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DTSTART;TZID=America/New_York:20210913T090000
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SUMMARY:Swampland Program
DESCRIPTION:During the 2021–2022 academic year\, the CMSA will host a program on the so-called “Swampland.” \nThe Swampland program aims to determine which low-energy effective field theories are consistent with nonperturbative quantum gravity considerations. Not everything is possible in String Theory\, and finding out what is and what is not strongly constrains the low energy physics. These constraints are naturally interesting for particle physics and cosmology\,  which has led to a great deal of activity in the field in the last years. \nThe Swampland is intrinsically interdisciplinary\, with ramifications in string compactifications\, holography\, black hole physics\, cosmology\, particle physics\, and even mathematics. \nThis program will include an extensive group of visitors and a slate of seminars. Additionally\, the CMSA will host a school oriented toward graduate students. \nMore information will be posted here. \nSeminars\nSwampland Seminar Series & Group Meetings \nProgram Visitors\n\nPieter Bomans\, Princeton\, 10/30/21 – 11/02/21\nIrene Valenzuela\, Instituto de Física Teórica\, 02/14/22 – 02/21/22\nMariana Grana\, CEA/Saclay\, 03/21/22 – 03/25/22\nHector Parra De Freitas\, IPHT Saclay\, 03/21/22 – 04/01/22\nTimo Weigand\, 03/21/22 – 03/28/22\nGary Shiu\, University of Wisconsin-Madison\, 04/03/22 – 04/10/22\nThomas van Riet\, Leuven University\, 04/03/22 – 04/09/22\nLars Aalsma\, University of Wisconsin-Madison\, 04/11/22 – 04/15/22\nSergio Cecotti\, 05/08/22 – 05/21/22\nTom Rudelius\, 05/09/22 – 05/13/22
URL:https://cmsa.fas.harvard.edu/event/swampland-program/
LOCATION:CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Programs
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DTSTART;TZID=America/New_York:20210915T093000
DTEND;TZID=America/New_York:20220525T103000
DTSTAMP:20260503T160231
CREATED:20240213T112446Z
LAST-MODIFIED:20240502T160729Z
UID:10002496-1631698200-1653474600@cmsa.fas.harvard.edu
SUMMARY:CMSA Colloquium 9/15/2021 - 5/25/2022
DESCRIPTION:During the 2021–22 academic year\, the CMSA will be hosting a Colloquium\, organized by Du Pei\, Changji Xu\, and Michael Simkin. It will take place on Wednesdays at 9:30am – 10:30am (Boston time). The meetings will take place virtually on Zoom. All CMSA postdocs/members are required to attend the weekly CMSA Members’ Seminars\, as well as the weekly CMSA Colloquium series. The schedule below will be updated as talks are confirmed. \nSpring 2022\n\n\n\n\nDate\nSpeaker\nTitle/Abstract\n\n\n1/26/2022\nSamir Mathur (Ohio State University)\nTitle: The black hole information paradox \nAbstract: In 1975\, Stephen Hawking showed that black holes radiate away in a manner that violates quantum theory. Starting in 1997\, it was observed that black holes in string theory did not have the form expected from general relativity: in place of “empty space will all the mass at the center\,” one finds a “fuzzball” where the mass is distributed throughout the interior of the horizon. This resolves the paradox\, but opposition to this resolution came from groups who sought to extrapolate some ideas in holography. In 2009 it was shown\, using some theorems from quantum information theory\, that these extrapolations were incorrect\, and the fuzzball structure was essential for resolving the puzzle. Opposition continued along different lines\, with a postulate that information would leak out through wormholes. Recently\, it was shown that this wormhole idea had some basic flaws\, leaving the fuzzball paradigm as the natural resolution of Hawking’s puzzle. \nVideo\n\n\n2/2/2022\nAdam Smith (Boston University)\nTitle: Learning and inference from sensitive data \nAbstract: Consider an agency holding a large database of sensitive personal information—say\,  medical records\, census survey answers\, web searches\, or genetic data. The agency would like to discover and publicly release global characteristics of the data while protecting the privacy of individuals’ records. \nI will discuss recent (and not-so-recent) results on this problem with a focus on the release of statistical models. I will first explain some of the fundamental limitations on the release of machine learning models—specifically\, why such models must sometimes memorize training data points nearly completely. On the more positive side\, I will present differential privacy\, a rigorous definition of privacy in statistical databases that is now widely studied\, and increasingly used to analyze and design deployed systems. I will explain some of the challenges of sound statistical inference based on differentially private statistics\, and lay out directions for future investigation.\n\n\n2/8/2022\nWenbin Yan (Tsinghua University)\n(special time: 9:30 pm ET)\nTitle: Tetrahedron instantons and M-theory indices \nAbstract: We introduce and study tetrahedron instantons. Physically they capture instantons on $\mathbb{C}^{3}$ in the presence of the most general intersecting codimension-two supersymmetric defects. In this talk\, we will review instanton moduli spaces\, explain the construction\, moduli space and partition functions of tetrahedron instantons. We will also point out possible relations with M-theory index which could be a generalization of Gupakuma-Vafa theory. \nVideo\n\n\n2/16/2022\nTakuro Mochizuki (Kyoto University)\nTitle: Kobayashi-Hitchin correspondences for harmonic bundles and monopoles \nAbstract: In 1960’s\, Narasimhan and Seshadri discovered the equivalence\nbetween irreducible unitary flat bundles and stable bundles of degree $0$ on compact Riemann surfaces. In 1980’s\, Donaldson\, Uhlenbeck and Yau generalized it to the equivalence between irreducible Hermitian-Einstein bundles\nand stable bundles on smooth projective varieties. This is a surprising bridge connecting differential geometry and algebraic geometry. Since then\, many interesting generalizations have been studied. \nIn this talk\, we would like to review a stream in the study of such correspondences for Higgs bundles\, integrable connections\, $D$-modules and periodic monopoles.\n\n\n2/23/2022\nBartek Czech (Tsinghua University)\nTitle: Holographic Cone of Average Entropies and Universality of Black Holes \nAbstract:  In the AdS/CFT correspondence\, the holographic entropy cone\, which identifies von Neumann entropies of CFT regions that are consistent with a semiclassical bulk dual\, is currently known only up to n=5 regions. I explain that average\nentropies of p-partite subsystems can be checked for consistency with a semiclassical bulk dual far more easily\, for an arbitrary number of regions n. This analysis defines the “Holographic Cone of Average\nEntropies” (HCAE). I conjecture the exact form of HCAE\, and find that it has the following properties: (1) HCAE is the simplest it could be\, namely it is a simplicial cone. (2) Its extremal rays represent stages of thermalization (black hole formation). (3) In a time-reversed picture\, the extremal rays of HCAE represent stages of unitary black hole evaporation\, as stipulated by the island solution of the black hole information paradox. (4) HCAE is bound by a novel\, infinite family of holographic entropy inequalities. (5) HCAE is the simplest it could be also in its dependence on the number of regions n\, namely its bounding inequalities are n-independent. (6) In a precise sense I describe\, the bounding inequalities of HCAE unify (almost) all previously discovered holographic inequalities and strongly constrain future inequalities yet to be discovered. I also sketch an interpretation of HCAE in terms of error correction and the holographic Renormalization Group. The big lesson that HCAE seems to be teaching us is about the universality of black hole physics.\n\n\n3/2/2022\nRichard Kenyon (Yale University)\n\n\n\n3/9/2022\nRichard Tsai (UT Austin)\n\n\n\n3/23/2022\nJoel Cohen (University of Maryland)\n\n\n\n3/30/2022\nRob Leigh (UIUC)\n\n\n\n4/6/2022\nJohannes Kleiner (LMU München)\n\n\n\n4/13/2022\nYuri Manin (Max-Planck-Institut für Mathematik)\n\n\n\n4/20/2022\nTBA\n\n\n\n4/27/2022\nTBA\n\n\n\n5/4/2022\nMelody Chan (Brown University)\n\n\n\n5/11/2022\nTBA\n\n\n\n5/18/2022\nTBA\n\n\n\n5/25/2022\nHeeyeon Kim (Rutgers University)\n\n\n\n\n\nFall 2021\n\n\n\n\nDate\nSpeaker\nTitle/Abstract\n\n\n9/15/2021\nTian Yang\, Texas A&M\nTitle: Hyperbolic Geometry and Quantum Invariants \nAbstract: There are two very different approaches to 3-dimensional topology\, the hyperbolic geometry following the work of Thurston and the quantum invariants following the work of Jones and Witten. These two approaches are related by a sequence of problems called the Volume Conjectures. In this talk\, I will explain these conjectures and present some recent joint works with Ka Ho Wong related to or benefited from this relationship.\n\n\n9/29/2021\nDavid Jordan\, University of Edinburgh\nTitle: Langlands duality for 3 manifolds \nAbstract: Langlands duality began as a deep and still mysterious conjecture in number theory\, before branching into a similarly deep and mysterious conjecture of Beilinson and Drinfeld concerning the algebraic geometry of Riemann surfaces. In this guise it was given a physical explanation in the framework of 4-dimensional super symmetric quantum field theory by Kapustin and Witten.  However to this day the Hilbert space attached to 3-manifolds\, and hence the precise form of Langlands duality for them\, remains a mystery. \nIn this talk I will propose that so-called “skein modules” of 3-manifolds give natural candidates for these Hilbert spaces at generic twisting parameter Psi \, and I will explain a Langlands duality in this setting\, which we have conjectured with Ben-Zvi\, Gunningham and Safronov. \nIntriguingly\, the precise formulation of such a conjecture in the classical limit Psi=0 is still an open question\, beyond the scope of the talk.\n\n\n10/06/2021\nPiotr Sulkowski\, U Warsaw\nTitle: Strings\, knots and quivers \nAbstract: I will discuss a recently discovered relation between quivers and knots\, as well as – more generally – toric Calabi-Yau manifolds. In the context of knots this relation is referred to as the knots-quivers correspondence\, and it states that various invariants of a given knot are captured by characteristics of a certain quiver\, which can be associated to this knot. Among others\, this correspondence enables to prove integrality of LMOV invariants of a knot by relating them to motivic Donaldson-Thomas invariants of the corresponding quiver\, it provides a new insight on knot categorification\, etc. This correspondence arises from string theory interpretation and engineering of knots in brane systems in the conifold geometry; replacing the conifold by other toric Calabi-Yau manifolds leads to analogous relations between such manifolds and quivers.