Optical Input Research Articles

An Endless Optical Phase Delay for Harmonic-Free Phase/Frequency Shifting in Coherent-Lite DCIs and Microwave Photonics

An optical IQ modulator (IQM), when driven by quadrature-phase sinusoidal electrical signals, adds a phase/frequency offset to the optical input. However, harmonics of the applied electrical signals are also generated in the optical domain. In this work, we analytically derive the waveform shapes that achieve a harmonic-free phase/frequency shift with high spectral purity using the IQM. Using these waveforms, an endless optical phase delay (EOPD), wherein the phase delay can be increased or decreased continuously and arbitrarily in a reset-free manner, has been presented. The EOPD can be used in coherent-lite or analog coherent receiver based DCIs, phased array LiDAR, and many other applications. In order to adjust for the bias voltages and control signal gains in the EOPD, some of which may be time varying, a multivariate gradient descent algorithm is presented. Use of the EOPD for phase synchronization in a self-homodyne coherent-lite optical link has been demonstrated, making it a promising solution for low-power high-capacity coherent data center interconnects (DCIs).

Optoelectronic Synaptic Memtransistor Based on 2D SnSe/MoS2 van der Waals Heterostructure under UV-Ozone Treatment.

Memristive switching devices with electrically and optically invoked synaptic behaviors show great promise in constructing an artificial biological visual system. Through rational design and integration, 2D materials and their van der Waals (vdW) heterostructures can be applied to realize multifunctional optoelectronic devices. Here, a multifunctional optoelectronic synaptic memtransistor based on a SnSe/MoS2 vdW p-n heterojunction to simulate the human biological visual system is reported. By employing simple mild UV-ozone treatment, the device exhibits reversible resistive switching (RS) behavior with switching ratio up to 103 . The retina-like selective response to different input light wavelengths is activated, as well as programmable multilevel resistance states and long-term synaptic plasticity. Moreover, memory and logic functions analogous to those found in the visual cortex of the brain are performed by controlling the optical and electrical input signals. This work proposes a feasible strategy to modulate RS in vdW heterostructures for memristive devices, which show significant potential for neuromorphic processing.

Facility for calibration of photometers for measurement of temporal light modulation

A facility for calibration of temporal light modulation (TLM) photometers has been developed. The facility is based on a laser-fed reference integrating sphere source, the optical input power of which can be modulated with an acousto-optic modulator. A system of photodiodes, amplifiers and an analogue-to-digital converter is used to sample the temporally modulated irradiance at one of the exit ports of the source. With the facility, a TLM photometer was calibrated for display contrast ratio root mean square with an absolute combined standard uncertainty of 0.037%. In addition, the facility has been characterised with the aim of measuring flicker and stroboscopic effect, considering the Ecodesign ‘Single Lighting Regulation’. The frequency response of the facility is shown to be sufficient to accommodate measurements of flicker and the stroboscopic effect.

A multifunctional optical‐thermal logic gate sensor array based on ferroelectric BiFeO3 thin films

AbstractThe growing need to process a diverse range of data has ignited effort in developing new multifunctional logic gate devices. In this article, we report a new form of all‐in‐one logic gate system that exploits the photoresponsivity of a self‐powered multifunctional BiFeO3 (BFO) sensor material. The BFO sensor can not only detect both light intensity and temperature, but it can also execute three common logic gates of “AND”, “OR”, and “NOT” by converting optical and thermal inputs into electrical output. The diverse functionality of the BFO logic gate sensor array utilizes the unique light‐and temperature‐controlled energy band structure and carrier behavior of the BFO material. To demonstrate the potential, a 3 × 3 logic gate sensor matrix is developed, which successfully detected light and temperature distributions, and accurately produced the three basic logic gate operations. This work provides a new route to construct highly integrated multifunctional electronic devices for the advancement of large sensing, communication, and computing operations.image

