday)

Refreshments

09:00am – 09:45am
Robert MacRae*
Title: Rationality for a large class of affine W-algebras
Abstract: One of the most important results in vertex operator algebras is Huang’s theorem that the representation category of a “strongly rational” vertex operator algebra is a semisimple modular tensor category. Conversely, it has been conjectured that every (unitary) modular tensor category is the representation category of a strongly rational (unitary) vertex operator algebra. In this talk, I will describe my results on strong rationality for a large class of affine W-algebras at admissible levels. This yields a large family of modular tensor categories which generalize those associated to affine Lie algebras at positive integer levels, as well as those associated to the Virasoro algebra.

10:00am – 10:45am
Bailin Song*
Title: The global sections of chiral de Rham complexes on compact Calabi-Yau manifolds
Abstract: Chiral de Rham complex is a sheaf of vertex algebras on a complex manifold. We will describe the space of global sections of the chiral de Rham complexes on compact Calabi-Yau manifolds.

11:00am – 11:45am
Carl Lian*
Title: Curve-counting with fixed domain
Abstract: The fixed-domain curve-counting problem asks for the number of pointed curves of fixed (general) complex structure in a target variety X subject to incidence conditions at the marked points. The question comes in two flavors: one can ask for a virtual count coming from Gromov-Witten theory, in which case the answer can be computed (in principle) from the quantum cohomology of X, or one can ask for the “honest” geometric count, which tends to be more subtle. The answers are conjectured to agree in the presence of sufficient positivity, but do not always. I will give an overview of some recent results and open directions. Some of this work is joint with Alessio Cela, Gavril Farkas, and Rahul Pandharipande.

11:45am – 01:30pm
Lunch

01:30pm – 02:15pm
Chin-Lung Wang
Title: A blowup formula in quantum cohomology
Abstract: We study analytic continuations of quantum cohomology $QH(Y)$ under a blowup $phi: Y to X$ of complex projective manifolds along the extremal ray variable $q^{ell}$. Under $H(Y) = phi^* H(X) oplus K$ where $K = ker phi_*$, we show that (i) the restriction of quantum product along the $phi^*H(X)$ direction, denoted by $QH(Y)_X$, is meromorphic in $x := 1/q^ell$, (ii) $K$ deforms uniquely to a quantum ideal $widetilde K$ in $QH(Y)_X$, (iii) the quotient ring $QH(Y)_X/widetilde K$ is regular over $x$, and its restriction to $x = 0$ is isomorphic to $QH(X)$. This is a joint work (in progress) with Y.-P. Lee and H.-W. Lin.

02:30pm – 03:15pm
Ivan Loseu
Title: Quantizations of nilpotent orbits and their Lagrangian subvarieties
Abstract: I’ll report on some recent progress on classifying quantizations of the algebras of regular functions of nilpotent orbits (and their covers) in semisimple Lie algebras, as well as the classification of quantizations of certain Lagrangian subvarieties. An ultimate goal here is to understand the classification of unitary representations of real semisimple Lie groups.

03:15pm – 03:45pm
Break

03:45pm – 04:30pm
Matt Kerr*
Title: $K_2$ and quantum curves
Abstract: The basic objects for this talk are motives consisting of a curve together with a $K_2$ class, and their mixed Hodge-theoretic invariants.
My main objective will be to explain a connection (recently proved in joint work with C. Doran and S. Sinha Babu) between (i) Hodge-theoretically distinguished points in the moduli of such motives and (ii) eigenvalues of operators on L^2(R) obtained by quantizing the equations of the curves.
By local mirror symmetry, this gives evidence for a conjecture in topological string theory (due to M. Marino, A. Grassi, and others) relating enumerative invariants of toric CY 3-folds to spectra of quantum curves.

04:45pm – 05:30pm
Flor Orosz Hunziker
Title: Tensor structures associated to the N=1 super Virasoro algebra
Abstract: We have recently shown that there is a natural category of representations associated to the N=1 super Virasoro vertex operator algebras that have braided tensor structure. We will describe this category and discuss the problem of establishing its rigidity at particular central charges. This talk is based on joint work in progress with Thomas Creutzig, Robert McRae and Jinwei Yang.

11/30 (Wednesday)

08:30am – 09:00am
Refreshments

09:00am – 09:45am
Tomoyuki Arakawa
Title: 4D/2D duality and representation theory
Abstract: This talk is about the 4D/2D duality discovered by Beem et al. rather recently in physics. It associates a vertex operator algebra (VOA) to any 4-dimensional superconformal field theory, which is expected to be a complete invariant of thl theory. The VOAs appearing in this manner may be regarded as chiralization of various symplectic singularities and their representations are expected to be closely related with the Coulomb branch of the 4D theory. I will talk about this remarkable 4D/2D duality from a representation theoretic perspective.