\n\n\n10/13/2021\nAlexei Oblomkov\, University of Massachusetts\nTitle: Knot homology and sheaves on the Hilbert scheme of points on the plane. \nAbstract: The knot homology (defined by Khovavov\, Rozansky) provide us with a refinement of the knot polynomial knot invariant defined by Jones. However\, the knot homology are much harder to compute compared to the polynomial invariant of Jones. In my talk I present recent developments that allow us to use tools of algebraic geometry to compute the homology of torus knots and prove long-standing conjecture on the Poincare duality the knot homology. In more details\, using physics ideas of Kapustin-Rozansky-Saulina\, in the joint work with Rozansky\, we provide a mathematical construction that associates to a braid on n strands a complex of sheaves on the Hilbert scheme of n points on the plane.  The knot homology of the closure of the braid is a space of sections of this sheaf. The sheaf is also invariant with respect to the natural symmetry of the plane\, the symmetry is the geometric counter-part of the mentioned Poincare duality.\n\n\n10/20/2021\nPeng Shan\, Tsinghua U\nTitle: Categorification and applications \nAbstract: I will give a survey of the program of categorification for quantum groups\, some of its recent development and applications to representation theory.\n\n\n10/27/2021\nKarim Adiprasito\, Hebrew University and University of Copenhagen\nTitle: Anisotropy\, biased pairing theory and applications \nAbstract: Not so long ago\, the relations between algebraic geometry and combinatorics were strictly governed by the former party\, with results like log-concavity of the coefficients of the characteristic polynomial of matroids shackled by intuitions and techniques from projective algebraic geometry\, specifically Hodge Theory. And so\, while we proved analogues for these results\, combinatorics felt subjugated to inspirations from outside of it.\nIn recent years\, a new powerful technique has emerged: Instead of following the geometric statements of Hodge theory about signature\, we use intuitions from the Hall marriage theorem\, translated to algebra: once there\, they are statements about self-pairings\, the non-degeneracy of pairings on subspaces to understand the global geometry of the pairing. This was used to establish Lefschetz type theorems far beyond the scope of algebraic geometry\, which in turn established solutions to long-standing conjectures in combinatorics. \nI will survey this theory\, called biased pairing theory\, and new developments within it\, as well as new applications to combinatorial problems. Reporting on joint work with Stavros Papadaki\, Vasiliki Petrotou and Johanna Steinmeyer.\n\n\n11/03/2021\nTamas Hausel\, IST Austria\nTitle: Hitchin map as spectrum of equivariant cohomology \nAbstract: We will explain how to model the Hitchin integrable system on a certain Lagrangian upward flow as the spectrum of equivariant cohomology of a Grassmannian.\n\n\n11/10/2021\nPeter Keevash\, Oxford\nTitle: Hypergraph decompositions and their applications \nAbstract: Many combinatorial objects can be thought of as a hypergraph decomposition\, i.e. a partition of (the edge set of) one hypergraph into (the edge sets of) copies of some other hypergraphs. For example\, a Steiner Triple System is equivalent to a decomposition of a complete graph into triangles. In general\, Steiner Systems are equivalent to decompositions of complete uniform hypergraphs into other complete uniform hypergraphs (of some specified sizes). The Existence Conjecture for Combinatorial Designs\, which I proved in 2014\, states that\, bar finitely many exceptions\, such decompositions exist whenever the necessary ‘divisibility conditions’ hold. I also obtained a generalisation to the quasirandom setting\, which implies an approximate formula for the number of designs; in particular\, this resolved Wilson’s Conjecture on the number of Steiner Triple Systems. A more general result that I proved in 2018 on decomposing lattice-valued vectors indexed by labelled complexes provides many further existence and counting results for a wide range of combinatorial objects\, such as resolvable designs (the generalised form of Kirkman’s Schoolgirl Problem)\, whist tournaments or generalised Sudoku squares. In this talk\, I plan to review this background and then describe some more recent and ongoing applications of these results and developments of the ideas behind them.\n\n\n11/17/2021\nAndrea Brini\, U Sheffield\nTitle: Curve counting on surfaces and topological strings \nAbstract: Enumerative geometry is a venerable subfield of Mathematics\, with roots dating back to Greek Antiquity and a present inextricably linked with developments in other domains. Since the early 90s\, in particular\, the interaction with String Theory has sent shockwaves through the subject\, giving both unexpected new perspectives and a remarkably powerful\, physics-motivated toolkit to tackle several traditionally hard questions in the field.\nI will survey some recent developments in this vein for the case of enumerative invariants associated to a pair (X\, D)\, with X a complex algebraic surface and D a singular anticanonical divisor in it. I will describe a surprising web of correspondences linking together several a priori distant classes of enumerative invariants associated to (X\, D)\, including the log Gromov-Witten invariants of the pair\, the Gromov-Witten invariants of an associated higher dimensional Calabi-Yau variety\, the open Gromov-Witten invariants of certain special Lagrangians in toric Calabi–Yau threefolds\, the Donaldson–Thomas theory of a class of symmetric quivers\, and certain open and closed Gopakumar-Vafa-type invariants. I will also discuss how these correspondences can be effectively used to provide a complete closed-form solution to the calculation of all these invariants.\n\n\n12/01/2021\nRichard Wentworth\, University of Maryland\nTitle: The Hitchin connection for parabolic G-bundles \nAbstract: For a simple and simply connected complex group G\, I will discuss some elements of the proof of the existence of a flat projective connection on the bundle of nonabelian theta functions on the moduli space of semistable parabolic G-bundles over families of smooth projective curves with marked points. Under the isomorphism with the bundle of conformal blocks\, this connection is equivalent to the one constructed by conformal field theory. This is joint work with Indranil Biswas and Swarnava Mukhopadhyay.\n\n\n12/08/2021\nMaria Chudnovsky\, Princeton\nTitle: Induced subgraphs and tree decompositions \nAbstract: Tree decompositions are a powerful tool in both structural\ngraph theory and graph algorithms. Many hard problems become tractable if the input graph is known to have a tree decomposition of bounded “width”. Exhibiting a particular kind of a tree decomposition is also a useful way to describe the structure of a graph. \nTree decompositions have traditionally been used in the context of forbidden graph minors; bringing them into the realm of forbidden induced subgraphs has until recently remained out of reach. Over the last couple of years we have made significant progress in this direction\, exploring both the classical notion of bounded tree-width\, and concepts of more structural flavor. This talk will survey some of these ideas and results.\n\n\n12/15/21\nConstantin Teleman (UC Berkeley)\nTitle: The Kapustin-Rozanski-Saulina “2-category” of a holomorphic integrable system \nAbstract: I will present a construction of the object in the title which\, applied to the classical Toda system\, controls the theory of categorical representations of compact Lie groups\, along with applications (some conjectural\, some rigorous) to gauged Gromov-Witten theory. Time permitting\, we will review applications to Coulomb branches and the categorified Weyl character formula.
URL:https://cmsa.fas.harvard.edu/event/cmsa-colloquium_2021-22/
LOCATION:CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220124T090000
DTEND;TZID=America/New_York:20220521T170000
DTSTAMP:20260503T160231
CREATED:20230904T083438Z
LAST-MODIFIED:20240215T103430Z
UID:10000055-1643014800-1653152400@cmsa.fas.harvard.edu
SUMMARY:General Relativity Program
DESCRIPTION:During the Spring 2022 semester\, the CMSA hosted a program on General Relativity. \nThis semester-long program included four minicourses\,  a conference\, and a workshop. \nGeneral Relativity Mincourses: March–May\, 2022 \nGeneral Relativity Conference: April 4–8\, 2022 \nGeneral Relativity Workshop: May 2–5\, 2022 \n  \nProgram Visitors \n\nDan Lee\, CMSA/CUNY\, 1/24/22 – 5/20/22\nStefan Czimek\, Brown\, 2/27/22 – 3/3/22\nLan-Hsuan Huang\, University of Connecticut\, 3/13/22 – 3/19/222\, 3/21/22 – 3/25/22\, 4/17 /22– 4/23/22\nMu-Tao Wang\, Columbia\, 3/21/22 – 3/25/22\, 5/7/22 – 5/9/22\nPo-Ning Chen\, University of California\, Riverside\, 3/21/22 – 3/25/22\,  5/7/22–5/9/22\nMarnie Smith\, Imperial College London\, 3/27/22 – 4/11/22\nChristopher Stith\, University of Michigan\, 3/27/22 – 4/23/22\nMartin Taylor\, Imperial College London\,  3/27/22 – 4/11/22\nMarcelo Disconzi\, Vanderbilt\, 5/9/22 – 5/21/22\nLydia Bieri\, University of Michigan\, 5/5/22 – 5/9/22\n\n 
URL:https://cmsa.fas.harvard.edu/event/general-relativity-program/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Event,Programs
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/GR-Program-Banner_800x450-2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220301T100000
DTEND;TZID=America/New_York:20220517T130000
DTSTAMP:20260503T160231
CREATED:20240215T103842Z
LAST-MODIFIED:20250328T144509Z
UID:10002743-1646128800-1652792400@cmsa.fas.harvard.edu
SUMMARY:General Relativity Program Minicourses
DESCRIPTION:Minicourses\nGeneral Relativity Program Minicourses \n\nDuring the Spring 2022 semester\, the CMSA hosted a program on General Relativity. \nThis 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. \n\n  \n\n\n\n\nSchedule\nSpeaker\nTitle\nAbstract\n\n\nMarch 1 – 3\, 2022\n10:00 am – 12:00 pm ET\, each dayLocation: Hybrid. CMSA main seminar room\, G-10.\nDr. Stefan Czimek\nCharacteristic Gluing for the Einstein Equations\nAbstract: 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).\n\n\nMarch 22 – 25\, 2022\n22nd & 23rd\, 10:00 am – 11:30am ET\n24th & 25th\, 11:00 am – 12:30pm ETLocation: Hybrid. CMSA main seminar room\, G-10.\nProf. Lan-Hsuan Huang\nExistence of Static Metrics with Prescribed Bartnik Boundary Data\nAbstract: 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 \n1. The conjecture and an overview of the results\n2. Static regular: a sufficient condition for existence and local uniqueness\n3. Convex boundary\, isometric embedding\, and static regular\n4. Perturbations of any hypersurface are static regular \nVideo on Youtube: March 22\, 2022\n\n\nMarch 29 – April 1\, 2022 10:00am – 12:00pm ET\, each day \nLocation: Hybrid. CMSA main seminar room\, G-10.\nProf. Martin Taylor\nThe nonlinear stability of the Schwarzschild family of black holes\nAbstract: 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.\n\n\nApril 19 & 21\, 2022\n10 am – 12 pm ET\, each dayZoom only\nProf. Håkan Andréasson\nTwo topics for the Einstein-Vlasov system: Gravitational collapse and properties of static and stationary solutions.\nAbstract: 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. \nVideo 4/19/2022 \nVideo 4/22/2022\n\n\nMay 16 – 17\, 2022\n10:00 am – 1:00 pm ET\, each dayLocation: Hybrid. CMSA main seminar room\, G-10.\nProf. Marcelo Disconzi\nA brief overview of recent developments in relativistic fluids\nAbstract: 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. \n1. Set-up\, review of standard results\, physical motivation.\n2. The relativistic Euler equations: null structures and the problem of shocks.\n3. The free-boundary relativistic Euler equations with a physical vacuum boundary.\n4. Relativistic viscous fluids. \nVideo 5/16/2022 \nVideo 5/17/2022
