Improving Quantum Optimization Algorithms by Constraint Relaxation
Quantum optimization is a significant area of quantum computing research with anticipated near-term quantum advantages. Current quantum optimization algorithms, most of which are hybrid variational-Hamiltonian-based algorithms, struggle to present quantum devices due to noise and decoherence. Existi...
Saved in:
| Main Authors: | Tomasz Pecyna, Rafał Różycki |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-09-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/14/18/8099 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Novel Application of Quantum Computing for Routing and Spectrum Assignment in Flexi-Grid Optical Networks
by: Oumayma Bouchmal, et al.
Published: (2024-10-01) -
Harnessing quantum power: Revolutionizing materials design through advanced quantum computation
by: Zikang Guo, et al.
Published: (2024-12-01) -
Solving Flexible Job-Shop Scheduling Problems Based on Quantum Computing
by: Kaihan Fu, et al.
Published: (2025-02-01) -
Application of the digital annealer unit in optimizing chemical reaction conditions for enhanced production yields
by: Shih-Cheng Li, et al.
Published: (2025-07-01) -
Solving the Independent Domination Problem by the Quantum Approximate Optimization Algorithm
by: Haoqian Pan, et al.
Published: (2024-12-01)