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Abstract

Motivated by the recently-established connection between Jarzynski’s equality and the theoretical framework of Stochastic Normalizing Flows, we investigate a protocol relying on out-of-equilibrium lattice Monte Carlo simulations to mitigate the infamous computational problem of topological freezing. We test our proposal on 2d CPN−1 models and compare our results with those obtained adopting the Parallel Tempering on Boundary Conditions proposed by M. Hasenbusch, obtaining comparable performances. Our work thus sets the stage for future applications combining our Monte Carlo setup with machine learning techniques.

Publication Date

2024-04-23

Publication Title

Journal of High Energy Physics

Volume

2024

Issue

4

Acceptance Date

2024-03-26

Deposit Date

2024-06-21

Funding

We thank A. Bulgarelli, M. Caselle, E. Cellini and M. Panero for insightful and helpful discussions. The work of C. B. is supported by the Spanish Research Agency (Agencia Estatal de Investigación) through the grant IFT Centro de Excelencia Severo Ochoa CEX2020-001007-S and, partially, by grant PID2021-127526NB-I00, both funded by MCIN/AEI/10.13039/501100011033. A. N. acknowledges support by the Simons Foundation grant 994300 (Simons Collaboration on Confinement and QCD Strings) and from the SFT Scientific Initiative of INFN. The work of D. V. is supported by STFC under Consolidated Grant No. ST/X000680/1. The numerical simulations were run on machines of the Consorzio Interuniversitario per il Calcolo Automatico dell’Italia Nord Orientale (CINECA).

Keywords

Algorithms and Theoretical Developments, Lattice Quantum Field Theory, Other Lattice Field Theories, Vacuum Structure and Confinement

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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