URL:https://cmsa.fas.harvard.edu/event/grminicourses/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220506T100000
DTEND;TZID=America/New_York:20220508T170000
DTSTAMP:20260503T160231
CREATED:20230706T181343Z
LAST-MODIFIED:20231227T080733Z
UID:10000104-1651831200-1652029200@cmsa.fas.harvard.edu
SUMMARY:2022 NSF FRG Workshop on Discrete Shapes
DESCRIPTION:On May 6–8\, 2022\, the CMSA  hosted a second NSF FRG Workshop. \nThis 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. \nScientific 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. \nThis workshop is part of the NSF FRG project: Geometric and Topological Methods for Analyzing Shapes. \nThe workshop was held in room G10 of the CMSA\, located at 20 Garden Street\, Cambridge\, MA. \n\nWorkshop on Discrete Shapes\nMay 6–8\, 2022\nOrganizers: \n\nDavid Glickenstein (University of Arizona)\nJoel Hass (University of California\, Davis)\nPatrice Koehl (University of California\, Davis)\nFeng Luo (Rutgers University\, New Brunswick)\nMaria Trnkova (University of California\, Davis)\nShing-Tung Yau (Harvard)\n\nSpeakers: \n\nMiri Ben-Chen (Technion)\nAlexander Bobenko (TU Berlin)\nJohn Bowers (James Madison)\nSteven Gortler (Harvard)\nDavid Gu (Stony Brook)\nAnil Hirani (UIUC)\nYanwen Luo (Rutgers)\nPeter Schroeder (Caltech)\nJustin Solomon (MIT)\nTianqi Wu (Clark University)\n\nContributed Talk Speakers: \n\nOded Stein (MIT)\nBohan Zhou (Dartmouth)\n\nSchedule\nSchedule (PDF) \nFriday\, May 6\, 2022 \n\n\n\n\n10:00–10:05 am\n\nWelcome Opening\n\n\n10:05–10:55 am\nAnil N. Hirani\nTitle: Discrete vector bundles with connection \nAbstract: 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.).\n\n\n11:10–12:00 pm\nDavid Gu\nTitle: Surface Quadrilateral Meshing Based on Abel-Jacobi Theory \nAbstract: 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. \nIn 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. \nThis 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.\n\n\n12:00–2:00 pm\nLunch Break\n\n\n\n2:00–2:50 pm\n Justin Solomon\nTitle:  Geometry Processing with Volumes \nAbstract:  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.\n\n\n3:00–3:20 pm\nOded Stein\nTitle: Optimization for flip-free parametrization \nAbstract: 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).\n\n\n3:20–4:00 pm\nBreak\n\n\n\n4:00–4:50 pm\nJohn Bowers\nTitle: Koebe-Andre’ev-Thurston Packings via Flow \nAbstract: 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. \nThe 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.\n\n\n5:00–5:30 pm\nMovies\n “conform!” & ”Koebe polyhedra”\n\n\n\n\n  \nSaturday\, May 7\, 2022 \n\n\n\n\n9:30–10:20 am\nAlexander Bobenko\nTitle: The Bonnet problem: Is a surface characterized by its metric and curvatures? \nAbstract: 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\n\n\n10:20–11:00 am\nBreak\n\n\n\n11:00–11:50 am\nMiri Ben Chen\nTitle: Surface Multigrid via Intrinsic Prolongation \nAbstract: 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.\n\n\n12:00–2:00 pm\nLunch Break\n\n\n\n2:00–2:50 pm\nSteven Gortler\nTitle: Reconstructing configurations and graphs from unlabeled distance measurements \nAbstract: 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.\n\n\n3:00–3:20 pm\nBohan Zhou\nTitle: Efficient and Exact Multimarginal Optimal Transport with Pairwise Costs \nAbstract: 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.\n\n\n3:20–4:00 pm\nBreak\n\n\n\n4:00–4:50 pm\nPeter Schroeder\nTitle: Constrained Willmore Surfaces \nAbstract: 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. \nJoint work with Yousuf Soliman (Caltech)\, Olga Diamanti (UGraz)\, Albert Chern (UCSD)\, Felix Knöppel (TU Berlin)\, Ulrich Pinkall (TU Berlin).\n\n\n5:00–5:50 pm\n\nProblems and Application discussions\n\n\n\n\n  \nSunday\, May 8\, 2022 \n\n\n\n\n9:00–9:50 am\nTianqi Wu\nTitle: Convergence of discrete uniformizations \nAbstract: 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.\n\n\n10:10–11:00 am\nYanwen Luo\nTitle:  Recent Progress in Spaces of Geodesic Triangulations of Surfaces\n\nAbstract: 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.\n\n\n11:10–12:00 pm\n\nProblems and Application discussions\n\n\n12:00–1:00 pm\nMovie\n“The Discrete Charm of Geometry”
URL:https://cmsa.fas.harvard.edu/event/2022-nsf-frg-workshop/
LOCATION:CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Event,Workshop
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/FRG-Poster-1-791x1024-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220509T090000
DTEND;TZID=America/New_York:20220512T123000
DTSTAMP:20260503T160231
CREATED:20230706T181710Z
LAST-MODIFIED:20231227T082643Z
UID:10000107-1652086800-1652358600@cmsa.fas.harvard.edu
SUMMARY:Conference in Memory of Professor Masatake Kuranishi
DESCRIPTION: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. \nOrganizers:  Tristan Collins (MIT) and Shing-Tung Yau (Harvard and Tsinghua) \nVideos are available on the conference playlist. \n  \nSpeakers: \nCharles Fefferman (Princeton University) \nTeng Fei (Rutgers University) \nRobert Friedman (Columbia University) \nKenji Fukaya (Simons Center\, Stony Brook) \nAkito Futaki (Tsinghua University) \nVictor Guillemin (Massachusetts Institute of Technology) \nNigel Hitchin (Oxford University) \nBlaine Lawson (Stony Brook University) \nYu-Shen Lin (Boston University) \nMelissa C.C. Liu (Columbia University) \nTakeo Ohsawa (Nagoya University) \nDuong H. Phong (Columbia University) \nSebastien Picard (University of British Columbia) \nPaul Seidel (Massachusetts Institute of Technology) \nGabor Szekelyhidi (University of Notre Dame) \nClaire Voisin (Institut de Mathematiques\, Jussieu\, France) \nShing-Tung Yau (Harvard University) \n  \n\n\n\nSchedule (download pdf) \n\nMonday\, May 9\, 2022 \n\n\n\n8:15 am\nLight breakfast & coffee/tea\n\n\n8:45–9:00 am\nOpening Remarks\n\n\n9:00–10:00 am\nKenji Fukaya\nTitle: Gromov Hausdorff convergence of filtered A infinity category \nAbstract: 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. \nVideo\n\n\n10:15–11:15 am\nNigel Hitchin (Zoom)\nTitle: Deformations: A personal perspective \nAbstract: 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. \nVideo\n\n\n11:30–12:30 pm\nH. Blaine Lawson\nTitle: Projective Hulls\, Projective Linking\, and Boundaries of Varieties \nAbstract: 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| \nVideo\n\n\n12:30–2:30 pm\nLunch Break\n\n\n\n2:30–3:30 pm\nGabor Szekelyhidi\nTitle: Singularities along the Lagrangian mean curvature flow. \nAbstract: 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. \nVideo\n\n\n3:30–4:00 pm\nCoffee Break\n \n\n\n4:00–5:00 pm\nTakeo Ohsawa\nTitle: Glimpses of embeddings and deformations of CR manifolds \nAbstract: 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. \nVideo\n\n\n\n  \n  \n  \nTuesday\, May 10\, 2022 \n  \n\n\n\n8:15 am\nLight breakfast & coffee/tea\n\n\n9:00–10:00 am\nCharles Fefferman (Zoom)\nTitle: Interpolation of Data by Smooth Functions \nAbstract: 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? \nThe results were obtained jointly with A. Israel\, B. Klartag\, G.K. Luli and P. Shvartsman over many years. \nVideo\n\n\n10:15–11:15 am\nClaire Voisin\nTitle: Deformations of K-trivial manifolds and applications to hyper-Kähler geometry \nSummary: 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. \nVideo\n\n\n11:30– 2:30 pm\nVictor Guillemin\nTitle: Semi-Classical Functions of Isotropic Type \nAbstract: 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. \nVideo\n\n\n12:30–2:30 pm\nLunch Break\n\n\n\n2:30–3:30 pm\nTeng Fei\nTitle: Symplectic deformations and the Type IIA flow \nAbstract: 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. \nVideo\n\n\nSpeakers Banquet\n\n\n\n\n\n  \n  \n  \nWednesday\, May 11\, 2022 \n  \n\n\n\n8:15 am\nLight breakfast & coffee/tea\n\n\n9:00–10:00 am\nShing-Tung Yau (Zoom)\nTitle: Canonical metrics and stability in mirror symmetry \nAbstract: 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. \nVideo\n\n\n10:15–11:15 am\nDuong H. Phong\nTitle: $L^\infty$ estimates for the Monge-Ampere and other fully non-linear equations in complex geometry \nAbstract: 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. \nVideo\n\n\n11:30–2:30 pm\nPaul Seidel\nTitle: The quantum connection: familiar yet puzzling \nAbstract: 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. \nVideo\n\n\n12:30–2:30 pm\nLunch Break\n\n\n\n2:30–3:30 pm\nMelissa C.C. Liu\nTitle: Higgs-Coulumb correspondence for abelian gauged linear sigma models \nAbstract: 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. \nVideo\n\n\n3:30–4:00 pm\nCoffee Break\n \n\n\n4:00–5:00 pm\nSebastien Picard\nTitle: Topological Transitions of Calabi-Yau Threefolds \nAbstract: 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. \nVideo\n\n\n\n  \n  \n  \nThursday\, May 12\, 2022 \n  \n\n\n\n8:15 am\nLight breakfast & coffee/tea\n\n\n9:00 am–10:00 am\nAkito Futaki (Zoom)\nTitle: Transverse coupled Kähler-Einstein metrics and volume minimization\n\nAbstract: 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\n\n\n10:15 am–11:15 am\nYu-Shen Lin\nTitle: SYZ Mirror Symmetry of Log Calabi-Yau Surfaces \nAbstract: 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. \nVideo\n\n\n11:30 am – 12:30 pm\nRobert Friedman\nTitle: Deformations of singular Fano and Calabi-Yau varieties \nAbstract: 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. \nVideo\n\n\n12:30 pm\nConcluding Remarks\n\n\n\n 
URL:https://cmsa.fas.harvard.edu/event/conference-in-memory-of-professor-masatake-kuranishi/
LOCATION:Science and Engineering Complex (SEC)\, 150 Western Ave\, Allston\, MA 02134\, MA
CATEGORIES:Conference,Event
ATTACH;FMTTYPE=image/jpeg:https://cmsa.fas.harvard.edu/media/Kuranishi_Harvard_10x12-2.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220509T130000
DTEND;TZID=America/New_York:20220509T140000
DTSTAMP:20260503T160231
CREATED:20230730T181939Z
LAST-MODIFIED:20240214T102113Z
UID:10001150-1652101200-1652104800@cmsa.fas.harvard.edu
SUMMARY:Inflation and light Dark Matter constraints from the Swampland
DESCRIPTION:Abstract: I will explore the interplay between Swampland conjectures and models of inflation and light Dark Matter. To that end\, I will briefly review the weak gravity conjecture (WGC) and the related Festina Lente (FL) bound. These have implications for light darkly and milli-charged particles and can disfavor a large portion of parameter space. The FL bound also implies strong restrictions on the field content of our universe during inflation and presents an opportunity for inflationary model building. At the same time\, it rules out some popular models like chromo-natural inflation and gauge-flation. Finally\, I will review  another Swampland conjecture related to Stückelberg photon masses and discuss its implications for astro-particle physics.
