Measuring glitch recoveries and braking indices with Bayesian model selection

Abstract

Abstract For a selection of 35 pulsars with large spin-up glitches (Δν/ν ≥ 10−6), 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 $|\ddot{\nu }|$ and $\dot{\nu }$, as well as between the glitch-induced spin-down rate change $\Delta \dot{\nu }_{\rm p}$ that does not relax exponentially and $\dot{\nu }$. We find that the ratio $\left|\Delta \dot{\nu }_{\mathrm{p}}/\ddot{\nu }\right|$ can be used as an estimate of glitch recurrence times, especially for those pulsars for which there are indications of a characteristic glitch size and interglitch waiting time. We calculate the interglitch braking index n and find that pulsars with large glitches typically have n greater than 3, suggesting that internal torques dominate the rotational evolution between glitches. The external torque, e.g. from electromagnetic dipole radiation, could dominate the observed $\ddot{\nu }$ for the youngest pulsars (≲ 104 yr), which may be expected to display n ∼ 3.