Results 1 to 10 of about 3,959 (191)

BHT-QAOA: The Generalization of Quantum Approximate Optimization Algorithm to Solve Arbitrary Boolean Problems as Hamiltonians [PDF]

Entropy
A new methodology is introduced to solve classical Boolean problems as Hamiltonians, using the quantum approximate optimization algorithm (QAOA). This methodology is termed the “Boolean-Hamiltonians Transform for QAOA” (BHT-QAOA). Because a great deal of
Ali Al-Bayaty, Marek Perkowski
exaly   +4 more sources

Impact of graph structures for QAOA on MaxCut [PDF]

Quantum Information Processing, 2021
The quantum approximate optimization algorithm (QAOA) is a promising method of solving combinatorial optimization problems using quantum computing. QAOA on the MaxCut problem has been studied extensively on specific families of graphs, however, little is known about the algorithm on arbitrary graphs.
Rebekah Herrman, James Ostrowski, Phillip C Lotshaw   +2 more
exaly   +3 more sources

Exploiting Symmetry Reduces the Cost of Training QAOA

IEEE Transactions on Quantum Engineering, 2021
A promising approach to the practical application of the quantum approximate optimization algorithm (QAOA) is finding QAOA parameters classically in simulation and sampling the solutions from QAOA with optimized parameters on a quantum computer. Doing so
Ruslan Shaydulin, Stefan M Wild
exaly   +3 more sources

Benchmarking the performance of portfolio optimization with QAOA

Quantum Information Processing, 2022
AbstractWe present a detailed study of portfolio optimization using different versions of the quantum approximate optimization algorithm (QAOA). For a given list of assets, the portfolio optimization problem is formulated as quadratic binary optimization constrained on the number of assets contained in the portfolio.
Vanessa Dehn
exaly   +5 more sources

Performance analysis of multi-angle QAOA for $$p > 1$$ p > 1 [PDF]

Scientific Reports
In this paper we consider the scalability of multi-angle QAOA with respect to the number of QAOA layers. We found that MA-QAOA is able to significantly reduce the depth of QAOA circuits, by a factor of up to 4 for the considered data sets.
Igor Gaidai, Rebekah Herrman
doaj   +2 more sources

Bayesian Optimization for QAOA

IEEE Transactions on Quantum Engineering, 2023
The Quantum Approximate Optimization Algorithm (QAOA) adopts a hybrid quantum-classical approach to find approximate solutions to variational optimization problems. In fact, it relies on a classical subroutine to optimize the parameters of a quantum circuit. In this work we present a Bayesian optimization procedure to fulfil this optimization task, and
Simone Tibaldi, Davide Vodola, Edoardo Tignone   +2 more
exaly   +5 more sources

Systematic study on the dependence of the warm-start quantum approximate optimization algorithm on approximate solutions [PDF]

Scientific Reports
Quantum 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, Hirofumi Nishi, Taichi Kosugi, Yu-ichiro Matsushita   +3 more
doaj   +2 more sources

Hybrid Classical-Quantum Simulation of MaxCut using QAOA-in-QAOA

2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)
The Quantum approximate optimization algorithm (QAOA) is a leading hybrid classical-quantum algorithm for solving complex combinatorial optimization problems. QAOA-in-QAOA (QAOA^2) uses a divide-and-conquer heuristic to solve large-scale Maximum Cut (MaxCut) problems, where many subgraph problems can be solved in parallel.
Aniello Esposito, Tamuz Danzig
exaly   +3 more sources

Reinforcement learning assisted recursive QAOA. [PDF]

EPJ Quantum Technol
AbstractIn recent years, variational quantum algorithms such as the Quantum Approximation Optimization Algorithm (QAOA) have gained popularity as they provide the hope of using NISQ devices to tackle hard combinatorial optimization problems. It is, however, known that at low depth, certain locality constraints of QAOA limit its performance.
Patel YJ, Jerbi S, Bäck T, Dunjko V.
europepmc   +6 more sources

Study on Quantum Approximation Optimization Algorithm in Airport Cargo Transportation Problem

Journal of Advanced Transportation
The vehicle routing problem (VRP) is a core NP-hard combinatorial optimization problem in logistics and supply chain management. Quantum computing, particularly the Quantum Approximate Optimization Algorithm (QAOA), is being explored as a promising ...
Xudong Zhao, Jianping Chen, Lan Liu, Leilei Kang   +3 more
doaj   +2 more sources