Results 91 to 100 of about 1,815,218 (351)
Quantum annealing for combinatorial clustering [PDF]
Quantum Information Processing, 2018 Clustering is a powerful machine learning technique that groups "similar" data points based on their characteristics. Many clustering algorithms work by approximating the minimization of an objective function, namely the sum of within-the-cluster distances between points.
Vaibhaw Kumar +3 more
openaire +2 more sources
Quantum Annealing via Environment-Mediated Quantum Diffusion
Physical Review Letters, 2017 4.5 pages of main text, 3.5 pages of Supplementary Material, 1 Figure, replacement contains minor ...
Smelyanskiy, Vadim N. +4 more
openaire +4 more sources
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
Quantum Annealing Effect on Entropic Slowing Down in Frustrated Decorated Bond System
, 2006 We propose that the importance of the quantum annealing procedure to find the ground state of frustrated decorated bond systems where 'entropic slowing down' happens due to peculiar density of states.
Kadowaki +5 more
core +1 more source
Performance of quantum annealing inspired algorithms for combinatorial optimization problems
Communications PhysicsTwo classes of quantum-annealing-inspired-algorithms (QAIA), namely different variants of simulated coherent Ising machine and simulated bifurcation, have been proposed for efficiently solving combinatorial optimization problems recently.
Qingguo Zeng +5 more
semanticscholar +1 more source
Advanced Functional Materials, EarlyView.PBTTT‐OR‐R, a C14‐alkoxy/alkyl‐PBTTT polymer derivative, is of substantial interest for optoelectronics due to its specific fullerene intercalation behavior and enhanced charge‐transfer absorption. Comparing this polymer with (S) and without (O) homocoupling defects reveals that PBTTT‐OR‐R(O) forms stable co‐crystals with PC61BM, while PBTTT‐OR‐R(S ...
Zhen Liu +14 more
wiley +1 more source
Advanced Functional Materials, EarlyView.A lack of standard approaches for testing and reporting the performance of metal halide perovskites and organic semiconductor radiation detectors has resulted in inconsistent interpretation of performance parameters, impeding progress in the field. This Perspective recommends key metrics and experimental details, which are suggested for reporting in ...
Jessie A. Posar +8 more
wiley +1 more source
Quantum Annealing Correction with Minor Embedding [PDF]
, 2015 Quantum annealing provides a promising route for the development of quantum optimization devices, but the usefulness of such devices will be limited in part by the range of implementable problems as dictated by hardware constraints.
Albash, Tameem +4 more
core +2 more sources
Quantum adiabatic machine learning by zooming into a region of the energy surface [PDF]
, 2020 Recent work has shown that quantum annealing for machine learning, referred to as QAML, can perform comparably to state-of-the-art machine learning methods with a specific application to Higgs boson classification.
Job, Joshua +5 more
core
Prospects for quantum enhancement with diabatic quantum annealing [PDF]
Nature Reviews Physics, 2020 Optimization, sampling and machine learning are topics of broad interest that have inspired significant developments and new approaches in quantum computing. One such approach is quantum annealing (QA).
E. Crosson, Daniel A. Lidar
semanticscholar +1 more source