arXiv subjects

Richard O'Shaughnessy

Publications and source records attributed to Richard O'Shaughnessy.

At least 37 records · Page 2Linked to original sources

arXiv2026

Analysis of GWTC-3 with fully precessing numerical relativity surrogate models

The third Gravitational-Wave Transient Catalog (GWTC-3) contains 90 binary coalescence candidates detected by the LIGO-Virgo-KAGRA Collaboration (LVK). We provide a re-analysis of binary black hole (BBH) events using a recently developed numerical relativity (NR) waveform surrogate model, NRSur7dq4, that includes all $\ell \leq 4$ spin-weighted spherical harmonic modes as well as the complete physical effects of precession. Properties of the remnant black holes' (BH's) mass, spin vector, and kick vector are found using an associated remnant surrogate model NRSur7dq4Remnant. Both NRSur7dq4 and NRSur7dq4Remnant models have errors comparable to numerical relativity simulations and allow for high-accuracy parameter estimates. We restrict our analysis to 47 BBH events that fall within the regime of validity of NRSur7dq4 (mass ratios greater than 1/6 and total masses greater than $60 M_{\odot}$). While for most of these events our results match the LVK analyses that were obtained using the semi-analytical models such as IMRPhenomXPHM and SEOBNRv4PHM, we find that for more than 20\% of events the NRSur7dq4 model recovers noticeably different measurements of black hole properties like the masses and spins, as well as extrinsic properties like the binary inclination and distance. For instance, GW150914_095045 exhibits noticeable differences in spin precession and spin magnitude measurements. Other notable findings include one event (GW191109_010717) that constrains the effective spin $χ_{eff}$ to be negative at a 99.3\% credible level and two events (GW191109_010717 and GW200129_065458) with well-constrained kick velocities. Furthermore, compared to the models used in the LVK analyses, NRSur7dq4 recovers a larger signal-to-noise ratio and/or Bayes factors for several events.

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arXiv2026

GW200105: A detailed study of eccentricity in the neutron star-black hole binary

GW200105_162426 is the first neutron star-black hole merger to be confidently confirmed through either gravitational-wave or electromagnetic observations. Although initially analyzed after detection, the event has recently gained renewed attention following a study [Morras et al. arXiv:2503.15393] that employed a post-Newtonian inspiral-only waveform model and reported strong evidence for orbital eccentricity. In this work, we perform a detailed analysis of GW200105 using state-of-the-art effective-one-body waveform models. Importantly, we present the first study of this event utilizing a physically complete model that incorporates both orbital eccentricity and spin precession across the full inspiral, merger, and ringdown stages, along with higher-order gravitational wave modes. Our results support the presence of eccentricity in the signal, with zero eccentricity excluded from the 99% credible interval, but yielding a mass ratio closer to the original LIGO-Virgo-KAGRA analysis, differing from the findings of [Morras et al. arXiv:2503.15393]. Additionally, similar to a previous eccentric-only analysis [de Lluc Planas et al. Astrophys. J. 995, 47 (2025).], we observe a multimodal structure in the eccentricity posterior distribution. We conduct targeted investigations to understand the origin of this multimodality and complement our analysis with numerical relativity simulations to examine how the inclusion of eccentricity impacts the merger dynamics.

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arXiv2025

Astrophysical assumptions and equation of state framework have larger impact on equation of state inference than individual neutron star observations

The wide range of nuclear densities achieved in neutron stars makes them probes of dense nuclear behavior in the form of the nuclear equation of state (EoS). Studying neutron stars both in isolation, with X-ray measurements and pulse profiling, and in dynamic events, such as neutron star mergers, have provided insight into these high nuclear densities. Though nominally congruent, here we highlight impact of implicit assumptions embedded in joint analysis of these messengers and their systematic impact on EoS inference. We show that astrophysical assumptions and EoS framework can have a larger effect on inferred EoS than individual contemporary neutron star observations. Performing a proof-of-concept demonstration using the chronologically first few observational constraints, after the application of 5 to 6 observational constraints, additional observations provided diminishing returns and modified the inferred EoS by shifting the radius of a 1.4 $\unit{M_\odot}$ NS by $\sim$ 0.1 km. By contrast, astrophysical priors, specifically the spin and mass ratio motivated by astrophysical source population uncertainties, and EoS framework tend to impact EoS inference much more substantially by shifting the 1.4 $\unit{M_\odot}$ NS radius by $\sim$ 0.5 km and by modifying shape of inferred mass-radius relationship. The inferred EoS depends strongly on the adopted choice of spectral parameterizations: when we employ a framework which explicitly enforces causality, we find a strong phase-transition-like feature at $\sim 10^{14.5}$ g cm$^{-3}$.

