📝 SummarXiv

Abstract

One of the most promising targets for Pulsar Timing Arrays (PTAs) is identifying an individual supermassive black hole binary (SMBHB) out of the population of binaries theorized to produce a gravitational wave background (GWB). In this work, we emulate an evolving PTA dataset, complete with an increasing number of pulsars and timing baseline, into which we inject a single binary on top of a Gaussian GWB signal. We vary the binary's source parameters, including sky position and frequency, and create an ensemble of simulated datasets with which we assess current Bayesian binary search techniques. We apply two waveform-based template models and a frequency-resolved anisotropy search to these simulations to understand how they compare in their detection and characterization abilities. We find that a template-based search including the full gravitational-wave signal structure (i.e., both Earth and pulsar effects of an incident GW) returns the highest Bayes Factors (BF), exceeding our estimator's capabilities by (S/N)~9-19, and has the most robust parameter estimation. Our anisotropy model attains a realization-median BF>10 at 7<(S/N)<15. Interestingly, despite being a deterministic model, the Earth-term template struggles to detect and characterize low-frequency binaries (5 nHz). These binaries require higher (S/N)~16-19 to reach the same BF threshold. This is likely due to neglected confusion effects between the pulsar and Earth terms. By contrast, the frequency-resolved anisotropy model shows promise for parameter estimation despite treating a binary's GW signal as excess directional GW power without phase modeling. Sky location and frequency parameter constraints returned by the anisotropy model are only surpassed by the Earth term template model at (S/N)~12-13. Milestones for a first detection using the full-signal GW model are included in a companion paper (Petrov et al. 2025).