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Development and evaluation of granular simulation for integrating computational thinking into computational physics courses. [PDF]

Educ Inf Technol (Dordr), 2022
Computational thinking (CT) is an essential skill in the twenty-first century. The computational physics course (CPC) is one subject that is designed to support students in the practice of CT.
Muliyati D, Sumardani D, Siswoyo S, Bakri F, Permana H, Handoko E, Sari NLK.   +6 more
europepmc   +2 more sources

Active learning algorithm for computational physics [PDF]

Physical Review Research, 2020
In large-scale computations of physical problems, one often encounters the situation of having to determine a multidimensional function, which can be numerically costly when computing each point in this multidimensional space is already time-demanding ...
Juan Yao, Yadong Wu, Jahyun Koo, Binghai Yan, Hui Zhai   +4 more
doaj   +2 more sources

Deep Learning and Computational Physics (Lecture Notes) [PDF]

arXiv.org, 2023
These notes were compiled as lecture notes for a course developed and taught at the University of the Southern California. They should be accessible to a typical engineering graduate student with a strong background in Applied Mathematics.
Deep Ray, Orazio Pinti, A. Oberai
semanticscholar   +1 more source

Physicality, modeling, and agency in a computational physics class [PDF]

Physical Review Physics Education Research, 2022
Computation is intertwined with essentially all aspects of physics research and is invaluable for physicists' careers. Despite its disciplinary importance, integration of computation into physics education remains a challenge and, moreover, has tended to
A. M. Phillips, E. Gouvea, B. Gravel, P. Beachemin, T. Atherton   +4 more
semanticscholar   +1 more source

Data augmentation and feature selection for automatic model recommendation in computational physics [PDF]

Mathematical and Computational Applications, 2021
Classification algorithms have recently found applications in computational physics for the selection of numerical methods or models adapted to the environment and the state of the physical system.
Thomas Daniel, F. Casenave, N. Akkari, D. Ryckelynck   +3 more
semanticscholar   +1 more source

An efficient ptychography reconstruction strategy through fine-tuning of large pre-trained deep learning model

iScience, 2023
Summary: With pre-trained large models and their associated fine-tuning paradigms being constantly applied in deep learning, the performance of large models achieves a dramatic boost, mostly owing to the improvements on both data quantity and quality ...
Xinyu Pan, Shuo Wang, Zhongzheng Zhou, Liang Zhou, Peng Liu, Chun Li, Wenhui Wang, Chenglong Zhang, Yuhui Dong, Yi Zhang   +9 more
doaj   +1 more source

Exploring Projections for HIV Infection with Pre-Exposure Prophylaxis Usage in a High-Risk Population

Applied Sciences, 2022
Prevention of type-1 human immunodeficiency virus (HIV) infections has primarily been through condom usage, abstinence, and behavioral and risk awareness programs.
Jeramy Lewis, Robert E. Camley
doaj   +1 more source

Parameterized neural ordinary differential equations: applications to computational physics problems [PDF]

Proceedings of the Royal Society A, 2020
This work proposes an extension of neural ordinary differential equations (NODEs) by introducing an additional set of ODE input parameters to NODEs. This extension allows NODEs to learn multiple dynamics specified by the input parameter instances.
Kookjin Lee, E. Parish
semanticscholar   +1 more source

Search for high-Tcconventional superconductivity at megabar pressures in the lithium-sulfur system [PDF]

Physical review B, 2016
Superconductivity at high-pressures has attracted considerable interest after the report of a record critical temperature (${T}_{c}$) of 203 K in sulfur hydride (H${}_{3}$S) at 200 GPa.
C. Kokail, C. Heil, L. B. I. O. Theoretical, Computational Physics, Graz University of Technology Department of Materials, U. Oxford   +5 more
semanticscholar   +1 more source

Need analysis to develop a generative learning model with a cognitive conflict strategy oriented to creative thinking in the Computational Physics course

Journal of Physics: Conference Series, 2022
The discovery learning model with the strategy of exploring questions no longer increases students’ understanding of Computational Physics, for this reason, a cognitive conflict-based generative learning model is developed.
A. Akmam, R. Hidayat, F. Mufit, N. Jalinus, A. Amran   +4 more
semanticscholar   +1 more source