2024A&A...687A.113V

Some of the most important information on a radio pulsar is derived from its average pulse profile. Many early pulsar studies were necessarily based on only a few such profiles. In these studies, discrete profile components were linked to emission mechanism models for individual stars through human interpretation. For the population as a whole, profile morphology must reflect the geometry and overall evolution of the radio emitting regions. The problem, however, is that this population is becoming too large for individual intensive studies of each source. Moreover, connecting profiles from a large collection of pulsars rapidly becomes cumbersome. In this article, we present ToPP, the first-ever unsupervised method to sort pulsars by profile-shape similarity using graph topology. We applied ToPP to the publicly available European Pulsar Network profile database, providing the first organised visual overview of multi-frequency profiles representing 90 individual pulsars. We found discrete evolutionary tracks varying from simple single-component profiles at all frequencies towards diverse mixtures of more complex profiles with frequency evolution. The profile evolution is continuous, extending out to millisecond pulsars, and does not fall into sharp classes. We interpret the profiles as being a mixture of pulsar core-cone emission type, spin-down energetics, and the line-of-sight impact angle towards the magnetic axis. We show how ToPP can systematically classify sources into the Rankin empirical profile scheme. ToPP comprises one of the key unsupervised methods that will be essential to exploring upcoming pulsar census data, such as the data expected from the Square Kilometer Array.