All-optical bistable switching in a strained piezoelectric self-electro-optic effect device

1994 ◽  
Vol 30 (18) ◽  
pp. 1521-1522 ◽  
Author(s):  
A.S. Pabla ◽  
R. Grey ◽  
G.J. Rees ◽  
J. Woodhead ◽  
M.A. Pate ◽  
...  
2016 ◽  
Vol 9 (4) ◽  
pp. 560-564 ◽  
Author(s):  
Mehdi Shirdel ◽  
Mohammad Ali Mansouri-Birjandi

2007 ◽  
Vol 90 (16) ◽  
pp. 161118 ◽  
Author(s):  
Myung-Ki Kim ◽  
In-Kag Hwang ◽  
Se-Heon Kim ◽  
Hyun-Joo Chang ◽  
Yong-Hee Lee

2003 ◽  
Vol 28 (24) ◽  
pp. 2506 ◽  
Author(s):  
Mehmet Fatih Yanik ◽  
Shanhui Fan ◽  
Marin Soljačić ◽  
J. D. Joannopoulos

2011 ◽  
Vol 109 (3) ◽  
pp. 033106 ◽  
Author(s):  
Jacopo Parravicini ◽  
Jassem Safioui ◽  
Vittorio Degiorgio ◽  
Paolo Minzioni ◽  
Mathieu Chauvet

2012 ◽  
Author(s):  
Javier Pérez-Moreno ◽  
Stijn Van Cleuvenbergen ◽  
Maarten Vanbel ◽  
Koen Clays ◽  
Edward W. Taylor

2021 ◽  
Author(s):  
Ting Yu ◽  
Xiaoxuan Ma ◽  
Ernest Pastor ◽  
Jonathan George ◽  
Simon Wall ◽  
...  

Abstract Deeplearning algorithms are revolutionising many aspects of modern life. Typically, they are implemented in CMOS-based hardware with severely limited memory access times and inefficient data-routing. All-optical neural networks without any electro-optic conversions could alleviate these shortcomings. However, an all-optical nonlinear activation function, which is a vital building block for optical neural networks, needs to be developed efficiently on-chip. Here, we introduce and demonstrate both optical synapse weighting and all-optical nonlinear thresholding using two different effects in one single chalcogenide material. We show how the structural phase transitions in a wide-bandgap phase-change material enables storing the neural network weights via non-volatile photonic memory, whilst resonant bond destabilisation is used as a nonlinear activation threshold without changing the material. These two different transitions within chalcogenides enable programmable neural networks with near-zero static power consumption once trained, in addition to picosecond delays performing inference tasks not limited by wire charging that limit electrical circuits; for instance, we show that nanosecond-order weight programming and near-instantaneous weight updates enable accurate inference tasks within 20 picoseconds in a 3-layer all-optical neural network. Optical neural networks that bypass electro-optic conversion altogether hold promise for network-edge machine learning applications where decision-making in real-time are critical, such as for autonomous vehicles or navigation systems such as signal pre-processing of LIDAR systems.


2018 ◽  
Vol 10 (4) ◽  
pp. 103 ◽  
Author(s):  
Gaetano Assanto ◽  
Sreekanth Perumbilavil ◽  
Armando Piccardi ◽  
Martti Kauranen

Using an external low-frequency electric field applied to dye-doped nematic liquid crystals, we demonstrate that random lasing obtained by optical pumping can be steered in angular direction by routing an all-optical waveguide able to collect the emitted light. By varying the applied voltage from 0 to 2 V, we reduce the walk-off and sweep the random laser guided beam over 7 degrees. Full Text: PDF ReferencesV. S. Letokhov, "Generation of light by a scattering medium with negative resonance absorption," Sov. Phys. JETP 26 (4), 835 (1968). DirectLink H. Cao, J. Y. Xu, D. Z. Zhang, S.-H. Chang, S. T. Ho, E. W. Seelig, X. Liu, and R. P. H. Chang, "Spatial Confinement of Laser Light in Active Random Media," Phys. Rev. Lett. 84 (24), 5584 (2000). CrossRef D. S. Wiersma, "The physics and applications of random lasers," Nature Phys. 4 (5) 359-367 (2008). CrossRef D. Wiersma and S. Cavalieri, "A temperature-tunable random laser," Nature 414, 708-709 (2001). CrossRef G. Strangi, S. Ferjani, V. 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Umeton, "Routing of Anisotropic Spatial Solitons and Modulational Instability in liquid crystals," Nature 432, 733-737 (2004). CrossRef J. Beeckman, K. Neyts and M. Haeltermann, "Patterned electrode steering of nematicons," J. Opt. A - Pure Appl. Opt. 8 (2), 214-220 (2006). CrossRef A. Piccardi, M. Peccianti, G. Assanto, A. Dyadyusha and M. Kaczmarek, "Voltage-driven in-plane steering of nematicons," Appl. Phys. Lett. 94, 091106 (2009). CrossRef R. Barboza, A. Alberucci, and G. Assanto, "Large electro-optic beam steering with Nematicons", Opt. Lett. 36 (14), 2611–2613 (2011). CrossRef A. Piccardi, A. Alberucci, R. Barboza, O. Buchnev, M. Kaczmarek, and G. Assanto, "In-plane steering of nematicon waveguides across an electrically adjusted interface", Appl. Phys. Lett. 100 (25), 251107 (2012). CrossRef Y. V. Izdebskaya, "Routing of spatial solitons by interaction with rod microelectrodes," Opt. Lett. 39(6), 1681-1684 (2014). CrossRef A. Pasquazi, A. Alberucci, M. Peccianti, and G. Assanto, "Signal processing by opto-optical interactions between self-localized and free propagating beams in liquid crystals," Appl. Phys. Lett. 87, 261104 (2005). CrossRef S. V. Serak, N. V. Tabiryan, M. Peccianti and G. Assanto, "Spatial Soliton All-Optical Logic Gates", IEEE Photon. Technol. Lett. 18 (12), 1287-1289 (2006). CrossRef M. Peccianti, C. Conti, G. Assanto, A. De Luca and C. Umeton, "All Optical Switching and Logic Gating with Spatial Solitons in Liquid Crystals," Appl. Phys. Lett. 81(18), 3335-3337 (2002). CrossRef A. Fratalocchi, A. Piccardi, M. Peccianti and G. Assanto, "Nonlinearly controlled angular momentum of soliton clusters," Opt. Lett. 32(11), 1447-1449 (2007). CrossRef Y. Izdebskaya, V. Shvedov, G. Assanto, and W. Krolikowski, Nat. Comm. 8, 14452 (2017). CrossRef M. Peccianti and G. Assanto, "Nematicons," Phys. Rep. 516, 147-208 (2012). CrossRef Y. Izdebskaya, A. Desyatnikov, G. Assanto and Y. 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Author(s):  
Michal Lipson ◽  
Sasikanth Manipatruni ◽  
Kyle Preston ◽  
Carl Poitras

Photonics on a silicon chip could enable a platform for monolithic integration of optics and microelectronics for applications of optical interconnects in which high data streams are required in a small footprint. In this talk I will review the challenges and achievement in the field of silicon photonics. Using highly confined photonic structures one can enhance the electro-optical and non-linearities properties of Silicon and enable ultra-compact and low power photonic components with very low loss. We have recently demonstrated several active components including GHz electro-optic low power switches and modulators, all-optical amplifiers and wavelength converters on silicon.


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