Results 11 to 20 of about 1,786,533 (325)
Physics informed deep learning for computational elastodynamics without labeled data [PDF]
Journal of engineering mechanics, 2020 Numerical methods such as finite element have been flourishing in the past decades for modeling solid mechanics problems via solving governing partial differential equations (PDEs).
Chengping Rao, Hao Sun, Yang Liu
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Machine learning–accelerated computational fluid dynamics [PDF]
Proceedings of the National Academy of Sciences of the United States of America, 2021 Significance Accurate simulation of fluids is important for many science and engineering problems but is very computationally demanding. In contrast, machine-learning models can approximate physics very quickly but at the cost of accuracy.
Dmitrii Kochkov +5 more
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Active learning algorithm for computational physics [PDF]
Physical Review Research, 2019 In large-scale computation of physics problems, one often encounters the problem of determining a multi-dimensional function, which can be time-consuming when computing each point in this multi-dimensional space is already time-demanding. In the work, we
Juan Yao +4 more
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Difference schemes of high order accuracy for mathematical physics problems in arbitrary domains
Mathematical Modelling and Analysis, 2000 In the present paper the difference schemes of high order accuracy for two‐dimensional equations of mathematical physics in an arbitrary domain are constructed. The computational domain is covered by a uniform rectangular grid.
P. P. Matus, A. N. Zyl
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Journal of Advances in Modeling Earth Systems, 2021 Previous studies have shown that atmospheric models with a spectral element grid can benefit from putting physics calculations on a relatively coarse finite volume grid.
W. Hannah +5 more
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Journal of Physics: Conference Series, 2019 Computational thinking that is an essential skill which everyone should learn, especially in Computational Physics courses. Problems in learning Computational Physics courses in the Department of Physics was the ability of students in analyzing problems ...
A. Akmam +3 more
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Quantum Computing for High-Energy Physics: State of the Art and Challenges [PDF]
PRX Quantum, 2023 Quantum computers offer an intriguing path for a paradigmatic change of computing in the natural sciences and beyond, with the potential for achieving a so-called quantum advantage—namely, a significant (in some cases exponential) speedup of numerical ...
A. D. Meglio +45 more
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Developing a project-based computational physics course grounded in expert practice [PDF]
, 2016 We describe a project-based computational physics course developed using a backwards course design approach. From an initial competency-based model of problem solving in computational physics, we interviewed faculty who use these tools in their own ...
Christopher J Burke, T. Atherton
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Lepton-nucleon interactions at the next-to-the-leading order [PDF]
, 2009 Next-to-Leading-Order (NLO) effects play a crucial role in tests of the Standard Model (SM), and require careful theoretical evaluation. Electroweak physics, which has just entered the precision age, is an excellent place to search for new physics, but ...
A Aleksejevs +7 more
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, 2018 Misconception is one of the factors causing students are not suitable in to choose a method for problem solving. Computational Physics course is a major subject in the Department of Physics FMIPA UNP Padang.
A. Akmam +4 more
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