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Stephen R. Taylor

Publications and source records attributed to Stephen R. Taylor.

At least 19 recordsLinked to original sources

JUG: JAX-based Unified pulsar timinG

We present JUG (JAX-based Unified pulsar timinG), a JAX-based, fully independent pulsar timing package emphasising speed and ease of use, designed to confidently handle the increasingly large and complex pulsar timing array datasets that are being created in the pulsar timing field. JUG implements the entire pulsar timing pipeline itself, from data handling and clock corrections through to the timing model and fitting, without relying on other timing software. It enables Pythonic programming at the speed of compiled code, is GPU-capable, and can be operated via a Python API or an interactive GUI. A user of JUG can interactively explore data, fit timing models with complex stochastic noise, model deterministic signals such as continuous gravitational waves, and obtain accurate point estimates of the parameters of the stochastic processes present, thereby bridging frequentist timing and Bayesian noise analysis. JUG is faster than PINT by more than fifty times and is comparably fast to Tempo2, can handle millions of arrival times, agrees with PINT at the picosecond level, and can reliably recover known timing model and noise parameter values. In this paper we describe its design, performance, and validation, and demonstrate its advantages for pulsar timing data analysis.

astro-ph.IM

Generalized Non-linear Bayesian Pulsar Timing with Enterprise

In this study, we use the Bayesian methods in the Enterprise package to examine the fully general parameterization of pulsar timing models in tandem with noise. We investigate four pulsars, PSR J1600$-$3053, PSR J2043+1711, PSR J0740+6620, and PSR J1640+2224, through the lens of Bayesian timing. These four are selected as they are well-studied, but exhibit interesting characteristics under the lens of Bayesian timing. Our new pulsar mass constraints (medians and 68\% confidence intervals) for our fully general non-linear Bayesian timing models are $m_{\mathrm{p}}=1.6(1)~\mathrm{M}_{\odot}$ for PSR J2043+1711 and $m_{\mathrm{p}}=2.3^{+0.9}_{-0.7}~\mathrm{M}_{\odot}$ for PSR J1600$-$3053 both using the NANOGrav 12.5-yr data release, and $m_{\mathrm{p}}=2.06(6)~\mathrm{M}_{\odot}$ for PSR J0740+6620 using the data from Fonseca, et al., 2021. We investigate the effects on placing physical priors on timing model parameters, including restricting the upper limit on the pulsar mass for PSR J1640+2224, which has a mass often estimated to be greater than $3~\mathrm{M}_{\odot}$. We find \ark{that restricting the allowed sampling space of the pulsar mass for PSR J1640+2224 to} $m_{\mathrm{p}}<3~\mathrm{M}_{\odot}$ results in a pulsar mass of $m_{\mathrm{p}}=2.2(5)~\mathrm{M}_{\odot}$ for PSR J1640+2224 using the NANOGrav 12.5-yr data release. For the first time, we find evidence for intrinsic red noise in PSR J2043+1711. We show how fully general Bayesian timing can better model the interplay of the intrinsic noise and the timing parameters.

astro-ph.HE

Evaluating the Fourier Approximation in Pulsar Timing Array Analysis

Pulsar timing arrays search for stochastic processes such as gravitational waves by comparing pulse time of arrival data for millisecond pulsars to expectations from a background with a given power spectral density (PSD). To make the analysis computationally tractable, the Bayesian likelihood is usually computed using an approximation in which the signal is taken to be a sum of Fourier modes appropriate to the total time of observation, even though the true signal is not periodic. We study the difference between likelihoods computed with this Fourier approximation method for power law spectra and those computed exactly (or using more-closely spaced frequencies as a proxy for the exact result) in the NANOGrav 15-year dataset. We find that the true marginal likelihoods for power-law PSDs are on average about half as large as the likelihoods computed using the Fourier approximation. This could lead to an error of a factor of two in model comparison. However, in the important comparison of uncorrelated vs. Hellings-Downs correlated models, a very similar correction appears in both, so the model comparison is essentially unaffected. We also compare parameter estimation results for power law PSDs, finding little difference between the methods. We briefly discuss spectra with sharper features, for which the approximation could be much worse.

