Basic Data Processing of Gravitational Waves
Fuente:
arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866913548101222400 |
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| author | Wu, Jingxu Yin, YuWei Li, Chenjia Wang, Yan |
| author_facet | Wu, Jingxu Yin, YuWei Li, Chenjia Wang, Yan |
| contents | This paper provides a comprehensive guide to gravitational wave data processing, with a particular focus on signal generation, noise modeling, and optimization techniques. Beginning with an introduction to gravitational waves and the detection techniques used by LIGO and Virgo, the manual covers the essentials of signal processing, including Fourier analysis, filtering, and the generation of quadratic chirp signals. The analysis of colored Gaussian noise and its impact on interferometric detectors like LIGO is explored in detail, alongside signal detection methods such as the Generalized Likelihood Ratio Test (GLRT). The paper also delves into optimization techniques like Particle Swarm Optimization (PSO), which can be applied to improve signal estimation accuracy. By providing MATLAB-based implementations, this manual serves as both a theoretical and practical resource for researchers in the field of gravitational wave astronomy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_11858 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Basic Data Processing of Gravitational Waves Wu, Jingxu Yin, YuWei Li, Chenjia Wang, Yan Instrumentation and Methods for Astrophysics General Relativity and Quantum Cosmology This paper provides a comprehensive guide to gravitational wave data processing, with a particular focus on signal generation, noise modeling, and optimization techniques. Beginning with an introduction to gravitational waves and the detection techniques used by LIGO and Virgo, the manual covers the essentials of signal processing, including Fourier analysis, filtering, and the generation of quadratic chirp signals. The analysis of colored Gaussian noise and its impact on interferometric detectors like LIGO is explored in detail, alongside signal detection methods such as the Generalized Likelihood Ratio Test (GLRT). The paper also delves into optimization techniques like Particle Swarm Optimization (PSO), which can be applied to improve signal estimation accuracy. By providing MATLAB-based implementations, this manual serves as both a theoretical and practical resource for researchers in the field of gravitational wave astronomy. |
| title | Basic Data Processing of Gravitational Waves |
| topic | Instrumentation and Methods for Astrophysics General Relativity and Quantum Cosmology |
| url | https://arxiv.org/abs/2410.11858 |