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arXiv · 2103.11965

Gauge covariant neural network for quarks and gluons

Yuki Nagai·Akio Tomiya
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Abstract

We propose gauge-covariant neural networks along with a specialized training algorithm for lattice QCD, designed to handle realistic quarks and gluons in four-dimensional space-time. We show that the smearing procedure can be interpreted as an extended version of residual neural networks with fixed parameters. To demonstrate the applicability of our neural networks, we develop a self-learning hybrid Monte Carlo algorithm in the context of two-color QCD, yielding outcomes consistent with those from the conventional Hybrid Monte Carlo approach.

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Yuki Nagai, Akio Tomiya. 2024-10-29. Gauge covariant neural network for quarks and gluons. https://doi.org/10.1103/physrevd.111.074501

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