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We perform a comprehensive analysis of state-of-the-art waveform models, focusing on their predictions concerning kick velocity and inferred gravitational wave memory. In our investigation we assess the accuracy of waveform models using…

General Relativity and Quantum Cosmology · Physics 2024-03-01 Fabio D'Ambrosio , Francesco Gozzini , Lavinia Heisenberg , Henri Inchauspé , David Maibach , Jann Zosso

One of the main bottlenecks in gravitational wave (GW) astronomy is the high cost of performing parameter estimation and GW searches on the fly. We propose a novel technique based on Reduced Order Quadratures (ROQs), an application and…

General Relativity and Quantum Cosmology · Physics 2013-09-26 Priscilla Canizares , Scott E. Field , Jonathan R. Gair , Manuel Tiglio

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…

Machine Learning · Computer Science 2022-07-18 Saurabh Deshpande , Jakub Lengiewicz , Stéphane P. A. Bordas

Simulating the mechanical response of advanced materials can be done more accurately using concurrent multiscale models than with single-scale simulations. However, the computational costs stand in the way of the practical application of…

Machine Learning · Computer Science 2024-02-21 J. Storm , I. B. C. M. Rocha , F. P. van der Meer

Characterizing the interior structure of exoplanets is an inverse problem often solved using Bayesian inference, but this approach is hampered by the high computational cost of planetary structure models. To overcome this barrier, we…

Earth and Planetary Astrophysics · Physics 2025-12-22 Tijn De Wringer , Caroline Dorn , Emily O. Garvin , Stefano Marelli

This article presents an original methodology for the prediction of steady turbulent aerodynamic fields. Due to the important computational cost of high-fidelity aerodynamic simulations, a surrogate model is employed to cope with the…

Fluid Dynamics · Physics 2019-12-05 Romain Dupuis , Jean-Christophe Jouhaud , Pierre Sagaut

Bayesian parameter estimation of gravitational waves from compact binary coalescence (CBC) typically requires more than millions of evaluations of computationally expensive template waveforms. We propose a technique to reduce the cost of…

General Relativity and Quantum Cosmology · Physics 2021-09-01 Soichiro Morisaki

Computational Intelligence (CI) techniques have shown great potential as a surrogate model of expensive physics simulation, with demonstrated ability to make fast predictions, albeit at the expense of accuracy in some cases. For many…

We continue the program of constructing, within the Effective-One-Body (EOB) approach, high accuracy, faithful analytic waveforms describing the gravitational wave signal emitted by inspiralling and coalescing binary black holes (BHs). We…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Thibault Damour , Alessandro Nagar

We construct a new factorized waveform including $(l,|m|)=(2,2),(2,1),(3,3),(4,4)$ modes based on effective-one-body (EOB) formalism, which is valid for spinning binary black holes (BBH) in general equatorial orbit. When combined with the…

General Relativity and Quantum Cosmology · Physics 2022-02-02 Xiaolin Liu , Zhoujian Cao , Zong-Hong Zhu

A machine-learning-based framework for modeling the error introduced by surrogate models of parameterized dynamical systems is proposed. The framework entails the use of high-dimensional regression techniques (e.g., random forests, LASSO)…

Numerical Analysis · Computer Science 2017-06-02 Sumeet Trehan , Kevin Carlberg , Louis J. Durlofsky

Global optimization of expensive functions has important applications in physical and computer experiments. It is a challenging problem to develop efficient optimization scheme, because each function evaluation can be costly and the…

Machine Learning · Statistics 2020-01-22 Ray-Bing Chen , Yuan Wang , C. F. Jeff Wu

Computational models are utilized in many scientific domains to simulate complex systems. Sensitivity analysis is an important practice to aid our understanding of the mechanics of these models and the processes they describe, but…

Methodology · Statistics 2022-08-12 Massimo Aufiero , Lucas Janson

Mounting evidence indicates that some of the gravitational wave signals observed by the LIGO/Virgo/KAGRA observatories might arise from eccentric compact object binaries, increasing the urgency for accurate waveform models for such systems.…

Surrogate models provide a quick-to-evaluate approximation to complex computational models and are essential for multi-query problems like design optimisation. The inputs of current deterministic computational models are usually…

Applications · Statistics 2024-10-15 Thomas A. Archbold , Ieva Kazlauskaite , Fehmi Cirak

Accurate and predictive scale-resolving simulations of laser-ignited rocket engines are highly time-consuming because the problem includes turbulent fuel-oxidizer mixing dynamics, laser-induced energy deposition, and high-speed flame…

Machine Learning · Computer Science 2026-03-10 Tony Zahtila , Ettore Saetta , Murray Cutforth , Davy Brouzet , Diego Rossinelli , Gianluca Iaccarino

Inferring the astrophysical parameters of coalescing compact binaries is a key science goal of the upcoming advanced LIGO-Virgo gravitational-wave detector network and, more generally, gravitational-wave astronomy. However, current…

General Relativity and Quantum Cosmology · Physics 2015-03-05 Priscilla Canizares , Scott E. Field , Jonathan Gair , Vivien Raymond , Rory Smith , Manuel Tiglio

Upgrades to current gravitational wave detectors for the next observation run and upcoming third-generation observatories, like the Einstein telescope, are expected to have enormous improvements in detection sensitivities and compact object…

General Relativity and Quantum Cosmology · Physics 2026-04-21 Suyog Garg , Feng-Li Lin , Kipp Cannon

We present a parameter estimation framework for gravitational wave (GW) signals that brings together several ideas to accelerate the inference process. First, we use the relative binning algorithm to evaluate the signal-to-noise-ratio…

General Relativity and Quantum Cosmology · Physics 2022-10-31 Tousif Islam , Javier Roulet , Tejaswi Venumadhav

Building upon several recent advances in the development of effective-one-body models for spin-aligned eccentric binaries with individual masses $(m_1,m_2)$ we introduce a new EOB waveform model that aims at describing inspiralling binaries…

General Relativity and Quantum Cosmology · Physics 2022-10-12 Alessandro Nagar , Simone Albanesi