Benchmarking the optimization of optical machines with the planted solutions
Abstract This research focuses on developing effective benchmarks for quadratic unconstrained binary optimization instances, crucial for evaluating the performance of Ising hardware and solvers. Currently, the field lacks accessible and reproducible models for systematically testing such systems, pa...
Saved in:
| Main Authors: | Nikita Stroev, Natalia G. Berloff, Nir Davidson |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-11-01
|
| Series: | Communications Physics |
| Online Access: | https://doi.org/10.1038/s42005-024-01870-9 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Virtual Power Plant Optimization Service - Benchmark of Solvers
by: Filipe Alves, et al.
Published: (2024-10-01) -
Benchmarking Variants of the Adam Optimizer for Quantum Machine Learning Applications
by: Tuan Hai Vu, et al.
Published: (2025-01-01) -
Machine learning-driven benchmarking of China's wastewater treatment plant electricity consumption
by: Minjian Li, et al.
Published: (2025-01-01) -
Efficient computation using spatial-photonic Ising machines with low-rank and circulant matrix constraints
by: Richard Zhipeng Wang, et al.
Published: (2025-03-01) -
Vector Ising spin annealer for minimizing Ising Hamiltonians
by: James S. Cummins, et al.
Published: (2025-05-01)