Probing minihalo lenses with diffracted gravitational waves

TL;DR

This paper introduces a novel time-domain interpolation method to efficiently analyze wave-optics gravitational lensing effects of minihalos on gravitational waves, enabling parameter inference with current detector sensitivities.

Contribution

It develops a new interpolation approach for the amplification factor, facilitating Bayesian inference of lens parameters in wave-optics gravitational lensing scenarios.

Findings

Potential to identify minihalo lensing events in gravitational wave data.

Ability to extract both lens and source parameters from lensed signals.

Implementation of methods in an open-source Python package.

Abstract

When gravitational waves pass near a gravitating object, they are deflected, or lensed. If the object is massive, such that the wavelength of the waves is small compared to its gravitational size, lensed gravitational wave events can be identified when multiple signals are detected at different times. However, when the wavelength is long, wave-optics diffraction effects will be important, and a lensed event can be identified by looking for frequency-dependent modulations to the gravitational waveform, without having to associate multiple signals. For current ground-based gravitational wave detectors observing stellar-mass binary compact object mergers, wave-optics effects are important for lenses with masses $\lesssim 1000 M_{\odot}$. Therefore, minihalos below this mass range could potentially be identified by lensing diffraction. The challenge with analyzing these events is that the frequency-dependent lensing modulation, or the amplification factor, is prohibitively expensive to compute for Bayesian parameter inference. In this work, we use a novel time-domain method to construct interpolators of the amplification factor for the Navarro-Frenk-White (NFW), generalized singular isothermal sphere (gSIS) and cored isothermal sphere (CIS) lens models. Using these interpolators, we perform Bayesian inference on gravitational-wave signals lensed by minihalos injected in mock detector noise, assuming current sensitivity of ground-based detectors. We find that we could potentially identify an event when it is lensed by minihalos and extract the values of all lens parameters in addition to the parameters of the GW source. All of the methods are implemented in Glworia, the accompanying open-source Python package, and can be generalized to study lensed signals detected by current and next-generation detectors.