nils-herrmann/clean_scirepeval huggingface dataset:
Bayesian super-resolution pansharpening using contourlets

Pansharpening is a technique that fuses a low resolution multispectral image and a high resolution panchromatic image, to obtain a multispectral image with the spatial resolution and quality of the panchromatic image while preserving spectral information of the multispectral image. In this paper, we present a new pansharpening method based on super-resolution and contourlet transform. The experimental results show that the proposed method not only enhances the spatial resolution of the pansharpened image, but also preserves the spectral information of the original multispectral image.
Transition from ballistic to ohmic transport in T-Branch junctions at room temperature in GalnAs/AlInAs heterostructures

We have developed technology based on GalnAs/AIInAs for building ballistic devices working at room temperature. We present processes for ballistic devices (T-branch junctions (TBJs), Y-branch junctions (YBJs)). Then we present DC characterization of TBJs to show the transition from ballistic to ohmic transport at room temperature and also experimental results for Y-branch junctions (YBJs).
Image restoration in astronomy: a Bayesian perspective

When preparing an article on image restoration in astronomy, it is obvious that some topics have to be dropped to keep the work at reasonable length. We have decided to concentrate on image and noise models and on the algorithms to find the restoration. Topics like parameter estimation and stopping rules are also commented on. We start by describing the Bayesian paradigm and then proceed to study the noise and blur models used by the astronomical community. Then the prior models used to restore astronomical images are examined. We describe the algorithms used to find the restoration for the most common combinations of degradation and image models. Then we comment on important issues such as acceleration of algorithms, stopping rules, and parameter estimation. We also comment on the huge amount of information available to, and made available by, the astronomical community.
Monte Carlo analysis of thermal effects in self-switching diodes

An attempt of exploitation of very high frequency Gunn oscillations to generate a TeraHertz radiation is realized with an asymetric planar GaN self-switching diode. In this work we compare the measured static behavior of real devices with calculations performed by means of Monte Carlo simulations. We analyze the influence of the temperature on the I-V characteristic of the SSD and also on the high frequency oscillations.
Double-gate HEMTs on transferred substrate

We report the fabrication and DC characterization of the first In/sub 0.52/Al/sub 0.48/Al/sub 0.48/As/In/sub 0.53/Ga/sub 0.47/As double-gate HEMTs with simple-command (DG-HEMT-SC) and double-command (DG-HEMT-DC). These devices have been obtained by photolithography and by transferred substrate technique. Although layer structure has not been optimized, a maximum extrinsic transconductance of 460 mS/mm with a drain current I/sub ds/ of 160mA/mm is achieved for 1.5 /spl mu/m gate length DG-HEMT-SC. A large ratio Gm/I/sub ds/ of 3V/sup -1/ is obtained, which indicates improvement of charge command efficiency.
A Generalized Drift-Diffusion Model for Rectifying Schottky Contact Simulation

We present a discussion on the modeling of Schottky barrier rectifying contacts (diodes) within the framework of partial-differential-equation-based physical simulations. We propose a physically consistent generalization of the drift-diffusion model to describe the boundary layer close to the Schottky barrier where thermionic emission leads to a non-Maxwellian carrier distribution, including a novel boundary condition at the contact. The modified drift-diffusion model is validated against Monte Carlo simulations of a GaAs device. The proposed model is in agreement with the Monte Carlo simulations not only in the current value but also in the spatial distributions of microscopic quantities like the electron velocity and concentration.
OPTTR induced current oscillations in GaN diodes Monte Carlo simulations

At very low temperature, when optical phonon emission is the dominant scattering mechanism, the phenomenon known as Optical Phonon Transit Time Resonance (OPTTR) may originate current oscillations in n+ nn+ diodes at frequencies in the terahertz range. In this work, by means of Monte Carlo simulations, we study the optimum conditions for the onset of such mechanism in GaN diodes. For this purpose, we analyze the influence of the following quantities: applied bias, temperature, length and doping of the n region. Under certain conditions, simulations show clear current oscillations which are enhanced when providing a characteristic frequency close to the plasma frequency of the active region. Even so, it is possible to achieve some degree of tunability of that oscillation frequency by varying the applied voltage and the length of the n region.
Multichannel image restoration using compound Gauss-Markov random fields