gr-qc

Prospects of resolving and localising individual supermassive black hole binaries with pulsar timing arrays: the host ranking challenge

Pulsar Timing Arrays (PTAs) are soon expected to detect individually resolved supermassive black hole (SMBH) binaries, opening the possibility for multi-messenger discoveries. The biggest challenge will be to pinpoint the host galaxy in a large localisation area. We simulate realistic binary populations consistent with the gravitational wave (GW) background, projecting the PTA sensitivity for the next 0-10 years. We inject the loudest binary on top of the background and use one of the standard detection pipelines to constrain its properties. We cross-match the localisation areas with comprehensive all-sky galaxy catalogues and estimate the number of candidate hosts in the localisation area assessing, for the first time, the number of missing galaxies due to incomplete coverage. We develop a ranking system that excludes galaxies with properties inconsistent with the GW posteriors, and prioritizes the remaining galaxies for follow-up observations. We find a $\approx$21, $\approx$38 and $\approx$51 percent probability of resolving a binary in the next 0, 5 and 10 years, respectively, reduced to 0.3, 3.8 and 14.1 percent if we require potentially well-constrained localisation areas. The localisation areas span hundreds of square degrees, but shrink significantly with the addition of more data. They contain on average $\approx$190,000 early type galaxies and $\approx$40,000 active galactic nuclei, with $\approx$25,000 missing candidate hosts. Our ranking method can exclude about half of the potential hosts and efficiently rank those remaining when the galaxy catalogue provides SMBH masses and redshifts, but becomes more inefficient when we rely on apparent magnitudes.

astro-ph.GA

Archival Multiband Gravitational-Wave Signals from Massive Black Hole Binary Mergers

While massive black hole binaries (MBHBs) merge at gravitational-wave frequencies above the pulsar timing array (PTA) sensitivity band, we show that they leave orphaned low-frequency contributions in the PTA pulsar term. Due to the light-propagation time between each pulsar in the array and Earth, the pulsar term acts as a time-delayed probe of a chirping merger with a specific frequency response determined by the direction of origin and intrinsic properties of the MBHB. We provide a detailed consideration of how such a multiband signal would manifest in a full PTA, demonstrate an approach to stack these orphaned pulsar terms across the array, and discuss prospects for an archival, multiband search in conjunction with MBHB mergers observed in astrometric data or spaceborne interferometers like LISA.

astro-ph.HE

Expectations for the first supermassive black-hole binary resolved by PTAs I: Model efficacy

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 realistic PTA datasets, complete with an increasing number of pulsars and timing baseline, in which we inject a single binary on top of a Gaussian GWB. We vary the binary's source parameters, including sky position and frequency, and create ten noise realizations for each source/PTA combination to synthesize an ensemble of datasets to assess current Bayesian binary search techniques. We develop a novel, cross-correlation based model, Spike Pixel (SP), tuned for the frequency-specific anisotropy induced by an individual SMBHB and compare its binary detection and characterization capabilities to two waveform-based template models. We find that a template-based search including the full gravitational-wave signal structure (i.e., both the Earth and pulsar effects of an incident GW) returns the highest Bayes Factors (BF) and the most robust parameter estimation. SP attains a realization-median BF>10 at source strengths (S/N)~7-15. Interestingly, despite being a deterministic model, the Earth-term template struggles to identify and characterize low-frequency binaries (i.e., 5 nHz). These binaries require higher source strengths (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, SP 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 SP 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. 2026.

astro-ph.IM

Expectations for the first supermassive black-hole binary resolved by PTAs II: Milestones for binary characterization

