Hypergeometric sheaves for classical groups via geometric Langlands
Masoud Kamgarpour, Daxin Xu, Lingfei Yi

TL;DR
This paper extends the geometric Langlands correspondence to hypergeometric sheaves associated with classical groups, constructing $ ext{G}$-local systems via automorphic data and Hitchin systems, and relating them to hypergeometric local systems.
Contribution
It introduces a new framework for realizing the geometric Langlands correspondence for classical groups using hypergeometric automorphic data and Hitchin systems, including the first explicit construction of such $ ext{G}$-local systems.
Findings
Construction of hypergeometric automorphic data for classical groups.
Proof of rigidity of these automorphic data under certain conditions.
Identification of $ ext{G}$-local systems with hypergeometric local systems.
Abstract
In a previous paper, the first and third authors gave an explicit realization of the geometric Langlands correspondence for hypergeometric sheaves, considered as -local systems. Certain hypergeometric local systems admit a symplectic or orthogonal structure, which can be viewed as -local systems, for a classical group . This article aims to realize the geometric Langlands correspondence for these -local systems. We study this problem from two aspects. In the first approach, we define the hypergeometric automorphic data for a classical group in the framework of Yun, one of whose local components is a new class of euphotic representations in the sense of Jakob-Yun. We prove the rigidity of hypergeometric automorphic data under natural assumptions, which allows us to define -local systems on…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Algebra and Geometry · Algebraic Geometry and Number Theory · Algebraic structures and combinatorial models
