A Python program for the implementation of the Γ-method for Monte Carlo simulations

We present a modular analysis program written in Python devoted to the estimation of autocorrelation times for Monte Carlo simulations by means of the Γ-method algorithm. We give a brief review of this method and describe the main features of the program. The latter is characterized by a user-friend...

Full description

Saved in:
Bibliographic Details
Published in:Computer physics communications Vol. 234; pp. 294 - 301
Main Authors: De Palma, Barbara, Erba, Marco, Mantovani, Luca, Mosco, Nicola
Format: Journal Article
Language:English
Published: Elsevier B.V 01.01.2019
Subjects:
Autocorrelation time
Monte Carlo simulations
Python
Statistical mechanics
Monte Carlo simulations
Statistical mechanics
Python
Autocorrelation time
ISSN:0010-4655, 1879-2944
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We present a modular analysis program written in Python devoted to the estimation of autocorrelation times for Monte Carlo simulations by means of the Γ-method algorithm. We give a brief review of this method and describe the main features of the program. The latter is characterized by a user-friendly interface and an open source environment which, along with its modularity, make it a versatile tool. Finally we present a simple application as an operational test for the program. Program Title: UNEW Program Files doi:http://dx.doi.org/10.17632/hvtvnjsg3h.1 Licensing provisions: MIT Programming language: Python Nature of problem: Computation of autocorrelation time for Monte Carlo generated data in an open source environment. Solution method: Modular package implementing the Γ-method with advanced data handling.
ISSN:0010-4655
1879-2944
DOI:10.1016/j.cpc.2018.07.004