28 July 2024 to 3 August 2024
Europe/London timezone

Exploring gauge-fixing conditions with gradient-based optimization

30 Jul 2024, 17:15
1h
Poster Algorithms and Artificial Intelligence Poster session and reception

Speaker

Gurtej Kanwar (University of Bern)

Description

Lattice gauge fixing is necessary to compute gauge-variant quantities, for example those used in RI-MOM renormalization. Recently, gauge-variant observables have also been found to be more amenable to signal-to-noise optimization using contour deformations. These applications motivate systematic parameterization and exploration of gauge-fixing schemes. This work introduces a differentiable parameterization which is broad enough to cover Landau gauge, Coulomb gauge, and maximal tree gauges. The adjoint state method allows gradient-based optimization to select gauge-fixing schemes that minimize an arbitrary target loss function.

Primary authors

William Detmold (MIT) Gurtej Kanwar (University of Bern) Dr Yin Lin (MIT) Phiala Shanahan (Massachusetts Institute of Technology) Michael Wagman (Fermilab)

Presentation materials

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