LIGO and Virgo detected 39 compact binary coalescence events in O3a, including 13 new ones, with black hole binaries up to 150 solar masses and the first significantly asymmetric mass ratios.
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Characterization of transient noise in Advanced LIGO relevant to gravitational wave signal GW150914
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abstract
On September 14, 2015, a gravitational wave signal from a coalescing black hole binary system was observed by the Advanced LIGO detectors. This paper describes the transient noise backgrounds used to determine the significance of the event (designated GW150914) and presents the results of investigations into potential correlated or uncorrelated sources of transient noise in the detectors around the time of the event. The detectors were operating nominally at the time of GW150914. We have ruled out environmental influences and non-Gaussian instrument noise at either LIGO detector as the cause of the observed gravitational wave signal.
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GlitchGAN generates class-conditioned time-domain glitches that pass Gravity Spy classification and show UMAP overlap with real samples while running at high speed.
F-statistic framework analytically maximizes over distance and polarization to enable faster Bayesian inference of compact binary coalescences with a new evidence formulation that matches full frequency-domain results at lower cost.
The LIGO and Virgo collaborations have released the gravitational-wave strain time series data from O1 and O2 observing runs, sampled at 16384 Hz, together with data-quality information through the Gravitational Wave Open Science Center.
Ringdown analysis of GW150914 with overtones measures remnant mass and spin consistent with a Kerr black hole, supporting the no-hair theorem at the 10% level.
A glitch-robust amortized inference framework combining normalizing flows, time-frequency multimodal fusion, and contrastive learning outperforms MCMC for Taiji massive black hole binary parameter estimation under noise contamination.
Bilby-antiglitch jointly models astrophysical signals and quasi-physical glitches to recover true source properties from simulated gravitational wave data contaminated by loud non-Gaussian transients.
DQRbuild toolkit automates data quality vetting for gravitational-wave events, recovering 96% of human-identified issues from O3 with a 24% false alarm rate.
Volunteers propose new glitch categories in LIGO data that connect to instrument states and pose difficulties for existing ML glitch classifiers.
GWTC-2.1 adds eight new high-significance compact binary coalescence events to the prior catalog, extending the observed black hole mass range and including candidates inside the pair-instability mass gap.
Pedagogical derivation from first principles of hierarchical Bayesian inference for population properties of compact binaries in the presence of selection effects, with two worked examples.
citing papers explorer
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GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run
LIGO and Virgo detected 39 compact binary coalescence events in O3a, including 13 new ones, with black hole binaries up to 150 solar masses and the first significantly asymmetric mass ratios.
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Realistic Time-Domain Synthesis of Gravitational-Wave Detector Glitches using Class-Conditional Derivative Generative Adversarial Networks
GlitchGAN generates class-conditioned time-domain glitches that pass Gravity Spy classification and show UMAP overlap with real samples while running at high speed.
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A Robust and Efficient F-statistic-based Framework for Consistent Bayesian Inference of Compact Binary Coalescences
F-statistic framework analytically maximizes over distance and polarization to enable faster Bayesian inference of compact binary coalescences with a new evidence formulation that matches full frequency-domain results at lower cost.
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Open data from the first and second observing runs of Advanced LIGO and Advanced Virgo
The LIGO and Virgo collaborations have released the gravitational-wave strain time series data from O1 and O2 observing runs, sampled at 16384 Hz, together with data-quality information through the Gravitational Wave Open Science Center.
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Testing the no-hair theorem with GW150914
Ringdown analysis of GW150914 with overtones measures remnant mass and spin consistent with a Kerr black hole, supporting the no-hair theorem at the 10% level.
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Robust parameter inference for Taiji via time-frequency contrastive learning and normalizing flows
A glitch-robust amortized inference framework combining normalizing flows, time-frequency multimodal fusion, and contrastive learning outperforms MCMC for Taiji massive black hole binary parameter estimation under noise contamination.
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A parametric signal plus noise inference framework for short duration non-Gaussian noise transients
Bilby-antiglitch jointly models astrophysical signals and quasi-physical glitches to recover true source properties from simulated gravitational wave data contaminated by loud non-Gaussian transients.
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Rapid data quality investigations of gravitational-wave events with the Data Quality Report Builder toolkit
DQRbuild toolkit automates data quality vetting for gravitational-wave events, recovering 96% of human-identified issues from O3 with a 24% false alarm rate.
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Hunting for new glitches in LIGO data using community science
Volunteers propose new glitch categories in LIGO data that connect to instrument states and pose difficulties for existing ML glitch classifiers.
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GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run
GWTC-2.1 adds eight new high-significance compact binary coalescence events to the prior catalog, extending the observed black hole mass range and including candidates inside the pair-instability mass gap.
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Inferring the properties of a population of compact binaries in presence of selection effects
Pedagogical derivation from first principles of hierarchical Bayesian inference for population properties of compact binaries in the presence of selection effects, with two worked examples.