Reinforcement learning assisted recursive QAOA

In 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 constrai...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	EPJ quantum technology Jg. 11; H. 1; S. 6
Hauptverfasser:	Patel, Yash J., Jerbi, Sofiene, Bäck, Thomas, Dunjko, Vedran
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2024 Springer Nature B.V
Schlagworte:	Algorithms Combinatorial analysis Design optimization Ising model Nanotechnology and Microengineering Optimization Physics Physics and Astronomy Quantum Information Technology Quantum Physics Spintronics Quantum computing Quantum approximate optimization algorithm Combinatorial optimization Reinforcement learning
ISSN:	2662-4400, 2196-0763, 2196-0763
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!