Neural networks parametrize gauge-invariant interpolators that extract ground-state Wilson loops with improved signal-to-noise ratio compared to traditional methods while preserving gauge invariance.
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1-loop lattice PT improvement of Wilson loops enhances precision in extracting α_s from the static energy using TUMQCD (2+1)-flavor lattice data.
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Wilson loops with neural networks
Neural networks parametrize gauge-invariant interpolators that extract ground-state Wilson loops with improved signal-to-noise ratio compared to traditional methods while preserving gauge invariance.
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Strong coupling constant from the 1-loop improved static energy
1-loop lattice PT improvement of Wilson loops enhances precision in extracting α_s from the static energy using TUMQCD (2+1)-flavor lattice data.