Spring 2023 Schedule
Monday
Swampland Seminar: 11:00am - 12:00pm ET, bi-weekly
Tuesday
Member Seminar: 12:00pm - 1:00pm ET
Quantum Matter in Mathematics and Physics Seminar: 1:15pm - 2:45pm ET
Wednesday
Colloquium: 12:30pm - 1:30pm ET
New Technologies in Mathematics Seminar: 2:00pm - 3:00pm ET
Probability Seminar: 3:30pm - 4:30pm ET
Thursday
General Relativity Seminar: 9:30am - 10:30am ET
Active Matter Seminar: 1:00pm - 2:00pm ET, bi-weekly
Friday
Algebraic Geometry in String Theory Seminar: 9:30am - 10:30am ET
Quantum Matter in Mathematics and Physics Seminar: 10:30am - 12:00pm ET
Category: Member Seminar |
Speaker: Chuck Doran, CMSATitle: Motivic Geometry of Two-Loop Feynman IntegralsMember Seminar Speaker: Chuck Doran Title: Motivic Geometry of Two-Loop Feynman Integrals Abstract: We study the geometry and Hodge theory of the cubic hypersurfaces attached to two-loop Feynman integrals for generic physical parameters. We show that the Hodge structure attached to planar two-loop Feynman graphs decomposes into a mixed Tate piece and a variation of Hodge structure from families of hyperelliptic curves, elliptic curves, or rational curves depending on the space-time dimension. We give more precise results for two-loop graphs with a small number of edges. In particular, we recover a result of Spencer Bloch that in the well-known double box example there is an underlying family of elliptic curves, and we give a concrete description of these elliptic curves. We show... |
Category: Colloquia |
Speaker: David Gamarnik, MITTitle: From spin glasses to Boolean circuits lower bounds Algorithmic barriers from the overlap gap propertySpeaker: David Gamarnik (MIT) Title: From spin glasses to Boolean circuits lower bounds. Algorithmic barriers from the overlap gap property Abstract: Many decision and optimization problems over random structures exhibit an apparent gap between the existentially optimal values and algorithmically achievable values. Examples include the problem of finding a largest independent set in a random graph, the problem of finding a near ground state in a spin glass model, the problem of finding a satisfying assignment in a random constraint satisfaction problem, and many many more. Unfortunately, at the same time no formal computational hardness results exist which explains this persistent algorithmic gap. In the talk we will describe a new approach for establishing an algorithmic intractability for these problems called... |
Category: Probability Seminar |
Speaker: Roland Bauerschmidt, CambridgeTitle: Title TBAProbability Seminar Speaker: Roland Bauerschmidt (Cambridge) |
Category: General Relativity Seminar |
Speaker: Maciej Zworski, UC BerkeleyTitle: Quasinormal modes and Ruelle resonances: mathematicians perspectiveGeneral Relativity Seminar Speaker: Maciej Zworski, UC Berkeley Title: Quasinormal modes and Ruelle resonances: mathematician's perspective Abstract: Quasinormal modes of gravitational waves and Ruelle resonances in hyperbolic classical dynamics share many general properties and can be considered "scattering resonances": they appear in expansions of correlations, as poles of Green functions and are associated to trapping of trajectories (and are both notoriously hard to observe in nature, unlike, say, quantum resonances in chemistry or scattering poles in acoustical scattering). I will present a mathematical perspective that also includes zeros of the Riemann zeta function (scattering resonances for the Hamiltonian given by the Laplacian on the modular surface) and stresses the importance of different kinds of trapping phenomena, resulting, for... |
Category: Probability Seminar |
Title: Title TBAProbability Seminar Speaker: Zhigang Yao (Harvard CMSA/National University of Singapore) |
Category: New Technologies in Mathematics Seminar |
Speaker: Sean Welleck, University of Washington and AI2Title: New Technologies in Mathematics Seminar Title TBANew Technologies in Mathematics Seminar Speaker: Sean Welleck, University of Washington and AI2 |
Category: Probability Seminar |
Speaker: Vishesh Jain, UICTitle: Title TBAProbability Seminar Speaker: Vishesh Jain (UIC) |
Category: New Technologies in Mathematics Seminar |
Speaker: Jimmy Ba, University of TorontoTitle: New Technologies in Mathematics Seminar Title TBANew Technologies in Mathematics Seminar Speaker: Jimmy Ba, University of Toronto |
Category: Probability Seminar |
Speaker: Jean-Christophe Mourrat, LyonTitle: Title TBAProbability Seminar Speaker: Jean-Christophe Mourrat (Lyon) |
Category: Swampland Seminar |
Speaker: David Andriot, Annecy, LAPTHTitle: Swampland Seminar Title TBASwampland Seminar Speaker: David Andriot (Annecy, LAPTH) |
Category: Probability Seminar |
Speaker: Wei-Kuo Chen, MinnesotaTitle: Title TBAProbability Seminar Speaker: Wei-Kuo Chen (Minnesota) |
Category: Swampland Seminar |
Speaker: Valerio De Luca, UPennTitle: Swampland Seminar Title TBASwampland Seminar Speaker: Valerio De Luca (UPenn) |
Category: Probability Seminar |
Speaker: Ahmed El Alaoui, CornellTitle: Title TBAProbability Seminar Speaker: Ahmed El Alaoui (Cornell) |
Category: Swampland Seminar |
Speaker: Seung-Joo Lee (IBS Daejeon), IBS DaejeonTitle: Swampland Seminar Title TBASwampland Seminar Speaker: Seung-Joo Lee (IBS Daejeon) |
Category: Colloquia |
Speaker: James Halverson, Northeastern UniversityTitle: Unexpected Uses of Neural Networks: Field Theory and Metric FlowsSpeaker: James Halverson (Northeastern University) Title: Unexpected Uses of Neural Networks: Field Theory and Metric Flows Abstract: We are now quite used to the idea that deep neural networks may be trained in a variety of ways to tackle cutting-edge problems in physics and mathematics, sometimes leading to rigorous results. In this talk, however, I will argue that breakthroughs in deep learning theory are also useful for making progress, focusing on applications to field theory and metric flows. Specifically, I will introduce a neural network approach to field theory with a different statistical origin, that exhibits generalized free field behavior at infinite width and interactions at finite width, and that allows for the study of symmetries via the study of correlation functions... |