Results 81 to 90 of about 118,204 (269)
A Genetic Quantum Annealing Algorithm
CoRR, 2022 12 pages, 12 ...
Steven Abel +2 more
openaire +2 more sources
Advanced Functional Materials, EarlyView.This review systematically highlights the latest achievements in mixed‐valence states relevant to hydrogen and oxygen evolution reactions, providing essential insights into future directions and methods for large‐scale practical implementation. This critical review is expected to provide an overview of recent advancements in diverse valence‐state metal
Jitendra N. Tiwari +4 more
wiley +1 more source
Quantum Annealing for Prime Factorization [PDF]
Scientific Reports, 2018 AbstractWe have developed a framework to convert an arbitrary integer factorization problem to an executable Ising model by first writing it as an optimization function then transforming the k-bit coupling (k ≥ 3) terms to quadratic terms using ancillary variables. Our resource-efficient method uses $${\mathscr{O}}({\mathrm{log}}^{2}(N))$$
Shuxian Jiang +4 more
openaire +3 more sources
2D Magnetic and Topological Quantum Materials and Devices for Ultralow Power Spintronics
Advanced Functional Materials, EarlyView.2D magnets and topological quantum materials enable ultralow‐power spintronics by combining robust magnetic order with symmetry‐protected, Berry‐curvature‐driven transport. Fundamentals of 2D anisotropy and spin‐orbit‐coupling induced band inversion are linked to scalable growth and vdW stacking.
Brahmdutta Dixit +5 more
wiley +1 more source
Mathematical foundation of quantum annealing [PDF]
Journal of Mathematical Physics, 2008 Quantum annealing is a generic name of quantum algorithms that use quantum-mechanical fluctuations to search for the solution of an optimization problem. It shares the basic idea with quantum adiabatic evolution studied actively in quantum computation. The present paper reviews the mathematical and theoretical foundations of quantum annealing.
Satoshi Morita, Hidetoshi Nishimori
openaire +3 more sources
Advanced Functional Materials, EarlyView.Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner +14 more
wiley +1 more source
Decoherence of a tunable capacitively shunted flux qubit
Communications PhysicsQuantum annealing is a method to solve optimization problems that leverages quantum tunneling in a coupled qubit system. We present a detailed study of the coherence of a tunable capacitively-shunted flux qubit, designed for coherent quantum annealing ...
Robbyn Trappen +21 more
doaj +1 more source
Quantum Annealing of a Disordered Magnet [PDF]
Science, 1999 Traditional simulated annealing uses thermal fluctuations for convergence in optimization problems. Quantum tunneling provides a different mechanism for moving between states, with the potential for reduced time scales. Thermal and quantum annealing are compared in a model disordered magnet, where the effects of quantum mechanics can be tuned by ...
J. Brooke +4 more
openaire +4 more sources
Advanced Functional Materials, EarlyView.Molten KNO2 treatment induces a lowrefractive index disordered carbon shell on fluorescent nanodiamonds, enhancing fluorescence emission while preserving spin coherence. Machine learningassisted correlative TEMPL enables direct single‐particle resolution of this enhancement relative to air‐oxidized nanodiamonds of similar morphology, establishing a ...
Parkarsh Kumar +10 more
wiley +1 more source
Efficiency of quantum versus classical annealing in non-convex learning problems
, 2017 Quantum annealers aim at solving non-convex optimization problems by exploiting cooperative tunneling effects to escape local minima. The underlying idea consists in designing a classical energy function whose ground states are the sought optimal ...
Baldassi, Carlo, Zecchina, Riccardo
core +1 more source