SporTran: A code to estimate transport coefficients from the cepstral analysis of (multivariate) current time series

被引：14

作者：

Ercole, Loris ^{[1
,2
]}

Bertossa, Riccardo ^{[2
]}

Bisacchi, Sebastiano ^{[2
,3
]}

Baroni, Stefano ^{[2
,4
]}

机构：

[1] Ecole Polytech Fed Lausanne, Natl Ctr Computat Design & Discovery Novel Mat MAR, Theory & Simulat Mat THEOS, CH-1015 Lausanne, Switzerland

[2] Scuola Int Super Studi Avanzati, SISSA, Via Bonomea 265, I-34136 Trieste, Italy

[3] Ist Statale Istruz Super Galileo Galilei, via Puccini 22, I-34170 Gorizia, Italy

[4] SISSA, Ist Officina Materiali, CNR, I-34136 Trieste, Italy

来源：

COMPUTER PHYSICS COMMUNICATIONS | 2022年 / 280卷

关键词：

Molecular dynamics; Transport coefficients; Green Kubo; Linear response; Time series; Cepstral analysis; STATISTICAL-MECHANICAL THEORY; MARKOV RANDOM-PROCESSES; IRREVERSIBLE-PROCESSES; RECIPROCAL RELATIONS;

D O I：

10.1016/j.cpc.2022.108470

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

SporTran is a Python utility designed to estimate generic transport coefficients in extended systems, based on the Green-Kubo theory of linear response and the recently introduced cepstral analysis of the current time series generated by molecular dynamics simulations. SporTran can be applied to univariate as well as multivariate time series. Cepstral analysis requires minimum discretion from the user, in that it weakly depends on two parameters, one of which is automatically estimated by a statistical model-selection criterion that univocally determines the resulting accuracy. In order to facilitate the optimal refinement of these parameters, SporTran features an easy-to-use graphical user interface. A command-line interface and a Python API, easy to embed in complex data-analysis workflows, are also provided. (C) 2022 Elsevier B.V. All rights reserved.

引用

页数：8

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