10:00am – 10:45am
Shashank Kanade
Title: Combinatorics of principal W-algebras of type A
Abstract: The combinatorics of principal W_r(p,p’) algebras of type A is controlled by cylindric partitions. However, very little seems to be known in general about fermionic expressions for the corresponding characters. Welsh’s work explains the case of Virasoro minimal models W_2(p,p’). Andrews, Schilling and Warnaar invented and used an A_2 version of the usual (A_1) Bailey machinery to give fermionic characters (up to a factor of (q)_infty) of some, but not all, W_3(3,p’) modules. In a recent joint work with Russell, we have given a complete set of conjectures encompassing all of the remaining modules for W_3(3,p’), and proved our conjectures for small values of p’. In another direction, characters of W_r(p,p’) algebras also arise as appropriate limits of certain sl_r coloured Jones invariants of torus knots T(p,p’), and we expect this to provide further insights on the underlying combinatorics.

11:00am – 11:45am
Gufang Zhao
Title: Quasimaps to quivers with potentials
Abstract: This talk concerns non-compact GIT quotient of a vector space, in the presence of an abelian group action and an equivariant regular function (potential) on the quotient. We define virtual counts of quasimaps from prestable curves to the critical locus of the potential. The construction borrows ideas from the theory of gauged linear sigma models as well as recent development in shifted symplectic geometry and Donaldson-Thomas theory of Calabi-Yau 4-folds. Examples of virtual counts arising from quivers with potentials are discussed. This is based on work in progress, in collaboration with Yalong Cao.

11:45am – 01:30pm
Group Photo, Lunch

01:30pm – 02:15pm
Yaping Yang
Title: Cohomological Hall algebras and perverse coherent sheaves on toric Calabi-Yau 3-folds
Abstract: Let X be a smooth local toric Calabi-Yau 3-fold. On the cohomology of the moduli spaces of certain sheaves on X, there is an action of the cohomological Hall algebra (COHA) of Kontsevich and Soibelman via “raising operators”. I will discuss the “double” of the COHA that acts on the cohomology of the moduli space by adding the “lowering operators”. We associate a root system to X. The double COHA is expected to be the shifted Yangian of this root system. We also give a prediction for the shift in terms of an intersection pairing. We provide evidence of the aforementioned expectation in various examples. This is based on my joint work with M. Rapcak, Y. Soibelman, and G. Zhao

02:30pm – 03:15pm
Fei Han
Title: Graded T-duality with H-flux for 2d sigma models
Abstract: T-duality in string theory can be realised as a transformation acting on the worldsheet fields in the two-dimensional nonlinear sigma model. Bouwknegt-Evslin-Mathai established the T-duality in a background flux for the first time upon compactifying spacetime in one direction to a principal circle by constructing the T-dual maps transforming the twisted cohomology of the dual spacetimes. In this talk, we will describe our recent work on how to promote the T-duality maps of Bouwknegt-Evslin-Mathai in two aspects. More precisely, we will introduce (1) graded T-duality, concerning the graded T-duality maps of all levels of twistings; (2) the 2-dimensional sigma model picture, concerning the double loop space of spacetimes. This represents our joint work with Mathai.

03:15pm – 3:45pm
Break

03:45pm – 04:30pm
Mauricio Romo
Title: Networks and BPS Counting: A-branes view point
Abstract: I will review the countings of BPS invariants via exponential/spectral networks and present an interpretation of this counting as a count of certain points in the moduli space of A-branes corresponding to degenerate Lagrangians.

04:45pm – 05:30pm
Shinobu Hosono
Title: Mirror symmetry of abelian fibered Calabi-Yau manifolds with ρ = 2
Abstract: I will describe mirror symmetry of Calabi-Yau manifolds fibered by (1,8)-polarized abelian surfaces, which have Picard number two. Finding a mirror family over a toric variety explicitly, I observe that mirror symmetry of all related Calabi-Yau manifods arises from the corresponding boundary points, which are not necessarily toric boundary points. Calculating Gromov-Witten invariants up to genus 2, I find that the generating functions are expressed elliptic (quasi-)modular forms, which reminds us the modular anomaly equation found for elliptic surfaces. This talk is based on a published work with Hiromichi Takaki (arXiv:2103.08150).

06:00pm
Banquet @ Royal East Restaurant, 782 Main St, Cambridge, MA 02139

12/1 (Thursday)

08:30am – 09:00am
Refreshments

09:00am – 09:45am
Conan Nai Chung Leung*
Title: Quantization of Kahler manifolds
Abstract: I will explain my recent work on relationships among geometric quantization, deformation quantization, Berezin-Toeplitz quantization and brane quantization.

