Towards learning optimized kernels for complex Langevin
Abstract We present a novel strategy aimed at restoring correct convergence in complex Langevin simulations. The central idea is to incorporate system-specific prior knowledge into the simulations, in order to circumvent the NP-hard sign problem. In order to do so, we modify complex Langevin using k...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
SpringerOpen
2023-04-01
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Series: | Journal of High Energy Physics |
Subjects: | |
Online Access: | https://doi.org/10.1007/JHEP04(2023)057 |