Results 151 to 160 of about 41,319 (304)
Using Differential Evolution to avoid local minima in Variational Quantum Algorithms. [PDF]
Sci Rep, 2023 Faílde D +3 more
europepmc +1 more source
Small scale quantum algorithms
, 2002 It appears, in principle, that the laws of quantum mechanics allow a quantum computer to solve certain mathematical problems more rapidly than can be done using a classical computer.
Travaglione, Benjamin Christopher
core
Advanced Science, EarlyView.This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
Advanced Science, EarlyView.A nanoparticle‐cluster‐on‐mirror (NPcoM) serves as a functionally deterministic sub‐nanocavity that emulates picocavities, enabling extreme light–matter interactions and polaritonic phenomena. ABSTRACT Pushing nanoscale optical confinement to its ultimate limits defines the regime of nano‐cavity quantum electrodynamics (nano‐cQED), where light‐matter ...
Huatian Hu +10 more
wiley +1 more source
Biomolecular and quantum algorithms for the dominating set problem in arbitrary networks. [PDF]
Sci Rep, 2023 Wong R +3 more
europepmc +1 more source
Quantum algorithms for optimizers
CoRRThis is a set of lecture notes for a graduate-level course on quantum algorithms, with an emphasis on quantum optimization algorithms. It is developed for applied mathematicians and engineers, and requires no previous background in quantum mechanics. The main topics of this course, in addition to a rigorous introduction to the computational model, are:
openaire +2 more sources
Quantum Algorithms for Spectral Sums
Proceedings of the AAAI Conference on Artificial IntelligenceWe propose new quantum algorithms for estimating spectral sums of positive semi-definite (PSD) matrices. For a matrix A and a function f, the spectral sum is the trace of f(A), equivalently the sum over eigenvalues of A of f applied to each eigenvalue. Typical examples of spectral sums are the von Neumann entropy, the trace of the inverse of A, the log-
Alessandro Luongo, Changpeng Shao
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ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
Advanced Science, EarlyView.The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
Physical Review ResearchQuantum algorithms reformulate computational problems as quantum evolutions in a large Hilbert space. Most quantum algorithms assume that the time evolution is perfectly unitary and that the full Hilbert space is available.
Marcel Niedermeier +2 more
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A Sparse-Event Simulation Engine to Model Coincidence-Based Ranging Architectures in Quantum Lidar
IEEE Transactions on Quantum EngineeringNonclassical radar and lidar systems have received substantial interest recently; however, although many experimental demonstrations have provided deep physical knowledge of such systems, there remains a lack of effective system models to obtain ...
Marco Passafiume +3 more
doaj +1 more source