26–30 Jun 2023
ECT*
Europe/Rome timezone

Deforming complex-valued distributions via machine learning

27 Jun 2023, 09:30
25m
Aula Renzo Leonardi (ECT*)

Aula Renzo Leonardi

ECT*

Strada delle Tabarelle 286, I-38123 Villazzano (Trento)

Speaker

Yukari Yamauchi (The Institute for Nuclear Theory)

Description

Sign problems in lattice QCD prevent us from non-perturbatively calculating many important properties of dense nuclear matter both in and out of equilibrium. In this talk, I will discuss recent developments in numerical methods for alleviating sign problems in lattice field theories. In these methods, the distribution function in the path integral is modified via machine learning such that the sign problem is tamed. I will demonstrate these methods in the $\phi^4$ scalar field theory and the Thirring model in 1+1-dimensions.

Primary author

Yukari Yamauchi (The Institute for Nuclear Theory)

Presentation materials