Fast, flexible, and accurate evaluation of gravitational-wave Malmquist bias with machine learning

Understand

Many astronomical surveys are limited by the brightness of the sources, and gravitational-wave searches are no exception.

• The detectability of gravitational waves from merging binaries is affected by the mass and spin of the constituent compact objects.
• To perform unbiased inference on the distribution of compact binaries, it is necessary to account for this selection effect, which is known as Malmquist bias.
• Since systematic error from selection effects grows with the number of events, it will be increasingly important over the coming years to accurately estimate the observational selection function for gravitational-wave astronomy.