URL:https://cmsa.fas.harvard.edu/event/5-9-2022-swampland-seminar/
LOCATION:Virtual
CATEGORIES:Swampland Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220511T103000
DTEND;TZID=America/New_York:20220511T120000
DTSTAMP:20260503T160231
CREATED:20240214T100851Z
LAST-MODIFIED:20240813T163022Z
UID:10002659-1652265000-1652270400@cmsa.fas.harvard.edu
SUMMARY:Cosmology from the vacuum
DESCRIPTION:Abstract: We are familiar with the idea that quantum gravity in AdS can holographically emerge from complex patterns of entanglement\, but can the physics of big bang cosmology emerge from a quantum many-body system? In this talk I will argue that standard tools of holography can be used to describe fully non-perturbative microscopic models of cosmology in which a period of accelerated expansion may result from the positive potential energy of time-dependent scalar fields evolving towards a region with negative potential. In these models\, the fundamental cosmological constant is negative\, and the universe eventually recollapses in a time-reversal symmetric way. The microscopic description naturally selects a special state for the cosmology. In this framework\, physics in the cosmological spacetime is dual to the vacuum physics in a static planar asymptotically AdS Lorentzian wormhole spacetime\, in the sense that the background spacetimes and observables are related by analytic continuation. The dual spacetime is weakly curved everywhere\, so any cosmological observables can be computed in the dual picture via effective field theory without detailed knowledge of the UV completion or the physics near the big bang. Based on 2203.11220 with S. Antonini\, P. Simidzija\, and M. Van Raamsdonk.
URL:https://cmsa.fas.harvard.edu/event/5-11-2022-quantum-matter-in-mathematics-and-physics/
CATEGORIES:Quantum Matter
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-QMMP-Seminar-05.11.22-1583x2048-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220512T103000
DTEND;TZID=America/New_York:20220512T120000
DTSTAMP:20260503T160231
CREATED:20240214T100601Z
LAST-MODIFIED:20240813T163153Z
UID:10002656-1652351400-1652356800@cmsa.fas.harvard.edu
SUMMARY:Oblique Lessons from the W Mass Measurement at CDF II
DESCRIPTION:Abstract: The CDF collaboration recently reported a new precise measurement of the W boson mass MW with a central value significantly larger than the SM prediction. We explore the effects of including this new measurement on a fit of the Standard Model (SM) to electroweak precision data. We characterize the tension of this new measurement with the SM and explore potential beyond the SM phenomena within the electroweak sector in terms of the oblique parameters S\, T and U. We show that the large MW value can be accommodated in the fit by a large\, nonzero value of U\, which is difficult to construct in explicit models. Assuming U = 0\, the electroweak fit strongly prefers large\, positive values of T. Finally\, we study how the preferred values of the oblique parameters may be generated in the context of models affecting the electroweak sector at tree- and loop-level. In particular\, we demonstrate that the preferred values of T and S can be generated with a real SU(2)L triplet scalar\, the humble swino\, which can be heavy enough to evade current collider constraints\, or by (multiple) species of a singlet-doublet fermion pair. We highlight challenges in constructing other simple models\, such as a dark photon\, for explaining a large MW value\, and several directions for further study.
URL:https://cmsa.fas.harvard.edu/event/5-12-2022-quantum-matter-in-mathematics-and-physics/
CATEGORIES:Quantum Matter
ATTACH;FMTTYPE=image/jpeg:https://cmsa.fas.harvard.edu/media/CMSA-QMMP-Seminar-05.12.22-1583x2048-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220512T153800
DTEND;TZID=America/New_York:20220512T173800
DTSTAMP:20260503T160231
CREATED:20240214T084325Z
LAST-MODIFIED:20240301T102818Z
UID:10002594-1652369880-1652377080@cmsa.fas.harvard.edu
SUMMARY:Geometric Models for Sets of Probability Measures
DESCRIPTION:Abstract: Many statistical and computational tasks boil down to comparing probability measures expressed as density functions\, clouds of data points\, or generative models.  In this setting\, we often are unable to match individual data points but rather need to deduce relationships between entire weighted and unweighted point sets. In this talk\, I will summarize our team’s recent efforts to apply geometric techniques to problems in this space\, using tools from optimal transport and spectral geometry. Motivated by applications in dataset comparison\, time series analysis\, and robust learning\, our work reveals how to apply geometric reasoning to data expressed as probability measures without sacrificing computational efficiency.
URL:https://cmsa.fas.harvard.edu/event/5-12-2022-interdisciplinary-science-seminar/
CATEGORIES:Interdisciplinary Science Seminar
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-Interdisciplinary-Science-Seminar-05.12.22-1583x2048-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220513T093000
DTEND;TZID=America/New_York:20220513T110000
DTSTAMP:20260503T160231
CREATED:20240214T084053Z
LAST-MODIFIED:20240301T105004Z
UID:10002593-1652434200-1652439600@cmsa.fas.harvard.edu
SUMMARY:Cobordism and Deformation Class of the Standard Model and Beyond: Proton Stability and Neutrino Mass
DESCRIPTION:Member Seminar \nSpeaker: Juven Wang \nTitle: Cobordism and Deformation Class of the Standard Model and Beyond: Proton Stability and Neutrino Mass \nAbstract: ‘t Hooft anomalies of quantum field theories (QFTs) with an invertible global symmetry G (including spacetime and internal symmetries) in a d-dim spacetime are known to be classified by a d+1-dim cobordism group TPd+1(G)\, whose group generator is a d+1-dim cobordism invariant written as a d+1-dim invertible topological field theory. Deformation class of QFT is recently proposed to be specified by its symmetry G and a d+1-dim invertible topological field theory. Seemly different QFTs of the same deformation class can be deformed to each other via quantum phase transitions. We ask which deformation class controls the 4d ungauged or gauged (SU(3)×SU(2)×U(1))/Zq Standard Model (SM) for q=1\,2\,3\,6 with a continuous or discrete (B−L) symmetry and with also a compatible discrete baryon plus lepton Z_{2Nf} B+L symmetry. (The Z_{2Nf} B+L is discrete due to the ABJ anomaly under the BPST instanton.) We explore a systematic classification of candidate perturbative local and nonperturbative global anomalies of the 4d SM\, including all these gauge and gravitational backgrounds\, via a cobordism theory\, which controls the SM’s deformation class. While many Grand Unified Theories violating the discrete B+L symmetry suffer from the proton decay\, the SM and some versions of Ultra Unification (constrained by Z_{16} class global anomaly that replaces sterile neutrinos with new exotic gapped/gapless topological or conformal sectors) can have a stable proton. Dictated by a Z_2 class global mixed gauge-gravitational anomaly\, there can be a gapless deconfined quantum critical region between Georgi-Glashow and Pati-Salam models — the Standard Model and beyond occur as neighbor phases. We will also comment on a new mechanism to give the neutrino mass via topological field theories and topological defects. Work based on arXiv:2112.14765\, arXiv:2204.08393\, arXiv:2202.13498 and references therein.
URL:https://cmsa.fas.harvard.edu/event/5-13-2022-member-seminar/
CATEGORIES:Member Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220517T090000
DTEND;TZID=America/New_York:20220517T180000
DTSTAMP:20260503T160231
CREATED:20230706T181958Z
LAST-MODIFIED:20240229T102937Z
UID:10000146-1652778000-1652810400@cmsa.fas.harvard.edu
SUMMARY:SMaSH: Symposium for Mathematical Sciences at Harvard
DESCRIPTION:SMaSH: Symposium for Mathematical Sciences at Harvard\nOn 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. \nOrganizing Committee \n\nMichael Brenner\, Applied Mathematics (SEAS)\nMichael Desai\, Organismic and Evolutionary Biology (FAS)\nSam Gershman\, Psychology (FAS)\nMichael Hopkins\, Mathematics (FAS)\nGary King\, Government (FAS)\nPeter Koellner\, Philosophy (FAS)\nScott Kominers\, Economics (FAS) & Entrepreneurial Management (HBS)\nXihong Lin\, Biostatistics (HSPH) & Statistics (FAS)\nYue Lu\, Electrical Engineering (SEAS)\nSusan Murphy\, Statistics (FAS) & Computer Science (SEAS)\nLisa Randall\, Physics (SEAS)\nEugene Shakhnovich\, Chemistry (FAS)\nSalil Vadhan\, Computer Science (SEAS)\nHorng-Tzer Yau\, Mathematics (FAS)\n\n\nThis event was held in-person at the Science and Engineering Complex (SEC) at 150 Western Ave\, Allston\, MA 02134\, and streamed on Zoom. \nHarvard graduate students and postdocs presented Poster Sessions. \n\nVenue: Science and Engineering Complex (SEC) \n\nSpeakers\n\nAnurag Anshu\, Computer Science (SEAS)\nMorgane Austern\, Statistics (FAS)\nDemba Ba\, Electrical Engineering & Bioengineering (SEAS)\nMichael Brenner\, Applied Mathematics (SEAS)\nRui Duan\, Biostatistics (HSPH)\nYannai A. Gonczarowski\, Economics (FAS) & Computer Science (SEAS)\nKosuke Imai\, Government & Statistics (FAS)\nSham M. Kakade\, Computer Science (SEAS) & Statistics (FAS)\nSeth Neel\, Technology & Operations Management (HBS)\nMelanie Matchett Wood\, Mathematics (FAS)\n\nSchedule PDF \nSchedule\n\n\n\n\n9:00–9:30 am\nCoffee and Breakfast\nWest Atrium (ground floor of the SEC)\n\n\n9:30–10:30 am\nFaculty Talks\nWinokur 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\n\n\n10:30–11:00 am\nCoffee Break\nWest Atrium (ground floor of the SEC)\n\n\n11:00–12:00 pm\nFaculty Talks\nWinokur 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\n\n\n12:00–1:00 pm\nLunch Break\nEngineering Yard Tent\n\n\n1:00–2:30 pm\nFaculty Talks\nWinokur 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.\n\n\n2:30–3:00 pm\nCoffee Break\nWest Atrium (ground floor of the SEC)\n\n\n3:00–4:30 pm\nFaculty Talks\nWinokur 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?\n\n\n4:30–5:30 pm\nReception with Jazz musicians\n& Poster Session\nEngineering Yard Tent\n\n\n\n\n\nFaculty Talks\n\n\n\n\nSpeaker\nTitle / Abstract / Bio\n\n\nAnurag Anshu\, Computer Science (SEAS)\nTitle: Operator-valued polynomial approximations and their use. \nAbstract: 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. \nBio: 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.\n\n\nMorgane Austern\, Statistics (FAS)\nTitle: Limit theorems for structured random objects \nAbstract: 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. \nBio: 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.\n\n\nDemba Ba\, Electrical Engineering & Bioengineering (SEAS)\nTitle: Geometry\, AI\, and the Brain \nAbstract: 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. \nBio: 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.\n\n\nMichael Brenner\, Applied Mathematics (SEAS)\nTitle: Towards living synthetic materials \nAbstract: 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. \nBio: I’ve been at Harvard for a long time. My favorite part of Harvard is the students.\n\n\nRui Duan\, Biostatistics (HSPH)\nTitle: Federated and transfer learning for healthcare data integration \nAbstract: 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. \nBio: 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.\n\n\nYannai A. Gonczarowski\, Economics (FAS) & Computer Science (SEAS)\nTitle: The Sample Complexity of Up-to-ε Multi-Dimensional Revenue Maximization \nAbstract: 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. \nOur 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. \nJoint work with S. Matthew Weinberg \nBio: 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.\n\n\nKosuke Imai\, Government & Statistics (FAS)\nTitle: Use of Simulation Algorithms for Legislative Redistricting Analysis and Evaluation \nAbstract: 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. \nBio: 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.\n\n\nSham M. Kakade\, Computer Science (SEAS) & Statistics (FAS)\nTitle: What is the Statistical Complexity of Reinforcement Learning? \nAbstract: 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. \nThis 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. \nBio: 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. \nSham 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.\n\n\nSeth Neel\, Technology & Operations Management (HBS)\nTitle: “Machine (Un)Learning” or Why Your Deployed Model Might Violate Existing Privacy Law \nAbstract:  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. \nBio: 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.\n\n\nMelanie Matchett Wood\, Mathematics (FAS)\nTitle: Understanding distributions of algebraic structures through their moments \nAbstract: 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. \nBio: 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.