A solution to the multichannel image restoration problem is provided using compound Gauss-Markov random fields. For the single channel deblurring problem the convergence of the simulated annealing (SA) and iterative conditional mode (ICM) algorithms has not been established. We propose two new iterative multichannel restoration algorithms which can be considered as extensions of the classical SA and ICM approaches and whose convergence is established. Experimental results with color images demonstrate the effectiveness of the proposed algorithms.
Microwave detection up to 43.5 GHz by GaN nanodiodes: Experimental and analytical responsivity

Planar nano-diodes fabricated on an AlGaN/GaN heterolayer have been measured, showing capability to detect microwave signals up to 43.5 GHz at room temperature. A single nano-diode with length L=1000 nm and width W=74 nm provides a response of approximately 55 mV DC output for a 0 dBm nominal input power at 1 GHz, with a very small fraction of the RF power reaching effectively the device due to a very large impedance mismatch. A comprehensive analytical study, which uses as input data just the measured DC current-voltage curve of the diodes, is able to replicate the values of the RF characterization and allows a deep understanding of the detection mechanism.
Plasma Enhanced Terahertz Rectification and Noise in InGaAs HEMTs

In this work, we explore high frequency collective phenomena present in InGaAs HEMTs which lead to a peak in the current noise spectrum and enhance their DC response to THz signals, thus originating a resonance in the rectification of AC signals. These phenomena have been evidenced in recent experiments, in which THz detection as a result of plasma wave resonances has been demonstrated. In this paper, by means of Monte Carlo simulations, the noise spectra and the AC-DC rectification properties of the devices have been calculated and linked to the properties of the plasma oscillations within two distinct parts of the source-gate region: the capped and the recessed sections of the channel.
Tunab e Tera ertz Resonance in Planar Asymmetric Nanodiodes

In this work, by means of Monte Carlo simulations, we analyze the presence of a resonance in the high-frequency response of an asymmetric nonlinear nanodiode. This device exhibits a tunable-by-geometry resonant DC current response to AC voltage excitations in the THz range. The resonance is linked to a noise mechanism: collective charge fluctuations in the space-charge region around the active channel of the device, which are visible both in noise and rectification. This effect, present at room temperature, could be useful for selective THz detection.
Room temperature nonlinear transport in InGaAs/AlInAs based ballistic nanodevices

By using a semi-classical 2D Monte Carlo simulation, simple ballistic devices based on AlInAs/InGaAs channels are analyzed. Our simulations qualitatively reproduce the main features of the experimental results in T-branch and Y-branch junctions as well as in a ballistic rectifier appearing as a result of electron ballistic transport. We show that a quantum description of electron transport is not essential for the physical explanation of these results, since phase coherence plays no significant role. On the contrary, its origin can be purely classical: the presence of classical electron transport and space charge inside the structures.
Variational Dirichlet Blur Kernel Estimation

Blind image deconvolution involves two key objectives: 1) latent image and 2) blur estimation. For latent image estimation, we propose a fast deconvolution algorithm, which uses an image prior of nondimensional Gaussianity measure to enforce sparsity and an undetermined boundary condition methodology to reduce boundary artifacts. For blur estimation, a linear inverse problem with normalization and nonnegative constraints must be solved. However, the normalization constraint is ignored in many blind image deblurring methods, mainly because it makes the problem less tractable. In this paper, we show that the normalization constraint can be very naturally incorporated into the estimation process by using a Dirichlet distribution to approximate the posterior distribution of the blur. Making use of variational Dirichlet approximation, we provide a blur posterior approximation that considers the uncertainty of the estimate and removes noise in the estimated kernel. Experiments with synthetic and real data demonstrate that the proposed method is very competitive to the state-of-the-art blind image restoration methods.
Monte Carlo Comparison Between InP-Based Double-Gate and Standard HEMTs

