Scalability of all-optical neural networks based on spatial light modulators

Author(s):

Ying Zuo, Zhao Yujun, You-Chiuan Chen, Shengwang Du & Liu, Junwei

Abstract:

“Optical implementation of artificial neural networks has been attracting great attention due to its potential in parallel computation at speed of light. Although all-optical deep neural networks (AODNNs) with a few neurons have been experimentally demonstrated with acceptable errors re- cently, the feasibility of large scale AODNNs remains unknown because error might accumulate inevitably with increasing number of neurons and connections. Here, we demonstrate a scalable AODNN with programmable linear operations and tunable nonlinear activation functions. We ver- ify its scalability by measuring and analyzing errors propagating from a single neuron to the entire network. The feasibility of AODNNs is further confirmed by recognizing handwritten digits and fashions respectively.”

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Publication: Physical Review Applied
Issue/Year: Physical Review Applied, 2021
DOI: https://doi.org/10.1103/PhysRevApplied.15.054034

Discretized continuous quantum-mechanical observables that are neither continuous nor discrete

Author(s):

Thais L. Silva, Łukasz Rudnicki, Daniel S. Tasca, and Stephen P. Walborn

Abstract:

“Most of the fundamental characteristics of quantum mechanics, such as nonlocality and contextuality, are manifest in discrete, finite-dimensional systems. However, many quantum information tasks that exploit these properties cannot be directly adapted to continuous variable systems. To access these quantum features, continuous quantum variables can be made discrete by binning together their different values, resulting in observables with a finite number, d, of outcomes. While direct measurement indeed confirms their manifestly discrete character, here we employ a salient feature of quantum physics known as mutual unbiasedness to show that such coarse-grained observables are in a sense neither continuous nor discrete. Depending on d, the observables can reproduce either the discrete or the continuous behavior, or neither. To illustrate these results, we present an example for the construction of such measurements and employ it in an optical experiment confirming the existence of four mutually unbiased measurements with d=3 outcomes in a continuous variable system, surpassing the number of mutually unbiased continuous variable observables.”

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Publication: Physical Review Research
Issue/Year: Physical Review Research, Volume 4; Number 1; Pages 013060; 2022
DOI: 10.1103/physrevresearch.4.013060

Representation of total angular momentum states of beams through a four-parameter notation

Author(s):

Fu, Shiyao; Hai, Lan; Song, Rui; Gao, Chunqing & Zhang, Xiangdong

Abstract:

“It has been confirmed beams carrying total angular momentums (TAMs) that consist of spin angular momentums (SAMs) and orbital angular momentums (OAMs) are widely used in classical and quantum optics. Here we propose and demonstrate a new kind of representation consisting of four real numbers to describe the TAM states of arbitrary beams. It is shown that any homogeneous polarization, scalar vortices and complex vectorial vortex field, all of which result from the TAMs of photons, can be well represented conveniently using our proposed four-parameter representation. Furthermore, the proposed representation can also reveal the internal change of TAMs as the conversion between SAMs and OAMs. The salient properties of the proposed representation is to give a universal form of TAMs associated with complicated polarizations and more exotic vectorial vortex beams, which offer an important basis for the future applications”

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Publication: New Journal of Physics
Issue/Year: New Journal of Physics, Volume 23; Number 8; Pages 083015; 2021
DOI: 10.1088/1367-2630/ac1695

All-optical image identification with programmable matrix transformation

Author(s):

Li, Shikang; Ni, Baohua; Feng, Xue; Cui, Kaiyu; Liu, Fang; Zhang, Wei & Huang, Yidong

Abstract:

“An optical neural network is proposed and demonstrated with programmable matrix transformation and nonlinear activation function of photodetection (square-law detection). Based on discrete phase-coherent spatial modes, the dimensionality of programmable optical matrix operations is 30∼37, which is implemented by spatial light modulators. With this architecture, all-optical classification tasks of handwritten digits, objects and depth images are performed. The accuracy values of 85.0% and 81.0% are experimentally evaluated for MNIST (Modified National Institute of Standards and Technology) digit and MNIST fashion tasks, respectively. Due to the parallel nature of matrix multiplication, the processing speed of our proposed architecture is potentially as high as 7.4∼74 T FLOPs per second (with 10∼100 GHz detector).”

