GlitchGAN generates class-conditioned time-domain glitches that pass Gravity Spy classification and show UMAP overlap with real samples while running at high speed.
2021 Class
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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.
citing papers explorer
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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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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.