Backpropagating neurons from bichromatic interaction with a three-level system

Optical implementation of a backpropagating neuron by means of a nonlinear Fabry-Perot etalon requires thresholding a forward signal beam while the transmittance of a backpropagating beam is multiplied by the differential of the forward signal. This is achievable by inputting a bichromatic field to a three-level system in an optical cavity. The response characteristics of this device have the added possibility of adaptability of the threshold by the backward probe input intensity

Experimental demonstration of an integrated on-chip p-bit core utilizing stochastic Magnetic Tunnel Junctions and 2D-MoS2_{2} FETs

Probabilistic computing is a novel computing scheme that offers a more efficient approach than conventional CMOS-based logic in a variety of applications ranging from optimization to Bayesian inference, and invertible Boolean logic. The probabilistic-bit (or p-bit, the base unit of probabilistic computing) is a naturally fluctuating entity that requires tunable stochasticity; by coupling low-barrier stochastic Magnetic Tunnel Junctions (MTJs) with a transistor circuit, a compact implementation is achieved. In this work, through integrating stochastic MTJs with 2D-MoS$_{2}$ FETs, the first on-chip realization of a key p-bit building block displaying voltage-controllable stochasticity is demonstrated. In addition, supported by circuit simulations, this work provides a careful analysis of the three transistor-one magnetic tunnel junction (3T-1MTJ) p-bit design, evaluating how the characteristics of each component influence the overall p-bit output. This understanding of the interplay between the characteristics of the transistors and the MTJ is vital for the construction of a fully functioning p-bit, making the design rules presented in this article key for future experimental implementations of scaled on-chip p-bit networks

Principles of Neuromorphic Photonics

In an age overrun with information, the ability to process reams of data has become crucial. The demand for data will continue to grow as smart gadgets multiply and become increasingly integrated into our daily lives. Next-generation industries in artificial intelligence services and high-performance computing are so far supported by microelectronic platforms. These data-intensive enterprises rely on continual improvements in hardware. Their prospects are running up against a stark reality: conventional one-size-fits-all solutions offered by digital electronics can no longer satisfy this need, as Moore's law (exponential hardware scaling), interconnection density, and the von Neumann architecture reach their limits. With its superior speed and reconfigurability, analog photonics can provide some relief to these problems; however, complex applications of analog photonics have remained largely unexplored due to the absence of a robust photonic integration industry. Recently, the landscape for commercially-manufacturable photonic chips has been changing rapidly and now promises to achieve economies of scale previously enjoyed solely by microelectronics. The scientific community has set out to build bridges between the domains of photonic device physics and neural networks, giving rise to the field of \emph{neuromorphic photonics}. This article reviews the recent progress in integrated neuromorphic photonics. We provide an overview of neuromorphic computing, discuss the associated technology (microelectronic and photonic) platforms and compare their metric performance. We discuss photonic neural network approaches and challenges for integrated neuromorphic photonic processors while providing an in-depth description of photonic neurons and a candidate interconnection architecture. We conclude with a future outlook of neuro-inspired photonic processing.Comment: 28 pages, 19 figure

Optical memory disks in optical information processing

We describe the use of optical memory disks as elements in optical information processing architectures. The optical disk is an optical memory devicew ith a storage capacity approaching 1010b its which is naturally suited to parallel access. We discuss optical disk characteristics which are important in optical computing systems such as contrast, diffraction efficiency, and phase uniformity. We describe techniques for holographic storage on optical disks and present reconstructions of several types of computer-generated holograms. Various optical information processing architectures are described for applications such as database retrieval, neural network implementation, and image correlation. Selected systems are experimentally demonstrated

QRsens:dual-purpose quick response code with built-in colorimetric sensors

QRsens represents a family of Quick Response (QR) sensing codes for in-situ air analysis with a customized smartphone application to simultaneously read the QR code and the colorimetric sensors. Five colorimetric sensors (temperature, relative humidity (RH), and three gas sensors (CO₂, NH₃ and H₂S)) were designed with the aim of proposing two end-use applications for ambient analysis, i.e., enclosed spaces monitoring, and smart packaging. Both QR code and colorimetric sensing inks were deposited by standard screen printing on white paper. To ensure minimal ambient light dependence of QRsens during the real-time analysis, the smartphone application was programmed for an effective colour correction procedure based on black and white references for three standard illumination temperatures (3000, 4000 and 5000 K). Depending on the type of sensor being analysed, this integration achieved a reduction of ∼71 – 87% of QRsens's dependence on the light temperature. After the illumination colour correction, colorimetric gas sensors exhibited a detection range of 0.7–4.1%, 0.7–7.5 ppm, and 0.13–0.7 ppm for CO2, NH3 and H2S, respectively. In summary, the study presents an affordable built-in multi-sensing platform in the form of QRsens for in-situ monitoring with potential in different types of ambient air analysis applications