URL:https://cmsa.fas.harvard.edu/event/smash-symposium-for-mathematical-sciences-at-harvard/
LOCATION:Science and Engineering Complex (SEC)\, 150 Western Ave\, Allston\, MA 02134\, MA
CATEGORIES:Conference,Event
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/SMaSH_2022-2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220517T093000
DTEND;TZID=America/New_York:20220517T103000
DTSTAMP:20260503T160231
CREATED:20240214T072604Z
LAST-MODIFIED:20240304T055019Z
UID:10002559-1652779800-1652783400@cmsa.fas.harvard.edu
SUMMARY:Hypergraph Matchings Avoiding Forbidden Submatchings
DESCRIPTION:Abstract:  In 1973\, Erdős conjectured the existence of high girth (n\,3\,2)-Steiner systems. Recently\, Glock\, Kühn\, Lo\, and Osthus and independently Bohman and Warnke proved the approximate version of Erdős’ conjecture. Just this year\, Kwan\, Sah\, Sawhney\, and Simkin proved Erdős’ conjecture. As for Steiner systems with more general parameters\, Glock\, Kühn\, Lo\, and Osthus conjectured the existence of high girth (n\,q\,r)-Steiner systems. We prove the approximate version of their conjecture.  This result follows from our general main results which concern finding perfect or almost perfect matchings in a hypergraph G avoiding a given set of submatchings (which we view as a hypergraph H where V(H)=E(G)). Our first main result is a common generalization of the classical theorems of Pippenger (for finding an almost perfect matching) and Ajtai\, Komlós\, Pintz\, Spencer\, and Szemerédi (for finding an independent set in girth five hypergraphs). More generally\, we prove this for coloring and even list coloring\, and also generalize this further to when H is a hypergraph with small codegrees (for which high girth designs is a specific instance). Indeed\, the coloring version of our result even yields an almost partition of K_n^r into approximate high girth (n\,q\,r)-Steiner systems.  If time permits\, I will explain some of the other applications of our main results such as to rainbow matchings.  This is joint work with Luke Postle.
URL:https://cmsa.fas.harvard.edu/event/5-17-2022-combinatorics-physics-and-probability-seminar/
CATEGORIES:Combinatorics Physics and Probability
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-Combinatorics-Physics-and-Probability-Seminar-05.17.22.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220518T093000
DTEND;TZID=America/New_York:20220518T103000
DTSTAMP:20260503T160231
CREATED:20240214T055948Z
LAST-MODIFIED:20240502T151226Z
UID:10002547-1652866200-1652869800@cmsa.fas.harvard.edu
SUMMARY:Statistical Mechanics of Mutilated Sheets and Shells
DESCRIPTION:Speaker: David Nelson\, Harvard University \nTitle: Statistical Mechanics of Mutilated Sheets and Shells \nAbstract:  Understanding deformations of macroscopic thin plates and shells has a long and rich history\, culminating with the Foeppl-von Karman equations in 1904\, a precursor of general relativity characterized by a dimensionless coupling constant (the “Foeppl-von Karman number”) that can easily reach  vK = 10^7 in an ordinary sheet of writing paper.  However\, thermal fluctuations in thin elastic membranes fundamentally alter the long wavelength physics\, as exemplified by experiments that twist and bend individual atomically-thin free-standing graphene sheets (with vK = 10^13!)   A crumpling transition out of the flat phase for thermalized elastic membranes has been predicted when kT is large compared to the microscopic bending stiffness\, which could have interesting consequences for Dirac cones of electrons embedded in graphene.   It may be possible to lower the crumpling temperature for graphene to more readily accessible range by inserting a regular lattice of laser-cut perforations\, an expectation an confirmed by extensive molecular dynamics simulations.    We then move on to analyze the physics of sheets mutilated with puckers and stitches.   Puckers and stitches lead to Ising-like phase transitions riding on a background of flexural phonons\, as well as an anomalous coefficient of thermal expansion.  Finally\, we argue that thin membranes with a background curvature lead to thermalized spherical shells that must collapse beyond a critical size at room temperature\, even in the absence of an external pressure.
URL:https://cmsa.fas.harvard.edu/event/statistical-mechanics-of-mutilated-sheets-and-shells/
CATEGORIES:Colloquium
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-Colloquium-05.18.22.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220518T160000
DTEND;TZID=America/New_York:20220518T173000
DTSTAMP:20260503T160231
CREATED:20240214T095418Z
LAST-MODIFIED:20240813T163304Z
UID:10002651-1652889600-1652895000@cmsa.fas.harvard.edu
SUMMARY:The Generalized Landau Paradigm (a review of generalized symmetries in condensed matter)
DESCRIPTION:Abstract: Recent advances in our understanding of symmetry in quantum many-body systems offer the possibility of a generalized Landau paradigm that encompasses all equilibrium phases of matter. This talk will be an elementary review of some of these developments\, based on: https://arxiv.org/abs/2204.03045
URL:https://cmsa.fas.harvard.edu/event/5-18-2022-quantum-matter-in-mathematics-and-physics/
LOCATION:Virtual
CATEGORIES:Quantum Matter
ATTACH;FMTTYPE=image/jpeg:https://cmsa.fas.harvard.edu/media/CMSA-QMMP-Seminar-05.18.22-1583x2048-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220518T160000
DTEND;TZID=America/New_York:20220518T173000
DTSTAMP:20260503T160231
CREATED:20240215T101105Z
LAST-MODIFIED:20240813T162341Z
UID:10002739-1652889600-1652895000@cmsa.fas.harvard.edu
SUMMARY:Boundary conditions and LSM anomalies of conformal field theories in 1+1 dimensions
DESCRIPTION:Speaker: Linhao Li (ISSP\, U Tokyo) \nTitle: Boundary conditions and LSM anomalies of conformal field theories in 1+1 dimensions \nAbstract: In this talk\, we will study a relationship between conformally invariant boundary conditions and anomalies of conformal field theories (CFTs) in 1+1 dimensions. For a given CFT with a global symmetry\, we consider symmetric gapping potentials which are relevant perturbations to the CFT. If a gapping potential is introduced only in a subregion of the system\, it provides a certain boundary condition to the CFT. From this equivalence\, if there exists a Cardy boundary state which is invariant under a symmetry\, then the CFT can be gapped with a unique ground state by adding the corresponding gapping potential. This means that the symmetry of the CFT is anomaly free. Using this approach\, we will systematically deduce the anomaly-free conditions for various types of CFTs with several different symmetries. When the symmetry of the CFT is anomalous\, it implies a Lieb-Schultz-Mattis type ingappability of the system. Our results are consistent with\, where available\, known results in the literature. Moreover\, we extend the discussion to other symmetries including spin groups and generalized time-reversal symmetries. As an application\, we propose 1d LSM theorem involving magnetic space group symmetries on the lattice. The extended LSM theorems apply to systems with a broader class of spin interactions\, such as Dzyaloshinskii-Moriya interactions and chiral three-spin interactions.
URL:https://cmsa.fas.harvard.edu/event/5-18-2022-quantum-matter-in-mathematics-and-physics-2/
LOCATION:Virtual
CATEGORIES:Quantum Matter
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220519T090000
DTEND;TZID=America/New_York:20220519T100000
DTSTAMP:20260503T160231
CREATED:20240214T084730Z
LAST-MODIFIED:20240301T102658Z
UID:10002598-1652950800-1652954400@cmsa.fas.harvard.edu
SUMMARY:The geometry of conditional independence models with hidden variables
DESCRIPTION:Abstract: Conditional independence (CI) is an important tool instatistical modeling\, as\, for example\, it gives a statistical interpretation to graphical models. In general\, given a list of dependencies among random variables\, it is difficult to say which constraints are implied by them. Moreover\, it is important to know what constraints on the random variables are caused by hidden variables. On the other hand\, such constraints are corresponding to some determinantal conditions on the tensor of joint probabilities of the observed random variables. Hence\, the inference question in statistics relates to understanding the algebraic and geometric properties of determinantal varieties such as their irreducible decompositions or determining their defining equations. I will explain some recent progress that arises by uncovering the link to point configurations in matroid theory and incidence geometry. This connection\, in particular\, leads to effective computational approaches for (1) giving a decomposition for each CI variety; (2) identifying each component in the decomposition as a matroid variety; (3) determining whether the variety has a real point or equivalently there is a statistical model satisfying a given collection of dependencies. The talk is based on joint works with Oliver Clarke\, Kevin Grace\, and Harshit Motwani. \nThe papers are available on arxiv: https://arxiv.org/pdf/2011.02450\nand https://arxiv.org/pdf/2103.16550.pdf
URL:https://cmsa.fas.harvard.edu/event/5-19-2022-cmsa-interdisciplinary-science-seminar/
CATEGORIES:Interdisciplinary Science Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220521T090000
DTEND;TZID=America/New_York:20220612T170000
DTSTAMP:20260503T160231
CREATED:20230706T182609Z
LAST-MODIFIED:20240229T094452Z
UID:10000147-1653123600-1655053200@cmsa.fas.harvard.edu
SUMMARY:2022 Summer Introduction to Mathematical Research
DESCRIPTION: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: \nSummer Introduction to Mathematical Research (sponsored by CMSA and the Harvard Math Department) \nIn 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. \nThe 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. \nPrerequisites: 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. \nThe 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. \nThis 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.) \nHowever: 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.) \nIf 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.