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Publication: Optics Express
Issue/Year: Optics Express, Volume 29; Number 17; Pages 26474; 2021
DOI: 10.1364/oe.430281

Quantum cryptography technique: A way to improve security challenges in mobile cloud computing (MCC)

Author(s):

Abidin, Shafiqul; Swami, Amit; Ramirez-As{‘{i}}s, Edwin; Alvarado-Tolentino, Joseph; Maurya, Rajesh Kumar & Hussain, Naziya

Abstract:

“Quantum cryptography concentrates on the solution of cryptography that is imperishable due to the reason of fortification of secrecy which is applied to the public key distribution of quantum. It is a very prominent technology in which 2 beings can securely communicate along with the sights belongings to quantum physics. However, on basis of classical level cryptography, the used encodes were bits for data. As quantum utilizes the photons or particles polarize ones for encoding the quantized property. This is presented in qubits as a unit. Transmissions depend directly on the inalienable mechanic’s law of quantum for security. This paper includes detailed insight into the three most used and appreciated quantum cryptography applications that are providing its domain-wide service in the field of mobile cloud computing. These services are (it) DARPA Network, (ii) IPSEC implementation, and (iii) the twisted light HD implementation along with quantum elements, key distribution, and protocols.”

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Publication: Materials Today: Proceedings
Issue/Year: Materials Today: Proceedings, 2021
DOI: 10.1016/j.matpr.2021.05.593

Orbital-Angular-Momentum-Controlled Hybrid Nanowire Circuit

Author(s):

Ren, Haoran; Wang, Xiaoxia; Li, Chenhao; He, Chenglin; Wang, Yixiong; Pan, Anlian & Maier, Stefan A.

Abstract:

“Plasmonic nanostructures can enable compact multiplexing of the orbital angular momentum (OAM) of light; however, strong dissipation of the highly localized OAM-distinct plasmonic fields in the near-field region hinders on-chip OAM transmission and processing. Superior transmission efficiency is offered by semiconductor nanowires sustaining highly confined optical modes, but only the polarization degree of freedom has been utilized for their selective excitation. Here we demonstrate that incident OAM beams can selectively excite single-crystalline cadmium sulfide (CdS) nanowires through coupling OAM-distinct plasmonic fields into nanowire waveguides for long-distance transportation. This allows us to build an OAM-controlled hybrid nanowire circuit for optical logic operations including AND and OR gates. In addition, this circuit enables the on-chip photoluminescence readout of OAM-encrypted information. Our results open exciting new avenues not only for nanowire photonics to develop OAM-controlled optical switches, logic gates, and modulators but also for OAM photonics to build ultracompact photonic circuits for information processing.”

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Publication: Nano Letters
Issue/Year: Nano Letters, Volume 21; Number 14; Pages 6220–6227; 2021
DOI: 10.1021/acs.nanolett.1c01979

Direct Tomography of High-Dimensional Density Matrices for General Quantum States of Photons

Author(s):

Zhou, Yiyu; Zhao, Jiapeng; Hay, Darrick; McGonagle, Kendrick; Boyd, Robert W. & Shi, Zhimin

Abstract:

“Quantum-state tomography is the conventional method used to characterize density matrices for general quantum states. However, the data acquisition time generally scales linearly with the dimension of the Hilbert space, hindering the possibility of dynamic monitoring of a high-dimensional quantum system. Here, we demonstrate a direct tomography protocol to measure density matrices of photons in the position basis through the use of a polarization-resolving camera, where the dimension of density matrices can be as large as 580×580 in our experiment. The use of the polarization-resolving camera enables parallel measurements in the position and polarization basis and as a result, the data acquisition time of our protocol does not increase with the dimension of the Hilbert space and is solely determined by the camera exposure time (on the order of 10 ms). Our method is potentially useful for the real-time monitoring of the dynamics of quantum states and paves the way for the development of high-dimensional, time-efficient quantum metrology techniques.”

