T. Skauli

Improved dispersion relations for GaAs and applications to nonlinear optics

The refractive index of GaAs has been measured in the wavelength range from 0.97 to 17 μm, which covers nearly the entire transmission range of the material. Linear and quadratic temperature coefficients of the refractive index have been fitted to data measured between room temperature and 95 °C. In the midinfrared, the refractive index and temperature dependence are obtained from analysis of etalon fringes measured by Fourier-transform spectroscopy in undoped GaAs wafers. In the near infrared, the refractive index is deduced from the quasiphasematching (QPM) wavelengths of second-harmonic generation in orientation-patterned GaAs crystals. Two alternative empirical expressions are fitted to the data to give the refractive index as a function of wavelength and temperature. These dispersion relations agree with observed QPM conditions for midinfrared difference-frequency generation and second-harmonic generation. Predictions for various nonlinear optical interactions are presented, including tuning curves f...

Measurement of the nonlinear coefficient of orientation-patterned GaAs and demonstration of highly efficient second-harmonic generation

Quasi-phase-matched (QPM) GaAs structures, 0.5 mm thick, 10 mm long, and with 61-mum grating periods, were grown by a combination of molecular-beam epitaxy and hydride vapor phase epitaxy. These were characterized by use of mid-IR second-harmonic generation (SHG) with a ZnGeP(2) (ZGP) optical parametric oscillator as a pump source. The SHG efficiencies of QPM GaAs and QPM LiNbO(3) were directly compared, and a ratio of nonlinear coefficients d(14)(GaAs)/d(33) (LiNbO(3))=5.01+/-0.3 was found at 4.1-mum fundamental wavelength. For input pulse energies as low as 50muJ and approximately 60-ns pulse duration, an internal SHG conversion efficiency of 33% was measured in QPM GaAs.

Real-time anomaly detection in hyperspectral images using multivariate normal mixture models and GPU processing

Hyperspectral imaging, which records a detailed spectrum of light arriving in each pixel, has many potential uses in remote sensing as well as other application areas. Practical applications will typically require real-time processing of large data volumes recorded by a hyperspectral imager. This paper investigates the use of graphics processing units (GPU) for such real-time processing. In particular, the paper studies a hyperspectral anomaly detection algorithm based on normal mixture modelling of the background spectral distribution, a computationally demanding task relevant to military target detection and numerous other applications. The algorithm parts are analysed with respect to complexity and potential for parallellization. The computationally dominating parts are implemented on an Nvidia GeForce 8800 GPU using the Compute Unified Device Architecture programming interface. GPU computing performance is compared to a multi-core central processing unit implementation. Overall, the GPU implementation runs significantly faster, particularly for highly data-parallelizable and arithmetically intensive algorithm parts. For the parts related to covariance computation, the speed gain is less pronounced, probably due to a smaller ratio of arithmetic to memory access. Detection results on an actual data set demonstrate that the total speedup provided by the GPU is sufficient to enable real-time anomaly detection with normal mixture models even for an airborne hyperspectral imager with high spatial and spectral resolution.

Difference frequency generation of 8-µm radiation in orientation-patterned GaAs

First-order quasi-phase-matched difference frequency generation of narrowband tunable mid-infrared light is demonstrated in orientation-patterned GaAs. The all-epitaxial orientation-patterned crystal is fabricated by a combination of molecular beam epitaxy and hydride vapor phase epitaxy. Lasers at 1.3 and 1.55 microm were mixed to give an idler output at 8 microm, with power and wavelength tuning consistent with theoretical estimates, indicating excellent material uniformity over the 19-mm-long and 500-microm-thick device.