The intrinsic static and dynamic performance of InAlAs/InGaAs double-gate high electron mobility transistors (DG-HEMTs) is studied by means of an ensemble 2D Monte Carlo simulator. Our model allows going deeply into the physical behavior of this novel device in comparison with similar standard HEMTs. Different gate lengths are analyzed in order to check the attenuation of short-channel effects expected in the DG-structures. The intrinsic cut-off frequency fc of the DG-HEMTs is found to be similar to that of HEMTs, but the higher values of the figures of merit gm/gd and Cgs/C gd lead to an improvement of fmax
Monte Carlo study of the noise performance of isolated-gate InAs HEMTs

In this work, the noise performance of an InAs/AlSb 225-nm isolated-gate HEMT has been studied by means of Monte Carlo (MC) simulations. Firstly, the experimental DC behavior and the intrinsic small signal equivalent circuit parameters have been adequately reproduced in order to validate the model. Then, the extrinsic ƒ<inf>T</inf> and ƒ<inf>max</inf> have been obtained and compared with experimental data, getting a good agreement for ƒ<inf>T</inf> but some discrepancies for ƒ<inf>max</inf>. Finally, the intrinsic and extrinsic noise characteristics of the InAs based HEMT have been simulated, showing an excellent noise performance (F<inf>min</inf>=0.3 dB@10 GHz), comparable to that obtained in InGaAs HEMTs with a much shorter gate length of 50 nm.
Langevin forces and generalized transfer fields for noise modeling in deep submicron devices

We show that the standard impedance field method that considers as noise source the spectral density of velocity fluctuations is not appropriate for the calculation of noise spectra in deep submicron devices where spatial correlations between velocity fluctuations cannot be neglected. To overcome this drawback, we develop a new scheme in which the noise sources are given by the instantaneous accelerations of relevant dynamic variables caused by scattering events. Accordingly, generalized transfer fields describing the propagation of fluctuations to the device terminals are introduced. By using this scheme, we show that, in contrast with the standard impedance field method, noise modeling in submicron structures can be performed with no major difficulty and the dual representation of voltage and current noise is recovered.
Monte Carlo comparison of the noise performance of InAlAs/InGaAs Double-Gate and Standard HEMTs

A comparison of the noise behavior of Double-Gate and Standard High Electron Mobility Transistors is established by means of Monte Carlo simulations. The intrinsic noise P, R, and C parameters are only moderately improved in the DG-device, but the extrinsic minimum noise figure NFmin reveals a significantly better extrinsic noise performance, more noticeable for higher frequencies due to the better dynamic performance of the DG-device.
A simple approach for the fabrication of ultrafast unipolar diodes

Recently a nanoscale unipolar rectifying diode based on electrostatic effects, so called self-switching diode (SSD), was presented in (Song et al., 2003). The main advantage of this device is that it can be fabricated with a simple single-step lithographic process so that its size can be easily reduced to the nanometer-range. This fact, together with the intrinsically high electron velocity of InGaAs channels, should permit the fabrication of devices working in the THz range. Indeed, the high frequency performance of SSDs can be dramatically boosted thanks to a much shorter transit time, due not only to a smaller channel length but also to an enhanced electron velocity associated to ballistic transport. In this work we will make use of a semiclassical 2D Monte Carlo (MC) simulator (employed previously to successfully model other nano-scaled ballistic devices ) to optimize the high frequency performance of SSDs.
Room Temperature Direct and Heterodyne Detection of 0.28–0.69-THz Waves Based on GaN 2-DEG Unipolar Nanochannels

