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تسجيل مستخدم جديدDetection of a Glitch in PSR J0908$-$4913 by UTMOST
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We report the first detection of a glitch in the radio pulsar PSR J0908$-$4913 (PSR B0906$-$49) during regular timing observations by the Molonglo Observatory Synthesis Telescope (MOST) as part of the UTMOST project.
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Seven years of pulse time-of-arrival measurements have been collected from observations of the young pulsar PSR B2334+61 using the Nanshan radio telescope of Urumqi Observatory. A phase-connected solution has been obtained over the whole data span, 2
002 August to 2009 August. This includes a very large glitch that occurred between 2005 August 26 and September 8 (MJDs 53608 and 53621). The relative increase in rotational frequency for this glitch, $Delta u_{g}/ u~sim~20.5times10^{-6}$, is the largest ever seen. Although accounting for less than 1% of the glitch, there were two well-defined exponential decay terms with time constants of 21 and 147 days respectively. There was also a large long-term increase in the spindown rate with $Deltadot u_p/dot u sim 0.011$ at the time of the glitch. A highly significant oscillation with a period of close to one year is seen in the post-glitch residuals. It is very unlikely that this can be accounted for by a pulsar position error or proper motion -- it appears to result from effects interior to the neutron star. Implications of these results for pulsar glitch models are discussed.
We report the detection of a glitch event in the pulsar J1709$-$4429 (also known as B1706$-$44) during regular monitoring observations with the Molonglo Observatory Synthesis Telescope (UTMOST). The glitch was found during timing operations, in which
we regularly observe over 400 pulsars with up to daily cadence, while commensally searching for Rotating Radio Transients, pulsars, and FRBs. With a fractional size of $Delta u/ u approx 52.4 times10^{-9}$, the glitch reported here is by far the smallest known for this pulsar, attesting to the efficacy of glitch searches with high cadence using UTMOST.
We present high-sensitivity, wide-band observations (704 to 4032 MHz) of the young to middle-aged radio pulsar J1452-6036, taken at multiple epochs before and, serendipitously, shortly after a glitch occurred on 2019 April 27. We obtained the data us
ing the new ultra-wide-bandwidth low-frequency (UWL) receiver at the Parkes radio telescope, and we used Markov Chain Monte Carlo techniques to estimate the glitch parameters robustly. The data from our third observing session began 3 h after the best-fitting glitch epoch, which we constrained to within 4 min. The glitch was of intermediate size, with a fractional change in spin frequency of $270.52(3) times 10^{-9}$. We measured no significant change in spin-down rate and found no evidence for rapidly-decaying glitch components. We systematically investigated whether the glitch affected any radiative parameters of the pulsar and found that its spectral index, spectral shape, polarisation fractions, and rotation measure stayed constant within the uncertainties across the glitch epoch. However, its pulse-averaged flux density increased significantly by about 10 per cent in the post-glitch epoch and decayed slightly before our fourth observation a day later. We show that the increase was unlikely caused by calibration issues. While we cannot exclude that it was due to refractive interstellar scintillation, it is hard to reconcile with refractive effects. The chance coincidence probability of the flux density increase and the glitch event is low. Finally, we present the evolution of the pulsars pulse profile across the band. The morphology of its polarimetric pulse profile stayed unaffected to a precision of better than 2 per cent.
One large glitch was detected in PSR B1737$-$30 using data spanning from MJD 57999 to 58406 obtained with the newly built Shanghai Tian Ma Radio Telescope (TMRT). The glitch took place at the time around MJD 58232.4 when the pulsar underwent an incre
ase in the rotation frequency of $Delta u$ about 1.38$times 10^{-6}$ Hz, corresponding to a fractional step change of $Delta u / u$ $thicksim$ 8.39$times 10^{-7}$. Post$textrm{-}$glitch $ u$ gradually decreased to the pre$textrm{-}$glitch value. The frequency derivative was observed to undergo a step change of about $-$9$times 10^{-16}$ s$^{-2}$. Since July 1987, there are 36 glitches already reported in PSR B1737$-$30 including this one. According to our analysis, the glitch size distribution is well described by the power law with index of 1.13. The distribution of the interval between two adjacent glitches (waiting time $Delta T$) follows a Poissonian probability density function. For PSR B1737$-$30, the interval is prone to be long after a large glitch. But no correlation is found between glitch size and the interval since previous glitch.
Pulsar timing experiments typically generate a phase-connected timing solution from a sequence of times-of-arrival (TOAs) by absolute pulse numbering, i.e. by fitting an integer number of pulses between TOAs in order to minimize the residuals with re
spect to a parametrized phase model. In this observing mode, rotational glitches are discovered, when the residuals of the no-glitch phase model diverge after some epoch, and glitch parameters are refined by Bayesian follow-up. Here an alternative, complementary approach is presented which tracks the pulse frequency $f$ and its time derivative $df/dt$ with a hidden Markov model (HMM), whose dynamics include stochastic spin wandering (timing noise) and impulsive jumps in $f$ and $df/dt$ (glitches). The HMM tracks spin wandering explicitly, as a specific realization of a discrete-time Markov chain. It discovers glitches by comparing the Bayes factor for glitch and no-glitch models. It ingests standard TOAs for convenience and, being fully automated, allows performance bounds to be calculated quickly via Monte Carlo simulations. Practical, user-oriented plots are presented of the false alarm probability and detection threshold (e.g. minimum resolvable glitch size) versus observational scheduling parameters (e.g. TOA uncertainty, mean delay between TOAs) and glitch parameters (e.g. transient and permanent jump sizes, exponential recovery time-scale). The HMM is also applied to $sim 1$ yr of real data bracketing the 2016 December 12 glitch in PSR J0835-4510 as a proof of principle. It detects the known glitch and confirms that no other glitch exists in the same data with size $> 10^{-7} f$.
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