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10 GB-100 GB Parallel Optical Interconnect Challenges. Presentation discusses special technology developed by the small company XLoom. Overview describes the need for optical interconnect solutions; current solutions; XLoom iFlame optical engine; 4 parallel lane 5 Gbps transceiver based on XLoom iFlame-Avdat.
On-centre impurity related electronic and optical properties are studied in a Boron nitride coupled quantum well. Confined energies for the intraband transition are investigated by studying differential cross section of electron Raman scattering taking into consideration of spatial confinement in a B{sub 0.3}Ga{sub 0.7}N/BN coupled quantum well. Raman gain as a function of incident optical pump intensity is computed for constant well width. The enhancement of Raman gain is observed with the application of pump power. The results can be applied for the potential applications for fabricating some optical devices such as optical switches, infrared photo-detectors and electro-optical modulator.
We show that a laser pulse can always be found that induces a desired optical response from an arbitrary dynamical system. As illustrations, driving fields are computed to induce the same optical response from a variety of distinct systems (open and closed, quantum and classical). As a result, the observed induced dipolar spectra without detailed information on the driving field are not sufficient to characterize atomic and molecular systems. The formulation may also be applied to design materials with specified optical characteristics. These findings reveal unexplored flexibilities of nonlinear optics.
Pairing the accuracy of the Kohn–Sham density-functional framework with the efficiency of a stochastic algorithmic approach, mixed stochastic-deterministic density functional theory (mDFT) achieves a favorable computational scaling with system sizes and electronic temperatures. We employ the recently developed mDFT formalism to investigate the dynamic charge-transport properties of systems in the warm dense matter regime. The optical conductivity spectra are computed for single- and multi- component mixtures of carbon, hydrogen, and beryllium using two complementary approaches: Kubo–Greenwood in the mDFT picture and real-time time-dependent mDFT. We further devise a decomposition of the Onsager coefficients leading up to the Kubo–Greenwood spectra to exhibit contributions from the deterministic, stochastic, and mixed electronic state transitions at different incident photon energies.
The recent emergence of novel computational devices, such as adiabatic quantum computers, CMOS annealers, and optical parametric oscillators, presents new opportunities for hybrid-optimization algorithms that leverage these kinds of specialized hardware. In this work, we propose the idea of an Ising processing unit as a computational abstraction for these emerging tools. Challenges involved in using and bench- marking these devices are presented, and open-source software tools are proposed to address some of these challenges. The proposed benchmarking tools and methodology are demonstrated by conducting a baseline study of established solution methods to a D-Wave 2X adiabatic quantum computer, one example of a commercially available Ising processing unit.
Increasing the energy efficiency and reducing the footprint of on-chip photodetectors enable dense optical interconnects for emerging computational and sensing applications. While heterojunction phototransistors (HPTs) exhibit high energy efficiency and negligible excess noise factor, their gain-bandwidth product (GBP) has been inferior to that of avalanche photodiodes at low optical powers. Here, we demonstrate that utilizing type-II energy band alignment in an Sb-based HPT results in six times smaller junction capacitance per unit area and a significantly higher GBP at low optical powers. These type-II HPTs were scaled down to 2 μm in diameter and fully integrated with photonic waveguides on silicon. Thanks to their extremely low dark current and high internal gain, these devices exhibit a GBP similar to the best avalanche devices (∼270 GHz) but with one order of magnitude better energy efficiency. Their energy consumption is about 5 fJ/bit at 3.2 Gbps, with an error rate below 10−9 at −25 dBm optical power at 1550 nm. These features suggest new opportunities for creating highly efficient and compact optical receivers based on phototransistors with type-II band alignment.
Abstract. Atmospheric aerosols have a substantial impact on climate and remain one of the largest sources of uncertainty in climate prediction. Accurate representation of their direct radiative effects is a crucial component of modern climate models. However, direct computation of the radiative properties of aerosol populations is far too computationally expensive to perform in a climate model, so optical properties are typically approximated using a parameterization. This work develops artificial neural networks (ANNs) capable of replacing the current aerosol optics parameterization used in the Energy Exascale Earth System Model (E3SM). A large training dataset is generated by using Mie code to directly compute the optical properties of a range of atmospheric aerosol populations given a large variety of particle sizes, wavelengths, and refractive indices. Optimal neural architectures for shortwave and longwave bands are identified by evaluating ANNs with randomly generated wirings. Randomly generated deep ANNs are able to outperform conventional multilayer-perceptron-style architectures with comparable parameter counts. Finally, the ANN-based parameterization produces significantly more accurate bulk aerosol optical properties than the current parameterization when compared with direct Mie calculations using mean absolute error. The success of this approach makes possible the future inclusion of much more sophisticated representations of aerosol optics in climate models that cannot be captured by extension of the existing parameterization scheme and also demonstrates the potential of random-wiring-based neural architecture search in future applications in the Earth sciences.
We developed an optical transmission module consisting of 16-channel analog-to-digital converter (ADC), digital-noise filter, and one-line serial transmitter, which transferred Superconducting Quantum Interference Device (SQUID) readout data to a computer by a single optical cable. A 16-channel ADC sent out SQUID readouts data with 32-bit serial data of 8-bit channel and 24-bit voltage data at a sample rate of 1.5 kSample/s. A digital-noise filter suppressed digital noises generated by digital clocks to obtain SQUID modulation as large as possible. One-line serial transmitter reformed 32-bit serial data to the modulated data that contained data and clock, and sent them through a single optical cable. When the optical transmission modules were applied to 152-channel SQUID magnetoencephalography system, this system maintained a field noise level of 3 fT/√Hz @ 100 Hz.
