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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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.
Parametric models incorporating waveform phase and amplitude uncertainties mitigate systematic errors in gravitational wave parameter estimation, producing consistent results across models and raw/deglitched data for events like GW191109_010717 and GW200129_065458.
VIGILant applies tree-based models and a ResNet CNN to classify Virgo O3b glitches with 98% accuracy and has been deployed for daily use with an interactive dashboard.
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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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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Mitigating Systematic Errors in Parameter Estimation of Binary Black Hole Mergers in O1-O3 LIGO-Virgo Data
Parametric models incorporating waveform phase and amplitude uncertainties mitigate systematic errors in gravitational wave parameter estimation, producing consistent results across models and raw/deglitched data for events like GW191109_010717 and GW200129_065458.
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VIGILant: an automatic classification pipeline for glitches in the Virgo detector
VIGILant applies tree-based models and a ResNet CNN to classify Virgo O3b glitches with 98% accuracy and has been deployed for daily use with an interactive dashboard.
- Inferring the properties of a population of compact binaries in presence of selection effects