An experimental demonstration of GaN-based asymmetric nanodiodes as direct and heterodyne detectors up to 0.69 THz has been performed at room temperature. Responsivities of 2 and 0.3 V/W in a free-space configuration were obtained at 0.30 and 0.69 THz, respectively. An intermediate frequency (IF) signal has been measured up to 40 and 13 GHz in the same frequency ranges. The characterization of the nanodiodes as mixers did not show any deviation from linearity between the RF input power and the IF output. Monte Carlo simulations, used to estimate nanodevice intrinsic conversion losses of 27 dB at 0.69 THz, have confirmed these results.
Influence of kink effect on the dynamic and noise performance of short-channel InAlAs/InGaAs HEMTs

We perform a microscopic analysis of the degradation originated by the kink effect in the dynamic and noise performance of short-channel InAlAs/InGaAs lattice matched HEMTs by using a 2D ensemble Monte Carlo simulator. The onset of kink effect leads to a significant increase of the drain conductance, whose frequency dependence reflects the influence of the processes at the origin of the kink effect. Concerning the noise performance, the kink effect provokes an enhancement in the drain- and gate-current noise at low frequency, with a characteristic cutoff frequency related to the impact ionization rate and hole recombination time.
Accurate predictions of terahertz noise in ultra-small devices: A limiting factor for their practical application?

With the aim of manufacturing faster devices, the electronic industry scales down device's dimensions and is today entering into a nanoscale and Terahertz frequency regimes. In this work, we show how the reduction of the length L of the active region of two terminal devices implies (apart from the expected improvement of their dynamic behavior) a typically disregarded increment on the fluctuations of the current. In particular, the high-frequency current fluctuations are proportional to 1/L so that the noise grows unlimitedly when the device's dimensions are reduced. This important drawback, common to classical and quantum regimes, remains mainly unnoticed by the scientific community.
SPECT image reconstruction using compound models

SPECT (single photon emission computed tomography) is used in nuclear medicine to determine the distribution of a radioactive isotope within a patient from tomographic views or projection data. These images are severely degraded due to the presence of noise and several physical factors like attenuation and scattering. We use, within the Bayesian framework, a compound Gauss Markov random field (CGMRF) as prior model to reconstruct such images. In order to find the maximum a posteriori (MAP) estimate we propose a new iterative method, which is stochastic for the line process and deterministic for the reconstruction. The proposed method is tested and compared with other reconstruction methods on both synthetic and real SPECT images.
Improved Monte Carlo algorithm for the simulation of /spl delta/-doped AlInAs/GaInAs HEMTs

A classical Monte Carlo (MC) device simulation has been modified to locally introduce the effects of electron degeneracy and nonequilibrium screening. Its validity in the case of AlInAs/GaInAs HEMTs has been checked through the comparison, first, with a quantum Schrodinger-Poisson (SP) simulation in the case of a complicated layer structure, which is actually used in the fabrication of real devices, and second, with experimental results of static characteristics of recessed /spl delta/-doped HEMTs.
Bayesian TV denoising of SAR images

Synthetic aperture radar (SAR) imagery suffers from the speckle phenomenon. Speckle gives rise to the presence of multiplicative noise which severely degrades the observed images. It is known that logarithmically transformed speckle can be well approximated by a Gaussian distribution. In this paper we propose an algorithm for despeckling images, within the log-transformed spatial domain, using a TV prior whose model parameter is automatically determined using the Evidence Analysis within the Hierarchical Bayesian Paradigm. The effectiveness of the proposed algorithm, over both synthetically speckled and real SAR images, is studied.
Blind Deconvolution Using a Variational Approach to Parameter, Image, and Blur Estimation

Following the hierarchical Bayesian framework for blind deconvolution problems, in this paper, we propose the use of simultaneous autoregressions as prior distributions for both the image and blur, and gamma distributions for the unknown parameters (hyperparameters) of the priors and the image formation noise. We show how the gamma distributions on the unknown hyperparameters can be used to prevent the proposed blind deconvolution method from converging to undesirable image and blur estimates and also how these distributions can be inferred in realistic situations. We apply variational methods to approximate the posterior probability of the unknown image, blur, and hyperparameters and propose two different approximations of the posterior distribution. One of these approximations coincides with a classical blind deconvolution method. The proposed algorithms are tested experimentally and compared with existing blind deconvolution methods
Bayesian parameter estimation in image reconstruction from subsampled blurred observations

