Parameter estimation of a two-component neutron star model with spin wandering

TL;DR

This paper develops a state-space expectation-maximization approach to estimate neutron star interior parameters from pulsar timing data, effectively separating intrinsic spin wandering from measurement and propagation noise.

Contribution

It introduces a novel linear dynamical system formulation and estimation method for neutron star interior parameters using combined gravitational-wave and electromagnetic data.

Findings

Accurately estimates all six model parameters with both data types.

Recovers relaxation time-scale, spin-down rate, and white-noise torque with electromagnetic data alone.

Biases in torque estimates increase when only electromagnetic data are used.

Abstract

It is an open challenge to estimate systematically the physical parameters of neutron star interiors from pulsar timing data while separating spin wandering intrinsic to the pulsar (achromatic timing noise) from measurement noise and chromatic timing noise (due to propagation effects). In this paper we formulate the classic two-component, crust-superfluid model of neutron star interiors as a noise-driven, linear dynamical system and use a state-space-based expectation-maximization method to estimate the system parameters using gravitational-wave and electromagnetic timing data. Monte Carlo simulations show that we can accurately estimate all six parameters of the two-component model provided that electromagnetic measurements of the crust angular velocity, and gravitational-wave measurements of the core angular velocity, are both available. When only electromagnetic data are available we can recover the overall relaxation time-scale, the ensemble-averaged spin-down rate, and the strength of the white-noise torque on the crust. However, the estimates of the secular torques on the two components and white noise torque on the superfluid are biased significantly.