Enhancing the use of Galactic neutron stars as physical laboratories with precise astrometry

TL;DR

This paper advances neutron star research by applying high-precision astrometry using VLBA and Gaia data, enabling better distance measurements and implications for gravitational wave detection.

Contribution

It introduces novel astrometric analysis techniques and presents the largest millisecond pulsar survey, improving neutron star distance and motion measurements.

Findings

First two magnetar parallaxes measured

Largest survey of millisecond pulsars conducted

Astrometric results aid gravitational wave background detection

Abstract

The existence of neutron stars was not confirmed until the discovery of pulsars at radio wavelengths in late 1960s. Since then, these highly compact and magnetized objects have been observed across the electromagnetic spectrum, and widely studied. However, lots of the studies related to neutron stars require precise determination of their distances and proper motions. This thesis focuses on high-precision astrometry of neutron stars using the data from the Very Long Baseline Array (VLBA) and the Gaia space telescope operating, respectively, at radio and optical frequencies. The neutron stars studied in the thesis include the extremely magnetized magnetars, the fast-spinning millisecond pulsars, the gravitational-wave-emitting double neutron stars and neutron star X-ray binaries. As a major accomplishment, this thesis presents the novel analysis and the results of the MSPSRpi project -- the largest astrometric survey of millisecond pulsars, then point out the abundant implications of the astrometric results. Additionally, the release of the astrometric results is bound to facilitate the detection of an ultra-low-frequency gravitational-wave background. Methodologically, this thesis applied advanced VLBI techniques to pulsar astrometry using the original data reduction pipeline psrvlbireduce, which leads to the first two significant magnetar parallaxes, and paves the way for studying magnetar formation channels with their velocity distribution. The astrometry Bayesian inference package sterne, developed during the PhD program, serves as a versatile and powerful tool for the inference of astrometric parameters.