Learning Trivializing Gradient Flows for Lattice Gauge Theories

Bacchio, Simone; Kessel, Pan; Schaefer, Stefan; Vaitl, Lorenz

doi:10.48550/arxiv.2212.08469

Cited by 4 publications

(4 citation statements)

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“…by modifying neural networks or using different flows, or by modification of the flow maps, e.g. using continues flows [98].…”

Section: Pos(lattice2022)227mentioning

confidence: 99%

Review on Algorithms for dynamical fermions

Finkenrath¹

2023

Proceedings of the 39th International Symposium on Lattice Field Theory — PoS(LATTICE2022)

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This review discusses the current and next steps in research of algorithms for dynamical fermions in large scale lattice QCD simulations. First a short overview on the state-of-the-art of ensemble generation at the physical point is given. Followed by an overview on required steps towards simulation of large lattices for the Hybrid Monte Carlo algorithm. Here, in particular, the status of iterative solvers and tuning procedures for numerical integrators within the molecular dynamics are discussed. This is followed by a review on the on-going developments for algorithms, with a focus on methods which are potentially useful to simulate gauge theories at very fine lattice spacings, i.e. well suited to overcome freezing of the topological charge. This includes modification of the HMC algorithm as well as a discussion of algorithms which includes the fermion weight via global correction steps. Parts of the discussions are on the application of generative models via gauge equivariant flows as well as multi-level algorithms.

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“…by modifying neural networks or using different flows, or by modification of the flow maps, e.g. using continues flows [98].…”

Section: Pos(lattice2022)227mentioning

confidence: 99%

Review on Algorithms for dynamical fermions

Finkenrath¹

2023

Proceedings of the 39th International Symposium on Lattice Field Theory — PoS(LATTICE2022)

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“…The state of the art algorithm for the gauge field generation in QCD is the Hybrid Monte Carlo (HMC) [1], and there are two major directions to cope with the critical slowing down in this algorithmic framework (see [2,3] for reviews). One is to align the velocity in the molecular dynamics (MD) among all the Fourier modes [4][5][6][7][8], and the other is to construct a field transformation such that the resulting effective action has advantageous sampling properties [10,11] (see also [12][13][14][15][16][17][18]).…”

Section: Introductionmentioning

confidence: 99%

Decimation map in 2D for accelerating HMC

Matsumoto,

Brower,

Izubuchi

2023

Proceedings of the 40th International Symposium on Lattice Field Theory — PoS(LATTICE2023)

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To accelerate the HMC with field transformation, we consider a variant of the trivializing map, the decimation map, which can be regarded as a coarse-graining transformation. Using the 2D 𝑈 (1) pure gauge model, combined with the guided Monte Carlo algorithm, we show that the integrated autocorrelation time of the topological charge can be exponentially improved in the wall clock time. Our study indicates that incorporating renormalization group picture is a powerful and essential ingredient to accelerate the HMC at large 𝛽.

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“…Using normalizing flows for sampling in lattice field theory has gained significant attention over the last few years. Several works have been carried out in the domain of scalar field theories [1][2][3][4][5][6][7][8][9][10], U (1) [11,12] and SU (N ) [13][14][15] pure gauge theories, and fermionic gauge theories [16,17]. This rapid development is attributed to the appealing conceptual properties of flow-based sampling.…”

Section: Introductionmentioning

confidence: 99%