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Bayesian inference for pulsar timing models | | Sarah J. Vigeland
; Michele Vallisneri
; | | Date: |
9 Oct 2013 | | Abstract: | The extremely regular, periodic radio emission from millisecond pulsars make
them useful tools for studying neutron star astrophysics, general relativity,
and low-frequency gravitational waves. These studies require that the observed
pulse time of arrivals are fit to complicated timing models that describe
numerous effects such as the astrometry of the source, the evolution of the
pulsar’s spin, the presence of a binary companion, and the propagation of the
pulses through the interstellar medium. In this paper, we discuss the benefits
of using Bayesian inference to obtain these timing solutions. These include the
validation of linearized least-squares model fits when they are correct, and
the proper characterization of parameter uncertainties when they are not; the
incorporation of prior parameter information and of models of correlated noise;
and the Bayesian comparison of alternative timing models. We describe our
computational setup, which combines the timing models of tempo2 with the
nested-sampling integrator MultiNest. We compare the timing solutions generated
using Bayesian inference and linearized least-squares for three pulsars:
B1953+29, J2317+1439, and J1640+2224, which demonstrate a variety of the
benefits that we posit. | | Source: | arXiv, 1310.2606 | | Services: | Forum | Review | PDF | Favorites | |
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