The NANOGrav 12.5-year Data Set: Chromatic Noise Characterization & Mitigation with Time-Domain Kernels
Abstract
Pulsar timing arrays (PTAs) have recently entered the detection era, quickly moving beyond the goal of simply improving sensitivity at the lowest frequencies for the sake of observing the stochastic gravitational wave background (GWB), and focusing on its accurate spectral characterization. While all PTA collaborations around the world use Fourier-domain Gaussian processes to model the GWB and intrinsic long time-correlated (red) noise, techniques to model the time-correlated radio frequency-dependent (chromatic) processes have varied from collaboration to collaboration. Here we test a new class of models for PTA data, Gaussian processes based on time-domain kernels that model the statistics of the chromatic processes starting from the covariance matrix. As we will show, these models can be effectively equivalent to Fourier-domain models in mitigating chromatic noise. This work presents a method for Bayesian model selection across the various choices of kernel as well as deterministic chromatic models for non-stationary chromatic events and the solar wind. As PTAs turn towards high frequency (>1/yr) sensitivity, the size of the basis used to model these processes will need to increase, and these time-domain models present some computational efficiencies compared to Fourier-domain models.
Keywords
Cite
@article{arxiv.2511.22597,
title = {The NANOGrav 12.5-year Data Set: Chromatic Noise Characterization & Mitigation with Time-Domain Kernels},
author = {Jeffrey S. Hazboun and Joseph Simon and Jeremy Baier and Bjorn Larsen and Daniel J. Oliver and Paul T. Baker and Bence Bécsy and Siyuan Chen and Alberto Diaz Hernandez and Justin A. Ellis and A. Miguel Holgado and Kristina Islo and Aaron Johnson and Andrew R. Kaiser and Nima Laal and Alexander McEwen and Nihan S. Pol and Joey Shapiro Key and Min Young Kim and Matthew Samson and Brent J. Shapiro-Albert and Jerry P. Sun and Stephen R. Taylor and Caitlin A. Witt and Jeremy Volpe and Christine Ye and Harsha Blumer and Paul R. Brook and Shami Chatterjee and James M. Cordes and Fronefield Crawford and H. Thankful Cromartie and Megan E. DeCesar and Paul B. Demorest and Timothy Dolch and Robert D. Ferdman and Elizabeth C. Ferrara and William Fiore and Emmanuel Fonseca and Nathan Garver-Daniels and Peter A. Gentile and Deborah C. Good and Ross J. Jennings and Megan L. Jones and David L. Kaplan and Michael T. Lam and T. Joseph W. Lazio and Duncan R. Lorimer and Jing Luo and Ryan S. Lynch and Dustin R. Madison and Maura A. McLaughlin and Chiara M. F. Mingarelli and Cherry Ng and David J. Nice and Timothy T. Pennucci and Scott M. Ransom and Paul S. Ray and Xavier Siemens and Renée Spiewak and Ingrid H. Stairs and Daniel R. Stinebring and Kevin Stovall and Joseph K. Swiggum and Jacob E. Turner and Michele Vallisneri and Sarah J. Vigeland},
journal= {arXiv preprint arXiv:2511.22597},
year = {2025}
}
Comments
30 pages, 12 Figures, 6 Tables