The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Large-scale Ising spin network based on degenerate optical parametric oscillators
Open accessAbstract
Solving combinatorial optimization problems is becoming increasingly important in modern society, where the analysis and optimization of unprecedentedly complex systems are required. Many such problems can be mapped onto the ground-state-search problem of the Ising Hamiltonian, and simulating the Ising spins with physical systems is now emerging as a promising approach for tackling such problems. Here, we report a large-scale network of artificial spins based on degenerate optical parametric oscillators (DOPOs), paving the way towards a photonic Ising machine capable of solving difficult combinatorial optimization problems. We generate >10,000 time-division-multiplexed DOPOs using dual-pump four-wave mixing in a highly nonlinear fibre placed in a cavity. Using those DOPOs, a one-dimensional Ising model is simulated by introducing nearest-neighbour optical coupling. We observe the formation of spin domains and find that the domain size diverges near the DOPO threshold, which suggests that the DOPO network can simulate the behaviour of low-temperature Ising spins. More than 10,000 time-division-multiplexed degenerate parametric oscillators are generated using phase-sensitive amplification in a nonlinear optical fibre. They can be used to simulate a coherent Ising machine that could solve difficult computing problems.
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Cites
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“Various schemes have been proposed and demonstrated that simulate the Ising Hamiltonian with physical systems, such as superconducting circuits [1], trapped ions [2], CMOS devices [3], and electro-mechanical oscillators [4].”
BackgroundNetwork of time-multiplexed optical parametric oscillators as a coherent Ising machine
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Self-citationCoherent Ising machine based on degenerate optical parametric oscillators
Wang, Z., Marandi, A., Wen, K., Byer, R. L., & Yamamoto, Y. (2013) · Physical Review A · doi:10.1103/physreva.88.063853 · Cited by 391
Self-citation
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Cited by
100,000-spin coherent Ising machine
Honjo, T., Sonobe, T., Inaba, K., Inagaki, T., Ikuta, T., Yamada, Y., Kazama, T., Enbutsu, K., Umeki, T., Kasahara, R., et al. (2021) · Science Advances · doi:10.1126/sciadv.abh0952 · Cited by 341
Self-citationHamerly, R., Inagaki, T., McMahon, P. L., Venturelli, D., Marandi, A., Onodera, T., Ng, E., Langrock, C., Inaba, K., Honjo, T., et al. (2019) · Science Advances · doi:10.1126/sciadv.aau0823 · Cited by 328
Self-citationSecurity intrusion detection using quantum machine learning techniques
Kalinin, M., & Krundyshev, V. (2022) · Journal of Computer Virology and Hacking Techniques · doi:10.1007/s11416-022-00435-0 · Cited by 118
Metadata
- Authors
- Inagaki, T., Inaba, K., Hamerly, R., Inoue, K., Yamamoto, Y., & Takesue, H.
- Venue
- Nature Photonics
- Published
- 2016-04-18
- Volume
- 10
- Issue
- 6
- Pages
- 415-419
- ISSN
- 1749-4885 (ISSN-L)
- 1749-4893
- OpenAlex
- W2338018404
- Cited by
- 258
- References
- 19
- FWCI
- 22.96
- Type
- journal article
- Language
- en
- Open access
- green
- Licence
- www.springer.com/tdm (tdm)
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