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Cited by 702

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

A fully programmable 100-spin coherent Ising machine with all-to-all connections

McMahon, Peter L., Marandi, Alireza, Haribara, Yoshitaka, Hamerly, Ryan, Langrock, Carsten, Tamate, Shuhei, Inagaki, Takahiro, Takesue, Hiroki, Utsunomiya, Shoko, Aihara, Kazuyuki, Byer, Robert L., Fejer, M. M., Mabuchi, Hideo, Yamamoto, Yoshihisa·2016·Science

Abstract

Taking the pulse of optimization: Finding the optimum solution of multiparameter or multifunctional problems is important across many disciplines, but it can be computationally intensive. Many such problems defined as computationally difficult can be mathematically mapped onto the so-called Ising problem, which looks at finding the minimum energy configuration for an array of coupled spins. Inagaki et al.and McMahon et al.show that an optical processing approach based on a network of coupled optical pulses in a ring fiber can be used to model and optimize large-scale Ising systems. Such a scalable architecture could help to optimize solutions to a wide range of complex problems. Science, this issue pp.603 and 614

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Metadata

Authors
McMahon, P. L., Marandi, A., Haribara, Y., Hamerly, R., Langrock, C., Tamate, S., Inagaki, T., Takesue, H., Utsunomiya, S., Aihara, K., Byer, R. L., Fejer, M. M., Mabuchi, H., & Yamamoto, Y.
Venue
Science
Published
2016-11-04
Volume
354
Issue
6312
Pages
614-617
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2538025098
Cited by
702
References
7
FWCI
41.22
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A fully programmable 100-spin coherent Ising machine with all-to-all connections. https://app.cochat.ai/papers/10.1126/science.aah5178
The paper
McMahon, P. L., Marandi, A., Haribara, Y., Hamerly, R., Langrock, C., Tamate, S., Inagaki, T., Takesue, H., Utsunomiya, S., Aihara, K., Byer, R. L., Fejer, M. M., Mabuchi, H., & Yamamoto, Y. (2016). A fully programmable 100-spin coherent Ising machine with all-to-all connections. Science. https://doi.org/10.1126/science.aah5178

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.