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Carlo.jl: A general framework for Monte Carlo simulations in Julia

by Lukas Weber

Submission summary

Authors (as registered SciPost users): Lukas Weber
Submission information
Preprint Link: scipost_202412_00026v1  (pdf)
Code repository: https://github.com/lukas-weber/Carlo.jl
Code version: v0.2.3
Code license: MIT License
Date accepted: 2024-12-18
Date submitted: 2024-12-13 18:42
Submitted by: Weber, Lukas
Submitted to: SciPost Physics Codebases
Ontological classification
Academic field: Physics
Specialties:
  • Condensed Matter Physics - Computational
  • Statistical and Soft Matter Physics
Approach: Computational

Abstract

Carlo.jl is a Monte Carlo simulation framework written in Julia. It provides MPI-parallel scheduling (including parallel tempering), organized storage of input, checkpoint, and output files, as well as statistical postprocessing. With a minimalist design, it aims to aid the development of high-quality Monte Carlo codes, especially for demanding applications in condensed matter and statistical physics. This hands-on user guide shows how to implement a simple code with Carlo.jl, how to run an existing stochastic series expansion code based on Carlo.jl, and provides benchmarks to show its efficacy.

List of changes

- adds discussion about sign problem in the case of mixed-sign $D^x_i$
- correction of typos and style improvements

Current status:
Accepted in target Journal

Editorial decision: For Journal SciPost Physics Codebases: Publish
(status: Editorial decision fixed and (if required) accepted by authors)

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