Big data approach to Kazhdan-Lusztig polynomials
arXiv:2412.01283 · doi:10.56994/JXM.002.001.002
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.
27 pages, many figures, comments welcome, appeared in J. Exp. Math, added a remark acknowledging E. O. Hjelle for proposing an AI-generated proof of Conjecture 6.4 (via ChatGPT 5.5 Pro), added a link to the complete proof on our GitHub repository