Quick design of feasible tensor networks for constrained combinatorial optimization
Quantum computers are expected to enable fast solving of large-scale combinatorial optimization problems. However, their limitations in fidelity and the number of qubits prevent them from handling real-world problems. Recently, a quantum-inspired solver using tensor networks has been proposed, which...
Saved in:
| Main Authors: | Hyakka Nakada, Kotaro Tanahashi, Shu Tanaka |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften
2025-07-01
|
| Series: | Quantum |
| Online Access: | https://quantum-journal.org/papers/q-2025-07-21-1799/pdf/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Inductive Construction of Variational Quantum Circuit for Constrained Combinatorial Optimization
by: Hyakka Nakada, et al.
Published: (2025-01-01) -
Explicitly Constrained Black-Box Optimization With Disconnected Feasible Domains Using Deep Generative Models
by: Naoki Sakamoto, et al.
Published: (2022-01-01) -
Learning tensor networks with tensor cross interpolation: New algorithms and libraries
by: Yuriel Núñez Fernández, Marc K. Ritter, Matthieu Jeannin, Jheng-Wei Li, Thomas Kloss, Thibaud Louvet, Satoshi Terasaki, Olivier Parcollet, Jan von Delft, Hiroshi Shinaoka, Xavier Waintal
Published: (2025-03-01) -
Quantum annealing for combinatorial optimization: a benchmarking study
by: Seongmin Kim, et al.
Published: (2025-05-01) -
Low-temperature Gibbs states with tensor networks
by: Denise Cocchiarella, et al.
Published: (2025-08-01)