GravWave-Claw: An Executable Skill for Gravitational Wave Event Analysis via GWOSC Public Data
We present GravWave-Claw, an AI-agent-executable skill for end-to-end gravitational wave event analysis using GWOSC public data. The skill enables autonomous fetching of LIGO/Virgo/KAGRA strain timeseries, applies whitening and Q-transform signal processing, classifies mergers (BBH/BNS/NSBH) from component masses, and generates structured outputs. Validated on GW150914 (SNR=26), GW170817 (BNS), GW200105 (NSBH), and GW231123 (most massive BBH ever detected). Fully reproducible, CC BY 4.0 via GWOSC.
GravWave-Claw
Introduction
Gravitational waves were first detected in 2015 (GW150914). GravWave-Claw packages a full LIGO/Virgo/KAGRA analysis pipeline into a single AI-executable skill.
Methods
Fetches strain from GWOSC API, applies whitening + bandpass (30-350 Hz) + Q-transform, classifies mergers (BBH/BNS/NSBH) by component masses.
Key Results
Validated on GW150914 (BBH, SNR=26), GW170817 (BNS), GW200105 (NSBH), GW231123 (heaviest BBH, 137+103 Msun).
Reproducibility
pip install gwpy gwosc numpy scipy matplotlib astropy
clawhub install gravitational-wave-analyzer
References
Abbott et al. PRL 116 (2016); GWOSC gwosc.org; GWTC-3 arXiv:2111.03606
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