# Improving efficiency of the path optimization method for a gauge theory

@article{Namekawa2022ImprovingEO, title={Improving efficiency of the path optimization method for a gauge theory}, author={Yusuke Namekawa and Kouji Kashiwa and Hidefumi Matsuda and Akira Ohnishi and Hayato Takase}, journal={Physical Review D}, year={2022} }

We investigate efficiency of a gauge-covariant neural network and an approximation of the Jacobian in optimizing the complexified integration path toward evading the sign problem in lattice field theories. For the construction of the complexified integration path, we employ the path optimization method. The $2$-dimensional $\text{U}(1)$ gauge theory with the complex gauge coupling constant is used as a laboratory to evaluate the efficiency. It is found that the gauge-covariant neural network…

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