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Abstract

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We present an improvement of the Gillespie Exact Stochastic Simulation Algorithm, which leverages a bitwise representation of variables to perform independent simulations in parallel. We show that the subsequent gain in computational yield is significant, and it may allow to perform simulations of non-well mixed chemical systems. We illustrate this idea with simulations of Frank model, originally introduced to explain the emergence of homochirality in prebiotic systems.

Details

1009240
Subject
Parallel processing;
Algorithms;
Independent variables
Identifier / keyword
Statistical Mechanics; Computational Physics
URL
http://arxiv.org/abs/2412.16613
Title
Parallelization of Gillespie algorithm based on binary words
Author
Lacoste, David; Castellana, Michele
Publication title
arXiv.org; Ithaca
Publication year
2024
Publication date
Dec 21, 2024
Section
Condensed Matter; Physics (Other)
Publisher
Cornell University Library, arXiv.org
Source
arXiv.org
Place of publication
Ithaca
Country of publication
United States
University/institution
Cornell University Library arXiv.org
Publication subject
Biology, Statistics, Physics, Mathematics, Engineering--Electrical Engineering, Computers--Computer Engineering, Business And Economics--Banking And Finance
e-ISSN
2331-8422
Source type
Working Paper
Language of publication
English
Document type
Working Paper
Publication history
 
 
Online publication date
2024-12-24
Milestone dates
2024-12-21 (Submission v1)
Publication history
 
 
   First posting date
24 Dec 2024
ProQuest document ID
3148979723
Document URL
https://www.proquest.com/working-papers/parallelization-gillespie-algorithm-based-on/docview/3148979723/se-2?accountid=208611
Full text outside of ProQuest
http://arxiv.org/abs/2412.16613
Copyright
© 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2024-12-25
Database
ProQuest One Academic