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Free keywords:
Astrophysics, Solar and Stellar Astrophysics, astro-ph.SR, Astrophysics, High Energy Astrophysical Phenomena, astro-ph.HE
Abstract:
We build a framework using tools from Bayesian data analysis to evaluate
models explaining the periodic variations in spin-down and beam-width of PSR
B1828-11. The available data consists of the time averaged spin-down rate,
which displays a distinctive double-peaked modulation, and measurements of the
beam-width. Two concepts exist in the literature that are capable of explaining
these variations; we will formulate predictive models from these and
quantitatively compare them. The first concept is phenomenological and
stipulates that the magnetosphere undergoes periodic switching between two
meta-stable states as first suggested by Lyne et al. (2010). The second
concept, precession, was first considered as a candidate for the modulation of
B1828-11 by Stairs et al. (2000). We quantitatively compare models built from
these concepts using a Bayesian odds-ratio. Because the phenomenological
switching model itself was informed by this data in the first place, it is
difficult to specify appropriate parameter- space priors that can be trusted
for an unbiased model comparison. Therefore we first perform a parameter
estimation using the spin-down data, and then use the resulting posterior
distributions as priors for model comparison on the beam-width data. We find
that a precession model with a simple circular Gaussian beam geometry fails to
appropriately describe the data, while allowing for a more general beam
geometry results in a model that seems strongly preferred by the data over a
switching model.
