English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

A Bayesian parameter estimation approach to pulsar time-of-arrival analysis

MPS-Authors
/persons/resource/persons42125

Messenger,  C.
Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)

1103.0518.pdf
(Preprint), 469KB

CQG_28_5_055001.pdf
(Any fulltext), 405KB

Supplementary Material (public)
There is no public supplementary material available
Citation

Messenger, C., Lommen, A., Demorest, P., & Ransom, S. (2011). A Bayesian parameter estimation approach to pulsar time-of-arrival analysis. Classical and quantum gravity, 28(5): 055001. doi:10.1088/0264-9381/28/5/055001.


Cite as: https://hdl.handle.net/11858/00-001M-0000-000F-090D-8
Abstract
The increasing sensitivities of pulsar timing arrays to ultra-low frequency (nHz) gravitational waves promises to achieve direct gravitational wave detection within the next 5-10 years. While there are many parallel efforts being made in the improvement of telescope sensitivity, the detection of stable millisecond pulsars and the improvement of the timing software, there are reasons to believe that the methods used to accurately determine the time-of-arrival (TOA) of pulses from radio pulsars can be improved upon. More specifically, the determination of the uncertainties on these TOAs, which strongly affect the ability to detect GWs through pulsar timing, may be unreliable. We propose two Bayesian methods for the generation of pulsar TOAs starting from pulsar "search-mode" data and pre-folded data. These methods are applied to simulated toy-model examples and in this initial work we focus on the issue of uncertainties in the folding period. The final results of our analysis are expressed in the form of posterior probability distributions on the signal parameters (including the TOA) from a single observation.