A study of the performance of classical minimizers in the quantum approximate optimization algorithm

DOI10.1016/j.cam.2021.113388zbMath1482.90183OpenAlexW3120643606MaRDI QIDQ2059592

Sofia Vallecorsa, Elías F. Combarro, Mario Fernández-Pendás, José Ranilla, Ignacio F. Rúa

Publication date: 14 December 2021

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2021.113388

zbMATH Keywords

combinatorial optimizationfunction minimizationmax-cutquantum approximate optimization algorithm

Mathematics Subject Classification ID

Combinatorial optimization (90C27)

Related Items

Solving the Kemeny ranking aggregation problem with quantum optimization algorithms

Uses Software

• SciPy
• Adam
• QISKit

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Generalized Trotter's formula and systematic approximants of exponential operators and inner derivations with applications to many-body problems
• A survey of truncated-Newton methods
• Applications of cut polyhedra. II
• Quantum walks for the determination of commutativity of finite dimensional algebras
• Benchmarking the quantum approximate optimization algorithm
• A Quantum Adiabatic Evolution Algorithm Applied to Random Instances of an NP-Complete Problem
• Multivariate stochastic approximation using a simultaneous perturbation gradient approximation
• Convergence of the Nelder--Mead Simplex Method to a Nonstationary Point
• A Limited Memory Algorithm for Bound Constrained Optimization
• Reducibility among Combinatorial Problems
• An efficient method for finding the minimum of a function of several variables without calculating derivatives
• Node-and edge-deletion NP-complete problems
• A Simplex Method for Function Minimization
• Methods of conjugate gradients for solving linear systems