Optical computers will be more interesting if they take advantage of phenomena that are unique to optics. In this respect, telecommunications hardware might have something to offer.
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References
- 1
Larger, L. et al. Opt. Exp. 20, 3241–3249 (2012).
- 2
Paquot, Y. et al. Sci. Rep. 2, 287 (2012).
- 3
Appeltant, L. et al. Nature Commun. 2, 468 (2011).
- 4
Rodan, A. & Tino, P. IEEE Trans. Neural Networ. 22, 131–141 (2011).
- 5
Caulfield, H. J. & Dolev, S. Nature Photon. 4, 261–263 (2010).
- 6
Miller, D. A. B. Nature Photon. 4, 3–5 (2010).
- 7
Miller, D. A. B. Nature Photon. 4, 406 (2010).
- 8
Tucker, R. S. Nature Photon. 4, 405 (2010).
- 9
Moore, C. & Mertens, S. The Nature of Computation (Oxford Univ. Press, 2011).
- 10
Tucker, R. S. J. Lightwave Technol. 24, 4655–4673 (2006).
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Woods, D., Naughton, T. Photonic neural networks. Nature Phys 8, 257–259 (2012). https://doi.org/10.1038/nphys2283
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