Results 31 to 40 of about 2,321 (167)
Constrained quantum optimization for extractive summarization on a trapped-ion quantum computer
Scientific Reports, 2022 Realizing the potential of near-term quantum computers to solve industry-relevant constrained-optimization problems is a promising path to quantum advantage.
Pradeep Niroula +6 more
doaj +1 more source
QuASeR -- Quantum Accelerated De Novo DNA Sequence Reconstruction
, 2020 In this article, we present QuASeR, a reference-free DNA sequence reconstruction implementation via de novo assembly on both gate-based and quantum annealing platforms.
Al-Ars, Zaid +2 more
core +1 more source
Multistart Methods for Quantum Approximate Optimization
, 2019 Hybrid quantum-classical algorithms such as the quantum approximate optimization algorithm (QAOA) are considered one of the most promising approaches for leveraging near-term quantum computers for practical applications.
Larson, Jeffrey +2 more
core +1 more source
Network Community Detection On Small Quantum Computers
, 2019 In recent years a number of quantum computing devices with small numbers of qubits became available. We present a hybrid quantum local search (QLS) approach that combines a classical machine and a small quantum device to solve problems of practical size.
Alexeev, Yuri +4 more
core +1 more source
Solution of SAT problems with the adaptive-bias quantum approximate optimization algorithm
Physical Review Research, 2023 The quantum approximate optimization algorithm (QAOA) is a promising method for solving certain classical combinatorial optimization problems on near-term quantum devices. When employing the QAOA to 3-SAT and Max-3-SAT problems, the quantum cost exhibits
Yunlong Yu +4 more
doaj +1 more source
Prog-QAOA: Framework for resource-efficient quantum optimization through classical programs [PDF]
QuantumCurrent state-of-the-art quantum optimization algorithms require representing the original problem as a binary optimization problem, which is then converted into an equivalent cost Hamiltonian suitable for the quantum device.
Bence Bakó +3 more
doaj +1 more source
qTorch: The Quantum Tensor Contraction Handler
, 2018 Classical simulation of quantum computation is necessary for studying the numerical behavior of quantum algorithms, as there does not yet exist a large viable quantum computer on which to perform numerical tests.
Aspuru-Guzik, Alán +5 more
core +2 more sources
Advanced Intelligent Discovery, EarlyView.This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley +1 more source
End‐to‐End Portfolio Optimization with Hybrid Quantum Annealing
Advanced Quantum Technologies, EarlyView.This works presents a hybrid quantum‐classical framework for portfolio optimization that combines quantum assisted asset selection and rebalancing with classical weight allocation. The approach processes real market data, embeds it into Quadratic Unconstrained Binary Optimization formulations, and evaluates performance within a unified workflow ...
Sai Nandan Morapakula +5 more
wiley +1 more source
For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances [PDF]
, 2018 The Quantum Approximate Optimization Algorithm, QAOA, uses a shallow depth quantum circuit to produce a parameter dependent state. For a given combinatorial optimization problem instance, the quantum expectation of the associated cost function is the ...
Brandao, Fernando G. S. L. +4 more
core +1 more source