On measure solutions of the Boltzmann equation, part I: Moment production and stability estimates

The spatially homogeneous Boltzmann equation with hard potentials is considered for measure valued initial data having finite mass and energy. We prove the existence of \emph{weak measure solutions}, with and without angular cutoff on the collision kernel; the proof in particular makes use of an approximation argument based on the Mehler transform. Moment production estimates in the usual form and in the exponential form are obtained for these solutions. Finally for the Grad angular cutoff, we also establish uniqueness and strong stability estimate on these solutions

Noise auto-correlation spectroscopy with coherent Raman scattering

Ultrafast lasers have become one of the most powerful tools in coherent nonlinear optical spectroscopy. Short pulses enable direct observation of fast molecular dynamics, whereas broad spectral bandwidth offers ways of controlling nonlinear optical processes by means of quantum interferences. Special care is usually taken to preserve the coherence of laser pulses as it determines the accuracy of a spectroscopic measurement. Here we present a new approach to coherent Raman spectroscopy based on deliberately introduced noise, which increases the spectral resolution, robustness and efficiency. We probe laser induced molecular vibrations using a broadband laser pulse with intentionally randomized amplitude and phase. The vibrational resonances result in and are identified through the appearance of intensity correlations in the noisy spectrum of coherently scattered photons. Spectral resolution is neither limited by the pulse bandwidth, nor sensitive to the quality of the temporal and spectral profile of the pulses. This is particularly attractive for the applications in microscopy, biological imaging and remote sensing, where dispersion and scattering properties of the medium often undermine the applicability of ultrafast lasers. The proposed method combines the efficiency and resolution of a coherent process with the robustness of incoherent light. As we demonstrate here, it can be implemented by simply destroying the coherence of a laser pulse, and without any elaborate temporal scanning or spectral shaping commonly required by the frequency-resolved spectroscopic methods with ultrashort pulses.Comment: To appear in Nature Physic

Deep Underground Neutrino Experiment (DUNE) near detector conceptual design report

The Deep Underground Neutrino Experiment (DUNE) is an international, world-class experiment aimed at exploring fundamental questions about the universe that are at the forefront of astrophysics and particle physics research. DUNE will study questions pertaining to the preponderance of matter over antimatter in the early universe, the dynamics of supernovae, the subtleties of neutrino interaction physics, and a number of beyond the Standard Model topics accessible in a powerful neutrino beam. A critical component of the DUNE physics program involves the study of changes in a powerful beam of neutrinos, i.e., neutrino oscillations, as the neutrinos propagate a long distance. The experiment consists of a near detector, sited close to the source of the beam, and a far detector, sited along the beam at a large distance. This document, the DUNE Near Detector Conceptual Design Report (CDR), describes the design of the DUNE near detector and the science program that drives the design and technology choices. The goals and requirements underlying the design, along with projected performance are given. It serves as a starting point for a more detailed design that will be described in future documents

Abrupt Onset of Second Energy Gap at Superconducting Transition of Underdoped Bi2212

The superconducting gap - an energy scale tied to the superconducting phenomena-opens on the Fermi surface at the superconducting transition temperature (TC) in conventional BCS superconductors. Quite differently, in underdoped high-TC superconducting cuprates, a pseudogap, whose relation to the superconducting gap remains a mystery, develops well above TC. Whether the pseudogap is a distinct phenomenon or the incoherent continuation of the superconducting gap above TC is one of the central questions in high-TC research. While some experimental evidence suggests they are distinct, this issue is still under intense debate. A crucial piece of evidence to firmly establish this two-gap picture is still missing: a direct and unambiguous observation of a single-particle gap tied to the superconducting transition as function of temperature. Here we report the discovery of such an energy gap in underdoped Bi2212 in the momentum space region overlooked in previous measurements. Near the diagonal of Cu-O bond direction (nodal direction), we found a gap which opens at TC and exhibits a canonical (BCS-like) temperature dependence accompanied by the appearance of the so-called Bogoliubov quasiparticles, a classical signature of superconductivity. This is in sharp contrast to the pseudogap near the Cu-O bond direction (antinodal region) measured in earlier experiments. The emerging two-gap phenomenon points to a picture of richer quantum configurations in high temperature superconductors.Comment: 16 pages, 4 figures, authors' version Corrected typos in the abstrac

Towards Intelligent Crowd Behavior Understanding through the STFD Descriptor Exploration