Following the recent evidence for a gravitational wave (GW) background found by pulsar timing array (PTA) experiments, the next major science milestone is resolving individual supermassive black hole binaries (SMBHBs). The detection of these systems could arise via searches using a power-based GW anisotropy model or a deterministic template model. In Schult et al. 2025, we compared the efficacy of these models in constraining the GW signal from a single SMBHB using realistic, near-future PTA datasets, and found that the full-signal deterministic continuous wave (CW) search may achieve detection and characterization first. Here, we continue our analyses using only the CW model given its better performance, focusing now on characterization milestones. We examine the order in which CW parameters are constrained as PTA data are accumulated and the signal-to-noise ratio (S/N) grows. We also study how these parameter constraints vary across sources of different sky locations and GW frequencies. We find that the GW frequency and strain are generally constrained at the same time (or S/N), closely followed by the sky location, and later the chirp mass (if the source is highly evolving) and inclination angle. At fixed S/N, sources at higher frequencies generally achieve better precision on the GW frequency, chirp mass, and sky location. The time (and S/N) at which the signal becomes constrained is dependent on the sky location and frequency of the source, with the effects of pulsar terms and PTA geometry playing crucial roles in source detection and localization.

astro-ph.IM

A Foundation for Gravitational-Wave Population Inference within the LISA Global Fit

Population inference in gravitational-wave astronomy allows us to connect individual detections to the astrophysics of compact objects and their environments. Current approaches employed for population inference with LIGO-Virgo-KAGRA data approximate evaluation of the hierarchical population likelihood via post-processing of individual-event posteriors. However, the case of the Laser Interferometer Space Antenna (LISA) will be more complex for two main reasons: the transdimensional "global fit" approach to LISA data analysis which models all signals and noise simultaneously, and the presence of both individually-resolved signals and the unresolved stochastic ``Galactic foreground" arising from the Galactic binary population, which induces a circular dependence between the resolved and unresolved systems and our ability to detect the former. These challenges are not without opportunity; LISA's data will contain every mHz compact binary in the Milky Way -- either individually or within the Galactic foreground -- with great potential for Galactic and stellar astrophysics. We therefore propose an alternative approach: direct evaluation of the full hierarchical population likelihood within the LISA global fit. We develop a statistical formalism for joint inference of individually-resolved gravitational-wave sources, an unresolved stochastic foreground, and a shared, underlying astrophysical population, present PELARGIR, a prototype GPU-accelerated population inference module for the LISA global fit, demonstrate the formalism and PELARGIR via a toy model analysis, and lay out a roadmap towards an astrophysically-motivated LISA global fit with embedded population inference. While we apply the formalism here to the population of LISA Galactic binaries, it is applicable across the gravitational-wave spectrum with use cases in pulsar timing and next-generation terrestrial observatories.

astro-ph.IM

On the angular localization of gravitational-wave signals by pulsar timing arrays

We provide a complete study of gravitational-wave signal localization using pulsar timing arrays. We derive analytical expressions for the Cram\'er-Rao sky localization precision that delineate the impact of the angular proximity, $\xi$, between the pulsar and the gravitational wave source, and the precision, $\sigma_L$, with which pulsar distances are known. Interference between the Earth and pulsar terms creates rapid angular oscillations for sky-coordinate Fisher matrix elements that aid localization, which is complemented by more broadly varying antenna response gradient information. The relative importance of these factors depends on whether pulsar distances are known precisely [i.e., $\sigma_L\leq\lambda_\mathrm{GW}/(1-\cos\xi)$] or imprecisely. If pulsar distances are known precisely, tightening this distance precision improves signal localization according to $\Delta\Omega_\mathrm{sky}\propto(\sigma_L/L)^2$ until the Earth-pulsar system reaches its diffraction limit, $\Delta\Omega_\mathrm{sky}\propto(\lambda_\mathrm{GW}/L)^2$. If pulsar distances are not known well, localization precision is degraded, but more pulsars in close proximity to the source is the best means of improving. With $\alpha$ indexing pulsars, this scales as $\Delta\Omega_\mathrm{sky}~\propto~(\sum_\alpha \mathrm{SNR}_\alpha^2/\xi_\alpha^2)^{-1}$ in the small-angle limit of the unmarginalized Fisher matrix, and we derive the analytic generalization to any angle between a pulsar and the source. Finally, we study a scenario where pulsar-term phases are treated as nuisance variables that are unconnected to binary or PTA properties. This phase-decoupled scenario, which is how all PTA continuous wave searches are currently conducted, delivers localization performance similar to the antenna-response--driven case, and does not exhibit significant improvement as pulsar distance precisions are tightened.

