Potts model solver based on hybrid physical and digital architecture

The Potts model describes Ising-model-like interacting spin systems with multivalued spin components, and ground-state search problems of the Potts model can be efficiently mapped onto various integer optimization problems thanks to the rich expression of the multivalued spins. Here, we demonstrate...

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Bibliographic Details
Published in:Communications physics 2022-05, Vol.5 (1), p.1-8, Article 137
Main Authors: Inaba, Kensuke, Inagaki, Takahiro, Igarashi, Koji, Utsunomiya, Shoko, Honjo, Toshimori, Ikuta, Takuya, Enbutsu, Koji, Umeki, Takeshi, Kasahara, Ryoichi, Inoue, Kyo, Yamamoto, Yoshihisa, Takesue, Hiroki
Format: Article
Language:English
Subjects:
639/766/25
639/766/400/385
Clustering
Digital computers
Graph coloring
Integers
Ising model
Iterative methods
Learning
Optical Parametric Oscillators
Optimization
Parametric amplifiers
Physics
Physics and Astronomy
Solvers
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Summary:The Potts model describes Ising-model-like interacting spin systems with multivalued spin components, and ground-state search problems of the Potts model can be efficiently mapped onto various integer optimization problems thanks to the rich expression of the multivalued spins. Here, we demonstrate a solver of this model based on hybrid computation using physical and digital architectures, wherein a digital computer updates the interaction matrices in the iterative calculations of the physical Ising-model solvers. This update of interactions corresponds to learning from the Ising solutions, which allows us to save resources when embedding a problem in a physical system. We experimentally solved integer optimization problems (graph coloring and graph clustering) with this hybrid architecture in which the physical solver consisted of coupled degenerate optical parametric oscillators. Hybrid computing seeks to divide operations based on the strengths of digital, analogue or physical architectures. Here, approximate solutions to the multi-state Potts model are found using a physical Ising solver, networked degenerate optical parametric oscillators, repeatedly with learning processes.
ISSN:2399-3650
2399-3650
DOI:10.1038/s42005-022-00908-0