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...
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...
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...
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...