A flexible organic mechanoluminophore device

A flexible mechanoluminophore device that is capable of converting mechanical energy into visualizable patterns through light-emission holds great promise in many applications, such as human-machine interfaces, Internet of Things, wearables, etc. However, the development has been very nascent, and more importantly, existing mechanoluminophore materials or devices emit light that cannot be discernible under ambient light, in particular with slight applied force or deformation. Here we report the development of a low-cost flexible organic mechanoluminophore device, which is constructed based on the multi-layered integration of a high-efficiency, high-contrast top-emitting organic light-emitting device and a piezoelectric generator on a thin polymer substrate. The device is rationalized based on a high-performance top-emitting organic light-emitting device design and maximized piezoelectric generator output through a bending stress optimization and have demonstrated that it is discernible under an ambient illumination as high as 3000 lux. A flexible multifunctional anti-counterfeiting device is further developed by integrating patterned electro-responsive and photo-responsive organic emitters onto the flexible organic mechanoluminophore device, capable of converting mechanical, electrical, and/or optical inputs into light emission and patterned displays.

Optomechanically induced gain using a trapped interacting Bose-Einstein condensate

We investigate the realization of the phenomenon of optomechanically induced gain in a hybrid optomechanical system consisting of an interacting Bose-Einstein condensate trapped inside the optical lattice of a cavity which is generated by an external coupling laser tuned to the red sideband of the cavity. It is shown that the system behaves as an optical transistor while the cavity is exposed to a weak input optical signal which can be amplified considerably in the cavity output if the system is in the unresolved sideband regime. Interestingly, the system has the capability to switch from the resolved to unresolved sideband regime by controlling the s-wave scattering frequency of atomic collisions. We show that the system gain can be enhanced considerably by controlling the s-wave scattering frequency as well as the coupling laser intensity while the system remains in the stable regime. Based on our obtained results, the input signal can be amplified more than 100 million percent in the system output which is much larger than those already reported in the previously proposed similar schemes.

Gamma Scientific Sets High Standards for Light Measurement

Gamma Scientific Sets High Standards for Light Measurement

All-Optical Phase Memory Circuit Based on Two Coupled Lasers and External Optical Injection

We propose a volatile static all-optical memory capable of storing phase information of a slowly-varying electric field. The scheme and its realization (a memory circuit) are based on two mutually coupled lasers subject to external optical injection. The proposed circuit has a single optical input for write and hold operations and two opposite-sign outputs for reading the memory. The proposed circuit operates with a single wavelength of light, a single direction of propagation, and without a need to switch the state of polarization. We prove mathematically that the proposed arrangement has equilibrium points that may discreetly quantify and store the phase in a bistable manner. The circuit is studied numerically for solid-state and semiconductor lasers with zero and non-zero linewidth enhancement factors, respectively. Simulations based on a rate equation system confirm the essential findings. Using typical parameters of a semiconductor laser and optimizing for a possibly wide range of operation, the write-read operations were simulated using PRBS-9 at the rate of 1 Gb/s with negligible errors. The proposed circuit will enable integrated memory implementations for future all-optical signal processing and computing systems.

GHz Rate Neuromorphic Photonic Spiking Neural Network With a Single Vertical-Cavity Surface-Emitting Laser (VCSEL)

Vertical-Cavity Surface-Emitting Lasers (VCSELs) are highly promising devices for the construction of neuromorphic photonic information processing systems, due to their numerous desirable properties such as low power consumption, high modulation speed, and compactness. Of particular interest is the ability of VCSELs to exhibit neuron-like spiking responses at ultrafast sub-nanosecond rates; thus offering great prospects for high-speed light-enabled spike-based processors. Recent works have shown spiking VCSELs are capable of tackling pattern recognition and image processing problems, but additionally, VCSELs have been used as nonlinear elements in photonic reservoir computing (RC) implementations, yielding state of the art operation. This work introduces and experimentally demonstrates for the first time a new GHz-rate photonic spiking neural network (SNN) built with a single VCSEL neuron. The reported system effectively implements a photonic VCSEL-based spiking reservoir computer, and demonstrates its successful application to a complex nonlinear classification task. Importantly, the proposed system benefits from a highly hardware-friendly, inexpensive realization (a single VCSEL device and off-the-shelf fibre-optic components), for high-speed (GHz-rate inputs) and low-power (sub-mW optical input power) photonic operation. These results open new pathways towards future neuromorphic photonic spike-based processing systems based upon VCSELs (or other laser types) for novel ultrafast machine learning and AI hardware.

