Big data approach to Kazhdan-Lusztig polynomials

Lacabanne, Abel, Tubbenhauer, Daniel, Vaz, Pedro

arXiv.org Artificial Intelligence 

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.