Developing reliable and tunable metamaterials is fundamental to next-generation optical-based nanodevices and computing schemes. In this review, an overview of recent progress made with a unique group of ceramic-based functional nanocomposites, i.e., vertically aligned nanocomposites (VANs), is presented, with the focus on the tunable anisotropic optical properties. Using a self-assembling bottom-up deposition method, the as-grown VANs present great promise in terms of structural flexibility and property tunability. Such broad tunability of functionalities is achieved through VAN designs, material selection, growth control, and strain coupling. The as-grown multi-phase VAN films also present enormous advantages, including wafer scale integration, epitaxial quality, sharp atomic interface, as well as designable materials and geometries. This review also covers the research directions with practical device potentials, such as multiplex sensing, high-temperature plasmonics, magneto-optical switching, as well as photonic circuits.
Optical accuracy is a primary driver of parabolic trough concentrating solar power (CSP) plant performance, but can be damaged by wind loads, gravity, error during installation, and regular plant operation. Collecting and analyzing optical measurements over an entire operating parabolic trough plant is difficult, given the large scale of typical installations. Distant Observer, a software tool developed at the National Renewable Energy Laboratory, uses images of the absorber tube reflected in the collector mirror to measure both surface slope in the parabolic mirror and offset of the absorber tube from the ideal focal point. This technology has been adapted for fast data collection using low-cost commercial drones, but until recently still required substantial human labor to process large amounts of data. A new method leveraging advanced deep learning and computer vision tools can drastically reduce the time required to process images. This new method addresses the primary analysis bottleneck, identifying featureless, reflective mirror corner points to a high degree of accuracy. Recent work has shown promising results using computer vision methods. The combined deep learning and computer vision approach presented here proved highly effective and has the potential to further automate data collection and analysis, making the tool more robust. The method presented in this paper automatically identified 74.3% of mirror corners within 2 pixels of their manually marked counterparts and 91.9% within 3 pixels. This level of accuracy is sufficient for practical Distant Observer analysis within a target uncertainty. A commercial drone collected video of over 100 parabolic trough modules at an operating CSP plant to demonstrate the deep learning and computer vision method's usefulness in processing large amounts of data. These troughs were successfully analyzed using Distant Observer, paired with the new deep learning and computer vision algorithm, and can provide plant operators and trough designers with valuable insight about plant performance, operating strategies, and plant-wide optical error trends.
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A wide-aperture aspheric lens for focusing a terahertz electromagnetic-radiation beam in a circle of the subwavelength size is proposed. The calculation of the lens and the estimation of size of created caustic were carried out using computational methods of geometric optics and electrodynamics. The lens is made of high-density polyethylene with the help of a turning machine. For experimental estimation of the spatial resolution provided by the lens, a THz imaging system based on raster scanning of the object’s surface was created. The imaging system was used in combination with wide-aperture THz optics to record images of the streak plates with different spatial frequencies. Analysis of the experimental data showed that the aspheric lens allows the resolution of two objects spaced at a distance of 0.95λ, providing contrast of 15%. The proposed THz optics is superior to classical THz spherical lenses and off-axis parabolic mirrors, greatly expanding the capabilities of THz-spectroscopy methods and imaging.
This work presents the computational evaluation of a new model for relative humidity sensor based on the principle of intermodal interference using a square-section no-core tapered optical fiber compared to a classical cylindrical tapered optical fiber sensor. Attempting at a new application of this type of sensor, simulations were carried out in the range of up to 60% of relative humidity, the main interest range of the pharmaceutical industry. Several materials were used in its modeling and an analysis was developed in its constructive dimensions, in order to verify the influence of each of them on the sensor performance.
A custom photobioreactor (PBR) was designed to enable automatic light adjustments using computerized feedback control. A black anodized aluminum enclosure, constructed to surround the borosilicate reactor vessel, prevents the transmission of ambient light and serves as a mount for arrays of light-emitting diodes (LEDs). The high-output LEDs provide narrow-band light of either 630 or 680 nm for preferential excitation of the cyanobacterial light-harvesting pigments, phycobilin or chlorophyll a, respectively. Custom developed software BioLume provides automatic control of optical properties and a computer feedback loop can automatically adjust the incident irradiance as necessary to maintain a fixed transmitted light through the culture, based on user-determined set points. This feedback control serves to compensate for culture dynamics which have optical effects, (e.g., changing cell density, pigment adaptations) and thus can determine the appropriate light conditions for physiological comparisons or to cultivate light-sensitive strains, without prior analyses. The LED PBR may also be controlled as a turbidostat, using a feedback loop to continuously adjust the rate of media-dilution based on the transmitted light measurements, with a fast and precise response. This cultivation system gains further merit as a high-performance analytical device, using non-invasive tools (e.g., dissolved gas sensors, online mass spectrometry) to automate real-time measurements, thus permitting unsupervised experiments to search for optimal growth conditions, to monitor physiological responses to perturbations, as well as to quantitate photophysiological parameters using an in situ light-saturation response routine.
Semiconductors composed of organic molecules are promising as components for flexible and inexpensive optoelectronic devices, with many recent studies aimed at understanding their electronic and optical properties. In particular, computational modeling of these complex materials has provided new understanding of the underlying properties which give rise to their excited-state phenomena. Here, this article provides an overview of recent many-body perturbation theory (MBPT) studies of optical excitations within organic molecules and solids. We discuss the accuracy of MBPT within the GW/BSE approach in predicting excitation energies and absorption spectra, and assess the impact of two commonly used approximations, the DFT starting point and the Tamm–Dancoff approximation. Moreover, we summarize studies that elucidate the role of solid-state structure on the nature of excitons in organic crystals. These studies show that a rich physical understanding of organic materials can be obtained from GW/BSE.