Optimal Interpolation and Prediction in Pulsar Timing

TL;DR

This paper introduces an optimal statistical method for predicting and interpolating pulsar pulse phases, improving accuracy in observational preparations and data analysis by modeling noise and measurement uncertainties.

Contribution

It presents a novel, statistically rigorous approach for pulse phase interpolation and prediction in pulsar timing, replacing ad hoc methods with a unified framework.

Findings

Enhanced prediction accuracy for pulsar phases.

Effective interpolation between measurements.

Framework adaptable to various noise models.

Abstract

For pulsar projects it is often necessary to predict the pulse phase in advance, for example, when preparing for new observations. Interpolation of the pulse phase between existing measurements is also often required, for example, when folding X-ray or gamma-ray observations according to the radio pulse phase. Until now these procedures have been done using various ad hoc methods. The purpose of this paper is to show how to interpolate or predict the pulse phase optimally using statistical models of the various noise processes and the phase measurement uncertainty.