Sherrington-Kirkpatrick (SK)
Emerging6papers using it
2024first seen
The Sherrington-Kirkpatrick (SK) benchmark is a dataset used to evaluate the performance of optimization algorithms, particularly in the context of solving optimization problems in statistical physics.
Papers using Sherrington-Kirkpatrick (SK) (6)
- Iterative Interpolation Schedules For Quantum Approximate Optimization AlgorithmPractical Noise Mitigation For Quantum Annealing Via Dynamical Decoupling: Toward Industry-relevant Optimization Using Trapped IonsLearning to Learn with Quantum Optimization via Quantum Neural NetworksQuantum Combinatorial Optimization Beyond The Variational Paradigm: Simple Schedules For Hard ProblemsQuantum enhanced Markov chains require fine-tuned quenchesQuantum combinatorial optimization beyond the variational paradigm:
simple schedules for hard problems