SIMBAD references

2015ApJ...809...40G - Astrophys. J., 809, 40 (2015/August-8)

Classifying X-ray binaries: a probabilistic approach.

GOPALAN G., VRTILEK S.D. and BORNN L.

Abstract (from CDS):

In X-ray binary star systems consisting of a compact object that accretes material from an orbiting secondary star, there is no straightforward means to decide whether the compact object is a black hole or a neutron star. To assist in this process, we develop a Bayesian statistical model that makes use of the fact that X-ray binary systems appear to cluster based on their compact object type when viewed from a three-dimensional coordinate system derived from X-ray spectral data where the first coordinate is the ratio of counts in the mid- to low-energy band (color 1), the second coordinate is the ratio of counts in the high- to low-energy band (color 2), and the third coordinate is the sum of counts in all three bands. We use this model to estimate the probabilities of an X-ray binary system containing a black hole, non-pulsing neutron star, or pulsing neutron star. In particular, we utilize a latent variable model in which the latent variables follow a Gaussian process prior distribution, and hence we are able to induce the spatial correlation which we believe exists between systems of the same type. The utility of this approach is demonstrated by the accurate prediction of system types using Rossi X-ray Timing Explorer All Sky Monitor data, but it is not flawless. In particular, non-pulsing neutron systems containing "bursters" that are close to the boundary demarcating systems containing black holes tend to be classified as black hole systems. As a byproduct of our analyses, we provide the astronomer with the public R code which can be used to predict the compact object type of XRBs given training data.

Abstract Copyright: © 2015. The American Astronomical Society. All rights reserved.

Journal keyword(s): methods: data analysis - methods: statistical - pulsars: general - stars: black holes - stars: neutron - X-rays: binaries

Simbad objects: 41

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2021.03.04-23:45:22

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