Results 61 to 70 of about 4,121,664 (393)
The Physics of Quantum Information [PDF]
arXiv, 2022 Rapid ongoing progress in quantum information science makes this an apt time for a Solvay Conference focused on The Physics of Quantum Information. Here I review four intertwined themes encompassed by this topic: Quantum computer science, quantum hardware, quantum matter, and quantum gravity.
arxiv
Cassirer and Bohr on Intuitive and Symbolic Knowledge in Quantum Physics
Theoria, 2014 This paper compares Cassirer´s and Bohr´s views on symbolic knowledge in quantum physics. Although both of them consider quantum physics as symbolic knowledge, for Cassirer this amounts to a complete renunciation to intuition in quantum physics, while ...
Hernán Pringe
doaj +1 more source
An Approach to Quantum Physics Teaching through Analog Experiments
Physics, 2022 With quantum physics being a particularly difficult subject to teach because of its contextual distance from everyday life, the need for multiperspective teaching material arises.
Stefan Aehle +2 more
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, 2012 In this paper, we review some features of quantum annealing and related topics from viewpoints of statistical physics, condensed matter physics, and computational physics.
Tamura, Ryo, Tanaka, Shu
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Fine-grained uncertainty relation and nonlocality of tripartite systems
, 2011 The upper bound of the fine-grained uncertainty relation is different for classical physics, quantum physics and no-signaling theories with maximal nonlocality (supper quantum correlation), as was shown in the case of bipartite systems [J.
A. S. Majumdar +3 more
core +1 more source
Quantum Algorithm for High Energy Physics Simulations.
Physical Review Letters, 2021 Simulating quantum field theories is a flagship application of quantum computing. However, calculating experimentally relevant high energy scattering amplitudes entirely on a quantum computer is prohibitively difficult.
B. Nachman +3 more
semanticscholar +1 more source
Quantum Convolutional Neural Networks for High Energy Physics Data Analysis [PDF]
Physical Review Research, 2020 This work presents a quantum convolutional neural network (QCNN) for the classification of high energy physics events. The proposed model is tested using a simulated dataset from the Deep Underground Neutrino Experiment.
Samuel Yen-Chi Chen +4 more
semanticscholar +1 more source
Physical Implementations for Quantum Communication in Quantum Networks [PDF]
Technical Digest. Summaries of Papers Presented at the International Quantum Electronics Conference. Conference Edition. 1998 Technical Digest Series, Vol.7 (IEEE Cat. No.98CH36236), 1999 A quantum network where the data stored, processed, and communicated consists of quantum bits, would offer exciting possibilities including teleportation, dense coding, quantum money, secured quantum key distribution, and perhaps distributed quantum computing. But how to implement such a network?
Briege, H. -J. +6 more
openaire +5 more sources
A condition for any realistic theory of quantum systems
, 2007 In quantum physics, the density operator completely describes the state. Instead, in classical physics the mean value of every physical quantity is evaluated by means of a probability distribution. We study the possibility to describe pure quantum states
A. Montina +8 more
core +1 more source
Quantum machine learning in high energy physics [PDF]
Machine Learning: Science and Technology, 2020 Machine learning has been used in high energy physics (HEP) for a long time, primarily at the analysis level with supervised classification. Quantum computing was postulated in the early 1980s as way to perform computations that would not be tractable ...
W. Guan +6 more
semanticscholar +1 more source