Efficient parameter inference for gravitational wave signals in the presence of transient noises using temporal and time-spectral fusion normalizing flow

Understand

Glitches represent a category of non-Gaussian and transient noise that frequently intersects with gravitational wave (GW) signals, exerting a notable impact on the processing of GW data.

• The inference of GW parameters, crucial for GW astronomy research, is particularly susceptible to such interference.
• In this study, we pioneer the utilization of temporal and time-spectral fusion normalizing flow for likelihood-free inference of GW parameters, seamlessly integrating the high temporal resolution of the time domain with the frequency separation characteristics of both time and frequency domains.
• Remarkably, our findings indicate that the accuracy of this inference method is comparable to traditional non-glitch sampling techniques.