4.2k citations · 16.9k across the 118 of their papers we have counts for
120 papers
Scalable and sequential inference of the neutron star equation of state with the Einstein Telescope
Thibeau Wouters, Thomas C. K. Ng, Hauke Koehn +4
Future gravitational-wave observatories such as the Einstein Telescope will detect tens of thousands of binary neutron star mergers per year, making gravitational waves a dominant…
Binary neutron stars in the next-generation era: Multi-messenger detection prospects and constraints on the equation of state, mass distribution, and cosmology
Hauke Koehn, Thibeau Wouters, Gilad Sadeh +5
Next-generation gravitational-wave (GW) observatories will provide crucial insights into the nature of neutron star (NS) matter and the cosmological expansion history. We estimate…
Detecting Tidal Resonances in Binary Neutron Stars
Fabian Gittins, Harsh Narola, Thibeau Wouters +3
As a binary neutron star inspirals due to the emission of gravitational waves, the rising tidal frequency resonantly excites vibrational modes. These oscillations are seismological…
Mitigating Systematic Errors in Parameter Estimation of Binary Black Hole Mergers in O1-O3 LIGO-Virgo Data
Sumit Kumar, Max Melching, Frank Ohme +3
Systematic errors in the parameter estimation (PE) of gravitational wave (GW) mergers can arise from various sources, including waveform systematics, noise mischaracterization, dat…
GW231123: Overlapping Gravitational Wave Signals?
Qian Hu, Harsh Narola, Jef Heynen +4
The recently discovered gravitational wave event GW231123 was interpreted as the merger of two black holes with a total mass of 190-265 , making it the heaviest such merge…
Incorporating neutron star physics into gravitational wave inference with physics-informed priors using normalizing flows
Thibeau Wouters, Peter T. H. Pang, Tim Dietrich +1
Bayesian inference, widely used in gravitational-wave parameter estimation, depends on the choice of priors, i.e., on our previously existing knowledge. However, to investigate neu…
Revealing tensions in neutron star observations with pressure anisotropy
Peter T. H. Pang, Stephanie M. Brown, Thibeau Wouters +1
Pressure isotropy, i.e., equality between radial and tangential pressure, is often assumed when studying neutron stars. However, mechanisms such as pion/kaon condensation, magnetic…
Pre-Merger Detection and Characterization of Inspiraling Binary Neutron Stars Derived from Neural Posterior Estimation
Wouter van Straalen, Alex Kolmus, Justin Janquart +1
As the sensitivity of the international gravitational wave detector network increases, observing binary neutron star signals will become more common. Moreover, since these signals…
ler: LVK (LIGO-Virgo-KAGRA collaboration) event (compact-binary mergers) rate calculator and simulator
Hemantakumar Phurailatpam, Anupreeta More, Harsh Narola +6
ler is a Python package for simulating compact-binary gravitational-wave populations and estimating detectable event rates for current and future LIGO-Virgo-KAGRA detector networks…
Tests of General Relativity with GW230529: a neutron star merging with a lower mass-gap compact object
Elise M. Sänger, Soumen Roy, Michalis Agathos +16
On May 29, 2023, the LIGO Livingston observatory detected the gravitational-wave signal GW230529_181500 from the merger of a neutron star with a lower mass-gap compact object. Its…
Possible Causes of False General Relativity Violations in Gravitational Wave Observations
Anuradha Gupta, K. G. Arun, Enrico Barausse +40
General relativity (GR) has proven to be a highly successful theory of gravity since its inception. The theory has thrivingly passed numerous experimental tests, predominantly in w…
Robust parameter estimation within minutes on gravitational wave signals from binary neutron star inspirals
Thibeau Wouters, Peter T. H. Pang, Tim Dietrich +1
The gravitational waves emitted by binary neutron star inspirals contain information on nuclear matter above saturation density. However, extracting this information and conducting…
Tuning neural posterior estimation for gravitational wave inference
Alex Kolmus, Justin Janquart, Tomasz Baka +3
Modern simulation-based inference techniques use neural networks to solve inverse problems efficiently. One notable strategy is neural posterior estimation (NPE), wherein a neural…
Uncovering faint lensed gravitational-wave signals and reprioritizing their follow-up analysis using galaxy lensing forecasts with detected counterparts
Leo C. Y. Ng, Justin Janquart, Hemantakumar Phurailatpam +4
Like light, gravitational waves can be gravitationally lensed by massive astrophysical objects. Strong gravitational lensing by galaxies and galaxy clusters is anticipated to becom…
Generating Higher Order Modes from Binary Black Hole mergers with Machine Learning
Tim Grimbergen, Stefano Schmidt, Chinmay Kalaghatgi +1
We introduce a machine learning model designed to rapidly and accurately predict the time domain gravitational wave emission of non-precessing binary black hole coalescences, incor…
cDVGAN: One Flexible Model for Multi-class Gravitational Wave Signal and Glitch Generation
Tom Dooney, Lyana Curier, Daniel Tan +3
Simulating realistic time-domain observations of gravitational waves (GWs) and GW detector glitches can help in advancing GW data analysis. Simulated data can be used in downstream…
Detection of anomalies amongst LIGO's glitch populations with autoencoders
Paloma Laguarta, Robin van der Laag, Melissa Lopez +9
Gravitational-wave (GW) interferometers are able to detect a change in distance of 1/10,000th the size of a proton. Such sensitivity leads to large appearance rates of non-G…
Comparing gravitational waveform models for binary black hole mergers through a hypermodels approach
Anna Puecher, Anuradha Samajdar, Gregory Ashton +2
The inference of source parameters from gravitational-wave signals relies on theoretical models that describe the emitted waveform. Different model assumptions on which the computa…
Relative binning for complete gravitational-wave parameter estimation with higher-order modes and precession, and applications to lensing and third-generation detectors
Harsh Narola, Justin Janquart, Quirijn Meijer +2
Once a gravitational wave signal is detected, the measurement of its source parameters is important to achieve various scientific goals. This is done through Bayesian inference, wh…
How well can modified gravitational wave propagation be constrained with strong lensing?
Harsh Narola, Justin Janquart, Leïla Haegel +3
Strong gravitational lensing produces multiple images of a gravitational wave (GW) signal, which can be observed by detectors as time-separated copies of the same event. It has bee…
Probing Quarkyonic Matter in Neutron Stars with the Bayesian Nuclear-Physics Multi-Messenger Astrophysics Framework
Peter T. H. Pang, Lars Sivertsen, Rahul Somasundaram +5
The interior of neutron stars contains matter at the highest densities realized in our Universe. Interestingly, theoretical studies of dense matter, in combination with the existen…
The Return of GOLUM: Improving Distributed Joint Parameter Estimation for Strongly-Lensed Gravitational Waves
Justin Janquart, K. Haris, Otto A. Hannuksela +1
Owing to the forecasted improved sensitivity of ground-based gravitational-wave detectors, new research avenues will become accessible. This is the case for gravitational-wave stro…
Revealing the strength of three-nucleon interactions with the Einstein Telescope
Henrik Rose, Nina Kunert, Tim Dietrich +5
Three-nucleon forces are crucial for the accurate description of nuclear systems, including dense matter probed in neutron stars. We explore nuclear Hamiltonians that reproduce two…
Normalizing flows as an avenue to study overlapping gravitational wave signals
Jurriaan Langendorff, Alex Kolmus, Justin Janquart +1
Due to its speed after training, machine learning is often envisaged as a solution to a manifold of the issues faced in gravitational-wave astronomy. Demonstrations have been given…