Results 1 to 10 of about 178 (50)
When quantum annealing meets multitasking: Potentials, challenges and opportunities
Array, 2023 Quantum computers have provided a promising tool for tackling NP hard problems. However, most of the existing work on quantum annealers assumes exclusive access to all resources available in a quantum annealer.
Tian Huang +3 more
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Solving the Traveling Salesman Problem on the D-Wave Quantum Computer
Frontiers in Physics, 2021 The traveling salesman problem is a well-known NP-hard problem in combinatorial optimization. This paper shows how to solve it on an Ising Hamiltonian based quantum annealer by casting it as a quadratic unconstrained binary optimization (QUBO) problem ...
Siddharth Jain
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Assessment of image generation by quantum annealer
Scientific Reports, 2021 Quantum annealing was originally proposed as an approach for solving combinatorial optimization problems using quantum effects. D-Wave Systems has released a production model of quantum annealing hardware.
Takehito Sato +2 more
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How to Solve Combinatorial Optimization Problems Using Real Quantum Machines: A Recent Survey
IEEE Access, 2022 A combinatorial optimization problem (COP) is the problem of finding the optimal solution in a finite set. When the size of the feasible solution set is large, the complexity of the problem increases, and it is not easy to solve in a reasonable time with
Sovanmonynuth Heng +3 more
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Molecular dynamics on quantum annealers
Scientific Reports, 2022 In this work we demonstrate a practical prospect of using quantum annealers for simulation of molecular dynamics. A methodology developed for this goal, dubbed Quantum Differential Equations (QDE), is applied to propagate classical trajectories for the ...
Igor Gaidai +7 more
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A Quantum Annealer for Subset Feature Selection and the Classification of Hyperspectral Images
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Hyperspectral images (HSIs) showing objects belonging to several distinct target classes are characterized by dozens of spectral bands being available.
Soronzonbold Otgonbaatar, Mihai Datcu
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Quantum annealing algorithms for track pattern recognition [PDF]
EPJ Web of Conferences, 2020 The High-Luminosity Large Hadron Collider (HL-LHC) starts from 2027 to extend the physics discovery potential at the energy frontier. The HL-LHC produces experimental data with a much higher luminosity, requiring a large amount of computing resources ...
Saito Masahiko +9 more
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PLoS ONE, 2022 The most advanced D-Wave Advantage quantum annealer has 5000+ qubits, however, every qubit is connected to a small number of neighbors. As such, implementation of a fully-connected graph results in an order of magnitude reduction in qubit count.
Alexander Teplukhin +4 more
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Scientific Reports, 2023 We present a comprehensive case study comparing the performance of D-Waves’ quantum-classical hybrid framework, Fujitsu’s quantum-inspired digital annealer, and Gurobi’s state-of-the-art classical solver in solving a transport robot scheduling problem ...
Dominik Leib +7 more
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Training Restricted Boltzmann Machines With a D-Wave Quantum Annealer
Frontiers in Physics, 2021 Restricted Boltzmann Machine (RBM) is an energy-based, undirected graphical model. It is commonly used for unsupervised and supervised machine learning. Typically, RBM is trained using contrastive divergence (CD).
Vivek Dixit +9 more
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