Calibration of statistical methods used to constrain pulsar geometries via multiband light curve modelling

TL;DR

This paper compares traditional and novel statistical methods for constraining pulsar geometries using multiband light curve data, aiming to improve the accuracy and utility of pulsar modeling.

Contribution

It introduces two new statistical approaches that treat radio and gamma-ray data equally, and applies them to real pulsar data for comparison with existing methods.

Findings

New statistical methods provide consistent geometric parameters.

Comparison shows potential advantages of the novel approaches.

Results will inform future pulsar magnetospheric modeling.

Abstract

Since its launch in 2008, the Fermi Large Area Telescope (LAT) has detected over 200 -ray pulsars above 100 MeV. This population of pulsars is characterised by a rich diversity of light curve morphologies. Researchers have been using both the radio and -ray light curves to constrain the inclination and observer angles for each of these pulsars. At first, this was done using a by-eye technique and later via statistical approaches. We have also developed two novel statistical approaches that place the radio and -ray data on equal footing despite their disparate relative flux errors. We chose eleven pulsars from the Second Fermi Pulsar Catalog, both old and young, and applied these new techniques as well as the by-eye technique to constrain their geometric parameters using standard pulsar models. We present first results on our comparison of the best-fit parameters yielded by each of the aforementioned techniques. This will assist us in determining the utility of our new statistical approaches, and gauge the overlap of the best-fit parameters (plus errors) from each of the different methods. Such a statistical fitting approach will provide the means for further pulsar magnetospheric model development using light curve data.