Isolated pulsar spin evolution on the P-Pdot Diagram

TL;DR

This study compares different spin-down models for isolated pulsars, emphasizing the P-Pdot diagram's features and how various properties influence pulsar evolution, ultimately favoring the magnetic dipole model with specific assumptions.

Contribution

It evaluates contrasting spin-down models, incorporating selection effects, and demonstrates that the magnetic dipole model best reproduces observed pulsar populations, with a publicly available simulation tool.

Findings

Magnetic dipole model better fits observed data.

Random alignment angles are crucial for accurate modeling.

Time decay of alignment angles affects pulsar evolution predictions.

Abstract

We look at two contrasting spin-down models for isolated radio pulsars and, accounting for selection effects, synthesize observable populations. While our goal is to reproduce all of the observable characteristics, in this paper we pay particular attention to the form of the spin period vs. period derivative (P-Pdot) diagram and its dependence on various pulsar properties. We analyse the initial spin period, the braking index, the magnetic field, various beaming models, as well as the pulsar's luminosity. In addition to considering the standard magnetic dipole model for pulsar spin-down, we also consider the recent hybrid model proposed by Contopoulos & Spitkovsky. The magnetic dipole model, however, does a better job of reproducing the observed pulsar population. We conclude that random alignment angles and period dependent luminosity distributions are essential to reproduce the observed P-Pdot diagram. We also consider the time decay of alignment angles, and attempt to reconcile various models currently being studied. We conclude that, in order to account for recent evidence for the alignment found by Weltevrede & Johnston, the braking torque on a neutron star should not depend strongly on the inclination. Our simulation code is publically available and includes a web-based interface to examine the results and make predictions for yields of current and future surveys.