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.

PycWB. A user-friendly, modular, and python-based framework for gravitational wave unmodelled search / Xu, Yumeng; Tiwari, Shubhanshu; Drago, Marco. - In: SOFTWAREX. - ISSN 2352-7110. - 26:(2024), pp. 1-7. [10.1016/j.softx.2024.101639]

PycWB. A user-friendly, modular, and python-based framework for gravitational wave unmodelled search

Drago, Marco
2024

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.
2024
gravitational wave search; burst search; physics; data handling; gravitational effects; information analysis; python
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PycWB. A user-friendly, modular, and python-based framework for gravitational wave unmodelled search / Xu, Yumeng; Tiwari, Shubhanshu; Drago, Marco. - In: SOFTWAREX. - ISSN 2352-7110. - 26:(2024), pp. 1-7. [10.1016/j.softx.2024.101639]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1702560
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