Aug 8 – 13, 2022
Hörsaalzentrum Poppelsdorf
Europe/Berlin timezone

Towards the Application of Skewed Detailed Balance in Lattice Gauge Theories

Aug 11, 2022, 10:40 AM
CP1-HSZ/1.004 (CP1-HSZ) - HS7 (CP1-HSZ)

CP1-HSZ/1.004 (CP1-HSZ) - HS7


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Oral Presentation Algorithms (including Machine Learning, Quantum Computing, Tensor Networks) Algorithms


Joao C. Pinto Barros (ETH Zürich)


Most Monte Carlo algorithms generally applied to lattice gauge theories, among other fields, satisfy the detailed balance condition (DBC) or break it in a very controlled way. While DBC is not essential to correctly simulate a given probability distribution, it ensures the proper convergence after the system has equilibrated. While being powerful from this perspective, it puts strong constraints on the algorithms.
In this talk, I will discuss how breaking DBC can accelerate equilibration and how it can be tailored to improve the sampling of specific observables. By focusing on the case of the so-called Skewed Detailed Balance Condition, I will discuss applications in lattice gauge theories and the perspective of improving sampling over topology, for theories with distinct topological sectors.

Primary author

Joao C. Pinto Barros (ETH Zürich)


Marina Krstic Marinkovic (ETH Zurich)

Presentation materials