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Schwinger-Dyson control variates for lattice fermions
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abstract
Previous work has shown that high-quality control variates for lattice Monte Carlo methods may be constructed from lattice Schwinger-Dyson relations. This paper extends that method to theories with lattice fermions, using the Thirring model in $1+1$ spacetime dimensions as a testbed. Past construction of these control variates involved a number of fitting parameters that scaled with lattice volume. By computing the control variate in perturbation theory, the number of fitting parameters required for an order-of-magnitude improvement in the signal-to-noise ratio at weak coupling is reduced to be of order one.
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Cited by 1 Pith paper
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Machine-learning approaches to accelerating lattice simulations
A review of unbiased machine-learning acceleration methods for lattice field theory, covering flow-based sampling, contour deformations, control variates, and surrogate observables.
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