Volume 453 -
The 40th International Symposium on Lattice Field Theory (LATTICE2023) -
Poster session
Normalizing Flows for Lattice Gauge Theories: Towards Finite Temperature Simulations
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Pre-published on:
May 03, 2024
Published on:
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Abstract
Flow-based machine learning techniques have demonstrated effectiveness in tackling significant computational obstacles, including critical slowing-down and topological freezing, encountered in the sampling of gauge field configurations within lattice field theories. We investigate the viability of this approach for simulations of gauge theories at finite temperature. Several tests are performed on two dimensional U(1) gauge theory at different temporal extents.
DOI: https://doi.org/10.22323/1.453.0134
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Copyright owned by the author(s) under the term of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Copyright owned by the author(s) under the term of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.