English

PycWB: A User-friendly, Modular, and Python-based Framework for Gravitational Wave Unmodelled Search

General Relativity and Quantum Cosmology 2024-03-05 v1 Instrumentation and Methods for Astrophysics

Abstract

Unmodelled searches and reconstruction is a critical aspect of gravitational wave data analysis, requiring sophisticated software tools for robust data analysis. This paper introduces PycWB, a user-friendly and modular Python-based framework developed to enhance such analyses based on the widely used unmodelled search and reconstruction algorithm Coherent Wave Burst (cWB). The main features include a transition from C++ scripts to YAML format for user-defined parameters, improved modularity, and a shift from complex class-encapsulated algorithms to compartmentalized modules. The pycWB architecture facilitates efficient dependency management, better error-checking, and the use of parallel computation for performance enhancement. Moreover, the use of Python harnesses its rich library of packages, facilitating post-production analysis and visualization. The PycWB framework is designed to improve the user experience and accelerate the development of unmodelled gravitational wave analysis.

Keywords

Cite

@article{arxiv.2308.08639,
  title  = {PycWB: A User-friendly, Modular, and Python-based Framework for Gravitational Wave Unmodelled Search},
  author = {Yumeng Xu and Shubhanshu Tiwari and Marco Drago},
  journal= {arXiv preprint arXiv:2308.08639},
  year   = {2024}
}

Comments

16 pages, 4 figures

R2 v1 2026-06-28T11:57:27.333Z