A massively parallel time-domain coupled electrodynamics–micromagnetics solver

We present a high-performance coupled electrodynamics–micromagnetics solver for full physical modeling of signals in microelectronic circuitry. The overall strategy couples a finite-difference time-domain approach for Maxwell’s equations to a magnetization model described by the Landau–Lifshitz–Gilbert equation. The algorithm is implemented in the Exascale Computing Project software framework, AMReX, which provides effective scalability on manycore and GPU-based supercomputing architectures. Furthermore, the code leverages ongoing developments of the Exascale Application Code, WarpX, which is primarily being developed for plasma wakefield accelerator modeling. Our temporal coupling scheme provides second-order accuracy in space and time by combining the integration steps for the magnetic field and magnetization into an iterative sub-step that includes a trapezoidal temporal discretization for the magnetization. The performance of the algorithm is demonstrated by the excellent scaling results on NERSC multicore and GPU systems, with a significant (59×) speedup on the GPU using a node-by-node comparison. We demonstrate the utility of our code by performing simulations of an electromagnetic waveguide and a magnetically tunable filter.

Simulated Annealing-Based Hyperspectral Data Optimization for Fish Species Classification: Can the Number of Measured Wavelengths Be Reduced?

Relative to standard red/green/blue (RGB) imaging systems, hyperspectral imaging systems offer superior capabilities but tend to be expensive and complex, requiring either a mechanically complex push-broom line scanning method, a tunable filter, or a large set of light emitting diodes (LEDs) to collect images in multiple wavelengths. This paper proposes a new methodology to support the design of a hypothesized system that uses three imaging modes—fluorescence, visible/near-infrared (VNIR) reflectance, and shortwave infrared (SWIR) reflectance—to capture narrow-band spectral data at only three to seven narrow wavelengths. Simulated annealing is applied to identify the optimal wavelengths for sparse spectral measurement with a cost function based on the accuracy provided by a weighted k-nearest neighbors (WKNN) classifier, a common and relatively robust machine learning classifier. Two separate classification approaches are presented, the first using a multi-layer perceptron (MLP) artificial neural network trained on sparse data from the three individual spectra and the second using a fusion of the data from all three spectra. The results are compared with those from four alternative classifiers based on common machine learning algorithms. To validate the proposed methodology, reflectance and fluorescence spectra in these three spectroscopic modes were collected from fish fillets and used to classify the fillets by species. Accuracies determined from the two classification approaches are compared with benchmark values derived by training the classifiers with the full resolution spectral data. The results of the single-layer classification study show accuracies ranging from ~68% for SWIR reflectance to ~90% for fluorescence with just seven wavelengths. The results of the fusion classification study show accuracies of about 95% with seven wavelengths and more than 90% even with just three wavelengths. Reducing the number of required wavelengths facilitates the creation of rapid and cost-effective spectral imaging systems that can be used for widespread analysis in food monitoring/food fraud, agricultural, and biomedical applications.

Underwater Spectral Imaging System Based on Liquid Crystal Tunable Filter

In the past decade, underwater spectral imaging (USI) has shown great potential in underwater exploration for its high spectral and spatial resolution. This proposal presents a stare-type USI system combined with the liquid crystal tunable filter (LCTF) spectral splitting device. Considering the working features of LCTF and the theoretical model of USI, the core structure containing “imaging lens-LCTF-imaging sensor” is designed and developed. The system is compact, and the optical geometry is constructed minimally. The spectral calibration test analysis proved that the spectral response range of the system covers a full band of 400 nm to 700 nm with the highest spectral resolution between 6.7 nm and 18.5 nm. The experiments show that the system can quickly collect high-quality spectral image data by switching between different spectral bands arbitrarily. The designed prototype provides a feasible and reliable spectral imaging solution for in situ underwater targets observation with high spectrum collecting efficiency.

Investigation of the phase delay of radiation by a transparent ferroelectric polymer film

In this paper, we study samples of an optically transparent ferroelectric polymer film with deposited nanoscale electrically conductive coatings designed to modulate the transmitted electromagnetic radiation of the visible and near-infrared wavelengths. Such films can be used, for example, in interference devices for phase delay compensation or for the implementation of the Phase Shifting Interferometry, in adaptive optics, etc. To measure the phase delay of the radiation passing through the samples under study, an installation based on the Mach-Zehnder interferometer was used. In the illumination branch of the installation, a broadband radiation source and an acousto-optic tunable filter are installed; in one of the arms of the interferometer, the test sample is installed. The interference pattern was recorded on a matrix radiation receiver; the phase information was decoded by digital holography methods. The report presents the results of measurements and shows that a modulation of the passed optical radiation occurs under the influence of the electric field as a result of changes in the geometrical dimensions of the film.

K-means clustering of zebrafish embryos images acquired with AOTF-based hyperspectral microscope

Model organism studies are widely implemented in biomedical research fields. Zebrafish is a common and convenient model organism. To provide in vivo investigation of living zebrafish the non-invasive imaging methods are implemented. Hyperspectral imaging utilizing acousto-optic tunable filters is a perspective modality for zebrafish embryos and larvae automated observation. In this paper, the hyperspectral microscope based on the acousto-optical tunable filter is described. Using the hyperspectral image arrays obtained with the described setup, the K-means clustering algorithm is tested. The results obtained for different number of clusters are presented and discussed.

Analysis of chromatic aberrations influence on operation of the tunable AOTF-based source

Developing a source with the possibility of tuning in wavelengths based on an acousto-optical tunable filter (AOTF), an essential factor is the ability to provide accurate color coordinates of the simulated color (in the case of developing a color standard for colorimetry) or the required wavelength (in the case of an application for spectral studies). As shown earlier, the choice of the principal layout – confocal or parallel beam path - primarily determines the dimensions and efficiency of using the luminous flux. However, these schemes also need to be analyzed for color or wavelength fidelity, considering other components used in the scheme. The analysis performed allows to identify the optimal scheme to ensure the required color reproduction accuracy and establish the requirements for correcting chromatic aberrations of the components.