• Advanced Photonics
  • Vol. 4, Issue 4, 046005 (2022)
Chengkuan Gao, Prabhav Gaur, Shimon Rubin*, and Yeshaiahu Fainman
Author Affiliations
  • University of California, San Diego, Department of Electrical and Computer Engineering, La Jolla, California, United States
  • show less
    DOI: 10.1117/1.AP.4.4.046005 Cite this Article Set citation alerts
    Chengkuan Gao, Prabhav Gaur, Shimon Rubin, Yeshaiahu Fainman. Thin liquid film as an optical nonlinear-nonlocal medium and memory element in integrated optofluidic reservoir computer[J]. Advanced Photonics, 2022, 4(4): 046005 Copy Citation Text show less
    References

    [1] M. Borghi et al. Nonlinear silicon photonics. J. Opt., 19, 093002(2017).

    [2] B. Corcoran et al. Green light emission in silicon through slow-light enhanced third-harmonic generation in photonic-crystal waveguides. Nat. Photonics, 3, 206-210(2009).

    [3] A. L. Gaeta, M. Lipson, T. J. Kippenberg. Photonic-chip-based frequency combs. Nat. Photonics, 13, 158-169(2019).

    [4] J. W. Silverstone et al. On-chip quantum interference between silicon photon-pair sources. Nat. Photonics, 8, 104-108(2014).

    [5] G. Van der Sande, D. Brunner, M. C. Soriano. Advances in photonic reservoir computing. Nanophotonics, 6, 561-576(2017).

    [6] J. Hasler, H. B. Marr. Finding a roadmap to achieve large neuromorphic hardware systems. Front. Neurosci., 7, 118(2013).

    [7] H. Jaeger. The echo state approach to analysing and training recurrent neural networks—with an erratum note(2001).

    [8] W. Maass, T. Natschläger, H. Markram. Real-time computing without stable states: a new framework for neural computation based on perturbations. Neural Comput., 14, 2531-2560(2002).

    [9] D. Verstraeten et al. An experimental unification of reservoir computing methods. Neural Networks, 20, 391-403(2007).

    [10] M. Lukoševičius, H. Jaeger. Reservoir computing approaches to recurrent neural network training. Comput. Sci. Rev., 3, 127-149(2009).

    [11] G. Tanaka et al. Recent advances in physical reservoir computing: a review. Neural Networks, 115, 100-123(2019).

    [12] T.W. Hughes et al. Wave physics as an analog recurrent neural network. Sci. Adv., 5, eaay6946(2019).

    [13] G. Wetzstein et al. Inference in artificial intelligence with deep optics and photonics. Nature, 588, 39-47(2020).

    [14] P. R. Prucnal, J. S. Bhavin, M. C. Teich. Neuromorphic Photonics(2017).

    [15] K. Vandoorne et al. Experimental demonstration of reservoir computing on a silicon photonics chip. Nat. Commun., 5, 3541(2014).

    [16] A. N. Tait et al. Neuromorphic photonic networks using silicon photonic weight banks. Sci. Rep., 7, 7430(2017).

    [17] H. T. Peng et al. Neuromorphic photonic integrated circuits. IEEE J. Sel. Top. Quantum Electron., 24, 1-15(2018).

    [18] L. Larger et al. High-speed photonic reservoir computing using time-delay-based architecture: million words per second classification. Phys. Rev. X, 7, 011015(2017).

    [19] M. Rafayelyan et al. Large-scale optical reservoir computing for spatiotemporal chaotic systems prediction. Phys. Rev. X, 10, 041037(2020).

    [20] S. Rubin, Y. Fainman. Nonlocal and nonlinear surface plasmon polaritons and optical spatial solitons induced by the thermocapillary effect. Phys. Rev. Lett., 120, 243904(2018).

    [21] S. Rubin, Y. Fainman. Nonlinear, tunable, and active optical metasurface with liquid film. Adv. Photonics, 1, 066003(2019).

    [22] C. G. M. Marangoni. Über die Ausbreitung der Tropfen einer Flüssigkeit auf der Oberfläche einer anderen. Ann. Phys. Chem., 219, 337(1871).