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arXiv2025

McFACTS II: Mass Ratio--Effective Spin Relationship of Black Hole Mergers in the AGN Channel

We use the Monte Carlo For AGN (active galactic nucleus) Channel Testing and Simulation (McFACTS, https://www.github.com/mcfacts/mcfacts) code to study the effect of AGN disk and nuclear star cluster parameters on predicted mass distributions for LIGO-Virgo-KAGRA (LVK) compact binaries forming in AGN disks. The assumptions we vary include the black hole (BH) initial mass function, disk model, disk size, disk lifetime, and the prograde-to-retrograde fraction of newly formed black hole binaries. Broadly we find that dense, moderately short-lived AGN disks are preferred for producing a $(q,χ_{\rm eff})$ anti-correlation like those identified from existing gravitational wave (GW) observations. Additionally, a BH initial mass function (MF $\propto M^{-2}$) is preferred over a more top-heavy MF ($M^{-1}$). The preferred fraction of prograde-to-retrograde is $>90\%$, to produce results consistent with observations.

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arXiv2025

McFACTS I: Testing the LVK AGN channel with Monte Carlo For AGN Channel Testing & Simulation (McFACTS)

Active galactic nuclei (AGN) are a promising source of the binary black hole (BBH) mergers observed in gravitational waves with LIGO-Virgo-Kagra (LVK). Constraining the AGN channel allows us to limit AGN parameter space (disk density, size, average lifetime) and nuclear star cluster (NSC) parameter space. Constraints on AGN and NSCs have implications for $Λ$CDM models of AGN feedback and models of AGN-driven SMBH merger and growth. Here we present several qualitative studies of the AGN channel using new public, open-source, fast, reproducible code \texttt{McFACTS}\footnote{https://github.com/mcfacts/mcfacts}:Monte Carlo for AGN channel Testing \& Simulation. We demonstrate several important features for testing the AGN channel, including: i) growth to large mass IMBH is helped by the presence of migration traps or swamps, ii) flat BH initial mass functions highlight hierarchical merger features in the mass spectrum, iii) the ($q,χ_{\rm eff}$) anti-correlation is a strong test of the bias to prograde mergers in the AGN channel, iv) spheroid encounters can drive a fraction of mergers with high in-plane spin components ($χ_{\rm p}$), v) a high rate of extreme mass ratio inspirals (EMRIs) are driven by an initial population of embedded retrograde BH, vi) Both LVK and LISA are powerful probes of models of AGN disks and their embedded populations.

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arXiv2025

Parameter estimation of gravitational waves from hyperbolic black hole encounters

Systems of two black holes with unbound orbits can produce a diverse array of gravitational wave signals with rich morphology. This parameter space encompasses both hyperbolic orbit scattering events and dynamical captures, including zoom-whirl orbits with multiple flybys and direct plunge mergers. These signals challenge traditional parameter estimation infrastructure, which is largely optimized for quasicircular inspiral binaries. In this work we discuss the adaptation of the Rapid Iterative FiTting (RIFT) algorithm to this problem using the TEOBResumSDALI waveform model which can simulate generic orbits. We present results from a study of simulated signals emulating a scatter and plunge event, utilizing the design sensitivity of the forthcoming Cosmic Explorer interferometer. Our analysis demonstrates that RIFT accurately recovers the mass, spins, and hyperbolic orbit parameters: the system energy and angular momentum defined at a fiducial initial separation.

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arXiv2025

McFacts III: Compact binary mergers from AGN disks over an entire synthetic universe

The Active Galactic Nuclei (AGN) channel for the formation of binary black hole (BBH) mergers has been previously studied as a potential formation channel for the merging compact binaries observed by the LIGO/Virgo/KAGRA (LVK) scientific collaboration. The first two papers in this series explored the McFACTS code for the evolution of black hole orbits in AGN accretion disks for individual galaxy models and described the characteristics of predicted BBH populations in realizations of those models (such as the correlation between mass ratio and aligned spin). In this work, we explore the impact of the properties of AGN host galaxies and assume an AGN lifetime and cosmological model for the density of AGN in a universe like our own. By sampling from an inferred population of AGN, we marginalize over galaxy mass to predict a population of BBH mergers observable by modern ground-based gravitational wave observatories. We find that for reasonable assumptions, AGN disk environments may account for massive BBH mergers such as GW190521 and GW190929_012149. We find that the majority of observable BBH mergers from our simulation are expected to originate in galaxies with a super-massive black hole between $10^{7}M_{\odot}$ and $10^{9.4}M_{\odot}$. We also find that if hierarchical mergers from AGN disks account for a substantial part of the LVK population, our current models require an AGN lifetime of 0.5 to 2.5 Myr.

