Results 11 to 20 of about 4,141,656 (337)
A computational framework for physics-informed symbolic regression with straightforward integration of domain knowledge [PDF]
Scientific Reports, 2022 Discovering a meaningful symbolic expression that explains experimental data is a fundamental challenge in many scientific fields. We present a novel, open-source computational framework called Scientist-Machine Equation Detector (SciMED), which ...
Liron Simon Keren +2 more
semanticscholar +1 more source
Educational Administration: Theory and Practice, 2022 This study aimed to analyze the factor model affecting the implementation of the Generative Learning Model with a Cognitive Conflict Strategy in the Computational Physics Course during the COVID-19 pandemic era.
A. Akmam +4 more
semanticscholar +1 more source
Jurnal Neutrino: Jurnal Fisika dan Aplikasinya, 2021 Neutrino can carry information from places that cannot be reached by the usual detection mechanism because it has a very weak interaction with matter. This can be utilized to study the heat flow process inside the earth by using information carried by ...
Akmal Ferdiyan +1 more
doaj +1 more source
An introduction to programming Physics-Informed Neural Network-based computational solid mechanics [PDF]
International Journal of Computational Methods, 2022 Physics-informed neural network (PINN) has recently gained increasing interest in computational mechanics. In this work, we present a detailed introduction to programming PINN-based computational solid mechanics.
Jinshuai Bai +8 more
semanticscholar +1 more source
Turbulence in Accretion Disks: Vorticity Generation and Angular Momentum Transport via the Global Baroclinic Instability [PDF]
, 2002 In this paper we present the global baroclinic instability as a source for vigorous turbulence leading to angular momentum transport in Keplerian accretion disks.
H. Klahr +5 more
semanticscholar +1 more source
Six textbook mistakes in computational physics [PDF]
, 2020 This article discusses several erroneous claims which appear in textbooks on numerical methods and computational physics. These are not typos or mistakes an individual author has made, but widespread misconceptions.
A. Gezerlis, M. Williams
semanticscholar +1 more source
CRYSTAL23: A Program for Computational Solid State Physics and Chemistry
Journal of Chemical Theory and Computation, 2022 The Crystal program for quantum-mechanical simulations of materials has been bridging the realm of molecular quantum chemistry to the realm of solid state physics for many years, since its first public version released back in 1988.
A. Erba +14 more
semanticscholar +1 more source
Transverse confinement of electron beams in a 2D optical lattice for compact coherent x-ray sources
New Journal of Physics, 2021 Compact coherent x-ray sources have been the focus of extensive research efforts over the past decades. As a result, several novel schemes like optical and nano-undulators for generating x-ray emissions in ‘table-top’ setups are proposed, developed, and ...
Arya Fallahi +2 more
doaj +1 more source
Equivariant neural networks for spin dynamics simulations of itinerant magnets
Machine Learning: Science and Technology, 2023 I present a novel equivariant neural network architecture for the large-scale spin dynamics simulation of the Kondo lattice model. This neural network mainly consists of tensor-product-based convolution layers and ensures two equivariances: translations ...
Yu Miyazaki
doaj +1 more source
Physics-Informed Deep Learning for Traffic State Estimation: A Survey and the Outlook
Algorithms, 2023 For its robust predictive power (compared to pure physics-based models) and sample-efficient training (compared to pure deep learning models), physics-informed deep learning (PIDL), a paradigm hybridizing physics-based models and deep neural networks ...
Xuan Di +3 more
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