Measuring glitch recoveries and braking indices with Bayesian model selection
Yang Liu, Michael J. Keith, Danai Antonopoulou, Patrick Weltevrede,, Benjamin Shaw, Benjamin W. Stappers, Andrew G. Lyne, Mitchell B. Mickaliger,, Avishek Basu

TL;DR
This paper analyzes 157 glitches in 35 pulsars using Bayesian model selection to understand post-glitch recoveries, revealing correlations and estimating glitch recurrence times, with implications for pulsar rotational evolution.
Contribution
It introduces a Bayesian approach to select the best model for pulsar glitch recoveries and provides new insights into glitch parameters and pulsar braking indices.
Findings
Strong correlation between interglitch otot{ u}| and ot{ u}
The ratio |\u2206 ot{ u}_p/otot{ u}| estimates glitch recurrence times
Pulsars with large glitches tend to have braking index n > 3
Abstract
For a selection of 35 pulsars with large spin-up glitches (), which are monitored by the Jodrell Bank Observatory, we analyse 157 glitches and their recoveries. All parameters are measured consistently and we choose the best model to describe the post-glitch recovery based on Bayesian evidence. We present updated glitch epochs, sizes, changes of spin down rate, exponentially recovering components (amplitude and corresponding timescale) when present, as well as pulsars' second frequency derivatives and their glitch associated changes if detected. We discuss the different observed styles of post-glitch recovery as well as some particularly interesting sources. Several correlations are revealed between glitch parameters and pulsar spin parameters, including a very strong correlation between a pulsar's interglitch and , as well as…
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