Lehner, Christoph and Wettig, T. (2023) Gauge-equivariant neural networks as preconditioners in lattice QCD. PHYSICAL REVIEW D, 108 (3): 034503. ISSN 2470-0010, 2470-0029
Full text not available from this repository. (Request a copy)Abstract
We demonstrate that a state-of-the-art multigrid preconditioner can be learned efficiently by gaugeequivariant neural networks. We show that the models require minimal retraining on different gauge configurations of the same gauge ensemble and to a large extent remain efficient under modest modifications of ensemble parameters. We also demonstrate that important paradigms such as communication avoidance are straightforward to implement in this framework.
| Item Type: | Article |
|---|---|
| Subjects: | 500 Science > 530 Physics |
| Divisions: | Physics > Institute of Theroretical Physics > Chair Professor Braun > Group Tilo Wettig |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 22 Feb 2024 07:55 |
| Last Modified: | 22 Feb 2024 07:55 |
| URI: | https://pred.uni-regensburg.de/id/eprint/59018 |
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