Workshop on the sign problem in QCD and beyond

Session

Thursday morning

23 Jan 2025, 08:30

Lecture Hall 099 (ExWi Building) (University of Bern)

4. Kernels and integration cycles in complex Langevin simulations

Michael Mandl (University of Graz)

23/01/2025, 08:30

talk

The complex Langevin method is an approach to solve the sign problem based on a stochastic evolution of the dynamical degrees of freedom. In principle, it solves the sign problem by trading the complex path integral weight for a real probability distribution in complexified field space. However, due to the complexification, the stochastic evolution sometimes converges to an equilibrium...

13. Machine learning kernels in complex Langevin for real time evolution

Enno Carstensen (University of Graz)

23/01/2025, 09:15

talk

Real time evolution in QFT poses a severe sign problem, which may be alleviated via a complex Langevin approach.
However, so far simulation results consistently fail to converge with a large real-time extent. A kernel in a complex Langevin equation is known to influence the appearance of the boundary terms, and thus kernel choice can improve the range of real-time extents with correct...

14. Enhancing Complex Langevin with Lefschetz Thimble-Based Regularizations

Paul Hotzy (TU Wien)

23/01/2025, 10:45

talk

The complex Langevin (CL) method is a promising tool for addressing the numerical sign problem.- Depending on the specific system, CL may produce unreliable results, which necessitates the use of ad-hoc stabilization methods. Building on the connection between CL and Lefschetz thimbles, we develop weight regularizations to enable correct convergence by deforming thimbles in systems with...

25. System specific prior knowledge - a key tool to tackle the sign problem

Dr Alexander Rothkopf (University of Stavanger)

23/01/2025, 11:30

talk

Here I present our recently developed strategy to exploit system specific prior knowledge [1], such as space-time symmetries, as a loophole to the computational challenge posed by NP-hard sign problems. As explicit example, I will showcase how complex Langevin simulations of strongly coupled scalar fields [2] can be amended with relevant prior information using learned kernels. Developments...