10:00am – 10:45am
Cuipo Jiang*
Title: Cohomological varieties associated to vertex operator algebras
Abstract: We define and examine the cohomological variety of a vertex algebra, a notion cohomologically dual to that of the associated variety, which measures the smoothness of the associated scheme at the vertex point. We study its basic properties. As examples, we construct a closed subvariety of the cohomological variety for rational affine vertex operator algebras constructed from finite dimensional simple Lie algebras. We also determine the cohomological varieties of the simple Virasoro vertex operator algebras. These examples indicate that, although the associated variety for a rational $C_2$-cofinite vertex operator algebra is always a simple point, the cohomological variety can have as large a dimension as possible. This talk is based on joint work with Antoine Caradot and Zongzhu Lin.

11:00am – 11:45am
Anne Moreau*
Title: Action of the automorphism group on the Jacobian of Klein’s quartic curve
Abstract: In a joint work with Dimitri Markouchevitch, we prove that the quotient variety of the 3-dimensional Jacobian of the plane Klein quartic curve by its full automorphism group of order 336 is isomorphic to the 3-dimensional weighted projective space with weights 1,2,4,7.
The latter isomorphism is a particular case of the general conjecture of Bernstein and Schwarzman suggesting that a quotient of the n-dimensional complex space by the action of an irreducible complex crystallographic group generated by reflections is a weighted projective space.
In this talk, I will explain this conjecture and the proof of our result. An important ingredient is the computation of the Hilbert function of the algebra of invariant theta-functions on the Jacobian.

11:45am – 11:50am
Closing remarks

11:50am
Free discussions and departure

* = Online speaker
CMSA COVID-19 Policies

Third Annual Yip Lecture
2023-02-02 19:00 - 20:00 | Harvard Science Center, 1 Oxford Street, Cambridge, MA, 02138
Andrew Strominger will give the Third Annual Yip Lecture on February 2, 2023.
Time: 7:00-8:00 pm ET
Location: Harvard Science Center Hall A

Title: Black Holes: The Most Mysterious Objects in the Universe
Abstract: In the last decade black holes have come to center stage in both theoretical and observational science. Theoretically, they were shown a half-century ago by Stephen Hawking and others to obey a precise but still-mysterious set of laws which imply they are paradoxically both the simplest and most complex objects in the universe. Compelling progress on this paradox has occurred recently. Observationally, they have finally and dramatically been seen in the sky, including at LIGO and the Event Horizon Telescope. Future prospects for progress on both fronts hinge on emergent symmetries occurring near the black holes. An elementary presentation of aspects of these topics and their interplay will be given.
Andrew Strominger is the Gwill E. York Professor of Physics and a senior faculty member at the Black Hole Initiative at Harvard University.
Introduction: Peter Galison (Harvard Physics & Black Hole Initiative)
Moderator: Daniel Kapec (Harvard CMSA)
The Yip Lecture takes place thanks to the support of Dr. Shing-Yiu Yip.

The previous Yip Lecture featured Avi Loeb (Harvard), who spoke on Extraterrestrial Life.

Special Lectures on Machine Learning and Protein Folding
2023-02-09 15:30 - 17:00 | CMSA Room G10, CMSA, 20 Garden Street, Cambridge, MA, 02138, United States
The CMSA hosted a series of three 90-minute lectures on the subject of machine learning for protein folding.
Thursday Feb. 9, Thursday Feb. 16, & Thursday March 9, 2023, 3:30-5:00 pm ET
Location: G10, CMSA, 20 Garden Street, Cambridge MA 02138 & via Zoom

Speaker: Nazim Bouatta, Harvard Medical School
Abstract: AlphaFold2, a neural network-based model which predicts protein structures from amino acid sequences, is revolutionizing the field of structural biology. This lecture series, given by a leader of the OpenFold project which created an open-source version of AlphaFold2, will explain the protein structure problem and the detailed workings of these models, along with many new results and directions for future research.
Thursday, Feb. 9, 2023

Thursday, Feb. 9, 2023
3:30–5:00 pm ET
Lecture 1: Machine learning for protein structure prediction, Part 1: Algorithm space
A brief intro to protein biology. AlphaFold2 impacts on experimental structural biology. Co-evolutionary approaches. Space of ‘algorithms’ for protein structure prediction. Proteins as images (CNNs for protein structure prediction). End-to-end differentiable approaches. Attention and long-range dependencies. AlphaFold2 in a nutshell.

Thursday, Feb. 16, 2023
3:30–5:00 pm ET
Lecture 2: Machine learning for protein structure prediction, Part 2: AlphaFold2 architecture
Turning the co-evolutionary principle into an algorithm: EvoFormer. Structure module and symmetry principles (equivariance and invariance). OpenFold: retraining AlphaFold2 and insights into its learning mechanisms and capacity for generalization. Applications of variants of AlphaFold2 beyond protein structure prediction: AlphaFold Multimer for protein complexes, RNA structure prediction.

