Related papers: A fully precessing higher-mode surrogate model of …
The phenomenological gravitational waveform models, which we refer to as PhenomA, PhenomB and PhenomC, generate full inspiral-merger-ringdown waveforms of coalescing binary back holes (BBHs). These models are defined in the Fourier domain,…
Building on the analytical description of the post-merger (ringdown) waveform of coalescing, non-precessing, spinning, (BBHs) introduced in Phys. Rev. D 90, 024054 (2014), we propose an analytic, closed form, time-domain, representation of…
We introduce \TEOBiResumSM{}, a nonspinning inspiral-merger-ringdown waveform model built within the effective one body (EOB) framework that includes gravitational waveform modes beyond the dominant quadrupole $(\ell,|m|) = (2,2)$. The…
The computational resources required to solve the full 3D inversion of time-domain electromagnetic data are immense. To overcome the time-consuming 3D simulations, we construct a surrogate model, more precisely, a data-driven statistical…
The present paper proposes a Bayesian framework for inverse problems that seamlessly integrates optimization and inversion to enable rapid surrogate modeling, accurate parameter inference, and rigorous uncertainty quantification. Bayesian…
The recent direct observation of gravitational waves has further emphasized the desire for fast, low-cost, and accurate methods to infer the parameters of gravitational wave sources. Due to expense in waveform generation and data handling,…
We present an accurate approximation of the full gravitational radiation waveforms generated in the merger of non-eccentric systems of two non-spinning black holes. Utilizing information from recent numerical relativity simulations and the…
We compare recently computed waveforms from second-order gravitational self-force (GSF) theory to those generated by a new, GSF-informed, effective one body (EOB) waveform model for (spin-aligned, eccentric) inspiralling black hole binaries…
Waveform models are important to gravitational wave data analysis. People recently pay much attention to the waveform model construction for eccentric binary black hole coalescence. Several Effective-One-Body Numerical-Relativity waveform…
Driven by advances in scattering amplitudes and worldline-based methods, recent years have seen significant progress in our ability to calculate gravitational two-body scattering observables. These observables effectively encapsulate the…
The estimation of unknown values of parameters (or hidden variables, control variables) that characterise a physical system often relies on the comparison of measured data with synthetic data produced by some numerical simulator of the…
We present the first attempt at calibrating the effective-one-body (EOB) model to accurate numerical-relativity simulations of spinning, non-precessing black-hole binaries. Aligning the EOB and numerical waveforms at low frequency over a…
In many mechanistic medical, biological, physical and engineered spatiotemporal dynamic models the numerical solution of partial differential equations (PDEs) can make simulations impractically slow. Biological models require the…
The surrogate matrix methodology delivers low-cost approximations of matrices (i.e., surrogate matrices) which are normally computed in Galerkin methods via element-scale quadrature formulas. In this paper, the methodology is applied to a…
We propose a surrogate function for efficient yet principled use of score-based priors in Bayesian imaging. We consider ill-posed inverse imaging problems in which one aims for a clean image posterior given incomplete or noisy measurements.…
Metasurface-based radar absorbing structures (RAS) are highly preferred for applications like stealth technology, electromagnetic (EM) shielding, etc. due to their capability to achieve frequency selective absorption characteristics with…
We introduce pyEFPEHM, a post-Newtonian (PN) inspiral waveform model for eccentric and spin-precessing compact binaries that includes higher-order modes and matter effects. Accurate and efficient waveform models capturing these effects are…
We present a framework for automatically structuring and training fast, approximate, deep neural surrogates of stochastic simulators. Unlike traditional approaches to surrogate modeling, our surrogates retain the interpretable structure and…
For many novel applications, such as patient-specific computer-aided surgery, conventional solution techniques of the underlying nonlinear problems are usually computationally too expensive and are lacking information about how certain can…
We develop a model for frequency-domain gravitational waveforms from inspiraling binary neutron stars. Our waveform model is calibrated by comparison with hybrid waveforms constructed from our latest high-precision numerical-relativity…