QRsens: Dual-purpose quick response code with built-in colorimetric sensors

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.snb.2022.133001.QRsens represents a family of Quick Response (QR) sensing codes for in-situ air analysis with a customized smartphone application to simultaneously read the QR code and the colorimetric sensors. Five colorimetric sensors (temperature, relative humidity (RH), and three gas sensors (CO2, NH3 and H2S)) were designed with the aim of proposing two end-use applications for ambient analysis, i.e., enclosed spaces monitoring, and smart packaging. Both QR code and colorimetric sensing inks were deposited by standard screen printing on white paper. To ensure minimal ambient light dependence of QRsens during the real-time analysis, the smartphone application was programmed for an effective colour correction procedure based on black and white references for three standard illumination temperatures (3000, 4000 and 5000 K). Depending on the type of sensor being analysed, this integration achieved a reduction of ~71 – 87% of QRsens’s dependence on the light temperature. After the illumination colour correction, colorimetric gas sensors exhibited a detection range of 0.7–4.1%, 0.7–7.5 ppm, and 0.13–0.7 ppm for CO2, NH3 and H2S, respectively. In summary, the study presents an affordable built-in multi-sensing platform in the form of QRsens for in-situ monitoring with potential in different types of ambient air analysis applications.Spanish MCIN/AEI/10.13039/ 501100011033/ (Projects PID2019–103938RB-I00, ECQ2018–004937- P and grant IJC2020–043307-I)Junta de Andalucía (Projects B- FQM-243-UGR18, P18-RT-2961)European Regional Development Funds (ERDF)European Union NextGenerationEU/PRT

Feasibility of an in situ measurement device for bubble size and distribution

The feasibility of in situ measurement device for bubble size and distribution was explored. A novel in situ probe measurement system, the EnviroCam™, was developed. Where possible, this probe incorporated strengths, and minimized weaknesses of historical and currently available real-time measurement methods for bubbles. The system was based on a digital, high-speed, high resolution, modular camera system, attached to a stainless steel shroud, compatible with standard Ingold ports on fermenters. Still frames and/or video were produced, capturing bubbles passing through the notch of the shroud. An LED light source was integral with the shroud. Bubbles were analyzed using customized commercially available image analysis software and standard statistical methods. Using this system, bubble sizes were measured as a function of various operating parameters (e.g., agitation rate, aeration rate) and as a function of media properties (e.g., viscosity, antifoam, cottonseed flour, and microbial/animal cell broths) to demonstrate system performance and its limitations. For selected conditions, mean bubble size changes qualitatively compared favorably with published relationships. Current instrument measurement capabilities were limited primarily to clear solutions that did not contain large numbers of overlapping bubbles

Quantitative Optical Studies of Oxidative Stress in Rodent Models of Eye and Lung Injuries

Optical imaging techniques have emerged as essential tools for reliable assessment of organ structure, biochemistry, and metabolic function. The recognition of metabolic markers for disease diagnosis has rekindled significant interest in the development of optical methods to measure the metabolism of the organ. The objective of my research was to employ optical imaging tools and to implement signal and image processing techniques capable of quantifying cellular metabolism for the diagnosis of diseases in human organs such as eyes and lungs. To accomplish this goal, three different tools, cryoimager, fluorescent microscope, and optical coherence tomography system were utilized to study the physiological metabolic markers and early structural changes due to injury in vitro, ex vivo, and at cryogenic temperatures. Cryogenic studies of eye injuries in animal models were performed using a fluorescence cryoimager to monitor two endogenous mitochondrial fluorophores, NADH (nicotinamide adenine dinucleotide) and FAD (flavin adenine dinucleotide). The mitochondrial redox ratio (NADH/ FAD), which is correlated with oxidative stress level, is an optical biomarker. The spatial distribution of mitochondrial redox ratio in injured eyes with different durations of the disease was delineated. This spatiotemporal information was helpful to investigate the heterogeneity of the ocular oxidative stress in the eyes during diseases and its association with retinopathy. To study the metabolism of the eye tissue, the retinal layer was targeted, which required high resolution imaging of the eye as well as developing a segmentation algorithm to quantitatively monitor and measure the metabolic redox state of the retina. To achieve a high signal to noise ratio in fluorescence image acquisition, the imaging was performed at cryogenic temperatures, which increased the quantum yield of the intrinsic fluorophores. Microscopy studies of cells were accomplished by using an inverted fluorescence microscope. Fixed slides of the retina tissue as well as exogenous fluorophores in live lung cells were imaged using fluorescent and time-lapse microscopy. Image processing techniques were developed to quantify subtle changes in the morphological parameters of the retinal vasculature network for the early detection of the injury. This implemented image cytometry tool was capable of segmenting vascular cells, and calculating vasculature features including: area, caliber, branch points, fractal dimension, and acellular capillaries, and classifying the healthy and injured retinas. Using time-lapse microscopy, the dynamics of cellular ROS (Reactive Oxygen Species) concentration was quantified and modeled in ROS-mediated lung injuries. A new methodology and an experimental protocol were designed to quantify changes of oxidative stress in different stress conditions and to localize the site of ROS in an uncoupled state of pulmonary artery endothelial cells (PAECs). Ex vivo studies of lung were conducted using a spectral-domain optical coherence tomography (SD-OCT) system and 3D scanned images of the lung were acquired. An image segmentation algorithm was developed to study the dynamics of structural changes in the lung alveoli in real time. Quantifying the structural dynamics provided information to diagnose pulmonary diseases and to evaluate the severity of the lung injury. The implemented software was able to quantify and present the changes in alveoli compliance in lung injury models, including edema. In conclusion, optical instrumentation, combined with signal and image processing techniques, provides quantitative physiological and structural information reflecting disease progression due to oxidative stress. This tool provides a unique capability to identify early points of intervention, which play a vital role in the early detection of eye and lung injuries. The future goal of this research is to translate optical imaging to clinical settings, and to transfer the instruments developed for animal models to the bedside for patient diagnosis