URL:https://cmsa.fas.harvard.edu/event/2022-summer-introduction-to-mathematical-research/
LOCATION:Virtual
CATEGORIES:Event,Programs
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220525T103000
DTEND;TZID=America/New_York:20220525T120000
DTSTAMP:20260503T160231
CREATED:20240215T101805Z
LAST-MODIFIED:20240215T102153Z
UID:10002740-1653474600-1653480000@cmsa.fas.harvard.edu
SUMMARY:Oblique Lessons from the W Mass Measurement at CDF II
DESCRIPTION:Speaker: Seth Koren (University of Chicago) \nTitle: Baryon Minus Lepton Number BF Theory for the Cosmological Lithium Problem \nAbstract: The cosmological lithium problem—that the observed primordial abundance is lower than theoretical expectations by order one—is perhaps the most statistically significant anomaly of SM+ ΛCDM\, and has resisted decades of attempts by cosmologists\, nuclear physicists\, and astronomers alike to root out systematics. We upgrade a discrete subgroup of the anomaly-free global symmetry of the SM to an infrared gauge symmetry\, and UV complete this at a scale Λ as the familiar U(1)_{B-N_cL} Abelian Higgs theory. The early universe phase transition forms cosmic strings which are charged under the emergent higher-form symmetry of the baryon minus lepton BF theory. These topological defects catalyze interactions which turn N_g baryons into N_g leptons at strong scale rates in an analogue of the Callan-Rubakov effect\, where N_g=3 is the number of SM generations. We write down a model in which baryon minus lepton strings superconduct bosonic global baryon plus lepton number currents and catalyze solely 3p^+ → 3e^+. We suggest that such cosmic strings have disintegrated O(1) of the lithium nuclei formed during Big Bang Nucleosynthesis and estimate the rate\, with our benchmark model finding Λ ~ 10^8 GeV gives the right number density of strings.
URL:https://cmsa.fas.harvard.edu/event/qm_51222/
LOCATION:Hybrid
CATEGORIES:Quantum Matter
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220526T090000
DTEND;TZID=America/New_York:20220526T100000
DTSTAMP:20260503T160231
CREATED:20240214T085539Z
LAST-MODIFIED:20240301T102538Z
UID:10002601-1653555600-1653559200@cmsa.fas.harvard.edu
SUMMARY:Extinction and coexistence for reaction-diffusion systems on metric graphs
DESCRIPTION:Abstract: In spatial population genetics\, it is important to understand the probability of extinction in multi-species interactions such as growing bacterial colonies\, cancer tumor evolution and human migration. This is because extinction probabilities are instrumental in determining the probability of coexistence and the genealogies of populations. A key challenge is the complication due to spatial effect and different sources of stochasticity. In this talk\, I will discuss about methods to compute the probability of extinction and other long-time behaviors for stochastic reaction-diffusion equations on metric graphs that flexibly parametrizes the underlying space. Based on recent joint work with Adrian Gonzalez-Casanova and Yifan (Johnny) Yang.
URL:https://cmsa.fas.harvard.edu/event/5-26-2022-interdisciplinary-science-seminar/
CATEGORIES:Interdisciplinary Science Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220602T161300
DTEND;TZID=America/New_York:20220602T171300
DTSTAMP:20260503T160231
CREATED:20240214T090758Z
LAST-MODIFIED:20240301T102323Z
UID:10002608-1654186380-1654189980@cmsa.fas.harvard.edu
SUMMARY:Fast Point Transformer
DESCRIPTION:Abstract: The recent success of neural networks enables a better interpretation of 3D point clouds\, but processing a large-scale 3D scene remains a challenging problem. Most current approaches divide a large-scale scene into small regions and combine the local predictions together. However\, this scheme inevitably involves additional stages for pre- and post-processing and may also degrade the final output due to predictions in a local perspective. This talk introduces Fast Point Transformer that consists of a new lightweight self-attention layer. Our approach encodes continuous 3D coordinates\, and the voxel hashing-based architecture boosts computational efficiency. The proposed method is demonstrated with 3D semantic segmentation and 3D detection. The accuracy of our approach is competitive to the best voxel-based method\, and our network achieves 129 times faster inference time than the state-of-the-art\, Point Transformer\, with a reasonable accuracy trade-off in 3D semantic segmentation on S3DIS dataset. \nBio: Jaesik Park is an Assistant Professor at POSTECH. He received his Bachelor’s degree from Hanyang University in 2009\, and he received his Master’s degree and Ph.D. degree from KAIST in 2011 and 2015\, respectively. Before joining POSTECH\, He worked at Intel as a research scientist\, where he co-created the Open3D library. His research interests include image synthesis\, scene understanding\, and 3D reconstruction. He serves as a program committee at prestigious computer vision conferences\, such as Area Chair for ICCV\, CVPR\, and ECCV.
URL:https://cmsa.fas.harvard.edu/event/6-2-2022-interdisciplinary-science-seminar/
CATEGORIES:Interdisciplinary Science Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220606T090000
DTEND;TZID=America/New_York:20220608T170000
DTSTAMP:20260503T160231
CREATED:20230706T182850Z
LAST-MODIFIED:20250305T172950Z
UID:10000893-1654506000-1654707600@cmsa.fas.harvard.edu
SUMMARY:Symposium on Foundations of Responsible Computing (FORC)
DESCRIPTION:On June 6-8\, 2022\, the CMSA hosted the 3rd annual Symposium on Foundations of Responsible Computing (FORC). \nThe 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. \nOrganizers: Cynthia Dwork\, Harvard SEAS | Omer Reingold\, Stanford | Elisa Celis\, Yale \nSchedule\nJune 6\, 2022 \n\n\n\n\n9:15 am–10:15 am\nOpening Remarks \nKeynote Speaker: Caroline Nobo\, Yale University\nTitle: From Theory to Impact: Why Better Data Systems are Necessary for Criminal Legal Reform \nAbstract: 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.\n\n\n10:15 am–10:45 am\nCoffee Break\n\n\n\n10:45 am–12:15 pm\nPaper Session 1\nSession Chair: Ruth Urner\n\n\n\nGeorgy Noarov\, University of Pennsylvania\nTitle: Online Minimax Multiobjective Optimization \nAbstract: 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.\n\n\n\nMatthew Eichhorn\, Cornell University\nTitle: Mind your Ps and Qs: Allocation with Priorities and Quotas \nAbstract: 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.\n\n\n\nHaewon Jeong\, Harvard University\nTitle: Fairness without Imputation: A Decision Tree Approach for Fair Prediction with Missing Values \nAbstract: 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.\n\n\n\nEmily Diana\, University of Pennsylvania\nTitle: Multiaccurate Proxies for Downstream Fairness \nAbstract: 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.\n\n\n12:15 pm–1:45 pm\nLunch Break\n\n\n\n1:45–3:15 pm\nPaper Session 2\nSession Chair: Guy Rothblum\n\n\n\nElbert Du\, Harvard University\nTitle: Improved Generalization Guarantees in Restricted Data Models \nAbstract: 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.\n\n\n\nRuth Urner\, York University\nTitle: Robustness Should not be at Odds with Accuracy \nAbstract: 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.\n\n\n\nSushant Agarwal\, University of Waterloo\nTitle: Towards the Unification and Robustness of Perturbation and Gradient Based Explanations \nAbstract: 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.\n\n\n\nTijana Zrnic\, University of California\, Berkeley\nTitle: Regret Minimization with Performative Feedback \nAbstract: 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.\n\n\n3:15 pm–3:45 pm\nCoffee Break\n\n\n\n3:45 pm–5:00 pm\nPanel Discussion\nTitle: What is Responsible Computing? \nPanelists: Jiahao Chen\, Cynthia Dwork\, Kobbi Nissim\, Ruth Urner \nModerator: Elisa Celis\n\n\n\n\n  \nJune 7\, 2022 \n\n\n\n\n9:15 am–10:15 am\nKeynote Speaker: Isaac Kohane\, Harvard Medical School\nTitle: What’s in a label? The case for and against monolithic group/ethnic/race labeling for machine learning \nAbstract: 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.\n\n\n10:15 am–10:45 am\nCoffee Break\n\n\n\n10:45 am–12:15 pm\nPaper Session 3\nSession Chair: Ruth Urner\n\n\n\nRojin Rezvan\, University of Texas at Austin\nTitle: Individually-Fair Auctions for Multi-Slot Sponsored Search \nAbstract: 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.\n\n\n\nJudy Hanwen Shen\, Stanford\nTitle: Leximax Approximations and Representative Cohort Selection \nAbstract: 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.\n\n\n\nJiayuan Ye\,\nNational University of Singapore\nTitle: Differentially Private Learning Needs Hidden State (or Much Faster Convergence) \nAbstract: 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.\n\n\n\nMahbod Majid\, University of Waterloo\nTitle: Efficient Mean Estimation with Pure Differential Privacy via a Sum-of-Squares Exponential Mechanism \nAbstract: 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. \nOur 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.\n\n\n12:15 pm–1:45 pm\nLunch Break\n\n\n\n1:45–3:15 pm\nPaper Session 4\nSession Chair: Kunal Talwar\n\n\n\nKunal Talwar\,\nApple\nTitle: Differential Secrecy for Distributed Data and Applications to Robust Differentially Secure Vector Summation \nAbstract: 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.\nIn 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.\n\n\n\nGiuseppe Vietri\, University of Minnesota\nTitle: Improved Regret for Differentially Private Exploration in Linear MDP \nAbstract: 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.\n\n\n\nMingxun Zhou\,\nCarnegie Mellon University\nTitle: 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?\nIn 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.\n\n\n\nBadih Ghazi\,\nGoogle Research\nTitle: Differentially Private Ad Conversion Measurement \nAbstract: 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\nbudget scope and enforcement point\, and provide\, for a natural space of configurations\, a complete characterization.\n\n\n3:15 pm–3:45 pm\nCoffee Break\n\n\n\n3:45 pm–5:00 pm\nOpen Poster Session\n\n\n\n\n\n  \nJune 8\, 2022 \n\n\n\n\n9:15 am–10:15 am\nKeynote Speaker: Nuria Oliver\, Data-Pop Alliance\nTitle: Data Science against COVID-19 \nAbstract: 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. \nI 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.\n\n\n10:15 am–10:45 am\nCoffee Break\n\n\n\n10:45 am–12:15 pm\nPaper Session 5\nSession Chair: Kunal Talwar\n\n\n\nShengyuan Hu\, Carnegie Mellon University\nTitle: Private Multi-Task Learning: Formulation and Applications to Federated Learning \nAbstract: 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\n\n\n\nChristina Yu\,\nCornell University\nTitle: Sequential Fair Allocation: Achieving the Optimal Envy-Efficiency Tradeoff Curve \nAbstract: 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.\n\n\n\nHedyeh Beyhaghi\, Carnegie Mellon University\nTitle: On classification of strategic agents who can both game and improve \nAbstract: 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.\n\n\n\nKeegan Harris\, Carnegie Mellon University\nTitle: Bayesian Persuasion for Algorithmic Recourse \nAbstract: 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.\n\n\n12:15 pm–1:45 pm\nLunch Break\n\n\n\n1:45–3:15 pm\nPaper Session 6\nSession Chair: Elisa Celis\n\n\n\nMark Bun\, Boston University\nTitle: Controlling Privacy Loss in Sampling Schemes: An Analysis of Stratified and Cluster Sampling \nAbstract: 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.\n\n\n\nSamson Zhou\, Carnegie Mellon University\nTitle: Private Data Stream Analysis for Universal Symmetric Norm Estimation \nAbstract: 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.\n\n\n\nAloni Cohen\, University of Chicago\nTitle: Attacks on Deidentification’s Defenses \nAbstract: 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.\nFirst\, 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. \nThe 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.\n\n\n\nSteven Wu\,\nCarnegie Mellon University\nTitle: Fully Adaptive Composition in Differential Privacy \nAbstract: 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.\n\n\n3:15 pm–3:45 pm\nFORC Reception\n\n\n\n3:45 pm–5:00 pm\nSocial Hour
URL:https://cmsa.fas.harvard.edu/event/symposium-on-foundations-of-responsible-computing-forc/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Conference,Event
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220616T090000
DTEND;TZID=America/New_York:20220616T100000
DTSTAMP:20260503T160231
CREATED:20240215T094047Z
LAST-MODIFIED:20240229T084329Z
UID:10002724-1655370000-1655373600@cmsa.fas.harvard.edu
SUMMARY:Surface hopping algorithms for non-adiabatic quantum systems
DESCRIPTION:Interdisciplinary Science Seminar\n\n\n\n\nSpeaker: Jianfeng Lu\, Duke UniversityTitle: Surface hopping algorithms for non-adiabatic quantum systems \nAbstract: Surface hopping algorithm is widely used in chemistry for mixed quantum-classical dynamics. In this talk\, we will discuss some of our recent works in mathematical understanding and algorithm development for surface hopping methods. These methods are based on stochastic approximations of semiclassical path-integral representation to the solution of multi-level Schrodinger equations; such methodology also extends to other high-dimensional transport systems.
