Results 41 to 50 of about 1,395,355 (286)

Neural network representation of quantum systems

Machine Learning: Science and Technology
It has been proposed that random wide neural networks near Gaussian process are quantum field theories around Gaussian fixed points. In this paper, we provide a novel map with which a wide class of quantum mechanical systems can be cast into the form of ...
Koji Hashimoto, Yuji Hirono, Jun Maeda, Jojiro Totsuka-Yoshinaka   +3 more
doaj   +1 more source

Numerical Simulation of the Solid Particle Sedimentation and Bed Formation Behaviors Using a Hybrid Method

Energies, 2020
In the safety analysis of sodium-cooled fast reactors, numerical simulations of various thermal-hydraulic phenomena with multicomponent and multiphase flows in core disruptive accidents (CDAs) are regarded as particularly difficult.
Md Abdur Rob Sheikh, Xiaoxing Liu, Tatsuya Matsumoto, Koji Morita, Liancheng Guo, Tohru Suzuki, Kenji Kamiyama   +6 more
doaj   +1 more source

Quantum discord and non-Markovianity of quantum dynamics

, 2012
The problem of recognizing (non-)Markovianity of a quantum dynamics is revisited through analyzing quantum correlations. We argue that instantaneously-vanishing quantum discord provides a necessary and sufficient condition for Markovianity of a quantum ...
A. Mani, A. T. Rezakhani, H. Carmichael, H.-P. Breuer, M. A. Nielsen, S. Alipour   +5 more
core   +1 more source

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

Advanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani, Surabhi Nadigotti, Erfan Fatehi, Derek Aranguren van Egmond, Behnam Ashrafi   +4 more
wiley   +1 more source

Machine learning-based compression of quantum many body physics: PCA and autoencoder representation of the vertex function

Machine Learning: Science and Technology
Theoretical approaches to quantum many-body physics require developing compact representations of the complexity of generic quantum states. This paper explores an interpretable data-driven approach utilizing principal component analysis (PCA) and ...
Jiawei Zang, Matija Medvidović, Dominik Kiese, Domenico Di Sante, Anirvan M Sengupta, Andrew J Millis   +5 more
doaj   +1 more source

Is Quantum Chaos Weaker Than Classical Chaos?

, 2003
We investigate chaotic behavior in a 2-D Hamiltonian system - oscillators with anharmonic coupling. We compare the classical system with quantum system.
Bohigas, Bohigas, Cametti, Caron, Casetti, D. Huard, Dahlquist, Dembrowski, Friedman, Friedrich, G. Melkonyan, H. Kröger, Heller, Hensinger, Huard, Iacomelli, Jirari, Jirari, Jirari, K.J.M. Moriarty, Kröger, L.A. Caron, L.P. Nadeau, Matinyan, McDonald, Milner, Parmenter, Partovi, Prasad, Pullen, Schwengelbeck, Steck   +31 more
core   +1 more source

First‐Principles Modeling of Solid Solution Softening and Hardening Effects in Al–Mg–Zr–Si Aluminum Alloys

Advanced Engineering Materials, EarlyView.
The role of various alloying elements in face‐centered cubic aluminum on the barrier of a Shockley partial dislocation during its motion is presented. The study aims to understand how alloying atoms such as Mg, Si, and Zr affect the energy landscape for dislocation motion, thus influencing the solid solution hardening and softening in aluminum, which ...
Inna Plyushchay, Zhengqing Wei, Nebahat Bulut, Sibylle Gemming   +3 more
wiley   +1 more source

Optimization of a Diamond Nitrogen Vacancy Centre Magnetometer for Sensing of Biological Signals

Frontiers in Physics, 2020
Sensing of signals from biological processes, such as action potential propagation in nerves, are essential for clinical diagnosis and basic understanding of physiology.
James L. Webb, Luca Troise, Nikolaj W. Hansen, Jocelyn Achard, Ovidiu Brinza, Robert Staacke, Michael Kieschnick, Jan Meijer, Jean-François Perrier, Kirstine Berg-Sørensen, Alexander Huck, Ulrik Lund Andersen   +11 more
doaj   +1 more source

Direct Electron Detection Electron Energy‐Loss Spectroscopy: Speeding Up 2D Analytical In Situ Transmission Electron Microscopy for Aluminum Alloys

Advanced Engineering Materials, EarlyView.
Scanning transmission electron microscopy imaging techniques are an essential tool to document dynamic developments, such as precipitation in aluminum alloys, during in situ heating experiments using transmission electron microscopy. However, in many cases, chemical information is required to interpret complex nanoscale processes.
Evelin Fisslthaler, Martina Dienstleder, Judith Lammer, Moritz Theissing, Daniel Knez   +4 more
wiley   +1 more source

Investigation of hydrogen generation from the reaction of beryllium pebbles with water vapor for WCCB-TBM

Nuclear Materials and Energy
Be pebble, as a neutron multiplier material, is being explored for the development of a Water-Cooled Ceramic Breeder Test Blanket Module (WCCB-TBM) in Japan for the International Thermonuclear Experiment Reactor (ITER) project.
Yuki Koga, Jae-Hwan Kim, Yuga Ohta, Yoshinori Kawamura, Masaru Nakamichi, Takanori Hirose   +5 more
doaj   +1 more source