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arXiv2025

Adapting a novel framework for rapid inference of massive black hole binaries for LISA

The Laser Interferometer Space Antenna (LISA) is designed to detect a variety of gravitational-wave events, including mergers of massive black hole binaries, stellar-mass black hole inspirals, and extreme mass-ratio inspirals. LISA's capability to observe signals with high signal-to-noise ratios raises concerns about waveform accuracy. Additionally, its ability to observe long-duration signals will raise the computational cost of Bayesian inference, making it challenging to use costly and novel models with standard stochastic sampling methods without incorporating likelihood and waveform acceleration techniques. In this work, we present our attempt to tackle these issues. We adapt ${\tt RIFT}$ for LISA to take advantage of its embarrassingly parallel architecture, enabling efficient analysis of large datasets with costly gravitational wave models without relying on likelihood or waveform acceleration. We demonstrate that our open-source code can accurately infer parameters of massive black hole binary signals by carrying out a zero-noise injection recovery using the numerical relativity surrogate model ${\tt NRHybSur3dq8}$. By utilizing all available $m\neq0$ modes in the inference, we study the impact of higher modes on LISA data analysis. We study the impact of multiple massive black hole binary signals in a dataset on the inference of a single signal, showing that the selected source's inference remains largely unaffected. Furthermore, we analyze the LDC-1A and blind LDC-2A datasets from the Radler and Sangria challenge of the LISA data challenges. When eschewing specialized hardware, we find ${\tt NRHybSur3dq8}$ injection-recovery takes approximately $20$ hours to complete, while the analysis of Sangria and Radler datasets takes about $10$ hours to complete.

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arXiv2025

Properties of 'Lite' Intermediate-Mass Black Hole Candidates in LIGO-Virgo's Third Observing Run

Over a hundred gravitational-wave (GW) detections and candidates have been reported from the first three observing runs of the Advanced LIGO-Virgo-KAGRA (LVK) detectors. Among these, the most intriguing events are binary black hole mergers that result in a 'lite' intermediate-mass black hole (IMBH) of ${\sim}10^2~\mathrm{M}_\odot$, such as GW170502 and GW190521. In this study, we investigate 11 GW candidates from LVK's Third Observing Run (April 2019-March 2020) that have a total detector-frame masses in the lite IMBH range. Using the Bayesian inference algorithm \texttt{RIFT}, we systematically analyze these candidates with three state-of-the-art waveform models that incorporate higher harmonics, which are crucial for resolving lite IMBHs in LVK data. For each candidate, we infer the pre-merger and post-merger black hole masses in the source frame, along with black hole spin projections across all three models. Under the assumption that these are binary black hole mergers, our analysis finds that 5 of them have a post-merger lite IMBH with masses ranging from $110\sim 350~\mathrm{M}_\odot$ with over 90\% confidence interval. Additionally, we note that one of their pre-merger black holes is within the pair-instability supernova mass gap ($60-120~\mathrm{M}_\odot$) with more than 90\% confidence interval, and additional two pre-merger black holes above the mass-gap. Furthermore, we report discrepancies among the three waveform models in their mass and spin inferences of lite IMBHs, with at least three GW candidates showing deviations beyond accepted statistical limits. While the astrophysical certainty of these candidates cannot be established, our study provides a foundation to probe the lite IMBH population that emerge within the low-frequency noise spectrum of LVK detectors.

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arXiv2025

Recovering Injected Astrophysics from the LISA Galactic Double White Dwarf Binaries

We present the successful recovery of common envelope ejection efficiency assumed in a simulated population of double white dwarf binaries like those which may be observed by the future LISA mission. We simulate the formation of double white dwarf binaries by using the COSMIC population synthesis code to sample binary formation conditions such as initial mass function, metallicity of star formation, initial orbital period, and initial eccentricity. These binaries are placed in the m12i synthetic Milky-Way-like galaxy, and their signal-to-noise ratio for the LISA instrument is estimated, considering a galactic gravitational wave foreground informed by the population. Through the use of Fisher estimates, we construct a likelihood function for the measurement error of the LISA-bright DWD binaries (> 20 SNR, fGW > 5mHz), in their gravitational wave frequency (fGW) and chirp mass. By repeating this process for different assumptions of the common envelope ejection efficiency, we apply Bayesian hierarchical inference to find the best match to an injected astrophysical assumption for a fiducial population model. We conclude that the impact of common envelope ejection efficiency on the mass transfer processes involved in double white dwarf formation may be statistically relevant in the future observed LISA population, and that constraints on binary formation may be found by comparing simulated populations to a future observed population.

