Neural spline flows perform fast posterior inference on 11-dimensional millilensed GW parameters with accuracy comparable to dynesty for most quantities and a 3-day to 0.8-second speedup.
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GP15 maps BBH spectrograms to parameter posteriors via residual networks and normalizing flows, producing results consistent with LVK analyses on GWTC-2.1 and GWTC-3 events while running in seconds.
Baselines of 8-11 ms light travel time for two CE detectors provide a reasonable compromise for BBH sky localization, with third detectors eliminating multimodality for most or all events.
citing papers explorer
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Parameter inference of millilensed gravitational waves using neural spline flows
Neural spline flows perform fast posterior inference on 11-dimensional millilensed GW parameters with accuracy comparable to dynesty for most quantities and a 3-day to 0.8-second speedup.
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Assessment of normalizing flows for parameter estimation on time-frequency representations of gravitational-wave data
GP15 maps BBH spectrograms to parameter posteriors via residual networks and normalizing flows, producing results consistent with LVK analyses on GWTC-2.1 and GWTC-3 events while running in seconds.
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Not too close! Evaluating the impact of the baseline on the localization of binary black holes by next-generation gravitational-wave detectors
Baselines of 8-11 ms light travel time for two CE detectors provide a reasonable compromise for BBH sky localization, with third detectors eliminating multimodality for most or all events.