Extraction of black hole coalescence waveforms from noisy data

TL;DR

This paper presents a method for extracting gravitational wave signals from noisy LIGO data, confirming the consistency of the waveforms with black hole coalescence templates and validating the analysis with simulated injections.

Contribution

It introduces an independent filtering approach to extract waveforms from LIGO data, providing a validation method that confirms waveform consistency and assesses uncertainties.

Findings

No evidence of non-Gaussian noise after filtering.

Extracted waveforms match black hole coalescence templates.

Analysis with simulated injections shows unbiased results.

Abstract

We describe an independent analysis of LIGO data for black hole coalescence events. Gravitational wave strain waveforms are extracted directly from the data using a filtering method that exploits the observed or expected time-dependent frequency content. Statistical analysis of residual noise, after filtering out spectral peaks (and considering finite bandwidth), shows no evidence of non-Gaussian behaviour. There is also no evidence of anomalous causal correlation between noise signals at the Hanford and Livingston sites. The extracted waveforms are consistent with black hole coalescence template waveforms provided by LIGO. Simulated events, with known signals injected into real noise, are used to determine uncertainties due to residual noise and demonstrate that our results are unbiased. Conceptual and numerical differences between our RMS signal-to-noise ratios (SNRs) and the published matched-filter detection SNRs are discussed.