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Publication: Physical Review Letters
Issue/Year: Physical Review Letters, Volume 127; Number 4; Pages 040402; 2021
DOI: 10.1103/PhysRevLett.127.040402

Toward simple, generalizable neural networks with universal training for low-SWaP hybrid vision

Author(s):

Muminov, Baurzhan; Perry, Altai; Hyder, Rakib; Asif, M. Salman & Vuong, Luat T.

Abstract:

“Speed, generalizability, and robustness are fundamental issues for building lightweight computational cameras. Here we demonstrate generalizable image reconstruction with the simplest of hybrid machine vision systems: linear optical preprocessors combined with no-hidden-layer, “small-brain” neural networks. Surprisingly, such simple neural networks are capable of learning the image reconstruction from a range of coded diffraction patterns using two masks. We investigate the possibility of generalized or “universal training” with these small brains. Neural networks trained with sinusoidal or random patterns uniformly distribute errors around a reconstructed image, whereas models trained with a combination of sharp and curved shapes (the phase pattern of optical vortices) reconstruct edges more boldly. We illustrate variable convergence of these simple neural networks and relate learnability of an image to its singular value decomposition entropy of the image. We also provide heuristic experimental results. With thresholding, we achieve robust reconstruction of various disjoint datasets. Our work is favorable for future real-time low size, weight, and power hybrid vision: we reconstruct images on a 15 W laptop CPU with 15,000 frames per second: faster by a factor of 3 than previously reported results and 3 orders of magnitude faster than convolutional neural networks.”

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Publication: Photonics Research
Issue/Year: Photonics Research, Volume 9; Number 7; Pages B253; 2021
DOI: 10.1364/prj.416614

768-ary Laguerre-Gaussian-mode shift keying free-space optical communication based on convolutional neural networks

Author(s):

Luan, Haitao; Lin, Dajun; Li, Keyao; Meng, Weijia; Gu, Min & Fang, Xinyuan

Abstract:

“Beyond orbital angular momentum of Laguerre-Gaussian (LG) modes, the radial index can also be exploited as information channel in free-space optical (FSO) communication to extend the communication capacity, resulting in the LG- shift keying (LG-SK) FSO communications. However, the recognition of radial index is critical and tough when the superposed high-order LG modes are disturbed by the atmospheric turbulences (ATs). In this paper, the convolutional neural network (CNN) is utilized to recognize both the azimuthal and radial index of superposed LG modes. We experimentally demonstrate the application of CNN model in a 10-meter 768-ary LG-SK FSO communication system at the AT \(C^2_n= 10^{-14}m^{-\frac{2}{3}}\). Based on the high recognition accuracy of the CNN model (>95%) in the scheme, a colorful image can be transmitted and the peak signal-to-noise ratio of the received image can exceed 35 dB. We anticipate that our results can stimulate further researches on the utilization of the potential applications of LG modes with non-zero radial index based on the artificial-intelligence-enhanced optoelectronic systems.”

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Publication: Optics Express
Issue/Year: Optics Express, Volume 29; Number 13; Pages 19807; 2021
DOI: 10.1364/oe.420176

Distinguishing intrinsic photon correlations from external noise with frequency-resolved homodyne detection

Author(s):

Lüders, Carolin & Assmann, Marc

Abstract:

“In this work, we apply homodyne detection to investigate the frequency-resolved photon statistics of a cw light field emitted by a driven-dissipative semiconductor system in real time. We demonstrate that studying the frequency dependence of the photon number noise allows us to distinguish intrinsic noise properties of the emitter from external noise sources such as mechanical noise while maintaining a sub-picosecond temporal resolution. We further show that performing postselection on the recorded data opens up the possibility to study rare events in the dynamics of the emitter. By doing so, we demonstrate that in rare instances, additional external noise may actually result in reduced photon number noise in the emission”

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Publication: Scientific Reports
Issue/Year: Scientific Reports, Volume 10; Number 1; 2020
DOI: 10.1038/s41598-020-79686-0