基于导数展开的函数重正化群的数值精度

IF 2.2 3区 物理与天体物理 Q2 MECHANICS
Andrzej Chlebicki
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引用次数: 0

摘要

我们研究了基于从线性化重正化群变换中提取特征值的函数重正化群数值实现的精度。为此,我们对三维 O(N)模型实施了局部势近似和导数展开阶数。我们确定了几类数值误差,并设计了简单的测试来跟踪它们作为数值参数函数的大小。我们的数值方案收敛正常,其误差比这些模型的导数展开误差小几个数量级。我们强调了我们的方法停止收敛的情况,这通常是由于舍入误差造成的。特别是,当网格在小于 3.5 倍局部势能最小值时被切断时,我们观察到离散化方案的收敛性受损。为本研究进行数值计算的程序以开放源代码库的形式共享,可供查阅和重复使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Numerical accuracy of the derivative-expansion-based functional renormalization group
We investigate the precision of the numerical implementation of the functional renormalization group based on extracting the eigenvalues from the linearized renormalization group transformation. For this purpose, we implement the local potential approximation and orders of the derivative expansion for the three-dimensional O(N) models with . We identify several categories of numerical error and devise simple tests to track their magnitude as functions of numerical parameters. Our numerical schemes converge properly and are characterized by errors of several orders of magnitude smaller than the error bars of the derivative expansion for these models. We highlight situations in which our methods cease to converge, most often due to rounding errors. In particular, we observe an impaired convergence of the discretization scheme when the grid is cut off at the value smaller than 3.5 times the local potential minimum. The program performing the numerical calculations for this study is shared as an open-source library accessible for review and reuse.
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来源期刊
CiteScore
4.50
自引率
12.50%
发文量
210
审稿时长
1.0 months
期刊介绍: JSTAT is targeted to a broad community interested in different aspects of statistical physics, which are roughly defined by the fields represented in the conferences called ''Statistical Physics''. Submissions from experimentalists working on all the topics which have some ''connection to statistical physics are also strongly encouraged. The journal covers different topics which correspond to the following keyword sections. 1. Quantum statistical physics, condensed matter, integrable systems Scientific Directors: Eduardo Fradkin and Giuseppe Mussardo 2. Classical statistical mechanics, equilibrium and non-equilibrium Scientific Directors: David Mukamel, Matteo Marsili and Giuseppe Mussardo 3. Disordered systems, classical and quantum Scientific Directors: Eduardo Fradkin and Riccardo Zecchina 4. Interdisciplinary statistical mechanics Scientific Directors: Matteo Marsili and Riccardo Zecchina 5. Biological modelling and information Scientific Directors: Matteo Marsili, William Bialek and Riccardo Zecchina
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