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[en] We investigate the sign problem in field theories by using the path optimization method (POM) with use of the feedforward neural network (FNN). We utilize FNN to prepare and optimize the trial function specifying the integration path (manifold) in field theories in the framework of POM. POM with use of FNN has been applied to several field theories having the sign problem. Specifically, the 0+1 dimensional QCD is discussed. It is found that the average phase factor is enhanced significantly and we can reduce the statistical errors of observables. (author)
Source
Dote, Akinobu; Morimatsu, Osamu (High Energy Accelerator Research Organization (KEK), Tsukuba, Ibaraki (Japan)) (eds.); Goto, Yuji (ed.) (RIKEN, Wako, Saitama (Japan)) (and others); [780 p.]; ISBN 978-4-89027-136-8; 
; 2019; p. 024011.1-024011.4; QNP2018: 8. international conference on quarks and nuclear physics; Tsukuba, Ibaraki (Japan); 13-17 Nov 2018; Available from https://doi.org/10.7566/JPSCP.26.024011; 14 refs., 1fig.
; 2019; p. 024011.1-024011.4; QNP2018: 8. international conference on quarks and nuclear physics; Tsukuba, Ibaraki (Japan); 13-17 Nov 2018; Available from https://doi.org/10.7566/JPSCP.26.024011; 14 refs., 1fig.