Machine learning mapping of lattice correlated data-Reference-Cited by-同舟云学术

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Machine learning mapping of lattice correlated data

Published:2024-09 Issue: Volume:856 Page:138894
ISSN:0370-2693
Container-title:Physics Letters B
language:en
Short-container-title:Physics Letters B

Author:

Kim Jangho^ORCID,Pederiva Giovanni,Shindler Andrea

Funder

National Science Foundation

Stichting DOEN

German Research Foundation

US Department of Energy

German-Israeli Foundation for Scientific Research and Development

Frankfurt University of Applied Sciences

Toyota Collaborative Safety Research Center

Publisher

Elsevier BV

Reference16 articles.

1. Machine learning estimators for lattice QCD observables;Yoon;Phys. Rev. D,2019

2. Properties and uses of the Wilson flow in lattice QCD;Lüscher;J. High Energy Phys.,2010

3. Chiral symmetry and the Yang–Mills gradient flow;Lüscher;J. High Energy Phys.,2013

4. Beyond-the-standard-model matrix elements with the gradient flow;Shindler;PoS LATTICE,2014

5. Moments of parton distribution functions of any order from lattice;Shindler;QCD,2023

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