arXiv subjects

Sofia V. Sosa Fiscella

Publications and source records attributed to Sofia V. Sosa Fiscella.

3 recordsLinked to original sources

arXiv2026

The NANOGrav 15 yr Dataset: Modified Functional Forms for Profile-Evolution Time Delays in Pulsar Timing Models

Radio pulsars exhibit frequency-dependent variations in the shape of their pulse profiles that introduce systematic delays in the observed pulse times of arrival (TOA) across an observing band. The North American Nanohertz Observatory for Gravitational Waves (NANOGrav) models these delays using a frequency-dependent (FD) log-polynomial function whose coefficients are fit to TOA measurements at different radio frequencies. However, FD parameters are prone to absorbing power from other chromatic effects, such as interstellar dispersion, leading to fitted FD values that overestimate profile evolution and vary significantly across datasets. To separate these effects, we introduce two new mathematical formulations of profile evolution: a monomial expansion (IFD) and a Legendre polynomial expansion (LIFD). We test these models on observations of 11 pulsars in the NANOGrav 15-year dataset and on simulated data, and also compare their performance to that of frequency-resolved pulse templates. We find that Legendre-based models generally predict timing delays that more closely replicate the true profile evolution, reducing the residual offset relative to FD by as much as 85% for the simulated data. Additionally, we find that the choice of profile evolution model can bias the fitted dispersion model, with FD-based models overestimating the injected DM by 0.013 pc cm^-3 compared to 0.0002 pc cm^-3 for LIFD. These results support the use of Legendre bases to mitigate covariances between chromatic effects, directly benefiting targeted timing studies of these effects and the development of advanced noise-modeling techniques for nanohertz gravitational-wave detection.

astro-ph.HE↗

arXiv2025

The NANOGrav 15-Year Data Set: Improved Timing Precision With VLBI Astrometric Priors

Accurate pulsar astrometric estimates play an essential role in almost all high-precision pulsar timing experiments. Traditional pulsar timing techniques refine these estimates by including them as free parameters when fitting a model to observed pulse time-of-arrival measurements. However, reliable sub-milliarcsecond astrometric estimations require years of observations and, even then, power from red noise can be inadvertently absorbed into astrometric parameter fits, biasing the resulting estimations and reducing our sensitivity to red noise processes, including gravitational waves (GWs). In this work, we seek to mitigate these shortcomings by using pulsar astrometric estimates derived from Very Long Baseline Interferometry (VLBI) as priors for the timing fit. First, we calibrated a frame tie to account for the offsets between the reference frames used in VLBI and timing. Then, we used the VLBI-informed priors and timing-based likelihoods of several astrometric solutions consistent with both techniques to obtain a maximum-posterior astrometric solution. We found offsets between our results and the timing-based astrometric solutions, which, if real, would lead to absorption of spectral power at frequencies of interest for single-source GW searches. However, we do not find significant power absorption due to astrometric fitting at the low-frequency domain of the GW background.

astro-ph.HE↗

arXiv2024

Improving Pulsar Timing Precision with Single Pulse Fluence Clustering

Traditional pulsar timing techniques involve averaging large numbers of single pulses to obtain a high signal-to-noise (S/N) profile, which is matched to a template to measure a time of arrival (TOA). However, the morphology of individual single pulses varies greatly due to pulse jitter. Pulses of different fluence contribute differently to the S/N of the pulse average. Our study proposes a method that accounts for these variations by identifying a range of states and timing each separately. We selected two 1-hour observations of PSR J2145-0750, each in a different frequency band with the Green Bank Telescope. We normalized the pulse amplitudes to account for scintillation effects and probed different excision algorithms to reduce radio-frequency interference. We then measured four pulse parameters (amplitude, position, width, and energy) to classify the single pulses using automated clustering algorithms. For each cluster, we calculated an average pulse profile and template and used both to obtain a TOA and TOA error. Finally, we computed the weighted average TOA and TOA error, the latter as a metric of the total timing precision for the epoch. The TOA is shifted relative to the one obtained without clustering, and we can estimate the shift with this weighting using the same data. For the 820 MHz and 1400 MHz bands, we obtained TOA uncertainties of 0.057 microseconds and 0.46 microseconds, compared to 0.066 microseconds and 0.74 microseconds when no clustering is applied. We conclude that tailoring this method could help improve the timing precision for certain bright pulsars in NANOGrav's dataset.

astro-ph.HE↗