🧬 Revolutionary LLM-guided framework for automated algorithmic discovery in gravitational wave detection. Combines evolutionary optimization with Monte Carlo Tree Search to systematically explore algorithm spaces and achieve 20.2% improvement over state-of-the-art methods on MLGWSC-1 benchmark.
🌊 AI-powered gravitational wave detection system using Model Context Protocol (MCP) for efficient parameter space exploration. Features optimization client, analysis server, and automated parameter exploration for LIGO GW150914 data with LLM-agent validation.
The direct detection of gravitational waves by LIGO has confirmed general relativity (GR) and sparked rapid growth in gravitational wave (GW) astronomy. However, subtle post-Newtonian (PN) deviations observed during the analysis of high …
Since the early stages of operation of ground-based gravitational-wave interferometers, careful monitoring of these detectors has been an important component of their successful operation and observations. Characterization of gravitational-wave …
An interactive gravitational wave simulation ([LIGO-G2001983-v3](https://dcc.ligo.org/LIGO-G2001983)) in JavaScript created by [Graham Woan](https://dcc.ligo.org/cgi-bin/private/DocDB/ListBy?authorid=234), suitable for talks etc on spinning NSs and BBHs.
Python Script to plot cumulative GW Events until the end of O3a and Public Alerts in O3b