Many-Body Localization in the Presence of a Single-Particle Mobility Edge

In one dimension, noninteracting particles can undergo a localization-delocalization transition in a quasiperiodic potential. Recent studies have suggested that this transition transforms into a many-body localization (MBL) transition upon the introduction of interactions. It has also been shown that mobility edges can appear in the single particle spectrum for certain types of quasiperiodic potentials. Here, we investigate the effect of interactions in two models with such mobility edges. Employing the technique of exact diagonalization for finite-sized systems, we calculate the level spacing distribution, time evolution of entanglement entropy, optical conductivity, and return probability to detect MBL. We find that MBL does indeed occur in one of the two models we study, but the entanglement appears to grow faster than logarithmically with time unlike in other MBL systems.

Monoclinic to cubic phase transformation in combustion synthesized gadolinium oxide

Gadolinium oxide, cerium oxide, and 10 mol% gadolinia doped ceria ceramic powders have been synthesized using combustion technique. Though the cubic gadolinia phase is stable at room temperature, single phase monoclinic gadolinia was obtained as a result of combustion synthesis using fuel lean and stoichiometric precursor compositions. This powder was subjected to calcination treatment and ceria doping to study the stability of phases and the rate of phase transformation from monoclinic to cubic gadolinia. It was found that monoclinic gadolinia transforms to cubic gadolinia upon calcination at temperatures less than 1200 degrees C. It was also found that rate of phase transformation is more for powder produced using fuel lean compositions; and the rate is enhanced upon ceria doping. (C) 2015 Elsevier Ltd. All rights reserved.

Comparison of Matching Pursuit Algorithm with Other Signal Processing Techniques for Computation of the Time-Frequency Power Spectrum of Brain Signals

Signals recorded from the brain often show rhythmic patterns at different frequencies, which are tightly coupled to the external stimuli as well as the internal state of the subject. In addition, these signals have very transient structures related to spiking or sudden onset of a stimulus, which have durations not exceeding tens of milliseconds. Further, brain signals are highly nonstationary because both behavioral state and external stimuli can change on a short time scale. It is therefore essential to study brain signals using techniques that can represent both rhythmic and transient components of the signal, something not always possible using standard signal processing techniques such as short time fourier transform, multitaper method, wavelet transform, or Hilbert transform. In this review, we describe a multiscale decomposition technique based on an over-complete dictionary called matching pursuit (MP), and show that it is able to capture both a sharp stimulus-onset transient and a sustained gamma rhythm in local field potential recorded from the primary visual cortex. We compare the performance of MP with other techniques and discuss its advantages and limitations. Data and codes for generating all time-frequency power spectra are provided.

The 2014 M-w 6.1 Bay of Bengal, Indian Ocean, Earthquake: A Possible Association with the 85 degrees E Ridge

Oceanic intraplate earthquakes are known to occur either on active ridge-transform structures or by reactivation of their inactive counterparts, generally referred to as fossil ridges or transforms. The Indian Ocean, one of the most active oceanic intraplate regions, has generated large earthquakes associated with both these types of structures. The moderate earthquake that occurred on 21 May 2014 (M-w 6.1) in the northern Bay of Bengal followed an alternate mechanism, as it showed no clear association either with active or extinct ridge-transform structures. Its focal depth of >50 km is uncommon but not improbable, given the similar to 90 Ma age of the ocean floor with 12-km-thick overlying sediments. No tectonic features have been mapped in the near vicinity of its epicenter, the closest being the 85 degrees E ridge, located similar to 100 km to its west, hitherto regarded as seismically inactive. The few earthquakes that have occurred here in the past are clustered around its southern or northern limits, and a few are located midway, at around 10 degrees N. The 2014 earthquake, sourced close to the northern cluster, seems to be associated with a northwest-southeast-oriented fracture, located on the eastern flanks of the 85 degrees E ridge. If this causal association is possible, we believe that reactivation of fossil hotspot trails could be considered as another mechanism for oceanic intraplate seismicity.

Low Resolution Face Recognition Across Variations in Pose and Illumination

We propose a completely automatic approach for recognizing low resolution face images captured in uncontrolled environment. The approach uses multidimensional scaling to learn a common transformation matrix for the entire face which simultaneously transforms the facial features of the low resolution and the high resolution training images such that the distance between them approximates the distance had both the images been captured under the same controlled imaging conditions. Stereo matching cost is used to obtain the similarity of two images in the transformed space. Though this gives very good recognition performance, the time taken for computing the stereo matching cost is significant. To overcome this limitation, we propose a reference-based approach in which each face image is represented by its stereo matching cost from a few reference images. Experimental evaluation on the real world challenging databases and comparison with the state-of-the-art super-resolution, classifier based and cross modal synthesis techniques show the effectiveness of the proposed algorithm.

IMAGE DENOISING IN MULTIPLICATIVE NOISE

We address the problem of denoising images corrupted by multiplicative noise. The noise is assumed to follow a Gamma distribution. Compared with additive noise distortion, the effect of multiplicative noise on the visual quality of images is quite severe. We consider the mean-square error (MSE) cost function and derive an expression for an unbiased estimate of the MSE. The resulting multiplicative noise unbiased risk estimator is referred to as MURE. The denoising operation is performed in the wavelet domain by considering the image-domain MURE. The parameters of the denoising function (typically, a shrinkage of wavelet coefficients) are optimized for by minimizing MURE. We show that MURE is accurate and close to the oracle MSE. This makes MURE-based image denoising reliable and on par with oracle-MSE-based estimates. Analogous to the other popular risk estimation approaches developed for additive, Poisson, and chi-squared noise degradations, the proposed approach does not assume any prior on the underlying noise-free image. We report denoising results for various noise levels and show that the quality of denoising obtained is on par with the oracle result and better than that obtained using some state-of-the-art denoisers.