Profile Stochasticity in PSR J1909-3744
L. Lentati, R. M. Shannon

TL;DR
This paper extends Bayesian pulsar timing analysis to include pulse profile stochasticity, improving gravitational wave detection sensitivity by decorrelating profile variations from GW signals, and applies it to PSR J1909-3744 data.
Contribution
The paper introduces a novel profile domain Bayesian framework that models pulse jitter and shape stochasticity directly from folded profile data, enhancing GW detection limits.
Findings
Profile variations can mimic GW signals in residuals.
Profile domain analysis reduces covariance with GW signals.
No significant pulse jitter detected in PSR J1909-3744 data.
Abstract
We extend the recently introduced Bayesian framework `Generative Pulsar Timing Analysis' to incorporate both pulse jitter (high frequency variation in the arrival time of the pulse) and epoch to epoch stochasticity in the shape of the pulse profile. This framework allows for a full timing analysis to be performed on the folded profile data, rather than the site arrival times as is typical in most timing studies. We apply this extended framework both to simulations, and to an 11 yr, 10 cm data set for PSR J19093744. Using simulations, we show that temporal profile variation can induce timing noise in the residuals that when performing a standard timing analysis is highly covariant with the signal expected from a gravitational wave (GW) background. When working in the profile domain, these variations are de-correlated from the expected GW signal, resulting in significant improvement in…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
