JOURNAL ARTICLE
Set Partitions, Fermions, and Skein Relations.
Published In: IMRN: International Mathematics Research Notices, 2023, v. 2023, n. 11. P. 9427 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Kim, Jesse; Rhoades, Brendon 3 of 3
Abstract
This article focuses on establishing a deep connection between two modules over the symmetric group \(\mathfrak{S}_n\): a combinatorial module defined via skein relations resolving crossings in noncrossing set partitions, and an algebraic module arising from the fermionic diagonal coinvariant ring \(FDR_n\). The authors construct explicit fermionic elements \(F_\pi\) and \(f_\pi\) in an exterior algebra that correspond to set partitions \(\pi\), proving that these fermions satisfy the skein relations and form bases for submodules of \(FDR_n\). They demonstrate an isomorphism between the skein representation on noncrossing partitions and a natural Catalan-dimensional submodule \(\overline{FDR_n}\) of \(FDR_n\), thereby providing an algebraic model for the skein action. The paper also develops a crossing resolution map \(p\) projecting arbitrary set partitions onto linear combinations of noncrossing partitions, characterized by equivariance under a sign-twisted permutation action, and explores related quadratic ideals encoding these relations. Finally, the authors discuss extensions of their framework to other reflection groups and multidiagonal fermionic coinvariant rings, posing open problems for further combinatorial and algebraic interpretations.
Additional Information
- Source:IMRN: International Mathematics Research Notices. 2023/06, Vol. 2023, Issue 11, p9427
- Document Type:Article
- Subject Area:Mathematics
- Publication Date:2023
- ISSN:1073-7928
- DOI:10.1093/imrn/rnac110
- Accession Number:164368112
- Copyright Statement:Copyright of IMRN: International Mathematics Research Notices is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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