Development and test of a next-generation positron detector

This report is focused on the development and test of a TDC (time to digital converter) and amplifier circuit for a state-of-the-art positron detector with position sensitivity. A newly developed one chip amplifier-shaper-discriminator (ASD) circuit with 16 channels input and a high-resolution TDC with a timing resolution on the order of picoseconds were tested. Silicon photomultipliers (SiPMs) were employed to give electric pulses for the optical input coming from a pulsed laser. We have successfully controlled the threshold level of the ASD circuit and measured the time structure of the SiPMs, as well as their multiple photon response from the pulse height histogram and the time over the threshold (TOT) histogram measured by the sub-nano second TDC. This is a technical basis for the next generation detector system with the positron tracking capability.

Time‐Lapse Image Classification Using a Diffractive Neural Network

Diffractive deep neural networks (D2NNs), comprised of spatially engineered passive surfaces, collectively process optical input information at the speed of light propagation through a thin diffractive volume, without any external computing power. Diffractive networks were demonstrated to achieve all‐optical object classification and perform universal linear transformations. Herein, a “time‐lapse” image classification scheme using a diffractive network is demonstrated for the first time, significantly advancing its classification accuracy and generalization performance on complex input objects by using the lateral movements of the input objects and/or the diffractive network, relative to each other. In a different context, such relative movements of the objects and/or the camera are routinely being used for image super‐resolution applications; inspired by their success, a time‐lapse diffractive network is designed to benefit from the complementary information content created by controlled or random lateral shifts. The design space and performance limits of time‐lapse diffractive networks are numerically explored, revealing a blind testing accuracy of 62.03% on the optical classification of objects from the CIFAR‐10 dataset. This constitutes the highest inference accuracy achieved so far using a single diffractive network on the CIFAR‐10 dataset. Time‐lapse diffractive networks will be broadly useful for the spatiotemporal analysis of input signals using all‐optical processors.

Wafer-Scale Fabrication of CMOS-Compatible Trapping-Mode Infrared Imagers with Colloidal Quantum Dots

Silicon-based complementary metal oxide semiconductor (CMOS) devices have dominated the technological revolution in the past decades. With increasing demands in machine vision, autonomous driving, and artificial intelligence, silicon CMOS imagers, as the major optical information input devices, face great challenges in spectral sensing ranges. In this paper, we demonstrate the development of CMOS-compatible infrared colloidal quantum-dot (CQD) imagers in the broadband short-wave and mid-wave infrared ranges (SWIR and MWIR, 1.5–5 μm). A new device architecture of trapping-mode detectors is proposed, fabricated, and demonstrated with lowered darkcurrents and improved responsivity. The CMOS-compatible fabrication process is completed with two-step sequential spin-coating processes of intrinsic and doped HgTe CQDs on an 8 in. CMOS readout wafer with photoresponse non-uniformity (PRNU) down to 4%, dead pixel rate of 0%, external quantum efficiency up to 175%, and detectivity as high as 2 × 1011 Jones for extended SWIR at 300 K and 8 × 1010 Jones for MWIR at 80 K. Both SWIR images and MWIR thermal images are demonstrated with great potential for semiconductor inspection, chemical identification, and temperature monitoring.

A Two‐Terminal Optoelectronic Synapses Array Based on the ZnO/Al2O3/CdS Heterojunction with Strain‐Modulated Synaptic Weight

AbstractArtificial optoelectronic synapses with flexibly regulated synaptic weight are crucial to the rapidly evolved artificial visual system. Although three‐terminal devices with transistor geometry have exhibited controllable synaptic response through applying electrical pulses on the gate terminal, the complicated device structure limits its integration with array configurations. In this work, a simple two‐terminal optoelectronic synapses array based on the ZnO/Al2O3/CdS heterojunction with tunable synaptic weight is presented. It can respond to UV and green light stimulation in a neuromorphic manner, allowing the implementation of the basic synaptic function. By introducing the piezo‐phototronic effect, the synaptic weight can be regulated in multilevels, extending the forgetting time by 30.08% and reducing training epochs for image recognition by 36.13%. In addition, the device can extract the target image from massive noisy optical inputs avoiding redundant data memorization. This work provides a novel method to regulate the synaptic weight of the simple two‐terminal device configuration through the piezo‐phototronic effect, showing potential applications for the mimicry of the human visual‐perception system.

