Results 81 to 90 of about 2,701,901 (263)
IEEE Transactions on Quantum EngineeringComputational fluid dynamics (CFD) simulations are crucial in industrial applications but require extensive computational resources, particularly for extreme turbulent regimes.
Francesco Turro +2 more
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Recall Performance for Content-Addressable Memory Using Adiabatic Quantum Optimization
Entropy, 2017 A content-addressable memory (CAM) stores key-value associations such that the key is recalled by providing its associated value. While CAM recall is traditionally performed using recurrent neural network models, we show how to solve this problem using ...
Jonathan Schrock +4 more
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The Fraunhofer quantum computing simulator
, 2022 S.469-480Fraunhofer FIRST develops a computing service and collaborative workspace providing a convenient tool for simulation and investigation of quantum algorithms1.
Rosé, H. +4 more
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Terra quantum at MIPT-QUANT 2020
, 2021 Funding Information: This work is supported by the Government of the Russian Federation (Agreement 05.Y09.21.0018) and by Terra Quantum AG. Publisher Copyright: © 2021 Author(s).Implementations of quantum information-processing systems require quantum ...
N. S. Kirsanov +9 more
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Advanced Functional Materials, EarlyView.Here, we develop a high‐throughput algorithm that accelerates the elucidation of phase diagrams of topological spin textures using limited computational resources at high numerical accuracy. Applying this framework to the van der Waals magnet CrSBr, we unveiled a hierarchy of previously unknown topological textures (domain‐wall bimerons, bimeron chains,
Andrew Lyall +4 more
wiley +1 more source
Impact of measurement noise on escaping saddles in variational quantum algorithms
Scientific ReportsStochastic gradient descent (SGD) is a widely used optimization technique in classical machine learning and the Variational Quantum Eigensolver (VQE). In VQE implementations on quantum hardware, measurement shot noise is inevitable.
Eriko Kaminishi +3 more
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Speeding up Answer Set Programming by Quantum Computing [PDF]
Quantum Computing has become a more and more prominent research field in the last few decades. This growth in interest is mainly related to the so-called quantum speed up that some quantum procedure exhibits.
Pessotto S. +7 more
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Advanced Functional Materials, EarlyView.Eu‐doped {ZnCdO/ZnO} structures grown on Si are developed, showcasing dual‐functionality controlled by europium doping. While high europium concentration transforms the device into an ultrafast, self‐powered photodetector, low‐doped structures can be used as an optoelectronic synapse.
Igor Perlikowski +3 more
wiley +1 more source
Quantum Machine Learning What Quantum Computing Means to Data Mining
, 2014 Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that explains the most ...
Wittek, Peter
core
Advanced Functional Materials, EarlyView.Nitride MXenes remain constrained by a persistent gap between computational prediction and experimental realization. This Review identifies the thermodynamic, kinetic, and chemical barriers limiting their synthesis, critically evaluates emerging fabrication routes, and proposes a multidimensional computational‐experimental framework to accelerate the ...
Naresh Varnakavi, Masoud Soroush
wiley +1 more source