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Bayesian Solar Wind Modeling with Pulsar Timing Arrays
by
Fonseca, Emmanuel
, Hazboun, Jeffrey S
, Crowter, Kathryn
, Jones, Megan L
, Levin, Lina
, Ferrara, Elizabeth C
, Cromartie, H. Thankful
, Jones, Glenn
, Lynch, Ryan S
, Arzoumanian, Zaven
, Ellis, Justin A
, Swiggum, Joseph K
, Nice, David J
, Pennucci, Timothy T
, Spiewak, Renée
, Lam, Michael T
, DeCesar, Megan E
, Ray, Paul S
, Demorest, Paul B
, Lorimer, Duncan R
, Ng, Cherry
, McLaughlin, Maura A
, Ransom, Scott M
, Zhu, Weiwei
, Madison, Dustin R
, Stairs, Ingrid H
, Simon, Joseph
, Gentile, Peter A
, Dolch, Timothy
, Stovall, Kevin
, Ferdman, Robert D
, The NANOGrav Collaboration , The NANOGrav Collaboration
in
Arrays
/ Bayesian analysis
/ Electron density
/ Electrons
/ Gravitational waves
/ Physics
/ Pulsars
/ Solar cycle
/ Solar electrons
/ Solar physics
/ Solar wind
/ Solar wind models
/ Wave analysis
2022
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Bayesian Solar Wind Modeling with Pulsar Timing Arrays
by
Fonseca, Emmanuel
, Hazboun, Jeffrey S
, Crowter, Kathryn
, Jones, Megan L
, Levin, Lina
, Ferrara, Elizabeth C
, Cromartie, H. Thankful
, Jones, Glenn
, Lynch, Ryan S
, Arzoumanian, Zaven
, Ellis, Justin A
, Swiggum, Joseph K
, Nice, David J
, Pennucci, Timothy T
, Spiewak, Renée
, Lam, Michael T
, DeCesar, Megan E
, Ray, Paul S
, Demorest, Paul B
, Lorimer, Duncan R
, Ng, Cherry
, McLaughlin, Maura A
, Ransom, Scott M
, Zhu, Weiwei
, Madison, Dustin R
, Stairs, Ingrid H
, Simon, Joseph
, Gentile, Peter A
, Dolch, Timothy
, Stovall, Kevin
, Ferdman, Robert D
, The NANOGrav Collaboration , The NANOGrav Collaboration
in
Arrays
/ Bayesian analysis
/ Electron density
/ Electrons
/ Gravitational waves
/ Physics
/ Pulsars
/ Solar cycle
/ Solar electrons
/ Solar physics
/ Solar wind
/ Solar wind models
/ Wave analysis
2022
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Do you wish to request the book?
Bayesian Solar Wind Modeling with Pulsar Timing Arrays
by
Fonseca, Emmanuel
, Hazboun, Jeffrey S
, Crowter, Kathryn
, Jones, Megan L
, Levin, Lina
, Ferrara, Elizabeth C
, Cromartie, H. Thankful
, Jones, Glenn
, Lynch, Ryan S
, Arzoumanian, Zaven
, Ellis, Justin A
, Swiggum, Joseph K
, Nice, David J
, Pennucci, Timothy T
, Spiewak, Renée
, Lam, Michael T
, DeCesar, Megan E
, Ray, Paul S
, Demorest, Paul B
, Lorimer, Duncan R
, Ng, Cherry
, McLaughlin, Maura A
, Ransom, Scott M
, Zhu, Weiwei
, Madison, Dustin R
, Stairs, Ingrid H
, Simon, Joseph
, Gentile, Peter A
, Dolch, Timothy
, Stovall, Kevin
, Ferdman, Robert D
, The NANOGrav Collaboration , The NANOGrav Collaboration
in
Arrays
/ Bayesian analysis
/ Electron density
/ Electrons
/ Gravitational waves
/ Physics
/ Pulsars
/ Solar cycle
/ Solar electrons
/ Solar physics
/ Solar wind
/ Solar wind models
/ Wave analysis
2022
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Journal Article
Bayesian Solar Wind Modeling with Pulsar Timing Arrays
2022
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Overview
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.
Publisher
IOP Publishing
Subject
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