Pattern-recognition techniques to search for gravitational waves from inspiraling, dark-dressed primordial black holes

TL;DR

This paper introduces a pattern-recognition method called generalized frequency-Hough to detect gravitational waves from primordial black hole binaries with dark dresses, accounting for dynamical friction effects that could otherwise reduce detection sensitivity.

Contribution

It demonstrates that the GFH method can identify signals affected by dark dresses with minimal modifications, advancing dark matter-aware gravitational wave search techniques.

Findings

Successfully recovered simulated signals in Gaussian noise

Shows minimal modifications needed for dark dress signals

Enhances detection sensitivity for asymmetric mass-ratio binaries

Abstract

Primordial black holes (PBHs) are compelling dark matter (DM) candidates, but current constraints suggest they cannot compose all of DM. This implies that additional DM components could coexist with PBHs, one of which could form "dark dresses" (DDs) around PBHs. DDs would cause PBH binaries to experience dynamical friction (DF), which would accelerate their inspirals with respect to those in vacuum. Ignoring DF effects in matched-filtering searches could lead to significant sensitivity loss, especially in systems with asymmetric mass-ratios of q ~ 10^{-3}. We thus show that a method designed to find time-frequency power-law tracks from inspiraling PBHs in vacuum could actually handle the presence of DDs with minimal modifications. This method, the generalized frequency-Hough (GFH), maps points in the detector's time-frequency plane to lines in the source parameter space. We show that this pattern-recognition technique can recover simulated DD signals in Gaussian noise, marking an important step forward in developing DM-aware methods beyond matched filtering.