All-optical information processing capacity of diffractive networks

2021 ◽  
Author(s):  
Onur Kulce ◽  
Deniz Mengu ◽  
Yair Rivenson ◽  
Aydogan Ozcan
Keyword(s):  
Information Processing ◽  
Processing Capacity ◽  
Optical Information ◽  
Optical Information Processing ◽  
Information Processing Capacity ◽  
All Optical

scholarly journals Ultralow-power all-optical switching via a chiral Mach-Zehnder interferometer

2021 ◽  
Author(s):  
Yaping Ruan ◽  
Haodong Wu ◽  
Shi-Jun Ge ◽  
Lei Tang ◽  
Zhixiang Li ◽  
...  
Keyword(s):  
Information Processing ◽  
Optical Switching ◽  
Extinction Ratio ◽  
Zehnder Interferometer ◽  
Optical Information ◽  
Optical Information Processing ◽  
All Optical ◽  
Ultralow Power ◽  
All Optical Switching ◽  
Mach Zehnder Interferometer

Abstract All-optical switching increasingly plays an important role in optical information processing. However, simultaneous achievement of ultralow power consumption, broad bandwidth and high extinction ratio remains challenging. We experimentally demonstrate an ultralow-power all-optical switching by exploiting chiral interaction between light and optically active material in a Mach-Zehnder interferometer (MZI). We achieve switching extinction ratio of 20.0(3.8) and 14.7(2.8) dB with power cost of 66.1(0.7) and 1.3(0.1) fJ/bit, respectively. The bandwidth of our all-optical switching is about 4.2 GHz. Our theoretical analysis shows that the switching bandwidth can, in principle, exceed 110 GHz. Moreover, the switching has the potential to be operated at few-photon level. Our all-optical switching exploits a chiral MZI made of linear optical components. It excludes the requisite of high-quality optical cavity or large optical nonlinearity, thus greatly simplifying realization. Our scheme paves the way towards ultralow-power and ultrafast all-optical information processing.

scholarly journals All-optical information-processing capacity of diffractive surfaces

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Onur Kulce ◽  
Deniz Mengu ◽  
Yair Rivenson ◽  
Aydogan Ozcan
Keyword(s):  
Information Processing ◽  
Optical Networks ◽  
Solution Space ◽  
Field Of View ◽  
Processing Capacity ◽  
Information Processing Capacity ◽  
Input And Output ◽  
All Optical ◽  
Output Field ◽  
Complex Valued

AbstractThe precise engineering of materials and surfaces has been at the heart of some of the recent advances in optics and photonics. These advances related to the engineering of materials with new functionalities have also opened up exciting avenues for designing trainable surfaces that can perform computation and machine-learning tasks through light–matter interactions and diffraction. Here, we analyze the information-processing capacity of coherent optical networks formed by diffractive surfaces that are trained to perform an all-optical computational task between a given input and output field-of-view. We show that the dimensionality of the all-optical solution space covering the complex-valued transformations between the input and output fields-of-view is linearly proportional to the number of diffractive surfaces within the optical network, up to a limit that is dictated by the extent of the input and output fields-of-view. Deeper diffractive networks that are composed of larger numbers of trainable surfaces can cover a higher-dimensional subspace of the complex-valued linear transformations between a larger input field-of-view and a larger output field-of-view and exhibit depth advantages in terms of their statistical inference, learning, and generalization capabilities for different image classification tasks when compared with a single trainable diffractive surface. These analyses and conclusions are broadly applicable to various forms of diffractive surfaces, including, e.g., plasmonic and/or dielectric-based metasurfaces and flat optics, which can be used to form all-optical processors.

New windows of opportunity for all-optical information processing: spatial solitons, EIT in microcavities, etc.

2005 ◽  
Author(s):  
Marin Solja-i ◽  
Elefterios Lidorikis ◽  
John D. Joannopoulos ◽  
Lene V. Hau ◽  
Mordechai Segev ◽  
...  
Keyword(s):  
Information Processing ◽  
Optical Information ◽  
Spatial Solitons ◽  
Optical Information Processing ◽  
Windows Of Opportunity ◽  
All Optical

scholarly journals Various functionalities Based on Semiconductor Optical Amplifer for All-Optical Information Processing

2002 ◽  
Vol 6 (4) ◽  
pp. 165-171 ◽  
Author(s):  
Seok Lee ◽  
Jae-Hun Kim ◽  
Young-Il Kim ◽  
Young-Tae Byun ◽  
Young-Min Jhon ◽  
...  
Keyword(s):  
Information Processing ◽  
Optical Information ◽  
Optical Information Processing ◽  
All Optical
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