Thursday, March 9, 2023
3:30–5:00 pm ET
Lecture 3: Machine learning for protein structure prediction, Part 3: AlphaFold2 limitations and insights learned from OpenFold
Limitations of AlphaFold2 and evolutionary ML pipelines. OpenFold: retraining AlphaFold2 yields new insights into its capacity for generalization.

Biography: Nazim Bouatta received his doctoral training in high-energy theoretical physics, and transitioned to systems biology at Harvard Medical School, where he received training in cellular and molecular biology in the group of Prof. Judy Lieberman. He is currently a Senior Research Fellow in the Laboratory of Systems Pharmacology led by Prof. Peter Sorger at Harvard Medical School, and an affiliate of the Department of Systems Biology at Columbia, in the group of Prof. Mohammed AlQuraishi. He is interested in applying machine learning, physics, and mathematics to biology at multiple scales. He recently co-supervised the OpenFold project, an optimized, trainable, and completely open-source version of AlphaFold2. OpenFold has paved the way for many breakthroughs in biology, including the release of the ESM Metagenomic Atlas containing over 600 million predicted protein structures.

Chair: Michael Douglas (Harvard CMSA)
Moderators: Farzan Vafa & Sergiy Verstyuk (Harvard CMSA)

Lecture 1: Machine learning for protein structure prediction, Part 1: Algorithm space

Lecture 2: Machine learning for protein structure prediction, Part 2: AlphaFold2 architecture

Lecture 3: Machine learning for protein structure prediction, Part 3: AlphaFold2 limitations and insights learned from OpenFold

Conference on Geometry and Statistics
2023-02-27 09:00 - 2023-03-01 17:30 | CMSA Room G10, CMSA, 20 Garden Street, Cambridge, MA, 02138, United States
On Feb 27-March 1, 2023 the CMSA will host a Conference on Geometry and Statistics.
Location: G10, CMSA, 20 Garden Street, Cambridge MA 02138
Organizing Committee:
Stephan Huckemann (Georg-August-Universität Göttingen)
Ezra Miller (Duke University)
Zhigang Yao (Harvard CMSA and Committee Chair)
Scientific Advisors:
Horng-Tzer Yau (Harvard CMSA)
Shing-Tung Yau (Harvard CMSA)
Speakers:

Tamara Broderick (MIT)
David Donoho (Stanford)
Ian Dryden (Florida International University in Miami)
David Dunson (Duke)
Charles Fefferman (Princeton)
Stefanie Jegelka (MIT)
Sebastian Kurtek (OSU)
Lizhen Lin (Notre Dame)
Steve Marron (U North Carolina)
Ezra Miller (Duke)
Hans-Georg Mueller (UC Davis)
Nicolai Reshetikhin (UC Berkeley)
Wolfgang Polonik (UC Davis)
Amit Singer (Princeton)
Zhigang Yao (Harvard CMSA)
Bin Yu (Berkeley)

Moderator: Michael Simkin (Harvard CMSA)

SCHEDULE
Monday, Feb. 27, 2023 (Eastern Time)

8:30 am
Breakfast

8:45–8:55 am
Zhigang Yao
Welcome Remarks

8:55–9:00 am
Shing-Tung Yau*
Remarks

Morning Session Chair: Zhigang Yao

9:00–10:00 am
David Donoho
Title: ScreeNOT: Exact MSE-Optimal Singular Value Thresholding in Correlated Noise
Abstract: Truncation of the singular value decomposition is a true scientific workhorse. But where to Truncate?
For 55 years the answer, for many scientists, has been to eyeball the scree plot, an approach which still generates hundreds of papers per year.
I will describe ScreeNOT, a mathematically solid alternative deriving from the many advances in Random Matrix Theory over those 55 years. Assuming a model of low-rank signal plus possibly correlated noise, and adopting an asymptotic viewpoint with number of rows proportional to the number of columns, we show that ScreeNOT has a surprising oracle property.
It typically achieves exactly, in large finite samples, the lowest possible MSE for matrix recovery, on each given problem instance – i.e. the specific threshold it selects gives exactly the smallest achievable MSE loss among all possible threshold choices for that noisy dataset and that unknown underlying true low rank model. The method is computationally efficient and robust against perturbations of the underlying covariance structure.
The talk is based on joint work with Matan Gavish and Elad Romanov, Hebrew University.