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arXiv2024

Effects of waveform systematics on inferences of neutron star population properties and the nuclear equation of state

Gravitational waves from inspiralling neutron stars carry information about matter at extreme gravity and density. The binary neutron star (BNS) event GW170817 provided, for the first time, insight into dense matter through this window. Since then, another BNS (GW190425) and several neutron star-black hole events have been detected, although the tidal measurements were not expected to be well-constrained from them. Collective information regarding the behavior of nuclear matter at extreme densities can be done by performing a joint population inference for the masses, spins, and equation-of-state [1] to enable better understanding. This population inference, in turn, relies on accurate estimates of intrinsic parameters of individual events. In this study, we investigate how the differences in parameter inference of BNS events using different waveform models can affect the eventual inference of the nuclear equation-of-state. We use the state-of-the-art model TEOBResumS with IMRPhenomD NRTidalv2 as a comparison model.

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arXiv2024

Kilonova Light-Curve Interpolation with Neural Networks

Kilonovae are the electromagnetic transients created by the radioactive decay of freshly synthesized elements in the environment surrounding a neutron star merger. To study the fundamental physics in these complex environments, kilonova modeling requires, in part, the use of radiative transfer simulations. The microphysics involved in these simulations results in high computational cost, prompting the use of emulators for parameter inference applications. Utilizing a training set of 22248 high-fidelity simulations (composed of 412 unique ejecta parameter combinations evaluated at 54 viewing angles), we use a neural network to efficiently train on existing radiative transfer simulations and predict light curves for new parameters in a fast and computationally efficient manner. Our neural network can generate millions of new light curves in under a minute. We discuss our emulator's degree of off-sample reliability and parameter inference of the AT2017gfo observational data. Finally, we discuss tension introduced by multi-band inference in the parameter inference results, particularly with regard to the neural network's recovery of viewing angle.

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arXiv2024

Inference on neutron star parameters and the nuclear equation of state with RIFT, using prior EOS information

In this paper, we present an inference method for determining neutron star parameters and constraining the nuclear equation of state (EOS) using the RIFT parameter inference engine. We incorporate externally-produced prior information about the EOS to improve the accuracy and efficiency of the inference process. We apply this method to the GW170817 event and assess its performance. Our results demonstrate the effectiveness of incorporating prior EOS information in the inference process, leading to sharper conclusions and more rapid inference on new detections. This approach has the potential to enhance our understanding of neutron stars and the nuclear EOS in future gravitational wave observations.

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arXiv2024

Eccentricity matters: Impact of eccentricity on inferred binary black hole populations

Gravitational waves (GW), emanating from binary black holes (BBH), encode vital information about their source. GW signals enable us to deduce key properties of the BBH population across the universe, including mass, spin, and eccentricity distribution. While the masses and spins of binary components are already recognized for their insights into formation, eccentricity stands out as a distinct and quantifiable indicator of formation and evolution. Yet, despite its significance, eccentricity is notably absent from most parameter estimation (PE) analyses associated with GW signals. To evaluate the precision with which the eccentricity distribution can be deduced, we generated two synthetic populations of eccentric binary black holes (EBBH) characterized by non-spinning, non-precessing dynamics and mass ranges between $10 M_\odot$ and $50 M_\odot$. This was achieved using an eccentric power law model, encompassing $100$ events with eccentricity distributions set at $σ_ε= 0.05$ and $σ_ε= 0.15$. This synthetic EBBH ensemble was contrasted against a circular binary black holes (CBBH) collection to discern how parameter inferences would vary without eccentricity. Employing Markov Chain Monte Carlo (MCMC) techniques, we constrained vital model parameters, including the event rate ($\mathcal{R}$), mass distribution, minimum mass ($m_{min}$), maximum mass ($m_{max}$), and the eccentricity distribution ($σ_ε$). Our analysis demonstrates that eccentric population inference can identify the signatures of even modest eccentricities, given sufficiently many events. Conversely, our study shows that an analysis neglecting eccentricity may draw biased conclusions about population parameters for populations with the optimistic values of eccentricity distribution used in our research.

