Skip to content
Menu
Close
High Energy Theory artwork
January 24, 20222:00 pm – 3:00 pm (CDT)

Automorphic Spectra and the Conformal Bootstrap

Speaker: Sridip Pal (Institute for Advanced Study)

Host: Anindya Sengupta

Location: MIST M108

Address: Mitchell Institute for Fundamental Physics & Astronomy, College Station, Texas, 77843

Event Details

We point out that the spectral geometry of hyperbolic manifolds provides a remarkably precise model of the modern conformal bootstrap. As an application, we use conformal bootstrap techniques to derive rigorous computer-assisted upper bounds on the lowest positive eigenvalue **\lambda_1(X)** of theLaplace-Beltrami operator on closed hyperbolic surfaces and 2-orbifolds **X**. In a number of notable cases, our bounds are nearly saturated by known surfaces and orbifolds. For instance, our bound on all genus-2 surfaces **X** is **\lambda_1(X)\leq 3.8388976481**, while the Bolza surface has **\lambda_1(X)\approx 3.838887258**.

I will explain that hyperbolic surface are of the form \Gamma\G/K with G=PSL(2,R), K=SO(2) /{\pm I} and \Gamma being Fuchsian group. For a given hyperbolic surface, one can define a Hilbert space of local operators, transforming under unitary irreps of a conformal group (PSL(2,R)) and introduce a notion of operator product expanion (OPE). The associativity of this OPE reflects the associativity of function multiplication on the space \Gamma\G and leads to the bootstrap equations. Now the functions on \Gamma\G can be thought of automorphic forms on the surface \Gamma\G/K and I will show that the scaling dimensions of these operators are in fact related to the automorphic spectra in particular the Laplacian eigenvalues on the surface. Hence the bootstrap equations imply bound on the Laplacian eigenvalues.

Finally, I will make some remarks about how our methods can be generalized to higher-dimensional hyperbolic manifolds (or orbifolds) and to yield stronger bounds in the two-dimensional case. This is based on a work (arXiv:2111.12716) with P. Kravchuk and D. Mazac.

Copyright © 2022. All rights reserved, Texas A&M University Trademark | Texas A&M University, College Station, Texas 77843