Related papers: Expect the unexpected: augmented mixture models fo…
Measuring the distribution of spin tilts-the angles between the spin vectors and the binary orbital angular momentum-in stellar-mass binary black holes detected by LIGO-Virgo-KAGRA would provide valuable insight into their astrophysical…
Gravitational waves from compact binary mergers provide a direct measurement of luminosity distance, which, in combination with redshift information, serves as a cosmological probe. In order to statistically infer merger redshifts, the…
We construct hybrid binary black holes merger waveforms using analytical model waveforms for the early inspiral phase and numerical relativity waveforms for late inspiral to merger and post merger phases. To hybridize analytical and…
Black hole (BH) binary mergers formed through dynamical interactions in dense star clusters are believed to be one of the main sources of gravitational waves for Advanced LIGO and Virgo. Here we present a fast numerical method for…
Prior to the detection of black holes (BHs) via the gravitational waves (GWs) they generate at merger, the presence of BHs was inferred in X-ray binaries, mostly via dynamical measurements, with masses in the range between $\sim…
The events detected by the LIGO Virgo KAGRA collaboration over a period of 10 years have yielded a treasure trove of signals from compact binary coalescences. None of these events have shown a confident signature of eccentricity. With…
Despite a decade's worth of gravitational wave observation, the origin of the binary black hole (BBH) mergers detected by the LIGO-VIRGO-Kagra (LVK) collaboration remains an open question. Towards assessing the feasibility and prevalence of…
Gravitational waves from extreme mass-ratio inspirals (EMRIs) will enable sub-percent measurements of massive black hole parameters and provide access to the demographics of compact objects in galactic nuclei. During the LISA mission,…
The population of the observed gravitational wave events encodes unique information on the formation and evolution of stellar-mass black holes, from the underlying astrophysical processes to the large-scale dynamics of the Universe. We use…
We pioneer the black hole mass gap as a powerful new tool for constraining modified gravity theories. These theories predict fifth forces that alter the structure and evolution of population-III stars, exacerbating the pair-instability.…
We develop a new method based on Gaussian process to reconstruct the mass distribution of binary black holes (BBHs). Instead of prespecifying the formalisms of mass distribution, we introduce a more flexible and nonparametric model with…
We study the phenomenology of non-spinning eccentric binary black hole (BBH) mergers using numerical relativity (NR) waveforms and \texttt{EccentricIMR} waveform model, as presented in Ref. \cite{Hinder:2017sxy} (Hinder, Kidder, and…
With better statistics and precision, eccentricity could prove to be a useful tool for understanding the origin and environment of binary black holes. Hierarchical triples in particular, which might be abundant in globular clusters and…
In numerical evolutions of binary black holes (BBH) it is desirable to easily control the orbital eccentricity of the BBH, and the number of orbits completed by the binary through merger. This paper presents fitting formulae that allow to…
We introduce a Bayesian approach to predictive density calibration and combination that accounts for parameter uncertainty and model set incompleteness through the use of random calibration functionals and random combination weights.…
We study mixture of linear regression (random coefficient) models, which capture population heterogeneity by allowing the regression coefficients to follow an unknown distribution $G^*$. In contrast to common parametric methods that fix the…
The Dirichlet process mixture model and more general mixtures based on discrete random probability measures have been shown to be flexible and accurate models for density estimation and clustering. The goal of this paper is to illustrate…
Binary black hole (BBH) mergers,, an important source of gravitational-waves(GWs), are assumed to be hosted in galaxies. The probability of a galaxy to host a BBH is related to its properties, for example stellar mass and star formation…
Hierarchical Bayesian inference is an essential tool for studying the population properties of compact binaries with gravitational waves. The basic premise is to infer the unknown prior distribution of binary black hole and/or neutron star…
To improve the predictability of complex computational models in the experimentally-unknown domains, we propose a Bayesian statistical machine learning framework utilizing the Dirichlet distribution that combines results of several…