High saturation photocurrent THz waveguide-type MUTC-photodiodes reaching mW output power within the WR3.4 band.

In this paper, we report on waveguide-type modified uni-traveling-carrier photodiodes (MUTC-PDs) providing a record high output power level for non-resonant photodiodes in the WR3.4 band. Indium phosphide (InP) based waveguide-type 1.55 µm MUTC-PDs have been fabricated and characterized thoroughly. Maximum output powers of -0.6 dBm and -2.7 dBm were achieved at 240 GHz and 280 GHz, respectively. This has been accomplished by an optimized layer structure and doping profile design that takes transient carrier dynamics into account. An energy-balance model has been developed to study and optimize carrier transport at high optical input intensities. The advantageous THz capabilities of the optimized MUTC layer structure are confirmed by experiments revealing a transit time limited cutoff frequency of 249 GHz and a saturation photocurrent beyond 20 mA in the WR3.4 band. The responsivity for a 16 µm long waveguide-type THz MUTC-PD is found to be 0.25 A/W. In addition, bow-tie antenna integrated waveguide-type MUTC-PDs are fabricated and reported to operate up to 0.7 THz above a received power of -40 dBm.

A 500 km Long Transmission with Coherent Optical OFDM Using Dual Polarization Quadrature Phase Shift Keying (QPSK) and Double Sideband Suppressed‐Enhanced Carrier (DSS‐EC)

AbstractCoherent optical orthogonal frequency division multiplexing (CO‐OFDM) systems are chosen for this task because of their high spectral efficiency, low inter‐symbol interference (ISI), low intercarrier interference (ICI), robustness against chromatic dispersion (CD), and high nonlinearity interference tolerance (HNIT). The DSS‐EC technique is utilized in this study to investigate a high‐speed 100 Gbps CO‐OFDM with a QPSK encoder over a 500 km uncompensated connection distance. The proposed system is compared to CO‐OFDM‐QPSK and CO‐OFDM‐16QAM systems in terms of log BER at various input optical signal to noise ratios (OSNRs). Results reveal that due to enhanced available bandwidth use of communication channels, the proposed CO‐OFDM‐DSS‐EC‐QPSK system provides minimum log BER at lower input OSNRs while the rest two systems show identical log BER performance at high input OSNRs. Therefore, proposed technique is a prominent solution for future generations high data demands and for a cost‐effective solution due to an uncompensated transmission channel.

Gigahertz optoacoustic vibration in Sub-5 nm tip-supported nano-optomechanical metasurface

The gigahertz acoustic vibration of nano-optomechanical systems plays an indispensable role in all-optical manipulation of light, quantum control of mechanical modes, on-chip data processing, and optomechanical sensing. However, the high optical, thermal, and mechanical energy losses severely limit the development of nano-optomechanical metasurfaces. Here, we demonstrated a high-quality 5 GHz optoacoustic vibration and ultrafast optomechanical all-optical manipulation in a sub-5 nm tip-supported nano-optomechanical metasurface (TSNOMS). The physical rationale is that the design of the semi-suspended metasurface supported by nanotips of <5 nm enhances the optical energy input into the metasurface and closes the mechanical and thermal output loss channels, result in dramatically improvement of the optomechanical conversion efficiency and oscillation quality of the metasurface. The design strategy of a multichannel-loss-mitigating semi-suspended metasurface can be generalized to performance improvements of on-chip processed nano-optomechanical systems. Applications include all-optical operation of nanomechanical systems, reconfigurable nanophotonic devices, optomechanical sensing, and nonlinear and self-adaptive photonic functionalities.

