Gauge invariant input to neural network for path optimization method
نویسندگان
چکیده
We investigate the efficiency of a gauge invariant input to neural network for path optimization method. While with completely gauge-fixed link-variable has successfully tamed sign problem in simple theory, does not work well when degrees freedom remain. propose employ input, such as plaquette, overcome this problem. The is evaluated 2-dimensional $U(1)$ theory complex coupling. average phase factor significantly enhanced by plaquette indicating good control It opens possibility that available complicated theories, including Quantum Chromodynamics, realistic setup.
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ژورنال
عنوان ژورنال: Physical review
سال: 2022
ISSN: ['0556-2813', '1538-4497', '1089-490X']
DOI: https://doi.org/10.1103/physrevd.105.034502