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Quantum Thermodynamics
Correspondence Between Ising Machines and Neural Networks
arXiv
Authors: Andrew G. Moore
Year
2025
Paper ID
17751
Status
Preprint
Abstract Read
~2 min
Abstract Words
87
Citations
N/A
Abstract
Computation with the Ising model is central to future computing technologies like quantum annealing, adiabatic quantum computing, and thermodynamic classical computing. Traditionally, computed values have been equated with ground states. This paper generalizes computation with ground states to computation with spin averages, allowing computations to take place at high temperatures. It then introduces a systematic correspondence between Ising devices and neural networks and a simple method to run trained feed-forward neural networks on Ising-type hardware. Finally, a mathematical proof is offered that these implementations are always successful.
Why This Paper Matters
- This paper contributes to the Quantum Thermodynamics research area in the Quantum Articles archive.
- It adds a 2025 reference point for readers tracking recent quantum research.
- Computation with the Ising model is central to future computing technologies like quantum annealing, adiabatic quantum computing, and thermodynamic classical computing.
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