Impact of quasi-periodic and steep-spectrum timing noise on the measurement of pulsar timing parameters

Abstract

Timing noise in pulsars is often modelled with a Fourier-basis Gaussian process that follows a power law with periodic boundary conditions on the observation time, $T_\mathrm{span}$. However the actual noise processes can extend well below $1/T_\mathrm{span}$, and many pulsars are known to exhibit quasi-periodic timing noise. In this paper we investigate several adaptions that try to account for these differences between the observed behaviour and the simple power-law model. Firstly, we propose to include an additional term that models the quasi-periodic spin-down variations known to be present in many pulsars. Secondly, we show that a Fourier basis of $1/2T_\mathrm{span}$ can be more suited for estimating long term timing parameters such as the spin frequency second derivative (F2), and is required when the exponent of the power spectrum is greater than ~4. We also implement a Bayesian version of the generalised least squares `Cholesky' method which has different limitations at low frequency, but find that there is little advantage over Fourier-basis methods. We apply our quasi-periodic spin down model to a sample of pulsars with known spin-down variations and show that this improves parameter estimation of F2 and proper motion for the most pathological cases, but in general the results are consistent with a power-law model. The models are all made available through the run_enterprise software package.