A collection of hyperspectral images for imaging systems research

A set of hyperspectral image data are made available, intended for use in modeling of imaging systems. The set contains images of faces, landscapes and buildings. The data cover wavelengths from 0.4 to 2.5 micrometers, spanning the visible, NIR and SWIR electromagnetic spectral ranges. The images have been recorded with two HySpex line-scan imaging spectrometers covering the spectral ranges 0.4 to 1 micrometers and 1 to 2.5 micrometers. The hyperspectral data set includes measured illuminants and software for converting the radiance data to estimated reflectance. The images are being made available for download at http://scien.stanford.edu

Calibration of the arsenic mole fraction in MBE grown GaAsySb1−y and AlxGa1−xAsySb1−y (y<0.2)

Abstract We present a systematic study mapping how the As incorporation into GaAs y Sb 1− y and Al x Ga 1− x As y Sb 1− y ( y

Wireless power transfer in the presence of metallic plates: Experimental results

We demonstrate efficient wireless power transfer between two high Q resonators, especially in a complex electromagnetic environment. In the close proximity of metallic plates, the transfer efficiency stays roughly the same as the free space efficiency with proper designs. The experimental data fits well with a coupled theory model. Resonance frequency matching, alignment of the magnetic field, and impedance matching are shown to be the most important factors for efficient wireless power transfer.

Mapping of CdZnTe substrates and CdHgTe epitaxial layers by X-ray diffraction

Abstract A simple procedure is described for mapping of lattice parameter and X-ray rocking curve width across Cd 1− y Zn y Te (CZT) substrates and Cd x Hg 1− x Te (CMT) epitaxial layers. It is shown how screening of the crystallinity and composition of CZT substrates can be utilized to make subsequent X-ray characterizations of epitaxial layers more reliable. This also allows selection of substrates with a close lattice matching to a given CMT composition, to reduce or avoid layer relaxation. Substrates with laterally varying Zn content give a varying lattice mismatch on a single epitaxial layer. Correlation of the lattice parameter maps of substrate and layer shows the resulting variations in layer strain, and the onset of relaxation can be clearly identified. Mapping of rocking curve peak widths on good quality CZT substrates and closely lattice matched CMT layers shows that the peak width can be below 6 arcsec, limited essentially by the intrinsic peak width of the materials. Additional broadening of the layer peaks is introduced primarily by substrate defects and misfit dislocations, unless epitaxial growth conditions deviate significantly from their optimum.

An airborne real-time hyperspectral target detection system

An airborne system for hyperspectral target detection is described. The main sensor is a HySpex pushbroom hyperspectral imager for the visible and near-infrared spectral range with 1600 pixels across track, supplemented by a panchromatic line imager. An optional third sensor can be added, either a SWIR hyperspectral camera or a thermal camera. In real time, the system performs radiometric calibration and georeferencing of the images, followed by image processing for target detection and visualization. The current version of the system implements only spectral anomaly detection, based on normal mixture models. Image processing runs on a PC with a multicore Intel processor and an Nvidia graphics processing unit (GPU). The processing runs in a software framework optimized for large sustained data rates. The platform is a Cessna 172 aircraft based close to FFI, modified with a camera port in the floor.

Target detection in hyperspectral images based on multicomponent statistical models for representation of background clutter

Hyperspectral imaging has potential for detection of low-contrast targets in the presence of significant background clutter. We consider here the important case of detecting small targets as anomalies in a spatially cluttered natural background. In order to achieve a low false alarm rate, the properties of the background must be captured by the analysis procedure in sufficient detail to represent the full range of natural variation. Here we examine a statistical background model where background variations are represented by a sum of several multivariate normal probability distributions. The parameters of the statistical model are estimated using the stochastic expectation maximization (SEM) method. The quality of the resulting models representation of natural backgrounds is discussed in terms of detection performance as a function of model complexity. Results are given for various illumination conditions and targets with different contrast to the background. We show that detection performance can be drastically improved by using multi-component background models, and that a low number of components is sufficient for detection of quite low contrast targets. The study is based on data with high spectral and spatial resolution from the Airborne Spectral Imager (ASI) hyperspectral sensor.