Directed searches for gravitational waves from ultralight bosons

Gravitational-wave detectors can be used to search for yet-undiscovered ultralight bosons, including those conjectured to solve problems in particle physics, high-energy theory, and cosmology. In particular, ground-based instruments could probe boson masses between ${10}^{\ensuremath{-}15}\text{ }\text{ }\mathrm{eV}$ and ${10}^{\ensuremath{-}11}\text{ }\text{ }\mathrm{eV}$, which are largely inaccessible to other experiments. In this paper, we explore the prospect of searching for the continuous gravitational waves generated by boson clouds around known black holes. We carefully study the predicted waveforms and use the latest-available numerical results to model signals for different black-hole and boson parameters. We then demonstrate the suitability of a specific method (hidden Markov model tracking) to efficiently search for such signals, even when the source parameters are not perfectly known as well as allowing for some uncertainty in theoretical predictions. We empirically study this method's sensitivity and computational cost in the context of boson signals, finding that it will be possible to target remnants from compact-binary mergers localized with at least three instruments. For signals from scalar clouds, we also compute detection horizons for future detectors (Advanced LIGO, LIGO Voyager, Cosmic Explorer, and the Einstein Telescope). Among other results, we find that, after one year of observation, an Advanced LIGO detector at design sensitivity could detect these sources up to over 100 Mpc, while Cosmic Explorer could reach over $1{0}^{4}\text{ }\text{ }\mathrm{Mpc}$. These projections offer a more complete picture than previous estimates based on analytic approximations to the signal power or idealized search strategies. Finally, we discuss specific implications for the follow-up of compact-binary coalescences and black holes in x-ray binaries. Along the way, we review the basic physics of bosons around black holes, in the hope of providing a bridge between the theory and data-analysis literatures.