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New method uses normalizing flows for SU(N) lattice gauge theory sampling

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a novel method for sampling SU(N) gauge theory on a 2D lattice using normalizing flows. This approach addresses the challenge of mapping sampled plaquettes to link variables in lattice gauge theory by reformulating the action in terms of holonomy variables. The method involves a conditional sampling problem where plaquettes are sampled independently, with weights determined by the group commutator of corner variables. This technique has shown high acceptance rates and moderate effective sample sizes in tests on various lattice sizes and couplings for SU(2) and SU(3) theories. AI

IMPACT Introduces a novel application of normalizing flows for complex physics simulations, potentially advancing computational methods in theoretical physics.

RANK_REASON Academic paper detailing a new computational method for a physics theory. [lever_c_demoted from research: ic=1 ai=0.7]

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New method uses normalizing flows for SU(N) lattice gauge theory sampling

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Academic paper detailing a new computational method for a physics theory. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    Sampling SU(N) gauge theory on a 2D lattice from independent plaquettes via holonomies and corner reweighting

    In the Wilson formulation of lattice gauge theory, the fundamental degrees of freedom are group-valued link variables, while the action is a sum over the trace of the plaquettes, the smallest Wilson loops. For generative sampling methods such as normalizing flows, this poses a ch…

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