10:00–10:10 am
Break

10:10–11:10 am
Steve Marron
Title: Modes of Variation in Non-Euclidean Spaces
Abstract: Modes of Variation provide an intuitive means of understanding variation in populations, especially in the case of data objects that naturally lie in non-Euclidean spaces. A variety of useful approaches to finding useful modes of variation are considered in several non-Euclidean contexts, including shapes as data objects, vectors of directional data, amplitude and phase variation and compositional data.

11:10–11:20 am
Break

11:20 am–12:20 pm
Zhigang Yao
Title: Manifold fitting: an invitation to statistics
Abstract: While classical statistics has dealt with observations which are real numbers or elements of a real vector space, nowadays many statistical problems of high interest in the sciences deal with the analysis of data which consist of more complex objects, taking values in spaces which are naturally not (Euclidean) vector spaces but which still feature some geometric structure. This manifold fitting problem can go back to H. Whitney’s work in the early 1930s (Whitney (1992)), and finally has been answered in recent years by C. Fefferman’s works (Fefferman, 2006, 2005). The solution to the Whitney extension problem leads to new insights for data interpolation and inspires the formulation of the Geometric Whitney Problems (Fefferman et al. (2020, 2021a)): Assume that we are given a set $Y subset mathbb{R}^D$. When can we construct a smooth $d$-dimensional submanifold $widehat{M} subset mathbb{R}^D$ to approximate $Y$, and how well can $widehat{M}$ estimate $Y$ in terms of distance and smoothness? To address these problems, various mathematical approaches have been proposed (see Fefferman et al. (2016, 2018, 2021b)). However, many of these methods rely on restrictive assumptions, making extending them to efficient and workable algorithms challenging. As the manifold hypothesis (non-Euclidean structure exploration) continues to be a foundational element in statistics, the manifold fitting Problem, merits further exploration and discussion within the modern statistical community. The talk will be partially based on a recent work Yao and Xia (2019) along with some on-going progress. Relevant reference:https://arxiv.org/abs/1909.10228

12:20–1:50 pm
12:20 pm Group Photo
followed by Lunch

Afternoon Session Chair: Stephan Huckemann

1:50–2:50 pm
Bin Yu*
Title: Interpreting Deep Neural Networks towards Trustworthiness
Abstract: Recent deep learning models have achieved impressive predictive performance by learning complex functions of many variables, often at the cost of interpretability. This lecture first defines interpretable machine learning in general and introduces the agglomerative contextual decomposition (ACD) method to interpret neural networks. Extending ACD to the scientifically meaningful frequency domain, an adaptive wavelet distillation (AWD) interpretation method is developed. AWD is shown to be both outperforming deep neural networks and interpretable in two prediction problems from cosmology and cell biology. Finally, a quality-controlled data science life cycle is advocated for building any model for trustworthy interpretation and introduce a Predictability Computability Stability (PCS) framework for such a data science life cycle.

2:50–3:00 pm
Break

3:00-4:00 pm
Hans-Georg Mueller
Title: Exploration of Random Objects with Depth Profiles and Fréchet Regression
Abstract: Random objects, i.e., random variables that take values in a separable metric space, pose many challenges for statistical analysis, as vector operations are not available in general metric spaces. Examples include random variables that take values in the space of distributions, covariance matrices or surfaces, graph Laplacians to represent networks, trees and in other spaces. The increasing prevalence of samples of random objects has stimulated the development of metric statistics, an emerging collection of statistical tools to characterize, infer and relate samples of random objects. Recent developments include depth profiles, which are useful for the exploration of random objects. The depth profile for any given object is the distribution of distances to all other objects (with P. Dubey, Y. Chen 2022).
These distributions can then be subjected to statistical analysis. Their mutual transports lead to notions of transport ranks, quantiles and centrality. Another useful tool is global or local Fréchet regression (with A. Petersen 2019) where random objects are responses and scalars or vectors are predictors and one aims at modeling conditional Fréchet means. Recent theoretical advances for local Fréchet regression provide a basis for object time warping (with Y. Chen 2022). These approaches are illustrated with distributional and other data.

4:00-4:10 pm
Break

4:10-5:10 pm
Stefanie Jegelka
Title: Some benefits of machine learning with invariances
Abstract: In many applications, especially in the sciences, data and tasks have known invariances. Encoding such invariances directly into a machine learning model can improve learning outcomes, while it also poses challenges on efficient model design. In the first part of the talk, we will focus on the invariances relevant to eigenvectors and eigenspaces being inputs to a neural network. Such inputs are important, for instance, for graph representation learning. We will discuss targeted architectures that can universally express functions with the relevant invariances – sign flips and changes of basis – and their theoretical and empirical benefits.
Second, we will take a broader, theoretical perspective. Empirically, it is known that encoding invariances into the machine learning model can reduce sample complexity. For the simplified setting of kernel ridge regression or random features, we will discuss new bounds that illustrate two ways in which invariances can reduce sample complexity. Our results hold for learning on manifolds and for invariances to (almost) any group action, and use tools from differential geometry.
This is joint work with Derek Lim, Joshua Robinson, Behrooz Tahmasebi, Lingxiao Zhao, Tess Smidt, Suvrit Sra, and Haggai Maron.

