1.3k citations · 14.6k across the 181 of their papers we have counts for
181 papers
: user-friendly neural posterior estimation for gravitational-wave astronomy
Liam Pinchbeck, Eric Thrane, Csaba Balazs +1
Bayesian inference plays a central role in the new field of gravitational-wave astronomy. However, traditional Bayesian inference with stochastic samplers is computationally expens…
Reconstructing Core-Collapse Supernova Gravitational-Wave Signals with Transdimensional Bayesian Inference
Hayden Chapman, Jade Powell, Nir Guttman +2
Core-collapse supernovae (CCSNe) are promising future sources of gravitational waves for current and next-generation observatories. Reconstructing CCSN gravitational-wave signals i…
Revealing Four Subpopulations of Binary Black-Hole Mergers with the Fifth Gravitational-Wave Transient Catalog
Nir Guttman, Paul D. Lasky, Eric Thrane
Gravitational-wave data are beginning to reveal a structured landscape of black-hole masses and spins, suggesting multiple formation processes are now being resolved observationall…
Fortifying gravitational-wave population inference with normalizing flows
Christian Adamcewicz, Hugh McDougall, Paul D. Lasky +1
As the LIGO-Virgo-KAGRA collaboration's (LVK's) gravitational-wave transient catalog grows, we are learning a wealth of information from the population properties of binary black h…
Joint inference for gravitational-wave signal and noise glitch: Method and application
Shun Yin Cheung, Rhiannon Udall, Derek Davis +2
Non-Gaussian noise transients ("glitches") in gravitational-wave observatories degrade our ability to accurately perform astrophysical inference. We present the analysis pipeline b…
Licence to Bin: Accurate and Scalable Inference for Binary Neutron Stars in Next-Generation Gravitational-Wave Detectors
Nir Guttman, A. Makai Baker, Paul D. Lasky +1
Next-generation gravitational-wave observatories will observe binary neutron-star mergers with much higher signal-to-noise ratios, over much longer durations and across broader fre…