Multigrid low-mode averaging

IF 5.3 2区 物理与天体物理 Q1 Physics and Astronomy
Roman Gruber, Tim Harris, Marina Krstić Marinković
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引用次数: 0

Abstract

We develop a generalization of low-mode averaging in which the number of low quark modes of the Dirac operator required for a constant variance reduction can be kept independent of the volume by exploiting their local coherence. Typically in lattice QCD simulations, the benefit of translation averaging quark propagators over the space-time volume is spoiled by large fluctuations introduced by the approximations needed to estimate the average. For quark-line connected diagrams at large separations, most of this additional variance can be efficiently suppressed by the introduction of hierarchical subspaces, thanks to the reduced size of the coarse grid operators that act within the subspaces. In this work, we investigate the contributions to the variance of the isovector vector current correlator with Nf=2 nonperturbatively O(a)-improved Wilson fermions on lattices approximately of size L=2, 3 and 4 fm. The numerical results obtained confirm that the variance decreases as the volume is increased when a multigrid decomposition is used with a fixed number of low modes. We obtain a speedup of more than an order of magnitude compared with a plain stochastic estimator. Compared with state-of-the-art low-mode averaging we practically eliminate the cost of generating low modes and the associated memory and storage overheads. While the proposed decomposition can be applied to any quark propagator, it is expected to be especially effective for quark-line connected diagrams at large separations, for example, the isovector contribution to the hadronic vacuum polarization or baryonic correlators. Published by the American Physical Society 2025
多网格低模式平均
我们开发了一种低模平均的推广方法,其中通过利用其局部相干性,可以使恒定方差减小所需的狄拉克算子的低夸克模数与体积无关。典型地,在晶格QCD模拟中,平移平均夸克传播子在时空体积上的优势被估计平均值所需的近似所引入的大波动所破坏。对于大间距的夸克线连接图,由于在子空间内作用的粗网格算子的大小减小,通过引入分层子空间可以有效地抑制大多数附加方差。在这项工作中,我们研究了Nf=2的非扰动O(a)改进Wilson费米子在尺寸约为L= 2,3和4fm的晶格上对等矢量矢量电流相关器方差的贡献。数值结果表明,当采用固定低模态数的多网格分解时,方差随体积的增大而减小。与普通随机估计器相比,我们得到了一个数量级以上的加速。与最先进的低模式平均相比,我们实际上消除了产生低模式的成本以及相关的内存和存储开销。虽然所提出的分解可以应用于任何夸克传播子,但预计它对大间距的夸克线连接图特别有效,例如,对强子真空极化或重子相关器的等矢量贡献。2025年由美国物理学会出版
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来源期刊
Physical Review D
Physical Review D 物理-天文与天体物理
CiteScore
9.20
自引率
36.00%
发文量
0
审稿时长
2 months
期刊介绍: Physical Review D (PRD) is a leading journal in elementary particle physics, field theory, gravitation, and cosmology and is one of the top-cited journals in high-energy physics. PRD covers experimental and theoretical results in all aspects of particle physics, field theory, gravitation and cosmology, including: Particle physics experiments, Electroweak interactions, Strong interactions, Lattice field theories, lattice QCD, Beyond the standard model physics, Phenomenological aspects of field theory, general methods, Gravity, cosmology, cosmic rays, Astrophysics and astroparticle physics, General relativity, Formal aspects of field theory, field theory in curved space, String theory, quantum gravity, gauge/gravity duality.
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