Modeling Energy Communities: A Case Study of Quantum Approximate Optimization on a Superconducting Processor
This work explores the use of variational quantum algorithms to optimize energy distribution among users in energy communities, using real data from a community lab. This requires integrating various energy sources, storage solutions, and the ability to respond to variations in demand within energy...
Saved in:
| Main Authors: | Mateo Alonso, Guillermo Rubinos Rodriguez, Pablo Diez-Valle, Ana Garbayo, Xela Garcia-Santiago, Gonzalo Blazquez Gil |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11030452/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Quantum Circuit Architecture Search on a Superconducting Processor
by: Kehuan Linghu, et al.
Published: (2024-11-01) -
Compiler-assisted code generation for quantum computing: leveraging the unique properties of quantum architectures
by: G. G. James, et al.
Published: (2025-05-01) -
Building photonic links for microwave quantum processors
by: Zhao Han
Published: (2025-02-01) -
Quantum-Enhanced Generalized Pattern Search Optimization
by: Colton Mikes, et al.
Published: (2024-09-01) -
Improving the Solving of Optimization Problems: A Comprehensive Review of Quantum Approaches
by: Deborah Volpe, et al.
Published: (2025-01-01)