Classification of Pulsar Glitch Amplitudes using Extreme Deconvolution

Understand

We carry out a classification of the glitch amplitudes of radio pulsars using Extreme Deconvolution technique based on the Gaussian Mixture Model, where the observed uncertainties in the glitch amplitudes $\Delta \nu/\nu$ are taken into account.

• Our dataset consists of 699 glitches from 238 pulsars.
• We then use information theory criteria such as AIC and BIC to determine the optimum number of glitch classes.
• We find that both AIC and BIC show that the pulsar glitch amplitudes can be optimally described using a bimodal distribution.