Results 21 to 30 of about 429 (149)
Hybrid quantum-classical algorithms for approximate graph coloring [PDF]
Quantum, 2022 We show how to apply the recursive quantum approximate optimization algorithm (RQAOA) to MAX-$k$-CUT, the problem of finding an approximate $k$-vertex coloring of a graph.
Sergey Bravyi +3 more
doaj +1 more source
Reachability Deficits in Quantum Approximate Optimization of Graph Problems [PDF]
Quantum, 2021 The quantum approximate optimization algorithm (QAOA) has become a cornerstone of contemporary quantum applications development. Here we show that the $density$ of problem constraints versus problem variables acts as a performance indicator.
V. Akshay +3 more
doaj +1 more source
QAOA-PCA: Enhancing Efficiency in the Quantum Approximate Optimization Algorithm via Principal Component Analysis [PDF]
Proceedings of the 2025 29th International Conference on Evaluation and Assessment in Software Engineering CompanionThe Quantum Approximate Optimization Algorithm (QAOA) is a promising variational algorithm for solving combinatorial optimization problems on near-term devices. However, as the number of layers in a QAOA circuit increases, which is correlated with the quality of the solution, the number of parameters to optimize grows linearly.
Parry, O., McMinn, P.
openaire +3 more sources
IEEE Transactions on Quantum Engineering, 2023 The advent of quantum computing can potentially revolutionize how complex problems are solved. This article proposes a two-loop quantum-classical solution algorithm for generation scheduling by infusing quantum computing, machine learning, and ...
Reza Mahroo, Amin Kargarian
doaj +1 more source
Scaling of the quantum approximate optimization algorithm on superconducting qubit based hardware [PDF]
Quantum, 2022 Quantum computers may provide good solutions to combinatorial optimization problems by leveraging the Quantum Approximate Optimization Algorithm (QAOA). The QAOA is often presented as an algorithm for noisy hardware.
Johannes Weidenfeller +6 more
doaj +1 more source
Fermionic quantum approximate optimization algorithm
Physical Review Research, 2023 Quantum computers are expected to accelerate solving combinatorial optimization problems, including algorithms such as Grover adaptive search and quantum approximate optimization algorithm (QAOA). However, many combinatorial optimization problems involve
Takuya Yoshioka +3 more
doaj +1 more source
npj Quantum Information, 2023 We compare the performance of the Quantum Approximate Optimization Algorithm (QAOA) with state-of-the-art classical solvers Gurobi and MQLib to solve the MaxCut problem on 3-regular graphs. We identify the minimum noiseless sampling frequency and depth p
Danylo Lykov +5 more
doaj +1 more source
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
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
Scientific ReportsQuantum approximate optimization algorithm (QAOA) is a promising hybrid quantum-classical algorithm to solve combinatorial optimization problems in the era of noisy intermediate-scale quantum computers.
Ken N. Okada +3 more
doaj +1 more source