    [23] J. R. A. Pearson. On convection cells induced by surface tension. J. Fluid Mech., 4, 489-500(1958).

    [24] V. G. Levich. Physicochemical Hydrodynamics(1962).

    [25] H. M. J. M. Wedershoven et al. Infrared laser induced rupture of thin liquid films on stationary substrates. Appl. Phys. Lett., 104, 054101(2014).

    [26] S. Rubin, B. Hong, Y. Fainman. Nonlinear, tunable, and active optical metasurface with liquid film. Light: Sci. Appl., 8, 77(2019).

    [27]

    [28] G. Montavon, M. Lukoševičiuset?al.. A practical guide to applying echo state networks. Neural Networks: Tricks of the Trade, 659-686(2012).

    [29]

    [30] S. Chatterjee, A. S. Hadi. Regression Analysis by Example(2013).

    [31] C. Mesaritakis, V. Papataxiarhis, D. Syvridis. Micro ring resonators as building blocks for an all-optical high-speed reservoir-computing bit-pattern-recognition system. J. Opt. Soc. Am. B, 30, 3048-3055(2013).

    [32] G. Lifante. Integrated Photonics: Fundamentals(2003).

    [33] G. C. Duree et al. Observation of self-trapping of an optical beam due to the photorefractive effect. Phys. Rev. Lett., 71, 533-536(1993).

    [34] C. Rotschild et al. Solitons in nonlinear media with an infinite range of nonlocality: first observation of coherent elliptic solitons and of vortex-ring solitons. Phys. Rev. Lett., 95, 213904(2005).

    [35] J. Komma et al. Thermo-optic coefficient of silicon at 1550 nm and cryogenic temperatures. Appl. Phys. Lett., 101, 041905(2012).

    [36] D. W. McLaughlin et al. A paraxial model for optical self-focussing in a nematic liquid crystal. Physica D, 88, 55-81(1995).

    [37] C. Conti, M. Peccianti, G. Assanto. Route to nonlocality and observation of accessible solitons. Phys. Rev. Lett., 91, 073901(2003).

    [38] G. Assanto, M. Peccianti. Spatial solitons in nematic liquid crystals. IEEE J. Quantum Electron., 39, 13-21(2003).

    [39] R. Boyd. Nonlinear Optics(2008).

    [40] K. Nakajima, M. Inubushi, I. Fischer et al. On the characteristics and structures of dynamical systems suitable for reservoir computing. Reservoir Computing: Theory, Physical Implementations, and Applications, 97-116(2020).

    [41] Y. LeCun. The MNIST database of handwritten digits(1998).

    [42] L. Lu, J. D. Joannopoulos, M. Soljačić. Topological photonics. Nat. Photonics, 8, 821-829(2014).

    [43] T. Ozawa et al. Topological photonics. Rev. Mod. Phys., 91, 015006(2019).

    [44] C. Fernando, S. Sojakka. Pattern recognition in a bucket. Lect. Notes Comput. Sci., 2801, 588-597(2003).

    [45] A. Adamatzky, B. D. L. Costello. Experimental logical gates in a reaction-diffusion medium: the XOR gate and beyond. Phys. Rev. E, 66, 046112(2002).

    [46] J. Sun et al. A 128 Gb/s PAM4 silicon microring modulator with integrated thermo-optic resonance tuning. IEEE J. Lightwave Technol., 37, 110-115(2019).

    [47] J. Feldmann et al. All-optical spiking neurosynaptic networks with self-learning capabilities. Nature, 569, 208-214(2019).

    [48] C. Rìos et al. Integrated all-photonic non-volatile multi-level memory. Nat. Photonics, 9, 725-732(2015).

    [49] M. Wuttig, H. Bhaskaran, T. Taubner. Phase-change materials for non-volatile photonic applications. Nat. Photonics, 11, 465-476(2017).

    Chengkuan Gao, Prabhav Gaur, Shimon Rubin, Yeshaiahu Fainman. Thin liquid film as an optical nonlinear-nonlocal medium and memory element in integrated optofluidic reservoir computer[J]. Advanced Photonics, 2022, 4(4): 046005
    Download Citation