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The NANOGrav 15 yr Dataset: Customized Chromatic Noise Models

  • Bjorn Larsen
  • , Jeremy G. Baier
  • , Daniel J. Oliver
  • , Kalista Wayt
  • , Yu Ting Chang
  • , Jeffrey S. Hazboun
  • , Chiara M.F. Mingarelli
  • , Joseph Simon
  • , Matthew T. Miles
  • , Gabriella Agazie
  • , Akash Anumarlapudi
  • , Anne M. Archibald
  • , Zaven Arzoumanian
  • , Paul T. Baker
  • , Paul R. Brook
  • , H. Thankful Cromartie
  • , Kathryn Crowter
  • , Megan E. DeCesar
  • , Paul B. Demorest
  • , Timothy Dolch
  • Elizabeth C. Ferrara, William Fiore, Emmanuel Fonseca, Gabriel E. Freedman, Nate Garver-Daniels, Peter A. Gentile, Joseph Glaser, Deborah C. Good, Ross J. Jennings, Megan L. Jones, David L. Kaplan, Matthew Kerr, Michael T. Lam, Duncan R. Lorimer, Jing Luo, Ryan S. Lynch, Alexander McEwen, Maura A. McLaughlin, Natasha McMann, Bradley W. Meyers, Cherry Ng, David J. Nice, Timothy T. Pennucci, Benetge B.P. Perera, Nihan S. Pol, Henri A. Radovan, Scott M. Ransom, Paul S. Ray, Ann Schmiedekamp, Carl Schmiedekamp, Brent J. Shapiro-Albert, Ingrid H. Stairs, Kevin Stovall, Abhimanyu Susobhanan, Joseph K. Swiggum, Haley M. Wahl
  • Yale University
  • Oregon State University
  • Simons Foundation
  • University of Colorado Boulder
  • Vanderbilt University
  • University of Wisconsin-Milwaukee
  • University of North Carolina at Chapel Hill
  • Newcastle University
  • NASA Goddard Space Flight Center
  • Widener University
  • University of Birmingham
  • National Research Council
  • University of British Columbia
  • George Mason University
  • National Science Foundation
  • Hillsdale College
  • Eureka Scientific, Inc.
  • University of Maryland, College Park
  • West Virginia University
  • Naval Research Laboratory
  • SETI Institute
  • Rochester Institute of Technology
  • University of Toronto
  • Curtin University
  • Lafayette College
  • Eötvös Loránd University
  • Texas Tech University
  • University of Puerto Rico
  • Pennsylvania State University
  • Indian Institute of Science Education and Research Thiruvananthapuram

Research output: Contribution to journalArticlepeer-review

Abstract

Pulsar timing arrays (PTAs) conduct low-frequency gravitational-wave (GW) searches, which require comprehensive accounting of various noise sources to achieve robust results. Interstellar propagation effects (e.g., dispersion and scattering) are especially complex noise sources, introducing chromatic delays that can reduce sensitivity to GWs and bias their inference if left unmodeled. These delays also strongly depend on the line-of-sight properties to each individual pulsar. To address this, we present customized chromatic noise models for 67 pulsars in the NANOGrav 15 yr dataset. These models are selected from an expanded suite of Gaussian processes to simultaneously characterize multiple types of chromatic delays and are tailored to each pulsar’s dataset. Alongside probing the interstellar medium, we use these models to infer the solar wind electron density over the course of ∼1.5 solar cycles. We also find evidence for nondispersive chromatic delays in 21 out of 67 NANOGrav pulsars. After applying our chromatic models, we observe significant impacts on the inference of achromatic noise in 19 out of 67 pulsars, finding in several cases that a previously significant achromatic noise process can be partially or entirely described as chromatic. These results demonstrate that refined noise modeling is essential to enhance the sensitivity and accuracy of low-frequency GW searches with PTAs.

Original languageEnglish
Article number29
JournalAstrophysical Journal
Volume1005
Issue number1
DOIs
StatePublished - Jul 1 2026

Keywords

  • Gaussian Processes regression (1930)
  • Gravitational wave detectors (676)
  • Gravitational waves (678)
  • Interstellar medium (847)
  • Millisecond pulsars (1062)
  • Solar wind (1534)

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