astro-ph.HE

LISA and the LISA Science Team

LISA, the Laser Interferometer Space Antenna, due to launch mid-2035, is a large class space mission by the European Space Agency (ESA). In partnership with NASA and ESA-member states, ESA is on track to launch what is expected to be the first space-based gravitational wave detector. By hosting detectors in space, one gains access to a lower frequency band of gravitational wave sources and, with them, a plethora of new science. To maximise this scientific gain, ESA and NASA selected 20 scientists for the LISA Science Team to carry out and/or lead the necessary actions leading up to LISA's launch. We give a short overview and update of the LISA mission, its science objectives and related waveforms, as well as the work of the LISA Science Team as of April 2026.

astro-ph.IM

The NANOGrav 15 yr Data Set: Piecewise Power-Law Reconstruction of the Gravitational-Wave Background

The NANOGrav 15-year (NG15) data set provides evidence for a gravitational-wave background (GWB) signal at nanohertz frequencies, which is expected to originate either from a cosmic population of inspiraling supermassive black-hole binaries or new particle physics in the early Universe. A firm identification of the source of the NG15 signal requires an accurate reconstruction of its frequency spectrum. In this paper, we provide such a spectral characterization of the NG15 signal based on a piecewise power-law (PPL) ansatz that strikes a balance between existing alternatives in the literature. Our PPL reconstruction is more flexible than the standard constant-power-law model, which describes the GWB spectrum in terms of only two parameters: an amplitude A and a spectral index gamma. Concurrently, it better approximates physically realistic GWB spectra -- especially those of cosmological origin -- than the free spectral model, since the latter allows for arbitrary variations in the GWB amplitude from one frequency bin to the next. Our PPL reconstruction of the NG15 signal relies on individual PPL models with a fixed number of internal nodes (i.e., constant power law, broken power law, doubly broken power law, etc.) that are ultimately combined in a Bayesian model average. The data products resulting from our analysis provide the basis for fast refits of spectral GWB models.

astro-ph.HE

FrankenStat I: a New Approach to Pulsar Timing Array Data Combination

In 2023, after more than two decades of searching, pulsar timing array (PTA) collaborations around the world announced evidence for a stochastic gravitational wave background. It was quickly followed by work from the International Pulsar Timing Array (IPTA), demonstrating that the results of regional collaborations were consistent with each other. The combination of these datasets is still ongoing and represents a significant investment of time and expertise. In that IPTA comparison, authors of this letter combined the separate datasets in the standard PTA optimal detection statistic for cross-correlations incoherently, that is, the data was combined without fitting a merged timing model across all PTA datasets, treating datasets of the same pulsar as independent, and neglecting the "same pulsar, different datasets" cross-correlations. This work refines that method by extending its core ideas beyond detection statistics and into a full, general data-combination method. We have demonstrated its efficacy and extreme efficiency on simulated data. This new method, \textit{FrankenStat}, is very similar in sensitivity and parameter-constraining power to traditional data combination methods while completing the full data combination in just a few minutes.

astro-ph.CO

Multimessenger Probes of the Supermassive Black Hole Binary Population: The Role of Pulsar Timing Arrays

