Results 311 to 320 of about 4,251,069 (374)
Some of the next articles are maybe not open access.

Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging: Combining physics and machine learning for improved medical imaging

IEEE Signal Processing Magazine, 2022
Physics-driven deep learning methods have emerged as a powerful tool for computational magnetic resonance imaging (MRI) problems, pushing reconstruction performance to new limits.
K. Hammernik   +6 more
semanticscholar   +1 more source

Racial hierarchy and masculine space: Participatory in/equity in computational physics classrooms

Computer Science Education, 2020
Background and Context Computing is being integrated into a range of STEM disciplines. Still, computing remains inaccessible to many minoritized groups, especially girls and certain people of color. In this mixed methods study, we investigated racial and
Niral Shah   +6 more
semanticscholar   +1 more source

Computational Physics

2016
Το βιβλίο έρχεται να καλύψει ένα σημαντικό κενό στην ελληνική επιστημονική βιβλιογραφία στο πεδίο του εισαγωγικού επιστημονικού προγραμματισμού για μηχανικούς και επιστήμονες. Βασίζεται σε τρία μαθήματα που ο συγγραφέας έχει θεμελιώσει και διδάξει από το 2004 στο ΕΜΠ και απευθύνεται κυρίως σε 3ετείς και 4ετείς προπτυχιακούς φοιτητές σχολών θετικών ...
  +4 more sources

Machine learning for modelling unstructured grid data in computational physics: a review

Information Fusion
Unstructured grid data are essential for modelling complex geometries and dynamics in computational physics. Yet, their inherent irregularity presents significant challenges for conventional machine learning (ML) techniques.
Sibo Cheng   +22 more
semanticscholar   +1 more source

Application of Wavelet Methods in Computational Physics

Annals of Physics
The quantitative study of many physical problems ultimately boils down to solving various partial differential equations (PDEs). Wavelet analysis, known as the “mathematical microscope”, has been hailed for its excellent Multiresolution Analysis (MRA ...
Jizeng Wang, Xiaojing Liu, Y. Zhou
semanticscholar   +1 more source

Computational Physics

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
openaire   +2 more sources

Physical computation

Concurrency: Practice and Experience, 1991
AbstractPhysical computation embraces a variety of physical analogies used to tackle non‐traditional problems. We describe Monte Carlo and deterministic methods, including simulated annealing and neural networks. Applications include economic change in Eastern Europe, the travelling salesman problem, vehicle navigation, track finding, and parallel ...
openaire   +1 more source

Physics’ Evolution Toward Computing

International Journal of Theoretical Physics, 2020
The paper is devoted to the problem of describing quantum computing by using quantum mechanics: The authors show various multiple operations through both the superposition and the phase factor connected by the phase kick-back formation. The authors review the construction of logical functions in a Boolean algebra, like AND, OR, XOR, and in general the ...
Tadao Nakamura, Koji Nagata
openaire   +2 more sources

Computer Supported Physics Experiments

AIP Conference Proceedings, 2007
The use of computer in physics experiments simplifies getting data. It also gives a great convenience in calculation and getting graphs that helps interpretation of the results. It’s possible to use a computer as a measurement device by correct interface system and software.
Istanbullu D.N., Dumanoglu I.
openaire   +1 more source

Computational Physics

Computers in Physics, 1997
Nicholas J. Giordano   +3 more
  +5 more sources

Home - About - Disclaimer - Privacy