# Neural Network Field Transformation and Its Application in HMC

@article{Jin2022NeuralNF, title={Neural Network Field Transformation and Its Application in HMC}, author={Xiaoyan Jin}, journal={Proceedings of The 38th International Symposium on Lattice Field Theory — PoS(LATTICE2021)}, year={2022} }

We propose a generic construction of Lie group agnostic and gauge covariant neural networks, and introduce constraints to make the neural networks continuous diﬀerentiable and invertible. We combine such neural networks and build gauge ﬁeld transformations that is suitable for Hybrid Monte Carlo (HMC). We use HMC to sample lattice gauge conﬁgurations in the transformed space by the neural network parameterized gauge ﬁeld transformations. Tested with 2D U(1) pure gauge systems at a range of…

## One Citation

### Applications of Machine Learning to Lattice Quantum Field Theory

- PhysicsArXiv
- 2022

Denis Boyda, 2 Salvatore Cal̀ı, 2 Sam Foreman, Lena Funcke, 2, 4 Daniel C. Hackett, 2, ∗ Yin Lin, 2 Gert Aarts, 6 Andrei Alexandru, 8 Xiao-Yong Jin, 9 Biagio Lucini, 11 and Phiala E. Shanahan 2, 4…

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