Abel Lacabanne

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2papers

2 Papers

RTDec 2, 2024
Big data approach to Kazhdan-Lusztig polynomials

Abel Lacabanne, Daniel Tubbenhauer, Pedro Vaz

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.

GTSep 6, 2025
On detection probabilities of link invariants

Abel Lacabanne, Daniel Tubbenhauer, Pedro Vaz et al.

We prove that the detection rate of n-crossing alternating links by link invariants insensitive to oriented mutation decays exponentially in n, implying that they detect alternating links with probability zero. This phenomenon applies broadly, in particular to quantum invariants such as the Jones or HOMFLYPT polynomials. We also use a big data approach to analyze several borderline cases (e.g. integral Khovanov or HOMFLYPT homologies), where our arguments almost, but not quite, apply, and we provide evidence that they too exhibit the same asymptotic behavior.