URL:https://cmsa.fas.harvard.edu/event/iss_61622/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Interdisciplinary Science Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220621T090000
DTEND;TZID=America/New_York:20220624T170000
DTSTAMP:20260503T160231
CREATED:20230706T183302Z
LAST-MODIFIED:20250305T175141Z
UID:10000894-1655802000-1656090000@cmsa.fas.harvard.edu
SUMMARY:Joint BHI/CMSA Conference on Flat Holography
DESCRIPTION: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). \nThe 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. \nThe conference was held in room G10 of the CMSA\, 20 Garden Street\, Cambridge\, MA. \nOrganizers: \n\nDaniel Kapec\, CMSA\nAndrew Strominger\, BHI\nShing-Tung Yau\, Harvard & Tsinghua\n\nConfirmed Speakers: \n\nNima Arkani-Hamed\, IAS\nShamik Banerjee\, Bhubaneswar\, Inst. Phys.\nMiguel Campiglia\, Republica U.\, Montevido\nGeoffrey Compere\, Brussels\nLaura Donnay\, Vienna\nNetta Engelhardt\, MIT\nLaurent Freidel\, Perimeter\nAlex Lupsasca\, Princeton\nJuan Maldacena\, IAS\nLionel Mason\, Oxford\nNatalie Paquette\, U. Washington\nSabrina Pasterski\, Princeton/Perimeter\nAndrea Puhm\, Ecole Polytechnique\nAna-Maria Raclariu\, Perimeter\nMarcus Spradlin\, Brown\nTomasz Taylor\, Northeastern\nHerman Verlinde\, Princeton\nAnastasia Volovich\, Brown\nBin Zhu\, Northeastern\n\nShort 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) \n\n\nSchedule\nMonday\, June 20\, 2022 \n\n\n\n\n\nArrival\n\n\n7:00–9:00 pm\nWelcome Reception at Andy’s residence\n\n\n\n\n  \nTuesday\, June 21\, 2022 \n\n\n\n\n9:00–9:30 am\nBreakfast\nlight breakfast provided\n\n\n\nMorning Session\nChair: Dan Kapec\n\n\n9:30–10:00 am\nHerman Verlinde\nTitle: Comments on Celestial Dynamics\n\n\n10:00–10:30 am\nJuan Maldacena\nTitle: What happens when you spend too much time looking at supersymmetric\nblack holes?\n\n\n10:30–11:00\nCoffee break\n\n\n\n11:00–11:30 am\nMiguel Campiglia\nTitle: Asymptotic symmetries and loop corrections to soft theorems\n\n\n11:30–12:00 pm\nGeoffrey Compere\nTitle: Metric reconstruction from $Lw_{1+\infty}$ multipoles \nAbstract: 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.\n\n\n12:00–2:00 pm\nLunch break\n\n\n\n\nAfternoon Session\nChair: Eduardo Casali\n\n\n2:00–2:30 pm\nNatalie Paquette\nTitle: New thoughts on old gauge amplitudes\n\n\n2:30–3:00 pm\nLionel Mason\nTitle: An open sigma model for celestial gravity \nAbstract: A global twistor construction for conformally self-dual split signature metrics on $S2\times S2$  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.\n\n\n3:00–3:30 pm\nCoffee break\n\n\n\n3:30–4:30 pm\nShort Talks\nDaniel Kapec: Soft Scalars and the Geometry of the Space of Celestial CFTs \nAlbert Law: Soft Scalars and the Geometry of the Space of Celestial CFTs \nSruthi Narayanan: Soft Scalars and the Geometry of the Space of Celestial CFTs \nStéphane Detournay: Non-conformal symmetries and near-extremal black holes \nFrancisco Rojas: Celestial string amplitudes beyond tree level \nTemple He: An effective description of energy transport from holography\n\n\n4:30–5:00 pm\nNima Arkani-Hamed\n(Dual) surfacehedra and flow particles know about strings\n\n\n\n\n  \nWednesday\, June 22\, 2022 \n\n\n\n\n9:00–9:30 am\nBreakfast\nlight breakfast provided\n\n\n\nMorning Session\nChair: Alfredo Guevara\n\n\n9:30–10:00 am\nLaurent Freidel\nTitle: Higher spin symmetry in gravity \nAbstract: In this talk\, I will review how the gravitational conservation laws at infinity reveal a tower of symmetry charges in an asymptotically flat spacetime.\nI will show how the conservation laws\, at spacelike infinity\, give a tower of soft theorems that connect to the ones revealed by celestial holography.\nI’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:\nsuch 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.\n\n\n10:00–10:30 am\nAna-Maria Raclariu\nTitle: Eikonal approximation in celestial CFT\n\n\n10:30–11:00 am\nCoffee break\n\n\n\n11:00–11:30 am\nAnastasia Volovich\nTitle: Effective Field Theories with Celestial Duals\n\n\n11:30–12:00 pm\nMarcus Spradlin\nTitle: Loop level gluon OPE’s in celestial holography\n\n\n12:00–2:00 pm\nLunch break\n\n\n\n\nAfternoon Session\nChair: Chiara Toldo\n\n\n2:00–2:30 pm\nNetta Engelhardt\nTitle: Wormholes from entanglement: true or false?\n\n\n2:30–3:00 pm\nShort Talks\nLuke Lippstreu: Loop corrections to the OPE of celestial gluons \nYangrui Hu: Light transforms of celestial amplitudes \nLecheng Ren: All-order OPE expansion of celestial gluon and graviton primaries from MHV amplitudes\n\n\n3:00–3:30 pm\nCoffee break\n\n\n\n3:30–4:30 pm\nShort Talks\nNoah Miller: C Metric Thermodynamics \nErin Crawley: Kleinian black holes \nRifath Khan: Cauchy Slice Holography: A New AdS/CFT Dictionary \nGonçalo Araujo-Regado: Cauchy Slice Holography: A New AdS/CFT Dictionary \nTianli Wang: Soft Theorem in the BFSS Matrix Model \nAdam Tropper: Soft Theorem in the BFSS Matrix Model\n\n\n7:00–9:00 pm\nBanquet\nMaharaja Restaurant\, 57 JFK Street\, Cambridge\, MA\n\n\n\n\n  \nThursday\, June 23\, 2022 \n\n\n\n\n9:00–9:30 am\nBreakfast\nlight breakfast provided\n\n\n\nMorning Session\nChair: Jordan Cotler\n\n\n9:30–10:00 am\nLaura Donnay\nTitle: A Carrollian road to flat space holography\n\n\n10:00–10:30 am\nAndrea Puhm\nTitle: Celestial wave scattering on Kerr-Schild backgrounds\n\n\n10:30–11:00 am\nCoffee break\n\n\n\n11:00–11:30 am\nSabrina Pasterski\nTitle: Mining Celestial Symmetries \nAbstract: 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. \nCome prepared to debate the central charge\, loop corrections\, contour prescriptions\, and orders of limits!\n\n\n11:30–12:00 pm\nShamik Banerjee\nTitle: Virasoro and other symmetries in CCFT \nAbstract:  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.\n\n\n12:00–2:00 pm\nLunch break\n\n\n\n\nAfternoon Session\nChair: Albert Law\n\n\n2:00–2:30 pm\nTomasz Taylor\nTitle: Celestial Yang-Mills amplitudes and D=4 conformal blocks\n\n\n2:30–3:00 pm\nBin Zhu\nTitle:  Single-valued correlators and Banerjee-Ghosh equations \nAbstract:  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.\n\n\n3:00–3:30 pm\nCoffee break\n\n\n\n3:30–4:00 pm\nAlex Lupsasca\nTitle: Holography of the Photon Ring\n\n\n4:00–5:30 pm\nShort Talks\nElizabeth Himwich: Celestial OPEs and w(1+infinity) symmetry of massless and massive amplitudes \nAdam Ball: Perturbatively exact $w_{1+\infty}$ asymptotic symmetry of quantum self-dual gravity \nRomain Ruzziconi: A Carrollian Perspective on Celestial Holography \nJordan Cotler: Soft Gravitons in 3D \nAlfredo Guevara: Comments on w_1+\inf \nAndrew Strominger: Top-down celestial holograms \nEduardo Casali: Celestial amplitudes as AdS-Witten diagrams \nWalker Melton: Top-down celestial holograms\n\n\n\n\n  \nFriday\, June 24\, 2022 \n\n\n\n\n9:00–9:30 am\nBreakfast\n\n\n9:30–12:30 pm\nOpen Discussion\n\n\n12:30–2:30 pm\nLunch provided at the BHI\n\n\n\nDeparture\n\n\n\n\n 
URL:https://cmsa.fas.harvard.edu/event/joint-bhi-cmsa-conference-on-flat-holography/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Conference,Event
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220623T090000
DTEND;TZID=America/New_York:20220623T100000
DTSTAMP:20260503T160232
CREATED:20240214T091046Z
LAST-MODIFIED:20240301T101920Z
UID:10002611-1655974800-1655978400@cmsa.fas.harvard.edu
SUMMARY:Some new algorithms in statistical genomics
DESCRIPTION:Abstract: The statistical analysis of genomic data has incubated many innovations for computational method development. This talk will discuss some simple algorithms that may be useful in analyzing such data. Examples include algorithms for efficient resampling-based hypothesis testing\, minimizing the sum of truncated convex functions\, and fitting equality-constrained lasso problems. These algorithms have the potential to be used in other applications beyond statistical genomics. \nBio: Hui Jiang is an Associate Professor in the Department of Biostatistics at the University of Michigan. He received his Ph.D. in Computational and Mathematical Engineering from Stanford University. Before joining the University of Michigan\, he was a postdoc in the Department of Statistics and Stanford Genome Technology Center at Stanford University. He is interested in developing statistical and computational methods for analyzing large-scale biological data generated using modern high-throughput technologies.
