Bayesian Solar Wind Modeling with Pulsar Timing Arrays

Authors

• Jeffrey S. Hazboun, University of Washington-Bothell
• Joseph Simon, University of Colorado Boulder
• Dustin R. Madison, University of the PacificFollow
• Zaven Arzoumanian, NASA Goddard Space Flight Center
• H. Thankful Cromartie, Cornell Center for Astrophysics and Planetary Science
• Kathryn Crowter, The University of British Columbia
• Megan E. Decesar, George Mason University
• Paul B. Demorest, National Radio Astronomy Observatory Socorro
• Timothy Dolch, Hillsdale College
• Justin A. Ellis, Infinia ML
• Robert D. Ferdman, University of East Anglia
• Elizabeth C. Ferrara, University of Maryland, College Park
• Emmanuel Fonseca, West Virginia University
• Peter A. Gentile, West Virginia University
• Glenn Jones, Rigetti Computing
• Megan L. Jones, University of Wisconsin-Milwaukee
• Michael T. Lam, Rochester Institute of Technology
• Lina Levin, The University of Manchester
• Duncan R. Lorimer, West Virginia University
• Ryan S. Lynch, Green Bank Observatory
• Maura A. McLaughlin, West Virginia University
• Cherry Ng, Dunlap Institute for Astronomy & Astrophysics

Document Type

Article

Publication Title

Astrophysical Journal

Department

Physics

ISSN

15384357

Volume

929

Issue

1

DOI

10.3847/1538-4357/ac5829

First Page

1

Last Page

11

Publication Date

4-11-2022

Abstract

Using Bayesian analyses we study the solar electron density with the NANOGrav 11 yr pulsar timing array (PTA) data set. Our model of the solar wind is incorporated into a global fit starting from pulse times of arrival. We introduce new tools developed for this global fit, including analytic expressions for solar electron column densities and open source models for the solar wind that port into existing PTA software. We perform an ab initio recovery of various solar wind model parameters. We then demonstrate the richness of information about the solar electron density, n E , that can be gleaned from PTA data, including higher order corrections to the simple 1/r 2 model associated with a free-streaming wind (which are informative probes of coronal acceleration physics), quarterly binned measurements of n E and a continuous time-varying model for n E spanning approximately one solar cycle period. Finally, we discuss the importance of our model for chromatic noise mitigation in gravitational-wave analyses of pulsar timing data and the potential of developing synergies between sophisticated PTA solar electron density models and those developed by the solar physics community.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Recommended Citation

Hazboun, Jeffrey S.; Simon, Joseph; Madison, Dustin R.; Arzoumanian, Zaven; Cromartie, H. Thankful; Crowter, Kathryn; Decesar, Megan E.; Demorest, Paul B.; Dolch, Timothy; Ellis, Justin A.; Ferdman, Robert D.; Ferrara, Elizabeth C.; Fonseca, Emmanuel; Gentile, Peter A.; Jones, Glenn; Jones, Megan L.; Lam, Michael T.; Levin, Lina; Lorimer, Duncan R.; Lynch, Ryan S.; McLaughlin, Maura A.; and Ng, Cherry, "Bayesian Solar Wind Modeling with Pulsar Timing Arrays" (2022). Pacific Faculty Work. 197.
https://scholarlycommons.pacific.edu/all-faculty/197