Realizing the automated and online detection of crowd anomalies from surveillance CCTVs is a research-intensive and application-demanding task. This research proposes a novel technique for detecting crowd abnormalities through analyzing the spatial and temporal features of input video signals. This integrated solution defines an image descriptor (named spatio-temporal feature descriptor - STFD) that reflects the global motion information of crowds over time. A CNN has then been adopted to classify dominant or large-scale crowd abnormal behaviors. The work reported has focused on: 1) detecting moving objects in online (or near real-time) manner through spatio-temporal segmentations of crowds that is defined by the similarity of group trajectory structures in temporal space and the foreground blocks based on Gaussian Mixture Model (GMM) in spatial space; 2) dividing multiple clustered groups based on the spectral clustering method by considering image pixels from spatio-temporal segmentation regions as dynamic particles; 3) generating the STFD descriptor instances by calculating the attributes (i.e., collectiveness, stability, conflict and crowd density) of particles in the corresponding groups; 4) inputting generated STFD descriptor instances into the devised convolutional neural network (CNN) to detect suspicious crowd behaviors. The test and evaluation of the devised models and techniques have selected the PETS database as the primary experimental data sets. Results against benchmarking models and systems have shown promising advancements of this novel approach in terms of accuracy and efficiency for detecting crowd anomalies

Towards Intelligent Crowd Behavior Understanding through the STFD Descriptor Exploration

Realizing the automated and online detection of crowd anomalies from surveillance CCTVs is a research-intensive and application-demanding task. This research proposes a novel technique for detecting crowd abnormalities through analyzing the spatial and temporal features of input video signals. This integrated solution defines an image descriptor (named spatio-temporal feature descriptor - STFD) that reflects the global motion information of crowds over time. A CNN has then been adopted to classify dominant or large-scale crowd abnormal behaviors. The work reported has focused on: 1) detecting moving objects in online (or near real-time) manner through spatio-temporal segmentations of crowds that is defined by the similarity of group trajectory structures in temporal space and the foreground blocks based on Gaussian Mixture Model (GMM) in spatial space; 2) dividing multiple clustered groups based on the spectral clustering method by considering image pixels from spatio-temporal segmentation regions as dynamic particles; 3) generating the STFD descriptor instances by calculating the attributes (i.e., collectiveness, stability, conflict and crowd density) of particles in the corresponding groups; 4) inputting generated STFD descriptor instances into the devised convolutional neural network (CNN) to detect suspicious crowd behaviors. The test and evaluation of the devised models and techniques have selected the PETS database as the primary experimental data sets. Results against benchmarking models and systems have shown promising advancements of this novel approach in terms of accuracy and efficiency for detecting crowd anomalies

Field Effect Transistors for Terahertz Detection: Physics and First Imaging Applications

Resonant frequencies of the two-dimensional plasma in FETs increase with the reduction of the channel dimensions and can reach the THz range for sub-micron gate lengths. Nonlinear properties of the electron plasma in the transistor channel can be used for the detection and mixing of THz frequencies. At cryogenic temperatures resonant and gate voltage tunable detection related to plasma waves resonances, is observed. At room temperature, when plasma oscillations are overdamped, the FET can operate as an efficient broadband THz detector. We present the main theoretical and experimental results on THz detection by FETs in the context of their possible application for THz imaging.Comment: 22 pages, 12 figures, review pape

Gold nanocrystals with variable index facets as highly effective cathode catalysts for lithium-oxygen batteries

© 2015 Nature Publishing Group All rights reserved. Cathode catalysts are the key factor in improving the electrochemical performance of lithium-oxygen (Li-O2) batteries via their promotion of the oxygen reduction and oxygen evolution reactions (ORR and OER). Generally, the catalytic performance of nanocrystals (NCs) toward ORR and OER depends on both composition and shape. Herein, we report the synthesis of polyhedral Au NCs enclosed by a variety of index facets: cubic gold (Au) NCs enclosed by {100} facets; truncated octahedral Au NCs enclosed by {100} and {110} facets; and trisoctahedral (TOH) Au NCs enclosed by 24 high-index {441} facets, as effective cathode catalysts for Li-O2 batteries. All Au NCs can significantly reduce the charge potential and have high reversible capacities. In particular, TOH Au NC catalysts demonstrated the lowest charge-discharge overpotential and the highest capacity of ∼ 20 298 mA h g-1. The correlation between the different Au NC crystal planes and their electrochemical catalytic performances was revealed: high-index facets exhibit much higher catalytic activity than the low-index planes, as the high-index planes have a high surface energy because of their large density of atomic steps, ledges and kinks, which can provide a high density of reactive sites for catalytic reactions