URL:https://cmsa.fas.harvard.edu/event/6-23-2022-interdisciplinary-science-seminar/
CATEGORIES:Interdisciplinary Science Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220630T162300
DTEND;TZID=America/New_York:20220630T172300
DTSTAMP:20260503T160232
CREATED:20240214T091304Z
LAST-MODIFIED:20240301T101730Z
UID:10002613-1656606180-1656609780@cmsa.fas.harvard.edu
SUMMARY:Entanglement and its key role in quantum information
DESCRIPTION:Abstract: Entanglement is a type of correlation found in composite quantum systems\, connected with various non-classical phenomena. Currently\, entanglement plays a key role in quantum information applications such as quantum computing\, quantum communication\, and quantum sensing. In this talk the concept of entanglement will be introduced along with various methods that have been proposed to detect and quantify it. The fundamental role of entanglement in both quantum theory and quantum technology will also be discussed. \nBio: Spyros Tserkis is a postdoctoral researcher at Harvard University\, working on quantum information theory. Before joining Harvard in Fall 2021\, he was a postdoctoral researcher at MIT and the Australian National University. He received his PhD from the University of Queensland.
URL:https://cmsa.fas.harvard.edu/event/6-30-2022-interdisciplinary-science-seminar/
CATEGORIES:Interdisciplinary Science Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220707T090000
DTEND;TZID=America/New_York:20220707T100000
DTSTAMP:20260503T160232
CREATED:20240215T094540Z
LAST-MODIFIED:20240229T085211Z
UID:10002727-1657184400-1657188000@cmsa.fas.harvard.edu
SUMMARY:The phenotype of the last universal common ancestor and the evolution of complexity
DESCRIPTION:Interdisciplinary Science Seminar\n\n\n\n\n\nSpeaker: Fouad El Baidouri\, Broad Institute \nTitle: The phenotype of the last universal common ancestor and the evolution of complexity \nAbstract: A fundamental concept in evolutionary theory is the last universal common ancestor (LUCA) from which all living organisms originated. While some authors have suggested a relatively complex LUCA it is still widely assumed that LUCA must have been a very simple cell and that life has subsequently increased in complexity through time. However\, while current thought does tend towards a general increase in complexity through time in Eukaryotes\, there is increasing evidence that bacteria and archaea have undergone considerable genome reduction during their evolution. This raises the surprising possibility that LUCA\, as the ancestor of bacteria and archaea may have been a considerably complex cell. While hypotheses regarding the phenotype of LUCA do exist\, all are founded on gene presence/absence. Yet\, despite recent attempts to link genes and phenotypic traits in prokaryotes\, it is still inherently difficult to predict phenotype based on the presence or absence of genes alone. In response to this\, we used Bayesian phylogenetic comparative methods to predict ancestral traits. Testing for robustness to horizontal gene transfer (HGT) we inferred the phenotypic traits of LUCA using two robust published phylogenetic trees and a dataset of 3\,128 bacterial and archaeal species. \nOur results depict LUCA as a far more complex cell than has previously been proposed\, challenging the evolutionary model of increased complexity through time in prokaryotes. Given current estimates for the emergence of LUCA we suggest that early life very rapidly evolved cellular complexity.
URL:https://cmsa.fas.harvard.edu/event/iss_7722/
CATEGORIES:Interdisciplinary Science Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220707T103000
DTEND;TZID=America/New_York:20220707T123000
DTSTAMP:20260503T160232
CREATED:20240215T100432Z
LAST-MODIFIED:20240229T091815Z
UID:10002737-1657189800-1657197000@cmsa.fas.harvard.edu
SUMMARY:Anomalies\, dynamics and phases in strongly-coupled chiral gauge theories: Recent developments
DESCRIPTION:Speaker: Kenichi Konishi (UNIPI.IT) \nTitle: Anomalies\, dynamics and phases in strongly-coupled chiral gauge theories: Recent developments \nAbstract: After many years of efforts\, still very little is known today about the physics of strongly-coupled chiral gauge theories in four dimensions\, in spite of an important role they might play in the physics of fundamental interactions beyond the standard SU(3)xSU(2)xU(1) model. This is in stark contrast with the vectorlike gauge theories for which we have many solid results\, thanks to some exact theorems\, to the lattice simulation studies\, to the Seiberg-Witten exact solution of N=2 supersymmetric gauge theories\, and last\, but not the least\, to the real-world strong-interaction phenomenology and experimental tests of Quantum Chromodynamics. \nThe purpose of this seminar is to discuss the results of our recent efforts to improve the understanding of the strongly-coupled chiral gauge theories. Among the main tools of analysis are the consideration of anomalies. We use both the conventional ’t Hooft anomaly-matching ideas\, and new\, more stringent constraints coming from the generalized anomalies involving some higher-form symmetries. Also\, the so-called strong anomalies\, little considered in the context of chiral gage theories\, are found to carry significant implications. \nAs the playground we study several classes of SU(N) gauge theories\, the so-called Bars-Yankielowicz models\, the generalized Georgi-Glashow models\, as well as a few other simple theories with the fermions in complex\, anomaly-free representations of the color SU(N). \nColor-flavor-locked dynamical Higgs phase and dynamical Abelianization\, emerge\, among others\, as two particularly interesting possible phases the system can flow into in the infrared\, depending on the matter fermion content of the model.
URL:https://cmsa.fas.harvard.edu/event/qm_7722/
LOCATION:Virtual
CATEGORIES:Quantum Matter
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220714T090000
DTEND;TZID=America/New_York:20220714T100000
DTSTAMP:20260503T160232
CREATED:20240214T091545Z
LAST-MODIFIED:20240301T101549Z
UID:10002614-1657789200-1657792800@cmsa.fas.harvard.edu
SUMMARY:Topological and geometrical aspects of spinors in insulating crystals
DESCRIPTION:Abstract:  Introducing internal degrees of freedom in the description of crystalline insulators has led to a myriad of theoretical and experimental advances. Of particular interest are the effects of periodic perturbations\, either in time or space\, as they considerably enrich the variety of electronic responses. Here\, we present a semiclassical approach to transport and accumulation of general spinor degrees of freedom in adiabatically driven\, weakly inhomogeneous crystals of dimensions one\, two and three under external electromagnetic fields. Our approach shows that spatio-temporal modulations of the system induce a spinor current and density that is related to geometrical and topological objects — the spinor-Chern fluxes and numbers — defined over the higher-dimensional phase-space of the system\, i.e.\, its combined momentum-position-time coordinates. \nThe results are available here: https://arxiv.org/abs/2203.14902 \nBio: Ioannis Petrides is a postdoctoral fellow at the School of Engineering and Applied Sciences at Harvard University. He received his Ph.D. from the Institute for Theoretical Physics at ETH Zurich. His research focuses on the topological and geometrical aspects of condensed matter systems.
URL:https://cmsa.fas.harvard.edu/event/7-14-2022-interdisciplinary-science-seminar/
CATEGORIES:Interdisciplinary Science Seminar
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-Interdisciplinary-Science-Seminar-07.14.22-1583x2048-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220721T090000
DTEND;TZID=America/New_York:20220721T100000
DTSTAMP:20260503T160232
CREATED:20240214T111802Z
LAST-MODIFIED:20240301T092042Z
UID:10002694-1658394000-1658397600@cmsa.fas.harvard.edu
SUMMARY:Infants’ sensory-motor cortices undergo microstructural tissue growth coupled with myelination
DESCRIPTION:Abstract: The establishment of neural circuitry during early infancy is critical for developing visual\, auditory\, and motor functions. However\, how cortical tissue develops postnatally is largely unknown. By combining T1 relaxation time from quantitative MRI and mean diffusivity (MD) from diffusion MRI\, we tracked cortical tissue development in infants across three timepoints (newborn\, 3 months\, and 6 months). Lower T1 and MD indicate higher microstructural tissue density and more developed cortex. Our data reveal three main findings: First\, primary sensory-motor areas (V1: visual\, A1: auditory\, S1: somatosensory\, M1: motor) have lower T1 and MD at birth than higher-level cortical areas. However\, all primary areas show significant reductions in T1 and MD in the first six months of life\, illustrating profound tissue growth after birth. Second\, significant reductions in T1 and MD from newborns to 6-month-olds occur in all visual areas of the ventral and dorsal visual streams. Strikingly\, this development was heterogenous across the visual hierarchies: Earlier areas are more developed with denser tissue at birth than higher-order areas\, but higher-order areas had faster rates of development. Finally\, analysis of transcriptomic gene data that compares gene expression in postnatal vs. prenatal tissue samples showed strong postnatal expression of genes associated with myelination\, synaptic signaling\, and dendritic processes. Our results indicate that these cellular processes may contribute to profound postnatal tissue growth in sensory cortices observed in our in-vivo measurements. We propose a novel principle of postnatal maturation of sensory systems: development of cortical tissue proceeds in a hierarchical manner\, enabling the lower-level areas to develop first to provide scaffolding for higher-order areas\, which begin to develop more rapidly following birth to perform complex computations for vision and audition. \nThis work is published here: https://www.nature.com/articles/s42003-021-02706-w
URL:https://cmsa.fas.harvard.edu/event/7-21-2022-interdisciplinary-science-seminar/
CATEGORIES:Interdisciplinary Science Seminar
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END:VCALENDAR