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Sunday, October 26 |
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Monday, October 27 |
- 15:30–16:30 Algebra and Number Theory Seminar, Kemeny 343

- Low-degree points on some rank 0 modular curves
- Alexis Newton, Augusta University
- Let $E$ be an elliptic curve defined over a number field $K$. We present some new progress on the classification of the finite groups which appear as the torsion subgroup of $E(K)$ as $K$ ranges over quartic, quintic and sextic number fields. In particular, we concentrate on determining the quartic, quintic and sextic points on certain modular curves $X_1(N)$ for which the rank of $J_0(N)$ is zero.
- 17:00–18:00 Undergraduate Math Society Talk, Kemeny 007

- CANCELLED
- Juliette Bruce, Dartmouth College
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Tuesday, October 28 |
- 11:00–12:00 Combinatorics Seminar, Kemeny 307

- Bruhat interval polytopes and posets arising as 1-skeleta of (directionally) simple polytopes
- Patricia Hersh, University of Oregon
- Questions regarding the complexity of the simplex method in linear programming for simple polytopes turn out to be related to questions about partially ordered sets in a perhaps surprising way. Exploring this connection led us to study lattices arising as 1-skeleta of simple polytopes, obtaining the homotopy type of the intervals in these posets as well as a geometric way of constructing lattice-theoretic joins. In recent joint work with Christian Gaetz, we generalized this to the setting of directionally simple polytopes, motivated by questions about Bruhat interval polytopes. We also proved that the facet ridge incidence graphs of the order complexes of these posets are not only connected but in fact highly connected. This talk will not assume background in this area and will mention several remaining open questions.
- 14:30–15:30 Applied and Computational Mathematics Seminar, Kemeny 242

- Privacy-preserving probabilistic machine learning: a preview
- Nianqiao "Phyllis" Ju, Dartmouth
- This talk is a preview of Math 146 in Winter 2026, which will focus on privacy-preserving probabilistic machine learning. The central goal is to learn about populations without revealing any sensitive information about any individual. We will give an accessible introduction to the definition of differential privacy, the randomized response mechanism, and the high-level ideas of differentially private optimization and sampling. No specialized background beyond probability and basic data analysis or machine learning is required. The goal is to provide a clear picture of what is currently possible and key open problems for further study. This will be a mostly nontechnical chalk talk.
- 15:30–16:30 Functional Analysis Seminar, Kemeny 343

- On Prequantization of Log-Symplectic Manifolds
- Ahmad Reza Haj Saeedi Sadegh, Dartmouth College
- We discuss a new approach to the geometric quantization of log symplectic manifolds using Lie groupoids and Lie algebroids. We will bridge the notion of prequantizability of Crainic for Lie algebroids and the prequantizability defined in the works of Lin-Loizides-Sjamaar-Song, Braverman-Loizides-Song, and Guillemin-Miranda-Weitsman. We then give a generalized geometric quantization method which allows for Poisson manifolds with a more complicated vanishing locus.
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Wednesday, October 29 |
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Thursday, October 30 |
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Friday, October 31 |
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Saturday, November 1 |
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Prev. week | October 26 – November 1, 2025 | Next week