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Identifying and mitigating noise sources in precision pulsar timing data sets

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 Added by Boris Goncharov
 Publication date 2020
  fields Physics
and research's language is English




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Pulsar timing array projects measure the pulse arrival times of millisecond pulsars for the primary purpose of detecting nanohertz-frequency gravitational waves. The measurements include contributions from a number of astrophysical and instrumental processes, which can either be deterministic or stochastic. It is necessary to develop robust statistical and physical models for these noise processes because incorrect models diminish sensitivity and may cause a spurious gravitational wave detection. Here we characterise noise processes for the 26 pulsars in the second data release of the Parkes Pulsar Timing Array using Bayesian inference. In addition to well-studied noise sources found previously in pulsar timing array data sets such as achromatic timing noise and dispersion measure variations, we identify new noise sources including time-correlated chromatic noise that we attribute to variations in pulse scattering. We also identify exponential dip events in four pulsars, which we attribute to magnetospheric effects as evidenced by pulse profile shape changes observed for three of the pulsars. This includes an event in PSR J1713$+$0747, which had previously been attributed to interstellar propagation. We present noise models to be used in searches for gravitational waves. We outline a robust methodology to evaluate the performance of noise models and identify unknown signals in the data. The detection of variations in pulse profiles highlights the need to develop efficient profile domain timing methods.



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242 - K.J.Lee 2014
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101 - X. J. Liu , M. J. Keith , C. Bassa 2019
We investigate the impact of noise processes on high-precision pulsar timing. Our analysis focuses on the measurability of the second spin frequency derivative $ddot{ u}$. This $ddot{ u}$ can be induced by several factors including the radial velocity of a pulsar. We use Bayesian methods to model the pulsar times-of-arrival in the presence of red timing noise and dispersion measure variations, modelling the noise processes as power laws. Using simulated times-of-arrival that both include red noise, dispersion measure variations and non-zero $ddot{ u}$ values, we find that we are able to recover the injected $ddot{ u}$, even when the noise model used to inject and recover the input parameters are different. Using simulations, we show that the measurement uncertainty on $ddot{ u}$ decreases with the timing baseline $T$ as $T^gamma$, where $gamma=-7/2+alpha/2$ for power law noise models with shallow power law indices $alpha$ ($0<alpha<4$). For steep power law indices ($alpha>8$), the measurement uncertainty reduces with $T^{-1/2}$. We applied this method to times-of-arrival from the European Pulsar Timing Array and the Parkes Pulsar Timing Array and determined $ddot{ u}$ probability density functions for 49 millisecond pulsars. We find a statistically significant $ddot{ u}$ value for PSR,B1937+21 and consider possible options for its origin. Significant (95 per cent C.L.) values for $ddot{ u}$ are also measured for PSRs,J0621+1002 and J1022+1001, thus future studies should consider including it in their ephemerides. For binary pulsars with small orbital eccentricities, like PSR,J1909$-$3744, extended ELL1 models should be used to overcome computational issues. The impacts of our results on the detection of gravitational waves are also discussed.
121 - John Ellis , Marek Lewicki 2020
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