arXiv Machine Learning By Abel Lacabanne, Daniel Tubbenhauer, Pedro Vaz

Big data approach to Kazhdan-Lusztig polynomials

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arXiv:2412. 01283v3 Announce Type: replace-cross Abstract: We investigate the structure of Kazhdan-Lusztig polynomials of the symmetric group by leveraging computational approaches from big data, including exploratory and topological data analysis, applied to the polynomials for symmetric groups of up to 11 strands.

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arXiv Machine Learning
23h ago

On detection probabilities of link invariants

arXiv:2509. 05574v3 Announce Type: replace-cross Abstract: We prove that, for many standard link invariants, both the proportion of distinct invariant values and the detection probability among prime alternating links with at most n crossings decay exponentially in n, with an explicit universal rate.

By Tuomas Kelom\"aki, Abel Lacabanne, Daniel Tubbenhauer, Pedro Vaz, Victor L. Zhang
arXiv Machine Learning
Jul 15

Learning the Graphical Nature of Symmetries

arXiv:2607. 12026v1 Announce Type: cross Abstract: Finite groups are rigid algebraic objects, whose Cayley graphs expose a rich network geometry through which group-theoretic structure can be measured, compared, and learned.

By Rashid Barket, Enrico Grimaldi, Yacoub Hendi, Edward Hirst, Adam Onus, Harmeet Singh