Gayathri V. | Searcharxiv

arXiv2023

Determining the Hubble Constant with AGN-assisted Black Hole Mergers

Gravitational waves from neutron star mergers have long been considered a promising way to measure the Hubble constant, $H_0$, which describes the local expansion rate of the universe. While black hole mergers are more abundantly observed, their expected lack of electromagnetic emission and poor gravitational-wave localization make them less well suited for measuring $H_0$. Black hole mergers within the disks of Active Galactic Nuclei (AGN) could be an exception. Accretion from the AGN disk may produce an electromagnetic signal, pointing observers to the host galaxy. Alternatively, the low number density of AGNs could help identify the host galaxy of $1-5\%$ of mergers. Here we show that black hole mergers in AGN disks may be a sensitive way to determine $H_0$ with gravitational waves. If $1\%$ ($10\%$) of LIGO's observations occur in AGN disks with identified host galaxies, we could measure $H_0$ with $12\%$ ($4\%$) uncertainty in five years, possibly comparable to the sensitivity of neutron star mergers and set to considerably improve current gravitational wave measurements.

astro-ph.HE↗

arXiv2018

Driving unmodelled gravitational-wave transient searches using astrophysical information

Transient gravitational-wave searches can be divided into two main families of approaches: modelled and unmodelled searches, based on matched filtering techniques and time-frequency excess power identification respectively. The former, mostly applied in the context of compact binary searches, relies on the precise knowledge of the expected gravitational-wave phase evolution. This information is not always available at the required accuracy for all plausible astrophysical scenarios, e.g., in presence of orbital precession, or eccentricity. The other search approach imposes little priors on the targetted signal. We propose an intermediate route based on a modification of unmodelled search methods in which time-frequency pattern matching is constrained by astrophysical waveform models (but not requiring accurate prediction for the waveform phase evolution). The set of astrophysically motivated patterns is conveniently encapsulated in a graph, that encodes the time-frequency pixels and their co-occurrence. This allows the use of efficient graph-based optimization techniques to perform the pattern search in the data. We show in the example of black-hole binary searches that such an approach leads to an averaged increase in the distance reach (+7-8\%) for this specific source over standard unmodelled searches.

astro-ph.IM↗