Individual skill
matched-filtering
Matched filtering techniques for gravitational wave detection. Use when searching for signals in detector data using template waveforms, including both time-domain and frequency-domain approaches. Works with PyCBC for generating templates and performing matched filtering.
tasks/gravitational-wave-detection/environment/skills/matched-filtering/SKILL.md
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# Matched Filtering for Gravitational Wave Detection
Matched filtering is the primary technique for detecting gravitational wave signals in noisy detector data. It correlates known template waveforms with the detector data to find signals with high signal-to-noise ratio (SNR).
## Overview
Matched filtering requires:
1. Template waveform (expected signal shape)
2. Conditioned detector data (preprocessed strain)
3. Power spectral density (PSD) of the noise
4. SNR calculation and peak finding
PyCBC supports both time-domain and frequency-domain approaches.
