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On the Prevalence and Nature of Computational Instruction in Undergraduate Physics Programs across the United States [PDF]
Physical Review Physics Education Research, 2018 A national survey of physics faculty was conducted to investigate the prevalence and nature of computational instruction in physics courses across the United States. 1246 faculty from 357 unique institutions responded to the survey.
Caballero, Marcos D., Merner, Laura
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, 2007 First published in 2007, this second edition describes the computational methods used in theoretical physics. New sections were added to cover finite element methods and lattice Boltzmann simulation, density functional theory, quantum molecular dynamics, Monte Carlo simulation, and diagonalisation of one-dimensional quantum systems.
Rubin H. Landau +2 more
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Computational Thinking in Introductory Physics [PDF]
The Physics Teacher, 2020 Computational Thinking (CT) is still a relatively new term in the lexicon of learning objectives and science standards. There is not yet widespread agreement on the precise definition or implementation of CT, and efforts to assess CT are still maturing ...
C. M. Orban, R. M. Teeling-Smith
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XXVI IUPAP Conference on Computational Physics (CCP2014) [PDF]
, 2015 The 26th IUPAP Conference on Computational Physics, CCP2014, was held in Boston, Massachusetts, during August 11-14, 2014. Almost 400 participants from 38 countries convened at the George Sherman Union at Boston University for four days of plenary and ...
Campbell, D.K. +3 more
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Undergraduate computational physics education: uneven history and promising future [PDF]
Computing in science & engineering (Print), 2016 While some physics educators have included computing in courses or have developed specialized courses for over 50 years, computational physics education has only slowly made inroads into the broader physics education community. Even now, when computation
Richard Martin
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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
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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
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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
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Physics computational literacy: An exploratory case study using computational essays [PDF]
Physical Review Physics Education Research, 2019 Computation is becoming an increasingly important part of physics education. However, there are currently few theories of learning that can be used to help explain and predict the unique challenges and affordances associated with computation in physics ...
T. Odden +2 more
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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
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