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arXiv2024

Parameter Estimation for Low-Mass Eccentric Black Hole Binaries

Recent studies have shown that orbital eccentricity may indicate dynamical assembly as a formation mechanism for binary black holes. Eccentricity leaves a distinct signature in gravitational wave signals and it may be measured if the binary remains eccentric when it enters the LIGO band. Although eccentricity has not yet been confidently detected, the possibility of detecting eccentric binaries is becoming more likely with the improved sensitivity of gravitational wave detectors such as LIGO, Virgo, and KAGRA. It is crucial to assess the accuracy of current search pipelines in recovering eccentricity from gravitational wave signals if it is present. In this study, we investigate the ability of parameter estimation pipeline RIFT to recover eccentricity in the non-spinning and aligned-spin cases for low mass binary black holes. We use TaylorF2Ecc and TEOBResumS to inject sets of synthetic signals and test how well RIFT accurately recovers key binary black hole parameters. Our findings provide valuable insights into the capability of current parameter estimation methods to detect and measure eccentricity in gravitational wave signals.

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arXiv2023

Iteratively Comparing Gravitational-Wave Observations to the Evolution of Massive Stellar Binaries

Gravitational-wave observations have the capability to strongly differentiate between different assumptions for how binary compact objects form. In this work, we show how to carefully interpolate a marginal likelihood between choices of binary evolution model parameters. Using the StarTrack binary evolution code, we compare one- and four-dimensional binary evolution models to the compact binary mergers reported in recent gravitational-wave observing runs. We first consider a one-dimensional model, studying the effect of supernova kick velocity (drawn from a Maxwellian with dispersion σ_eff) on the simulated population of compact binary mergers, and find support for substantial SN recoil kicks. We follow this up with a four-dimensional study of σ_eff, mass transfer efficiency (fa) and the efficiency of angular momentum depletion from ejected material (\b{eta}) during Roche-lobe accretion, and an observation-driven reduction in the mass-loss rate estimated from stellar wind models (fwind1). We find that three of them (σ_eff, fa, and fwind1) can be efficiently limited by these observational comparisons. After initially sampling from a uniform prior in the space of these parameters, we refined our sampling by iteratively estimating a Bayesian likelihood for each simulation and fitting that likelihood to a parametric model (a truncated Gaussian) in order to propose new. Our maximum likelihood simulation (K0559) has parameters: σ_eff = 108.3 km/s (indicating substantial SN recoil kicks), fa = 0.922 (indicating efficient mass transfer), and fwind1 = 0.328 (indicating support for reduced wind-driven mass loss). Note that our estimates are only valid within one particular model of compact binary formation through isolated binary evolution and do not yet take into account the impact of other uncertain pieces of stellar physics and binary evolution.

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arXiv2023

Interpolated kilonova spectra models: necessity for a phenomenological, blue component in the fitting of AT2017gfo spectra

In this work, we present a simple interpolation methodology for spectroscopic time series, based on conventional interpolation techniques (random forests) implemented in widely-available libraries. We demonstrate that our existing library of simulations is sufficient for training, producing interpolated spectra that respond sensitively to varied ejecta parameter, post-merger time, and viewing angle inputs. We compare our interpolated spectra to the AT2017gfo spectral data, and find parameters similar to our previous inferences using broadband light curves. However, the spectral observations have significant systematic short-wavelength residuals relative to our models, which we cannot explain within our existing framework. Similar to previous studies, we argue that an additional blue component is required. We consider a radioactive heating source as a third component characterized by light, slow-moving, lanthanide-free ejecta with $M_{\rm th} = 0.003~M_\odot$, $v_{\rm th} = 0.05$c, and $κ_{\rm th} = 1$ cm$^2$/g. When included as part of our radiative transfer simulations, our choice of third component reprocesses blue photons into lower energies, having the opposite effect and further accentuating the blue-underluminosity disparity in our simulations. As such, we are unable to overcome short-wavelength deficits at later times using an additional radioactive heating component, indicating the need for a more sophisticated modeling treatment.

astro-ph.HE↗

arXiv2023

Surrogate light curve models for kilonovae with comprehensive wind ejecta outflows and parameter estimation for AT2017gfo

The electromagnetic emission resulting from neutron star mergers have been shown to encode properties of the ejected material in their light curves. The ejecta properties inferred from the kilonova emission has been in tension with those calculated based on the gravitational wave signal and numerical relativity models. Motivated by this tension, we construct a broad set of surrogate light curve models derived for kilonova ejecta. The four-parameter family of two-dimensional anisotropic simulations and its associated surrogate explore different assumptions about the wind outflow morphology and outflow composition, keeping the dynamical ejecta component consistent. We present the capabilities of these surrogate models in interpolating kilonova light curves across various ejecta parameters and perform parameter estimation for AT2017gfo both without any assumptions on the outflow and under the assumption that the outflow must be representative of solar r-process abundance patterns. Our parameter estimation for AT2017gfo shows these surrogate models help alleviate the ejecta property discrepancy while also illustrating the impact of systematic modeling uncertainties on these properties, urging further investigation.

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