Customized chromatic noise models for 67 pulsars detect non-dispersive delays in 21 cases, alter achromatic noise inferences in 19, and enable solar wind density estimates over 1.5 cycles.
Targeted search for continuous gravitational waves: Bayesian versus maximum-likelihood statistics
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
abstract
We investigate the Bayesian framework for detection of continuous gravitational waves (GWs) in the context of targeted searches, where the phase evolution of the GW signal is assumed to be known, while the four amplitude parameters are unknown. We show that the orthodox maximum-likelihood statistic (known as F-statistic) can be rediscovered as a Bayes factor with an unphysical prior in amplitude parameter space. We introduce an alternative detection statistic ("B-statistic") using the Bayes factor with a more natural amplitude prior, namely an isotropic probability distribution for the orientation of GW sources. Monte-Carlo simulations of targeted searches show that the resulting Bayesian B-statistic is more powerful in the Neyman-Pearson sense (i.e. has a higher expected detection probability at equal false-alarm probability) than the frequentist F-statistic.
verdicts
UNVERDICTED 3representative citing papers
FIREFLY accelerates multi-mode GW ringdown analysis by analytically marginalizing QNM amplitudes and phases via Bayesian principles and importance sampling.
Customized chromatic noise models applied to NANOGrav 15 yr data raise the Bayes factor for Hellings-Downs GWB correlations by a factor of ~8, lower the amplitude to 2.1e-15, and increase the spectral index to 3.5.
citing papers explorer
-
The NANOGrav 15 yr Data Set: Customized Chromatic Noise Models
Customized chromatic noise models for 67 pulsars detect non-dispersive delays in 21 cases, alter achromatic noise inferences in 19, and enable solar wind density estimates over 1.5 cycles.
-
A practical Bayesian method for gravitational-wave ringdown analysis with multiple modes
FIREFLY accelerates multi-mode GW ringdown analysis by analytically marginalizing QNM amplitudes and phases via Bayesian principles and importance sampling.
-
The NANOGrav 15 yr Data Set: Impacts of Customized Chromatic Noise Models on Gravitational Wave Analyses
Customized chromatic noise models applied to NANOGrav 15 yr data raise the Bayes factor for Hellings-Downs GWB correlations by a factor of ~8, lower the amplitude to 2.1e-15, and increase the spectral index to 3.5.