Pulsar Observations at Low Frequencies: Applications to Pulsar Timing and Solar Wind Models

TL;DR

This paper evaluates the effectiveness of solar wind models in pulsar timing at low frequencies, demonstrating that non-stationary models informed by solar observations are necessary for high-precision timing.

Contribution

It provides a comparative analysis of stationary and non-stationary solar wind models using long-term pulsar data, highlighting the need for dynamic models in pulsar timing.

Findings

Stationary solar wind models are insufficient for precise pulsar timing.

Non-stationary models improve timing residuals by accounting for solar wind variability.

Long-term data from the Long Wavelength Array supports these conclusions.

Abstract

Efforts are underway to use high-precision timing of pulsars in order to detect low-frequency gravitational waves. A limit to this technique is the timing noise generated by dispersion in the plasma along the line of sight to the pulsar, including the solar wind. The effects due to the solar wind vary with time, influenced by the change in solar activity on different time scales, ranging up to $\sim 11$ years for a solar cycle. The solar wind contribution depends strongly on the angle between the pulsar line of sight and the solar disk, and is a dominant effect at small separations. Although solar wind models to mitigate these effects do exist, they do not account for all the effects of the solar wind and its temporal changes. Since low-frequency pulsar observations are most sensitive to these dispersive delays, they are most suited to test the efficacy of these models and identify alternative approaches. Here, we investigate the efficacy of some solar wind models commonly used in pulsar timing using long-term, high-cadence data on 6 pulsars taken with the Long Wavelength Array, and compare them with an operational solar wind model. Our results show that stationary models of the solar wind correction are insufficient to achieve the timing noise desired by pulsar timing experiments, and we need to use non-stationary models, which are informed by other solar wind observations, to obtain accurate timing residuals.