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We study the coalescence of non-spinning binary black holes from near the innermost stable circular orbit down to the final single rotating black hole. We use a technique that combines the full numerical approach to solve Einstein…

General Relativity and Quantum Cosmology · Physics 2009-09-25 J. Baker , B. Bruegmann , M. Campanelli , C. O. Lousto , R. Takahashi

The rapid expansion of data from diverse sources has made anomaly detection (AD) increasingly essential for identifying unexpected observations that may signal system failures, security breaches, or fraud. As datasets become more complex…

Machine Learning · Computer Science 2025-03-18 Haoqi Huang , Ping Wang , Jianhua Pei , Jiacheng Wang , Shahen Alexanian , Dusit Niyato

Weakly-modelled searches for gravitational waves are essential for ensuring that all potential sources are accounted for in detection efforts, as they make minimal assumptions regarding source morphology. While these searches primarily…

General Relativity and Quantum Cosmology · Physics 2025-10-06 Leigh Smith , Matteo Scialpi , Francesco di Clemente , Michał Bejger

Deep learning approaches to anomaly detection have recently improved the state of the art in detection performance on complex datasets such as large collections of images or text. These results have sparked a renewed interest in the anomaly…

Orbital eccentricity in compact binary mergers carries crucial information about the binary's formation and environment. There are emerging signs that some of the mergers detected by the LIGO and Virgo gravitational wave detectors could…

Anomaly detection based on one-class classification algorithms is broadly used in many applied domains like image processing (e.g. detection of whether a patient is "cancerous" or "healthy" from mammography image), network intrusion…

Machine Learning · Statistics 2017-07-14 Evgeny Burnaev , Pavel Erofeev , Dmitry Smolyakov

Dark matter overdensities around black holes can alter the dynamical evolution of a companion object orbiting around it, and cause a dephasing of the gravitational waveform. Here, we present a refined calculation of the co-evolution of the…

General Relativity and Quantum Cosmology · Physics 2025-10-10 Theophanes K. Karydas , Bradley J. Kavanagh , Gianfranco Bertone

Black-hole binary coalescences are one of the most promising sources for the first detection of gravitational waves. Fast and accurate theoretical models of the gravitational radiation emitted from these coalescences are highly important…

General Relativity and Quantum Cosmology · Physics 2014-10-17 Michael Pürrer

With the goal of bringing theory, particularly numerical relativity, to bear on an astrophysical problem of critical interest to gravitational wave observers we introduce a model for coalescence radiation from binary black hole systems. We…

Astrophysics · Physics 2009-11-07 J. Baker , M. Campanelli , C. O. Lousto , R. Takahashi

Establishing accurate morphological measurements of galaxies in a reasonable amount of time for future big-data surveys such as EUCLID, the Large Synoptic Survey Telescope or the Wide Field Infrared Survey Telescope is a challenge. Because…

Instrumentation and Methods for Astrophysics · Physics 2017-06-14 D. Tuccillo , M. Huertas-Company , E. Decenciere , S. Velasco-Forero

The detection of gravitational-wave signals from coalescing eccentric binary black holes would yield unprecedented information about the formation and evolution of compact binaries in specific scenarios, such as dynamical formation in dense…

General Relativity and Quantum Cosmology · Physics 2021-06-09 Yoshinta Setyawati , Frank Ohme

Quadratic quasinormal modes encode fundamental properties of black hole spacetimes. They are also one of the key ingredients of nonlinearities of General Relativity in the ringdown stage of binary black hole coalescence. In this work, we…

General Relativity and Quantum Cosmology · Physics 2025-06-23 Neev Khera , Sizheng Ma , Huan Yang

We construct few deep generative models of gravitational waveforms based on the semi-supervising scheme of conditional autoencoders and their variational extensions. Once the training is done, we find that our best waveform model can…

Instrumentation and Methods for Astrophysics · Physics 2021-06-30 Chung-Hao Liao , Feng-Li Lin

Active learning has been utilized as an efficient tool in building anomaly detection models by leveraging expert feedback. In an active learning framework, a model queries samples to be labeled by experts and re-trains the model with the…

Machine Learning · Computer Science 2023-09-19 Minkyung Kim , Junsik Kim , Jongmin Yu , Jun Kyun Choi

We use artificial intelligence (AI) to learn and infer the physics of higher order gravitational wave modes of quasi-circular, spinning, non precessing binary black hole mergers. We trained AI models using 14 million waveforms, produced…

Instrumentation and Methods for Astrophysics · Physics 2022-10-28 Asad Khan , E. A. Huerta , Prayush Kumar

Binary black hole systems are among the most important sources for gravitational wave detection. And also they are good objects for theoretical research for general relativity. Gravitational waveform template is important to data analysis.…

General Relativity and Quantum Cosmology · Physics 2017-08-30 Zhoujian Cao , Wen-Biao Han

Recent advances in scanning transmission electron and scanning probe microscopies have opened exciting opportunities in probing the materials structural parameters and various functional properties in real space with angstrom-level…

The development of both ground- and space-based gravitational wave detectors provides new opportunities to observe the radiation from binaries containing neutron stars and black holes. Numerical simulations in 3-D are essential for…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Joan M. Centrella

There are two major types of uncertainty one can model. Aleatoric uncertainty captures noise inherent in the observations. On the other hand, epistemic uncertainty accounts for uncertainty in the model -- uncertainty which can be explained…

Computer Vision and Pattern Recognition · Computer Science 2017-10-06 Alex Kendall , Yarin Gal