Low-Frequency Spectral Turn-Overs in Millisecond Pulsars Studied from Imaging Observations

TL;DR

This study uses archival imaging data at multiple radio frequencies to measure millisecond pulsar flux densities, revealing spectral turn-overs and providing insights unaffected by interstellar scattering effects.

Contribution

It introduces a novel imaging-based approach to study MSP spectra, overcoming limitations of pulse profile methods at low frequencies.

Findings

Identified six MSPs with likely spectral turn-overs.

Determined three new spectral indices for MSPs.

Validated imaging data as a reliable method for MSP flux measurement.

Abstract

Measurements of pulsar flux densities are of great importance for understanding the pulsar emission mechanism and for predictions of pulsar survey yields and the pulsar population at large. Typically these flux densities are determined from phase-averaged "pulse profiles", but this method has limited applicability at low frequencies because the observed pulses can easily be spread out by interstellar effects like scattering or dispersion, leading to a non-pulsed continuum component that is necessarily ignored in this type of analysis. In particular for the class of the millisecond pulsars (MSPs) at frequencies below 200MHz, such interstellar effects can seriously compromise de- tectability and measured flux densities. In this paper we investigate MSP spectra based on a complementary approach, namely through investigation of archival con- tinuum imaging data. Even though these images lose sensitivity to pulsars since the on-pulse emission is averaged with off-pulse noise, they are insensitive to effects from scattering and provide a reliable way to determine the flux density and spectral indices of MSPs based on both pulsed and unpulsed components. Using the 74MHz VLSSr as well as the 325MHz WENSS and 1.4GHz NVSS catalogues, we investigate the imaging flux densities of MSPs and evaluate the likelihood of spectral turn-overs in this population. We determine three new MSP spectral indices and identify six new MSPs with likely spectral turn-overs.