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DTSTART;TZID=America/New_York:20240207T110000
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SUMMARY:AQFT Lecture Series | Minhyong Kim
DESCRIPTION:Arithmetic Quantum Field Theory Program Lecture Series\nSpeaker: Minhyong Kim\, University of Edinburgh \nTopic: Arithmetic topology and field theory \nAbstract: The setup of arithmetic topology as a bridge between the background of QFT to that of arithmetic (both “global” and “local”)\, including the “middle realm” of positive characteristic function fields. \nSlides (pdf)
URL:https://cmsa.fas.harvard.edu/event/aqft-lecture-series-minhyong-kim-2724/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:AQFT Lecture Series,Colloquia & Seminar
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DTSTART;TZID=America/New_York:20240207T130000
DTEND;TZID=America/New_York:20240207T140000
DTSTAMP:20260721T212014
CREATED:20240102T163838Z
LAST-MODIFIED:20240207T220617Z
UID:10000149-1707310800-1707314400@cmsa.fas.harvard.edu
SUMMARY:Large language models\, mathematical discovery\, and search in the space of strategies: an anecdote
DESCRIPTION:New Technologies in Mathematics Seminar \nSpeaker: Jordan Ellenberg (UW Madison) \nTitle: Large language models\, mathematical discovery\, and search in the space of strategies: an anecdote \nAbstract: I spent a portion of 2023 working with a team at DeepMind on the “cap set problem” – how large can a subset of (Z/3Z)^n be which contains no three terms which sum to zero? (I will explain\, for those not familiar with this problem\, something about the role it plays in combinatorics\, its history\, and why number theorists care about it a lot.) By now\, there are many examples of machine learning mechanisms being used to help generate interesting mathematical knowledge\, and especially interesting examples. This project used a novel protocol; instead of searching directly for large cap sets\, we used LLMs trained on code to search the space of short programs for those which\, when executed\, output large cap sets. One advantage is that a program is much more human-readable than a large collection of vectors over Z/3Z\, bringing us closer to the not-very-well-defined-but-important goal of “interpretable machine learning.” I’ll talk about what succeeded in this project (more than I expected!) what didn’t\, and what role I can imagine this approach to the math-ML interface playing in near-future mathematical practice. \nThe paper: https://www.nature.com/articles/s41586-023-06924-6 \n 
URL:https://cmsa.fas.harvard.edu/event/nt2724/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:New Technologies in Mathematics Seminar
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-NTM-Seminar-02.07.24.png
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DTSTART;TZID=America/New_York:20240207T143000
DTEND;TZID=America/New_York:20240207T153000
DTSTAMP:20260721T212014
CREATED:20240125T174235Z
LAST-MODIFIED:20240206T180625Z
UID:10001358-1707316200-1707319800@cmsa.fas.harvard.edu
SUMMARY:AQFT Lecture Series | Brian Williams
DESCRIPTION:Arithmetic Quantum Field Theory Program Lecture Series\nSpeaker: Brian Williams\, Boston University \nTopic: Algebraic quantum field theory \nAbstract: Questions and structures in arithmetic that have been / might be amenable to inspiration from QFT\, in particular the theory of L-functions and the Langlands program.
URL:https://cmsa.fas.harvard.edu/event/aqft-lecture-series-brian-williams-2724/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:AQFT Lecture Series,Colloquia & Seminar
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