Results 151 to 160 of about 2,804,318 (294)

Probing black hole charge from the binary black hole inspiral

Physical Review D
Recent gravitational wave (GW) observations have enabled us to look beyond the standard paradigm of gravitational physics, namely general relativity (GR). Along with the mass and the angular momentum, which typical astrophysical black holes (BHs) are endowed with, theories beyond GR generically induce `charge' to these BHs.
N. V. Krishnendu, Sumanta Chakraborty
openaire   +2 more sources

Binary black-hole simulation SXS:BBH:0932

, 2019
Simulation of a black-hole binary system evolved by the SpEC ...
SXS Collaboration (6908459), SXS Collaboration   +1 more
core   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Binary black-hole simulation SXS:BBH:1015

, 2019
Simulation of a black-hole binary system evolved by the SpEC ...
SXS Collaboration (6908459), SXS Collaboration   +1 more
core   +1 more source

FastCat: Autonomous Discovery of Multielement Layered Double Hydroxide Alloy Catalysts for Alkaline Oxygen Evolution Reaction

Advanced Intelligent Discovery, EarlyView.
A machine learning‐guided self‐driving laboratory screened over 500 nickel‐based layered double‐hydroxide catalysts for alkaline oxygen evolution. Out of the eight metals, the robot uncovered a quaternary Ni–Fe–Cr–Co catalysts requiring only 231 mV overpotential to reach 20 mA cm−2.
Nis Fisker‐Bødker, Enzo Raffaele Moretti, Jin Hyun Chang, Tejs Vegge   +3 more
wiley   +1 more source

The Metallicity Dependence and Evolutionary Times of Merging Binary Black Holes: Combined Constraints from Individual Gravitational-wave Detections and the Stochastic Background

The Astrophysical Journal
The advent of gravitational-wave astronomy is now allowing for the study of compact binary merger demographics throughout the Universe. This information can be leveraged as tools for understanding massive stars, their environments, and their evolution ...
Kevin Turbang, Max Lalleman, Thomas A. Callister, Nick van Remortel   +3 more
doaj   +1 more source

Binary black-hole simulation SXS:BBH:0663

, 2019
Simulation of a black-hole binary system evolved by the SpEC ...
Matt Giesler (6912353), SXS Collaboration (6908459), SXS Collaboration, Matt Giesler   +3 more
core   +1 more source

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

Binary black-hole simulation SXS:BBH:0772

, 2019
Simulation of a black-hole binary system evolved by the SpEC ...
SXS Collaboration (6908459), SXS Collaboration   +1 more
core   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source