Monitoring of Continuous-Wave Hardware Injections in LIGO Interferometers during the O4 Observing Run

TL;DR

This paper discusses the injection and monitoring of simulated continuous gravitational-wave signals in LIGO detectors during the O4 run to validate detection pipelines and detector response.

Contribution

It introduces three methods for monitoring hardware injections, emphasizing a new templated approach for precise phase and timing validation.

Findings

Successful recovery of simulated signals over 10^11 cycles

Validation of detector response and data pipelines

Enhanced understanding of timing delays and signal parameters

Abstract

Although there have now been hundreds of transient gravitational-wave detections of merging compact stars by the LIGO-Virgo-KAGRA (LVK) detector network, no continuous-wave (CW) signals have yet been discovered. To ensure that such signals, expected to be exceedingly weak, can be detected in the ongoing O4 observing run by coherent integration over years, simulated waveforms ('hardware injections') are injected directly into the LIGO data by continuously modulating the positions of the interferometer mirrors so as to mimic nearly sinusoidal signals from fast-spinning galactic neutron stars. A set of 18 such simulated CW sources are injected with signal frequencies spanning much of the LIGO detection band and with varying sky locations. By verifying the successful recovery of the simulated signals, including preservation of absolute phase over as many as 10^{11} signal cycles, we validate our understanding of detector response and end-to-end search pipelines, including data cleaning. Daily and weekly monitoring of the signal reconstruction is meant to catch any unexpected sudden changes in interferometer response, to verify that signal-to-noise ratio increases as expected and to verify that simulated source parameters are recovered correctly. We describe three methods of monitoring: 1) a highly templated matched filter to extract signal amplitude and phase precisely; 2) a frequentist Fstatistic evaluation that marginalizes over amplitude, phase and orientation of the star; and 3) a Bayesian reconstruction of the source parameters together with noise characterization. Results from each method are shown, with emphasis on the new templated method, which yields precise measurement of the critical phase offset parameter and therefore validates understanding of absolute timing delays in the detector response and data stream.