Pulsar Glitch Detection with a Hidden Markov Model
A Melatos, LM Dunn, S Suvorova, W Moran, RJ Evans
The Astrophysical Journal | IOP Publishing | Published : 2020
Pulsar timing experiments typically generate a phase-connected timing solution from a sequence of times of arrival (TOAs) by absolute pulse numbering, i.e., by fitting an integer number of pulses between TOAs in order to minimize the residuals with respect to a parameterized phase model. In this observing mode, rotational glitches are discovered, when the residuals of the no-glitch phase model diverge after some epoch, and glitch parameters are refined by Bayesian follow-up. Here, we present an alternative, complementary approach which tracks the pulse frequency f and its time derivative f with a hidden Markov model (HMM), whose dynamics include stochastic spin wandering (timing noise) and i..View full abstract
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Awarded by Australian Research Council
The authors thank Stefan Oslowski and Marcus Lower for pointing out important references and for providing access to data from the Molonglo Synthesis Radio Telescope for experimentation while developing the HMM algorithm. The PSR J0835-4510 data analyzed in Section 7 are described by Sarkissian et al. (2017a, 2017b). This research was supported by the Australian Research Council Centre of Excellence for Gravitational Wave Discovery (OzGrav), grant No. CE170100004.