By inferring the gravitational wave background (GWB) from a population of supermassive black hole binaries (SMBHBs), pulsar timing arrays (PTAs) enable the study of massive black holes. In many ways, PTAs manifest the promise of a multimessenger approach to astronomy: they can constrain SMBHB population characteristics that are otherwise difficult to constrain using electromagnetic observations, such as hardening mechanisms at sub-parsec separations. In this work, we quantify this multimessenger promise using Bayesian inference of many realizations of simulated PTA data, while adopting a model for the SMBHBs that has been successfully applied to the 15-year data set of the North American Nanohertz Observatory for Gravitational Waves (NANOGrav). Our analyses of 200 realistic, simulated NANOGrav data sets show that there is a greater than 50\% chance of reducing the prior uncertainty in the SMBHB hardening rate by more than 50\%, and in the SMBHB evolutionary lifetime by 25--75\%. Additionally, there is an 88\% chance that PTA data can reduce the prior uncertainty in the characteristic mass variable of the galaxy stellar mass function (GSMF) by 25--50\%. For $M_{\text{BH}}$--$M_{\text{Bulge}}$ parameters (in a model without redshift evolution) and the overall normalization parameter of the GSMF, PTA data can provide only marginal information gain beyond the constraints from electromagnetic observations. Our work delineates the domains over which electromagnetic and gravitational-wave data constrain the demographics and dynamics of the supermassive black-hole binary population, offering a clearer picture of the impact of population multi-messenger astrophysics probes with PTAs.

astro-ph.HE

The NANOGrav 12.5-year Data Set: Chromatic Noise Characterization & Mitigation with Time-Domain Kernels

Pulsar timing arrays (PTAs) have recently entered the detection era, quickly moving beyond the goal of simply improving sensitivity at the lowest frequencies for the sake of observing the stochastic gravitational wave background (GWB), and focusing on its accurate spectral characterization. While all PTA collaborations around the world use Fourier-domain Gaussian processes to model the GWB and intrinsic long time-correlated (red) noise, techniques to model the time-correlated radio frequency-dependent (chromatic) processes have varied from collaboration to collaboration. Here we test a new class of models for PTA data, Gaussian processes based on time-domain kernels that model the statistics of the chromatic processes starting from the covariance matrix. As we will show, these models can be effectively equivalent to Fourier-domain models in mitigating chromatic noise. This work presents a method for Bayesian model selection across the various choices of kernel as well as deterministic chromatic models for non-stationary chromatic events and the solar wind. As PTAs turn towards high frequency (>1/yr) sensitivity, the size of the basis used to model these processes will need to increase, and these time-domain models present some computational efficiencies compared to Fourier-domain models.

astro-ph.IM

The Dawn of Gravitational Wave Astronomy at Light-year Wavelengths: Insights from Pulsar Timing Arrays

Arrays of precisely-timed millisecond pulsars are used to search for gravitational waves with periods of months to decades. Gravitational waves affect the path of radio pulses propagating from a pulsar to Earth, causing the arrival times of those pulses to deviate from expectations based on the physical characteristics of the pulsar system. By correlating these timing residuals in a pulsar timing array (PTA), one can search for a statistically isotropic background of gravitational waves by revealing evidence for a distinctive pattern predicted by General Relativity, known as the Hellings \& Downs curve. On June 29 2023, five regional PTA collaborations announced the first evidence for GWs at light-year wavelengths, predicated on support for this correlation pattern with statistical significances ranging from $\sim\!2-4σ$. The amplitude and shape of the recovered GW spectrum has also allowed many investigations of the expected source characteristics, ranging from a cosmic population of supermassive binary black holes to numerous processes in the early Universe. In the future, we expect to resolve signals from individual binary systems of supermassive black holes, and probe fundamental assumptions about the background, including its polarization, anisotropy, Gaussianity, and stationarity, all of which will aid efforts to discriminate its origin. In tandem with new facilities like DSA-2000 and the SKA, fueling further observations by regional PTAs and the International Pulsar Timing Array, PTAs have extraordinary potential to be engines of nanohertz GW discovery.

astro-ph.HE

Finite Populations & Finite Time: The Non-Gaussianity of a Gravitational Wave Background

