activity
20162021
most citedConstraining the primordial black hole scenario with Bayesian inference and machine learning: the GWTC-2 gravitational wave catalog

144 citations · 358 across the 10 of their papers we have counts for

collaborators

20 papers

gr-qc2021

Discriminating between different scenarios for the formation and evolution of massive black holes with LISA

Alexandre Toubiana, Kaze W. K. Wong, Stanislav Babak +5

Electromagnetic observations have provided strong evidence for the existence of massive black holes in the center of galaxies, but their origin is still poorly known. Different sce…

gr-qc2021

Looking for the parents of LIGO's black holes

Vishal Baibhav, Emanuele Berti, Davide Gerosa +2

Solutions to the two-body problem in general relativity allow us to predict the mass, spin and recoil velocity of a black-hole merger remnant given the masses and spins of its bina…

gr-qc2021

The missing link in gravitational-wave astronomy: A summary of discoveries waiting in the decihertz range

Manuel Arca Sedda, Christopher P L Berry, Karan Jani +25

Since 2015 the gravitational-wave observations of LIGO and Virgo have transformed our understanding of compact-object binaries. In the years to come, ground-based gravitational-wav…

astro-ph.HE2020

Joint constraints on the field-cluster mixing fraction, common envelope efficiency, and globular cluster radii from a population of binary hole mergers via deep learning

Kaze W. K. Wong, Katelyn Breivik, Kyle Kremer +1

The recent release of the second Gravitational-Wave Transient Catalog (GWTC-2) has increased significantly the number of known GW events, enabling unprecedented constraints on form…

gr-qc2020144 cited

Constraining the primordial black hole scenario with Bayesian inference and machine learning: the GWTC-2 gravitational wave catalog

Kaze W. K. Wong, Gabriele Franciolini, Valerio De Luca +4

Primordial black holes (PBHs) might be formed in the early Universe and could comprise at least a fraction of the dark matter. Using the recently released GWTC-2 dataset from the t…

astro-ph.HE20207 cited

Gravitational-wave signal-to-noise interpolation via neural networks

Kaze W. K. Wong, Ken K. Y. Ng, Emanuele Berti

Computing signal-to-noise ratios (SNRs) is one of the most common tasks in gravitational-wave data analysis. While a single SNR evaluation is generally fast, computing SNRs for an…