Tuesday, Feb. 28, 2023 (Eastern Time)

8:30-9:00 am
Breakfast

Morning Session Chair: Zhigang Yao

9:00-10:00 am
Charles Fefferman*
Title: Lipschitz Selection on Metric Spaces
Abstract: The talk concerns the problem of finding a Lipschitz map F from a given metric space X into R^D, subject to the constraint that F(x) must lie in a given compact convex “target” K(x) for each point x in X. Joint work with Pavel Shvartsman and with Bernat Guillen Pegueroles.

10:00-10:10 am
Break

10:10-11:10 am
David Dunson
Title: Inferring manifolds from noisy data using Gaussian processes
Abstract: In analyzing complex datasets, it is often of interest to infer lower dimensional structure underlying the higher dimensional observations. As a flexible class of nonlinear structures, it is common to focus on Riemannian manifolds. Most existing manifold learning algorithms replace the original data with lower dimensional coordinates without providing an estimate of the manifold in the observation space or using the manifold to denoise the original data. This article proposes a new methodology for addressing these problems, allowing interpolation of the estimated manifold between fitted data points. The proposed approach is motivated by novel theoretical properties of local covariance matrices constructed from noisy samples on a manifold. Our results enable us to turn a global manifold reconstruction problem into a local regression problem, allowing application of Gaussian processes for probabilistic manifold reconstruction. In addition to theory justifying the algorithm, we provide simulated and real data examples to illustrate the performance. Joint work with Nan Wu – see https://arxiv.org/abs/2110.07478

11:10-11:20 am
Break

11:20 am-12:20 pm
Wolfgang Polonik
Title: Inference in topological data analysis
Abstract: Topological data analysis has seen a huge increase in popularity finding applications in numerous scientific fields. This motivates the importance of developing a deeper understanding of benefits and limitations of such methods. Using this angle, we will present and discuss some recent results on large sample inference in topological data analysis, including bootstrap for Betti numbers and the Euler characteristics process.

12:20–1:50 pm
Lunch

Afternoon Session Chair: Stephan Huckemann

1:50-2:50 pm
Ezra Miller
Title: Geometric central limit theorems on non-smooth spaces
Abstract: The central limit theorem (CLT) is commonly thought of as occurring on the real line, or in multivariate form on a real vector space. Motivated by statistical applications involving nonlinear data, such as angles or phylogenetic trees, the past twenty years have seen CLTs proved for Fréchet means on manifolds and on certain examples of singular spaces built from flat pieces glued together in combinatorial ways. These CLTs reduce to the linear case by tangent space approximation or by gluing. What should a CLT look like on general non-smooth spaces, where tangent spaces are not linear and no combinatorial gluing or flat pieces are available? Answering this question involves figuring out appropriate classes of spaces and measures, correct analogues of Gaussian random variables, and how the geometry of the space (think “curvature”) is reflected in the limiting distribution. This talk provides an overview of these answers, starting with a review of the usual linear CLT and its generalization to smooth manifolds, viewed through a lens that casts the singular CLT as a natural outgrowth, and concluding with how this investigation opens gateways to further advances in geometric probability, topology, and statistics. Joint work with Jonathan Mattingly and Do Tran.

2:50-3:00 pm
Break

3:00-4:00 pm
Lizhen Lin
Title: Statistical foundations of deep generative models
Abstract: Deep generative models are probabilistic generative models where the generator is parameterized by a deep neural network. They are popular models for modeling high-dimensional data such as texts, images and speeches, and have achieved impressive empirical success. Despite demonstrated success in empirical performance, theoretical understanding of such models is largely lacking. We investigate statistical properties of deep generative models from a nonparametric distribution estimation viewpoint. In the considered model, data are assumed to be observed in some high-dimensional ambient space but concentrate around some low-dimensional structure such as a lower-dimensional manifold structure. Estimating the distribution supported on this low-dimensional structure is challenging due to its singularity with respect to the Lebesgue measure in the ambient space. We obtain convergence rates with respect to the Wasserstein metric of distribution estimators based on two methods: a sieve MLE based on the perturbed data and a GAN type estimator. Such an analysis provides insights into i) how deep generative models can avoid the curse of dimensionality and outperform classical nonparametric estimates, and ii) how likelihood approaches work for singular distribution estimation, especially in adapting to the intrinsic geometry of the data.