Strong evidence for an isotropic, Gaussian gravitational wave background (GWB) has been found by multiple pulsar timing arrays (PTAs). The GWB is expected to be sourced by a finite population of supermassive black hole binaries (SMBHBs) emitting in the PTA sensitivity band, and astrophysical inference of PTA data sets suggests a GWB signal that is at the higher end of GWB spectral amplitude estimates. However, current inference analyses make simplifying assumptions, such as modeling the GWB as Gaussian, assuming that all SMBHBs only emit at frequencies that are integer multiples of the total observing time, and ignoring the interference between the signals of different SMBHBs. In this paper, we build analytical and numerical models of an astrophysical GWB from circular, inspiralling binaries inclined relative to the line-of-sight of the observer, without the above approximations, and compare the statistical properties of its induced PTA signal to those of a signal produced by a Gaussian GWB. We show that finite population and windowing effects introduce non-Gaussianities in the PTA signal, which are currently unmodeled in PTA analyses.

gr-qc

Rapid Construction of Joint Pulsar Timing Array Datasets: The Lite Method

The International Pulsar Timing Array (IPTA)'s second data release (IPTA DR2) combines decades of observations of 65 millisecond pulsars from 7 radio telescopes. IPTA datasets should be the most sensitive datasets to nanohertz gravitational waves (GWs), but take years to assemble, often excluding valuable recent data. To address this, we introduce the IPTA "Lite" analysis, where a Figure of Merit is used to select an optimal PTA dataset to analyze for each pulsar, enabling immediate access to new data and preliminary results prior to full combination. We test the capabilities of the Lite analysis using IPTA DR2, finding that "DR2 Lite" can be used to detect the common red noise process with an amplitude of $A = 4.8^{+1.8}_{-1.8} \times 10^{-15}$ at $γ= 13/3$. This amplitude is slightly large in comparison to the combined analysis, and likely biased high as DR2 Lite is more sensitive to systematic errors from individual pulsars than the full dataset. Furthermore, although there is no strong evidence for Hellings-Downs correlations in IPTA DR2, we still find the full dataset is better at resolving Hellings-Downs correlations than DR2 Lite. Alongside the Lite analysis, we also find that analyzing a subset of pulsars from IPTA DR2, available at a hypothetical "early" stage of combination (EDR2), yields equally competitive results as the full dataset. Looking ahead, the Lite method will enable rapid synthesis of the latest PTA data, offering preliminary GW constraints before the superior full dataset combinations are available.

astro-ph.HE

Mapping the Gravitational-wave Background Across the Spectrum with a Next-Generation Anisotropic Per-frequency Optimal Statistic

With pulsar timing arrays (PTAs) having observed a gravitational wave background (GWB) at nanohertz frequencies, the focus of the field is shifting towards determining and characterizing its origin. While the primary candidate is a population of GW-emitting supermassive black hole binaries (SMBHBs), many other cosmological processes could produce a GWB with similar spectral properties as have been measured. One key argument to help differentiate an SMBHB GWB from a cosmologically sourced one is its level of anisotropy; a GWB sourced by a finite population will likely exhibit greater anisotropy than a cosmological GWB through finite source effects (``shot noise'') and potentially large-scale structure. Current PTA GWB anisotropy detection methods often use the frequentist PTA optimal statistic for its fast estimation of pulsar pair correlations and relatively low computational overhead compared to spatially-correlated Bayesian analyses. However, there are critical limitations with the status quo approach. In this paper, we improve this technique by incorporating three recent advancements: accounting for covariance between pulsar pairwise estimates of correlated GWB power; the per-frequency optimal statistic to dissect the GWB across the spectrum; and constructing null-hypothesis statistical distributions that include cosmic variance. By combining these methods, our new pipeline can localize GWB anisotropies to specific frequencies, through which anisotropy detection prospects -- while impacted by cosmic variance -- are shown to improve in our simulations from a $p$-value of $\sim0.2$ in a broadband search to $\sim0.01$ in the per-frequency search. Our methods are already incorporated in community-available code and ready to deploy on forthcoming PTA datasets.

astro-ph.IM