Quantum Optimization of Fully Connected Spin Glasses

2014/06/29 by Davide Venturelli, Salvatore Mandrà, Sergey Knysh +4 · 2 citations
Computer Science · Mathematics · Physics and Astronomy · #Algorithm #Artificial intelligence #Computer science #Embedding #Graph #Mathematics #Physics #Quantum #Quantum Computing Algorithms and Architecture #Quantum annealing #Quantum computer #Quantum many-body systems #Quantum mechanics #Qubit #Scaling #Simulated annealing #Spin glass #Statistical physics #Theoretical and Computational Physics #Theoretical computer science #cond-mat.dis-nn #quant-ph

paper · pdf · doi:10.1103/physrevx.5.031040

published as Phys. Rev. X 5, 031040 (2015) · includes supplemental material

arxiv created 2014/06/29 · openalex publication_date 2015/09/18 · arxiv updated 2015/09/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

Quantum computing promises to be more efficient and significantly faster than today's classical computing. Researchers compare the performance of a quantum annealer with that of classical algorithms for the first time on hard spin-glass problems.

Citations

• Finding Large Clique Minors is Hard
• Quantum Annealing in the Transverse Ising Model
• Mathematical foundation of quantum annealing
• Quantum annealing with manufactured spins
• Defining and detecting quantum speedup
• Quantum Annealing of a Disordered Magnet

Cited by

• Viewing vanilla quantum annealing through spin glasses
• Optimally Stopped Optimization
• Addressing the Minor-Embedding Problem in Quantum Annealing and Evaluating State-of-the-Art Algorithm Performance