Wide-band profile domain pulsar timing analysis

Abstract

We extend profile domain pulsar timing to incorporate wide-band effects such as frequencydependent profile evolution and broadband shape variation in the pulse profile. We also incorporate models for temporal variations in both pulse width and in the separation in phase of the main pulse and interpulse. We perform the analysis with both nested sampling and Hamiltonian Monte Carlo methods. In the latter case we introduce a new parameterisation of the posterior that is extremely efficient in the low signal-to-noise regime and can be readily applied to a wide range of scientific problems. We apply this methodology to a series of simulations, and to between seven and nine yr of observations for PSRs J1713+0747, J1744−1134, and J1909−3744 with frequency coverage that spans 700-3600 MHz. We use a smooth model for profile evolution across the full frequency range, and compare smooth and piecewise models for the temporal variations in DM. We find the profile domain framework consistently results in improved timing precision compared to the standard analysis paradigm by as much as 40% for timing parameters. Incorporating smoothness in the DM variations into the model further improves timing precision by as much as 30%. For PSR J1713+0747 we also detect pulse shape variation uncorrelated between epochs, which we attribute to variation intrinsic to the pulsar at a level consistent with previously published analyses. Not accounting for this shape variation biases the measured arrival times at the level of ∼30 ns, the same order of magnitude as the expected shift due to gravitational-waves in the pulsar timing band.

A Multi-telescope Campaign on FRB 121102: Implications for the FRB Population

“…Pulsar pulse shapes evolve with frequency on GHz frequency scales, presumably due to changes in the beam shape (Lyne & Manchester 1988). The burst-dependent DM changes are on the order of 1% of the total DM (equivalent to a delay rate up to 2 ms GHz −1 ), which is much larger than typically observed (Lentati et al 2017). Our modeling of the VLA burst dynamic spectra show a weak correlation between larger apparent DM and pulse width.…”

The NANOGrav 12.5 yr Data Set: Observations and Narrowband Timing of 47 Millisecond Pulsars

“…The dispersive delay is proportional to the column density of free electrons along the line of sight, which is called the dispersion measure (DM), and the measurement and accommodation of DM changes is an outstanding problem in high-precision pulsar timing (Jones et al 2017;Lam et al 2016a;Lee et al 2014;Keith et al 2013;Lentati et al 2013a). Additionally, as bandwidths grow, more subtle effects arising from the inhomogeneity in the ISM become more prominent in pulsar timing; these effects include profile broadening (Geyer et al 2017;Lentati et al 2017a;Geyer & Karastergiou 2016;Levin et al 2016), non-dispersive delays (Lam et al 2018b;Foster & Cordes 1990), and frequency-dependent DMs (Lam et al 2020;Donner et al 2019;Cordes et al 2016).…”

Improved pulsar timing via principal component mode tracking

“…This would optimally extract the timing information from the phase measurements but would substantially complicate fitting a timing solution, since least-squares would no longer be applicable. Our PCA mode tracking method addresses issues similar to those addressed via "profile-domain pulsar timing" Lentati & Shannon 2015;Lentati et al 2017), particularly, what these authors refer to as "lowfrequency stochasticity" and "phase-correlated stochasticity". The profile-domain techniques uses pre-defined uncor-related shapelet components to contribute to the individual profiles.…”