Results 71 to 80 of about 3,098,393 (374)

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, G. Perdue, Arthur Pesah, M. Schuld, K. Terashi, S. Vallecorsa, J. Vlimant   +6 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., Cirac, J. I., Dür, W., van Enk, S. J., Kimble, H. J., Mabuchi, H., Zoller, P.   +6 more
openaire   +5 more sources

Mechanistic basis for inhibition of the extended‐spectrum β‐lactamase GES‐1 by enmetazobactam and tazobactam

FEBS Letters, EarlyView.
Antimicrobial resistance (AMR) is of huge importance, resulting in over 1 million deaths each year. Here, we describe how a new drug, enmetazobactam, designed to help fight resistant bacterial diseases, inhibits a key enzyme (GES‐1) responsible for AMR. Our data show it is a more potent inhibitor than the related tazobactam, with high‐level computation
Michael Beer, Philip Hinchliffe, Marko Hanževački, Christopher R. Bethel, Catherine L. Tooke, Marc W. Van der Kamp, Krisztina M. Papp‐Wallace, Robert A. Bonomo, Stuart Shapiro, Adrian J. Mulholland, James Spencer   +10 more
wiley   +1 more source

Quantumness speeds up quantum thermodynamics processes

iScience
Summary: Quantum thermodynamic process involves manipulating and controlling quantum states to extract energy or perform computational tasks with high efficiency.
Ming-Xing Luo
doaj   +1 more source

Quantum Systems for Enhanced High Energy Particle Physics Detectors

Frontiers in Physics, 2022
Developments in quantum technologies in the last decades have led to a wide range of applications, but have also resulted in numerous novel approaches to explore the low energy particle physics parameter space.
M. Doser, E. Auffray, F.M. Brunbauer, I. Frank, I. Frank, H. Hillemanns, G. Orlandini, G. Orlandini, G. Kornakov   +8 more
doaj   +1 more source

A Categorical Framework for Quantum Theory

, 2009
Underlying any theory of physics is a layer of conceptual frames. They connect the mathematical structures used in theoretical models with physical phenomena, but they also constitute our fundamental assumptions about reality.
Aharonov, Aspect, Bell, Bitbol, Cramer, Dalla Chiara, deWitt, Einstein, Einstein, Everett, Filk, Ghirardi, Greenberger, Griffiths, Haag, Hiley, Horodecki, Károlyházy, Omnés, Oppenheim, Oppenheim, Rovelli, Schlosshauer, Scully, Scully, Smerlak, Tumulka, von Weizsäcker   +27 more
core   +1 more source

From Cbits to Qbits: Teaching computer scientists quantum mechanics [PDF]

, 2002
A strategy is suggested for teaching mathematically literate students, with no background in physics, just enough quantum mechanics for them to understand and develop algorithms in quantum computation and quantum information theory.
Mermin, N. David
core   +2 more sources

Teaching Einsteinian physics at schools: part 2, models and analogies for quantum physics [PDF]

, 2017
The Einstein-First project approaches the teaching of Einsteinian physics through the use of physical models and analogies. This paper presents an approach to the teaching of quantum physics which begins by emphasising the particle-nature of light ...
T. Kaur, David Blair, John Moschilla, M. Zadnik   +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, T. Wei, Chao Zhang, Haiwang Yu, Shinjae Yoo   +4 more
semanticscholar   +1 more source

Mechanochemical Synthesis and Characterization of Nanostructured ErB4 and NdB4 Rare‐Earth Tetraborides

Advanced Engineering Materials, Volume 27, Issue 6, March 2025.
ErB4 and NdB4 nanostructured powders are produced by mechanochemical synthesis. 5 h mechanical alloying and 4 M HCl acid leaching are used in the production. ErB4 and NdB4 powders exhibit maximum magnetization of 0.4726 emu g−1 accompanied with an antiferromagnetic‐to‐paramagnetic phase transition at about TN = 18 K and 0.132 emu g−1 with a maximum at ...
Burçak Boztemur, Faruk Kaya, Bora Derin, Mustafa Lütfi Öveçoğlu, Ju Li, Duygu Ağaoğulları   +5 more
wiley   +1 more source