Light‐Triggered and Polarity‐Switchable Homojunctions for Optoelectronic Logic Devices

AbstractSemiconductor homojunctions based on 2D materials are promising candidates for optoelectronic logic devices due to their excellent electrostatic tunability and photoelectric characteristic. However, to reach programmable logic functions, the 2D homojunctions usually suffer from compulsory combinations of electrical and optical inputs. Here, a light‐triggered and polarity‐switchable homojunction made from the vertically stacked MoTe2/CuInP2S6/Au layers in a dual‐floating gate transistor configuration, is demonstrated. Utilizing the band alignment between MoTe2 and CuInP2S6, the photocarriers in MoTe2 can be excited to Au layer across the insulating CuInP2S6 efficiently, serving as floating gate to modulate the polarity of the MoTe2 homojunctions which produce photocurrents simultaneously in photovoltaic mode. A logic gate XOR is achieved in one single device without the need for any applied voltage. Moreover, the devices exhibit both anomalous photoresponse and optical memory behaviors in photoconductive mode. The results provide a potential route for the development of optoelectronic logic devices with fully light‐actuated sensing capability.

Ag2S island network reservoir that works with direct optical signal inputs

A physical reservoir that accepts direct light irradiation as input was developed using a Ag2S island network. Short-term memory and nonlinearity required for reservoirs are achieved by the diffusion of Ag+ cations in each Ag2S island and the growth of Ag filaments between Ag2S islands. We found that direct light irradiation to Ag2S islands changes local conductivity in a reservoir, which enhances the performance in short-term memory and nonlinearity of the reservoir. Using the effect, we performed a pattern classification of light that was irradiated to a Ag2S island network reservoir through a rectangular slit, which resulted in the accuracy of over 95%.

In-Field Pine Seedling Counting Using End-to-End Deep Learning for Inventory Management

Highlights A deep learning-based machine vision system was developed for pine seedling counting. Automated seedling counting achieved less error than the manual sampling-based practice. Regression-based counting from optical flow inputs achieved the best performance. Machine counting produces seedling density maps for management practice improvement. Abstract. The southern U.S. produces over 1 billion pine seedlings for market sales per year, with prices varying from 50 to 435 dollars per thousand seedlings. An accurate inventory of seedlings provides nursery management with insights into how many seedlings can be sold and/or if there is any loss due to washout, mechanical damage, or pest/diseases that can still be mitigated. In this study, we developed a system to count pine seedlings at production sites and map the seedling density in the field. A system with three cameras was developed to collect video from different drills in the seedling bed. The videos were preprocessed to restrict the region of interest to the center portion of the image in each camera and separated each drill into individual videos. Two different modalities, i.e., video and optical flow, were evaluated as inputs to a convolutional neural network followed by a long short-term recurrent network to model the sequence of frames and regress to the seedling count for each plot. The mean absolute percentage error (MAPE) of our best performing model was 7.5%, which is an improvement over the baseline manual sampling-based approach with a MAPE of 11%. The results showed that the proposed approach was able to count seedlings in a crowded scene under complex field conditions with higher accuracy than the standard manual practice. Therefore, the proposed system and results demonstrated the potential to replace manual counting and even provide further information such as a seedling density map over the field for precision forest nursery management and seedling harvesting. Keywords: CNN, LSTM, Nursery Inventory, Optical Flow, Pine Seedling, Regression.

SAR Ship Detection Based on Deep Domain Adaptation with Limited Samples

Ship detection in synthetic aperture radar (SAR) images have important applications in military and civil fields. Nonetheless, SAR images usually suffer from the disadvantage of having limited labeled samples. This is undoubtedly a challenge for the deep learning based methods, which require a large number of samples for training. To solve this problem, many researchers have applied the domain adaptation (DA) methods for the SAR ship detection tasks, which use optical images as the source domain and transform optical images to SAR domain directly. However, there is large difference between SAR and optical images. Hence, the deep learning detector may not be able to learn the target features accurately when the transformed images are used for training. In order to solve above problem, a novel ship detection method with limited labeled samples is proposed, whose training and test process is mainly implemented in the optical domain. In the training stage, optical images are used to pre-train the model. Here, the transformed optical images from SAR images are used to further fine-tune the pre-trained model. Accordingly, in the test stage, SAR images are transformed to optical domain and input in the model to obtain the detection results. Experimental results based on the real dataset demonstrate the effectiveness of the proposed method for SAR ship detection.