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.
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A meta-learning framework with ALNP, SOM clustering, and mixture density models improves AGN light-curve reconstruction by 60-70% and parameter recovery on simulated and ZTF data.
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
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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.
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A Meta-Learning Framework for Multitask Reverberation Mapping in Active Galactic Nuclei
A meta-learning framework with ALNP, SOM clustering, and mixture density models improves AGN light-curve reconstruction by 60-70% and parameter recovery on simulated and ZTF data.
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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.