Search Results for author: Karl Jansen

Found 5 papers, 1 papers with code

Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models

no code implementations14 Jul 2020 Kim A. Nicoli, Christopher J. Anders, Lena Funcke, Tobias Hartung, Karl Jansen, Pan Kessel, Shinichi Nakajima, Paolo Stornati

In this work, we demonstrate that applying deep generative machine learning models for lattice field theory is a promising route for solving problems where Markov Chain Monte Carlo (MCMC) methods are problematic.

BIG-bench Machine Learning

Multilevel Monte Carlo for quantum mechanics on a lattice

1 code implementation7 Aug 2020 Karl Jansen, Eike Hermann Müller, Robert Scheichl

This paper discusses hierarchical sampling methods to tame this growth in autocorrelations.

High Energy Physics - Lattice Numerical Analysis Numerical Analysis Computational Physics 81-08, 81T25, 65Y20, 60J22 F.2; J.2

Detecting and Mitigating Mode-Collapse for Flow-based Sampling of Lattice Field Theories

no code implementations27 Feb 2023 Kim A. Nicoli, Christopher J. Anders, Tobias Hartung, Karl Jansen, Pan Kessel, Shinichi Nakajima

In this work, we first point out that the tunneling problem is also present for normalizing flows but is shifted from the sampling to the training phase of the algorithm.

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