Quantum Field Theory and Physical Mathematics Seminar Speaker: Brian Williams, Boston University Title: Dolbeault Virasoro algebra and M5 branes Abstract: The worldvolume theory on a stack of M5 branes in M-theory is superconformal. We propose a conjecture that in the holomorphic twist of the theory on a stack of M5 branes an infinite-dimensional enhancement of […]
Math and Machine Learning Program Discussion
Member Seminar Speaker: Keyou Zeng Title: Scattering Amplitude from a Twistor Point of View Abstract: Scattering amplitude is a key quantity in quantum field theory. Although challenging to compute at higher loops and for large particle numbers, physicists have developed various tools to gain a deeper understanding of amplitudes. In this seminar, I will introduce […]
Math and Machine Learning Program Discussion
General Relativity Seminar Speaker: Christoph Kehle, MIT Title: Gravitational collapse to extremal Reissner-Nordström and the third law of black hole thermodynamics Abstract: In this talk, I will present a proof that extremal Reissner-Nordström black holes can form in finite time in gravitational collapse of charged matter. In particular, this construction provides a definitive disproof of […]
Topics in Deep Learning Theory Eli Grigsby
Geometry and Quantum Theory Seminar Speaker: Mayuko Yamashita, Kyoto University Title: Topological Modular Forms, its equivariant refinements and relation with supersymmetric quantum field theories Abstract: This talk is about the Segal-Stolz-Teichner program, which is one of the most deep and interesting topics relating homotopy theory and physics. Mathematically, they propose a geometric model of TMF, […]
Math and Machine Learning Program Discussion
CMSA Q&A Seminar Speaker: Nazim Bouatta (HMS) Topic: What are AlphaFold2 and OpenFold
https://youtu.be/OYOuSAAE7QQ New Technologies in Mathematics Seminar Speaker: Anirudh Goyal (University of Montreal) Title: From Word Prediction to Complex Skills: Data Flywheels for Mathematical Reasoning Abstract: This talk examines how large language models (LLMs) evolve from simple word prediction to complex skills, with a focus on mathematical problem solving. A major driver of AI products today is the […]
Speaker: Andrew Neitzke, Yale University Location: Harvard University Science Center Hall D & via Zoom webinar Dates: October 16 & 17, 2024 Time: 4:00 pm https://youtu.be/1SyGyeMmWoM Wednesday, Oct. 16, 2024 Title: Abelianization in analysis of ODEs Abstract: I will describe the exact WKB method for asymptotic analysis of families of ODEs in one […]
Topics in Deep Learning Theory Eli Grigsby