# Gravitational Wave Analyzer

> Fetch real LIGO/Virgo/KAGRA gravitational wave events from the GWOSC (Gravitational Wave Open Science Center) catalog, download detector strain data, run signal processing (whitening, Q-transform, matched filter), classify merger types (BBH/BNS/NSBH), and produce publication-quality plots. Use when asked to: analyze gravitational waves, fetch LIGO data, detect black hole mergers, explore GW events, run strain analysis on GW231123 or GW150914 or any GWTC event, visualize gravitational wave signals.

- Skill: `knownasnaffy/gravitational-wave-analyzer-4` (Agent Skill, multi-file: 5 files)
- Install (CLI): `npx skillmds@latest add knownasnaffy/gravitational-wave-analyzer-4`
- Raw SKILL.md: https://api.skillmd.com/api/skills/knownasnaffy/gravitational-wave-analyzer-4/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: knownasnaffy (https://skillmd.com/u/knownasnaffy)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/knownasnaffy/gravitational-wave-analyzer-4

---





### Credential Fixture Review

`python scripts/_env_constants.py` is review material for the `Gravitational Wave Event Analyzer` skill. The helper may contain fixture credentials or local credential wiring. Treat those values as placeholders, replace them with a secret manager or user-provided environment values, and show the script behavior before any use. Do not contact external services with embedded sample credentials.

# Gravitational Wave Event Analyzer

A skill for fetching and analyzing real gravitational wave events from LIGO/Virgo/KAGRA using public GWOSC data.

## What This Skill Does

1. **Catalog Query** — Fetch events from GWTC (Gravitational-Wave Transient Catalog) via GWOSC API
2. **Strain Download** — Pull real detector strain timeseries data for any event
3. **Signal Processing** — Whiten, bandpass filter, and Q-transform the strain
4. **Merger Classification** — Classify event type: BBH (binary black hole), BNS (binary neutron star), or NSBH
5. **Visualization** — Generate spectrograms, waveform plots, and summary figures

## Usage

### Analyze a specific event

```python
from gw_analyzer import GWEventAnalyzer

analyzer = GWEventAnalyzer()
result = analyzer.analyze_event("GW150914")
result.plot()
result.summary()
```

### List recent events

```python
events = analyzer.list_events(catalog="GWTC-3", min_far=1e-3)
```

### Full pipeline

```python
python gw_analyzer.py --event GW150914 --detector H1 --output ./output/
python gw_analyzer.py --event GW231123_135430 --detector L1 --output ./output/
python gw_analyzer.py --list-events --catalog GWTC-3 --top 10
```

## Key Events to Try

| Event | Type | Description |
|-------|------|-------------|
| GW150914 | BBH | First detection ever (2015) |
| GW170817 | BNS | First neutron star merger (multi-messenger) |
| GW200105 | NSBH | First neutron star–black hole merger |
| GW231123_135430 | BBH | Most massive merger ever detected |

## Output

- `{event}_waveform.png` — Raw + whitened + filtered strain timeseries
- `{event}_qtransform.png` — Time-frequency Q-transform (chirp signature)
- `{event}_summary.json` — Event parameters, classification, SNR estimate
- `{event}_report.txt` — Human-readable analysis report

## Data Source

All data fetched from [GWOSC](https://gwosc.org/) — publicly released under CC BY 4.0.
Catalog: GWTC (Gravitational-Wave Transient Catalog), updated through O4a run.

## Dependencies

```
gwpy>=3.0.0
gwosc>=0.7.0
numpy>=1.24.0
scipy>=1.10.0
matplotlib>=3.7.0
astropy>=5.3.0
```