Speaker
Description
Primordial black holes (PBHs) are compelling dark matter (DM) candidates; however, current observational constraints indicate that they cannot account for the entirety of the DM abundance. This motivates scenarios in which additional DM components coexist with PBHs and form dense structures, often referred to as ``dark dresses,'' around them. Such environments induce dynamical friction, accelerating the inspiral rate of PBH binaries relative to vacuum evolution. Neglecting such environmental effects in gravitational-wave searches can lead to substantial losses in sensitivity. In particular, for third-generation detectors such as the Einstein Telescope, searching for inspirals affected by DM environments using templates that neglect DM effects can lead to signal-to-noise ratio (SNR) losses of up to $\sim70\%$ in certain regions of parameter space, especially for binaries with highly asymmetric mass ratios ($q \sim 10^{-3}$). We demonstrate that a search strategy originally developed for vacuum PBH inspirals can remain effective in the presence of dark dresses with only minimal modifications. Specifically, we apply the generalized frequency-Hough (GFH) method, a pattern-recognition technique that maps time--frequency tracks in detector's plane to lines in source parameter space. Using simulated signals embedded in Gaussian noise, we show that the GFH method successfully recovers inspirals affected by DM environments. These results highlight the potential of DM aware, non-matched-filtering approaches for future gravitational-wave searches and provide a robust framework for probing environmental effects around primordial black holes.