Improved Pulsar Timing via Principle Component Mode Tracking

TL;DR

This paper introduces a principal component analysis method to track and correct short-term variability in pulsar profiles, enhancing timing precision and enabling effective timing with shorter observation segments.

Contribution

The authors develop a PCA-based technique coupled with a likelihood method to improve pulsar timing accuracy by accounting for profile variability.

Findings

Successfully applied to PSR J2139+0040 with four years of data.

Achieved improved timing solutions compared to traditional methods.

Enables pulsar timing with shorter, less contiguous observations.

Abstract

We present a principal component analysis method which tracks and compensates for short-timescale variability in pulsar profiles, with a goal of improving pulsar timing precision. We couple this with a fast likelihood technique for determining pulse time of arrival, marginalizing over the principal component amplitudes. This allows accurate estimation of timing errors in the presence of pulsar variability. We apply the algorithm to the slow pulsar PSR J2139+0040 using an archived set of untargeted raster-scan observations at arbitrary epochs across four years, obtaining an improved timing solution. The method permits accurate pulsar timing in data sets with short contiguous on-source observations, opening opportunities for commensality between pulsar timing and mapping surveys.