In this paper we consider the estimation of the unknown hyperparameters for the problem of reconstructing a high-resolution image from multiple undersampled, shifted, blurred and degraded frames with subpixel displacement errors. We derive mathematical expressions for the iterative calculation of the maximum likelihood estimate (mle) of the unknown hyperparameters given the low resolution observed images. Finally, the proposed method is tested on a synthetic image.
Bayesian and regularization methods for hyperparameter estimation in image restoration

In this paper, we propose the application of the hierarchical Bayesian paradigm to the image restoration problem. We derive expressions for the iterative evaluation of the two hyperparameters applying the evidence and maximum a posteriori (MAP) analysis within the hierarchical Bayesian paradigm. We show analytically that the analysis provided by the evidence approach is more realistic and appropriate than the MAP approach for the image restoration problem. We furthermore study the relationship between the evidence and an iterative approach resulting from the set theoretic regularization approach for estimating the two hyperparameters, or their ratio, defined as the regularization parameter. Finally the proposed algorithms are tested experimentally.
Spike and slab variational inference for blind image deconvolution

In this work, we propose a new variational blind deconvolution method for spike and slab prior models. Soft-sparse or shrinkage priors such as the Laplace and other related Gaussian Scale Mixture priors may not be ideal sparsity promoting priors. They assign zero probability mass to events we may be interested in assigning a probability greater than zero. The truly sparse nature of the spike and slab priors allows us to discard irrelevant information in the blur estimation process, resulting in improved performance. We present an efficient inference algorithm to estimate the unknown blur kernel in the filter space, from which we estimate the final deblurred image. The VB approach we propose in this paper handles the inference in a much more efficient way than MCMC, and is more accurate than the standard mean field variational approximation. We prove the efficacy of our method by means of a series of experiments on both synthetically generated and real images.
Time-domain Monte Carlo simulations of resonant-circuit operation of GaN Gunn diodes

The time-domain operation of GaAs, InP and GaN vertical n+n-nn+ Gunn diodes and GaN planar self-switching diodes (SSDs) is numerically investigated by using the Monte Carlo (MC) technique. To this end, the MC simulation of the intrinsic devices is coupled with the consistent solution of a parallel RLC resonant circuit connected in series. We show that equivalent operating conditions can be achieved by the direct application of a sinusoidal AC voltage superimposed to the DC component. By virtue of the larger saturation velocity of GaN, for a given diode length, oscillation frequencies are higher than for GaAs and InP structures. Current oscillations at frequencies as high as 560 GHz, with a DC to AC conversion efficiency of 0.3%, are predicted at the third harmonic in 1 μm-long GaN diodes. In a 0.5 μm-long GaN SSD, frequencies up to 275 GHz with an efficiency of 0.2% can be achieved, with the advantage of enhanced heat dissipation thanks to the planar geometry.
Monte Carlo Study of the Dynamic Performance of a 100-nm-Gate InAlAs/InGaAs Velocity Modulation Transistor

We report a Monte Carlo study of the dynamic behavior of an InAlAs/InGaAs velocity modulation transistor (VMT) based on the topology of a double-gate high electron mobility transistor (DG HEMT), which is a HEMT with two opposite gates controlling the carrier flow through the conducting channel. In the VMT, the source and drain electrodes are connected by two channels with different mobilities, and electrons are transferred between both by changing the gate voltages in differential mode (DM). As a result, the drain current is modulated while keeping the total carrier density constant, thus, in principle, avoiding capacitance charging/discharging delays. However, the low values taken by the transconductance, as well as the high capacitance between the two gates in DM operation, lead to a deficient dynamic performance.