The glitch activity of neutron stars

Abstract

We present a statistical study of the glitch population and the behaviour of the glitch activity across the known population of neutron stars. An unbiased glitch database was put together based on systematic searches of radio timing data of 898 rotation-powered pulsars obtained with the Jodrell Bank and Parkes observatories. Glitches identified in similar searches of 5 magnetars were also included. The database contains 384 glitches found in the rotation of 141 of these neutron stars. We confirm that the glitch size distribution is at least bimodal, with one sharp peak at approximately 20 µ Hz, which we call large glitches, and a broader distribution of smaller glitches. We also explored how the glitch activityν g , defined as the mean frequency increment per unit of time due to glitches, correlates with the spin frequency ν, spin-down rate |ν|, and various combinations of these, such as energy loss rate, magnetic field, and spin-down age. It is found that the activity is insensitive to the magnetic field and that it correlates strongly with the energy loss rate, though magnetars deviate from the trend defined by the rotation-powered pulsars. However, we find that a constant ratiȯ ν g /|ν| = 0.010 ± 0.001 is consistent with the behaviour of all rotation-powered pulsars and magnetars. This relation is dominated by large glitches, which occur at a rate directly proportional to |ν|. For low |ν|, only small glitches have been detected, making the inferred glitch activity formally lower than that predicted by the constant ratio, in many cases zero. However, we can attribute this to the low predicted rate for large glitches, together with the insufficient observing time, which makes it unlikely to detect any large glitches in this range. Taking this into consideration, we show that the behaviour of each rotation-powered pulsar and magnetar is statistically consistent with the above relationship, including those objects where no glitches have been detected so far. The only exception are the rotation-powered pulsars with the highest values of |ν|, such as the Crab pulsar and PSR B0540−69, which exhibit a much smaller glitch activity, intrinsically different from each other and from the rest of the population. The activity due to small glitches also shows an increasing trend with |ν|, but this relation is biased by selection effects.

Glitch time series and size distributions in eight prolific pulsars

“…However, this statement has to be confirmed with more data in the future. Fuentes et al (2017) found that all pulsars (with the strong exception of the Crab pulsar and PSR B0540−69) are consistent with a constant ratio between the glitch activity,ν g , and the spindown rate,ν g /|ν| = 0.010 ± 0.001, i.e., ≈ 1% of their spin-down is recovered by the glitches. This fraction has been interpreted as the fraction of the moment of inertia in a superfluid component that transfers its angular momentum to the rest of the star in the glitches (Link et al 1999;Andersson et al 2012).…”

“…Correlations between glitch sizes and the times to the nearest glitches, either backward or forward, are naturally expected. We know that glitch activity is driven by the spin-down rate (Fuentes et al 2017), which suggests that glitches are the release of some stress that builds up at a rate determined by |ν|. If the stress is completely released at each glitch, then one should expect a correlation between size and the time since the last glitch.…”

Timing of young radio pulsars – II. Braking indices and their interpretation

“…where T g is the mean time between glitches. In turn, Fuentes et al (2017) showed that T g ∝ ν −1 . Combining this with equation 2, yields the remarkable relationship for the braking index between glitches, n g , which then depends only on ν, n g = 10 −0.2±1.4 ν.…”

“…Second, for each pulsar we compute the glitch rate and typical glitch size. For this we use the metric for the glitch rate given by Fuentes et al (2017) along with the parameterisation of large glitch sizes given in the same paper. As a check on the metric, we use Poisson statistics and determine that we expect ∼3.2 pulsars in our sample to have glitched in the 15 year observing span of the data.…”

“…The presence of glitches, and in particular the glitch recovery, further complicates the measurement of ν and hence the braking index. Following a glitch event, a pulsar enters a recovery stage during which an increase in the spin-down rate and a relaxation towards the pre-glitch rotational state is observed over a timescale of days to years (Yu et al 2013, Fuentes et al 2017. Both the spin-up event and the subsequent recovery stage are interpreted as the presence of a superfluid component in the inner crust and core of the star (Haskell & Melatos 2015).…”