Detecting and modeling neutron stars glitches with Bayesian techniques

Abstract

Glitches are sudden, sharp increases in the spin frequencies of pulsars. A fraction of this change is recovered in subsequent relaxation, sometimes consists of exponential transients. Glitches are commonly attributed to the transfer of angular momentum between distinct components of the pulsar, namely the star's crust and the interior neutron superfluid. Therefore, the study of glitches offer the opportunity to better understand dense nuclear matter and the inner structure of pulsars. With pulsar timing techniques, 679 glitches from 226 pulsars have been recorded in the Jodrell Bank Observatory (JBO) glitch catalogue. The work in this thesis presented a systematic pipeline for measuring pulsar glitches and associated recoveries based on Bayesian parameter inference and model selection. All methods have been implemented in the \textsc{run\_enterprise} Bayesian framework. Based on this, we study the statistics of pulsar glitches with the JBO database. For a selection of 35 pulsars with large spin-up glitches ($\Delta{\nu}/\nu\geq10^{-6}$), which are monitored by the JBO, 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 $|\ddot{\nu}|$ (the $\ddot{\nu}$ between glitches) 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 $n$ in the range of $10-100$, which is consistent with previous works, 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 ($\lesssim10^{4}\;\mathrm{yr}$), which may be expected to display $n\sim3$. We also discuss the statistics of $\ddot{\nu}$ in the population of pulsars. We model $\ddot{\nu}$ as the combination of a Gaussian term describing the statistic of pulsar population and a power-law scaling relationship with $\nu$ and $\dot{\nu}$ describing the glitch recovery process. The effect of glitch recovery is more pronounced in younger pulsars, while the Gaussian term, believed to result from stochastic processes, has a mean consistent with zero and a large variance, playing a more significant role in older pulsars. This variance is independent of the observation time span on the order of decades, suggesting $\dot{\nu}$ evolves at constant rate on such time scales. This variance does not seem to be the same process as the short term timing noise measured in previous works.

Date of Award	6 Jan 2025
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Michael Keith (Supervisor) & Patrick Weltevrede (Supervisor)