4:00-4:10 pm
Break

4:10-5:10 pm
Conversation session

Wednesday, March 1, 2023 (Eastern Time)

8:30-9:00 am
Breakfast

Morning Session Chair: Ezra Miller

9:00-10:00 am
Amit Singer*
Title: Heterogeneity analysis in cryo-EM by covariance estimation and manifold learning
Abstract: In cryo-EM, the 3-D molecular structure needs to be determined from many noisy 2-D tomographic projection images of randomly oriented and positioned molecules. A key assumption in classical reconstruction procedures for cryo-EM is that the sample consists of identical molecules. However, many molecules of interest exist in more than one conformational state. These structural variations are of great interest to biologists, as they provide insight into the functioning of the molecule. Determining the structural variability from a set of cryo-EM images is known as the heterogeneity problem, widely recognized as one of the most challenging and important computational problem in the field. Due to high level of noise in cryo-EM images, heterogeneity studies typically involve hundreds of thousands of images, sometimes even a few millions. Covariance estimation is one of the earliest methods proposed for heterogeneity analysis in cryo-EM. It relies on computing the covariance of the conformations directly from projection images and extracting the optimal linear subspace of conformations through an eigendecomposition. Unfortunately, the standard formulation is plagued by the exorbitant cost of computing the N^3 x N^3 covariance matrix. In the first part of the talk, we present a new low-rank estimation method that requires computing only a small subset of the columns of the covariance while still providing an approximation for the entire matrix. This scheme allows us to estimate tens of principal components of real datasets in a few minutes at medium resolutions and under 30 minutes at high resolutions. In the second part of the talk, we discuss a manifold learning approach based on the graph Laplacian and the diffusion maps framework for learning the manifold of conformations. If time permits, we will also discuss the potential application of optimal transportation to heterogeneity analysis. Based on joint works with Joakim Andén, Marc Gilles, Amit Halevi, Eugene Katsevich, Joe Kileel, Amit Moscovich, and Nathan Zelesko.

10:00-10:10 am
Break

10:10-11:10 am
Ian Dryden
Title: Statistical shape analysis of molecule data
Abstract: Molecular shape data arise in many applications, for example high dimension low sample size cryo-electron microscopy (cryo-EM) data and large temporal sequences of peptides from molecular dynamics simulations. In both applications it is of interest to summarize the shape evolution of the molecules in a succinct, low-dimensional representation. However, Euclidean techniques such as principal components analysis (PCA) can be problematic as the data may lie far from in a flat manifold. Principal nested spheres gives a fundamentally different decomposition of data from the usual Euclidean subspace based PCA. Subspaces of successively lower dimension are fitted to the data in a backwards manner with the aim of retaining signal and dispensing with noise at each stage. We adapt the methodology to 3D sub-shape spaces and provide some practical fitting algorithms. The methodology is applied to cryo-EM data of a large sliding clamp multi-protein complex and to cluster analysis of peptides, where different states of the molecules can be identified. Further molecular modeling tasks include resolution matching, where coarse resolution models are back-mapped into high resolution (atomistic) structures. This is joint work with Kwang-Rae Kim, Charles Laughton and Huiling Le.

11:10-11:20 am
Break

11:20 am-12:20 pm
Tamara Broderick
Title: An Automatic Finite-Sample Robustness Metric: Can Dropping a Little Data Change Conclusions?
Abstract: One hopes that data analyses will be used to make beneficial decisions regarding people’s health, finances, and well-being. But the data fed to an analysis may systematically differ from the data where these decisions are ultimately applied. For instance, suppose we analyze data in one country and conclude that microcredit is effective at alleviating poverty; based on this analysis, we decide to distribute microcredit in other locations and in future years. We might then ask: can we trust our conclusion to apply under new conditions? If we found that a very small percentage of the original data was instrumental in determining the original conclusion, we might not be confident in the stability of the conclusion under new conditions. So we propose a method to assess the sensitivity of data analyses to the removal of a very small fraction of the data set. Analyzing all possible data subsets of a certain size is computationally prohibitive, so we provide an approximation. We call our resulting method the Approximate Maximum Influence Perturbation. Our approximation is automatically computable, theoretically supported, and works for common estimators. We show that any non-robustness our method finds is conclusive. Empirics demonstrate that while some applications are robust, in others the sign of a treatment effect can be changed by dropping less than 0.1% of the data — even in simple models and even when standard errors are small.

12:20-1:50 pm
Lunch

Afternoon Session Chair: Ezra Miller

1:50-2:50 pm
Nicolai Reshetikhin*
Title: Random surfaces in exactly solvable models in statistical mechanics.
Abstract: In the first part of the talk I will be an overview of a few models in statistical mechanics where a random variable is a geometric object such as a random surface or a random curve. The second part will be focused on the behavior of such random surfaces in the thermodynamic limit and on the formation of the so-called “limit shapes”.

