A 24-Hour Global Campaign To Assess Precision Timing of the Millisecond Pulsar J1713+0747

TL;DR

This study presents a 24-hour global observation of pulsar J1713+0747 to analyze timing noise sources, including pulse jitter and interstellar scintillation, to improve gravitational wave detection precision.

Contribution

It provides the first comprehensive, multi-telescope 24-hour dataset of pulsar timing, highlighting intrinsic pulse jitter and scintillation effects on timing precision.

Findings

Pulse phase jitter dominates timing noise at high S/N.

Interstellar scintillation affects timing precision over tens of hours.

Data set enables future detailed noise source analysis.

Abstract

The radio millisecond pulsar J1713+0747 is regarded as one of the highest-precision clocks in the sky, and is regularly timed for the purpose of detecting gravitational waves. The International Pulsar Timing Array collaboration undertook a 24-hour global observation of PSR J1713+0747 in an effort to better quantify sources of timing noise in this pulsar, particularly on intermediate (1 - 24 hr) timescales. We observed the pulsar continuously over 24 hr with the Arecibo, Effelsberg, GMRT, Green Bank, LOFAR, Lovell, Nancay, Parkes, and WSRT radio telescopes. The combined pulse times-of-arrival presented here provide an estimate of what sources of timing noise, excluding DM variations, would be present as compared to an idealized root-N improvement in timing precision, where N is the number of pulses analyzed. In the case of this particular pulsar, we find that intrinsic pulse phase jitter dominates arrival time precision when the S/N of single pulses exceeds unity, as measured using the eight telescopes that observed at L-band/1.4 GHz. We present first results of specific phenomena probed on the unusually long timescale (for a single continuous observing session) of tens of hours, in particular interstellar scintillation, and discuss the degree to which scintillation and profile evolution affect precision timing. This paper presents the data set as a basis for future, deeper studies.