2:50-3:00 pm
Break

3:00-4:00 pm
Sebastian Kurtek
Title: Robust Persistent Homology Using Elastic Functional Data Analysis
Abstract: Persistence landscapes are functional summaries of persistence diagrams designed to enable analysis of the diagrams using tools from functional data analysis. They comprise a collection of scalar functions such that birth and death times of topological features in persistence diagrams map to extrema of functions and intervals where they are non-zero. As a consequence, variation in persistence diagrams is encoded in both amplitude and phase components of persistence landscapes. Through functional data analysis of persistence landscapes, under an elastic Riemannian metric, we show how meaningful statistical summaries of persistence landscapes (e.g., mean, dominant directions of variation) can be obtained by decoupling their amplitude and phase variations. This decoupling is achieved via optimal alignment, with respect to the elastic metric, of the persistence landscapes. The estimated phase functions are tied to the resolution parameter that determines the filtration of simplicial complexes used to construct persistence diagrams. For a dataset obtained under geometric, scale and sampling variabilities, the phase function prescribes an optimal rate of increase of the resolution parameter for enhancing the topological signal in a persistence diagram. The proposed approach adds to the statistical analysis of data objects with rich structure compared to past studies. In particular, we focus on two sets of data that have been analyzed in the past, brain artery trees and images of prostate cancer cells, and show that separation of amplitude and phase of persistence landscapes is beneficial in both settings. This is joint work with Dr. James Matuk (Duke University) and Dr. Karthik Bharath (University of Nottingham).

4:00-4:10 pm
Break

4:10-5:10 pm
Conversation session

5:10-5:20 pm
Stephan Huckemann, Ezra Miller, Zhigang Yao
Closing Remarks

* Virtual Presentation

2023 Ding Shum Lecture
2023-03-21 17:00 - 18:00 | Harvard Science Center, 1 Oxford Street, Cambridge, MA, 02138
On March 21, 2023, the CMSA hosted the fourth annual Ding Shum Lecture, given by Cynthia Dwork (Harvard SEAS and Microsoft Research).

Time: 5:00-6:00 pm ET
Location: Harvard University Science Center Hall D
This event was be held in person and via Zoom webinar.

Title: Measuring Our Chances: Risk Prediction in This World and its Betters
Abstract: Prediction algorithms score individuals, assigning a number between zero and one that is often interpreted as an individual probability: a 0.7 “chance” that this child is in danger in the home; an 80% “probability” that this woman will succeed if hired; a 1/3 “likelihood” that they will graduate within 4 years of admission. But what do words like “chance,” “probability,” and “likelihood” actually mean for a non-repeatable activity like going to college? This is a deep and unresolved problem in the philosophy of probability. Without a compelling mathematical definition we cannot specify what an (imagined) perfect risk prediction algorithm should produce, nor even how an existing algorithm should be evaluated. Undaunted, AI and machine learned algorithms churn these numbers out in droves, sometimes with life-altering consequences.
An explosion of recent research deploys insights from the theory of pseudo-random numbers – sequences of 0’s and 1’s that “look random” but in fact have structure – to yield a tantalizing answer to the evaluation problem, together with a supporting algorithmic framework with roots in the theory of algorithmic fairness.
We can aim even higher. Both (1) our qualifications, health, and skills, which form the inputs to a prediction algorithm, and (2) our chances of future success, which are the desired outputs from the ideal risk prediction algorithm, are products of our interactions with the real world. But the real world is systematically inequitable. How, and when, can we hope to approximate probabilities not in this world, but in a better world, one for which, unfortunately, we have no data at all? Surprisingly, this novel question is inextricably bound with the very existence of nondeterminism.

Professor Cynthia Dwork is Gordon McKay Professor of Computer Science at the Harvard University John A. Paulson School of Engineering and Applied Sciences, Affiliated Faculty at Harvard Law School, and Distinguished Scientist at Microsoft. She uses theoretical computer science to place societal problems on a firm mathematical foundation.
Her recent awards and honors include the 2020 ACM SIGACT and IEEE TCMF Knuth Prize, the 2020 IEEE Hamming Medal, and the 2017 Gödel Prize.

Talk Chair: Horng-Tzer Yau (Harvard Mathematics & CMSA)

Moderator: Faidra Monachou (Harvard CMSA)

The 2020-2022 Ding Shum lectures were postponed due to Covid-19.

The 2019 Ding Shum Lecture featured Ronald Rivest on “Election Security.”

This event is made possible by the generous funding of Ding Lei and Harry Shum.

Watch the Lecture on Youtube:
