Laser wakefield and direct acceleration in the plasma bubble regime

Laser wakefield acceleration (LWFA) and direct laser acceleration (DLA) are two different kinds of laser plasma electron acceleration mechanisms. LWFA relies on the laser-driven plasma wave to accelerate electrons. The interaction of ultra-short ultra-intensive laser pulses with underdense plasma leads the LWFA into a highly nonlinear regime (“plasma bubble regime”) that attracts particular interest nowadays. DLA accelerates electrons by laser electromagnetic wave in the ion channel or the plasma bubble through the Betatron resonance. This dissertation presents a hybrid laser plasma electron acceleration mechanism. We investigate its features through particle-in-cell (PIC) simulations and the single particle model. The hybrid laser plasma electron acceleration is the merging concept between the LWFA and the DLA, so called laser wakefield and direct acceleration (LWDA). The requirements of the initial conditions of the electron to undergo the LWDA are determined. The electron must have a large initial transverse energy. Two electron injection mechanisms that are suitable for the LWDA, density bump injection and ionization induced injection, are studied in detail. The features of electron beam phase space and electron dynamics are explored. Electron beam phase space appears several unique features such as spatially separated two groups, the correlation between the transverse energy and the relativistic factor and the double-peak spectrum. Electrons are synergistically accelerated by the wakefield as well as by the laser electromagnetic field in the laser-driven plasma bubble. LWDA are also investigated in the moderate power regime (10 TW) in regarding the effects of laser color and polarization. It is found that the frequency upshift laser pulse has better performance on avoiding time-jitter of electron energy spectra, electron final energy and electron charge yield. Some basic characters that related to the LWDA such as the effects of the subluminal laser wave, the effects of the longitudinal accelerating field, the electron beam emittance, the electron charge yield and potentially applications as radiation source are discussed.Physic

Evolution of binary stars and its implications for evolutionary population synthesis

Most stars are members of binaries, and the evolution of a star in a close binary system differs from that of an ioslated star due to the proximity of its companion star. The components in a binary system interact in many ways and binary evolution leads to the formation of many peculiar stars, including blue stragglers and hot subdwarfs. We will discuss binary evolution and the formation of blue stragglers and hot subdwarfs, and show that those hot objects are important in the study of evolutionary population synthesis (EPS), and conclude that binary interactions should be included in the study of EPS. Indeed, binary interactions make a stellar population younger (hotter), and the far-ultraviolet (UV) excess in elliptical galaxies is shown to be most likely resulted from binary interactions. This has major implications for understanding the evolution of the far-UV excess and elliptical galaxies in general. In particular, it implies that the far-UV excess is not a sign of age, as had been postulated prviously and predicts that it should not be strongly dependent on the metallicity of the population, but exists universally from dwarf ellipticals to giant ellipticals.Comment: Oral talk on IAUS 262, Brazi

Symmetric Versus Nonsymmetric Structure of the Phosphorus Vacancy on InP(110)

The atomic and electronic structure of positively charged P vacancies on InP(110) surfaces is determined by combining scanning tunneling microscopy, photoelectron spectroscopy, and density-functional theory calculations. The vacancy exhibits a nonsymmetric rebonded atomic configuration with a charge transfer level 0.75+-0.1 eV above the valence band maximum. The scanning tunneling microscopy (STM) images show only a time average of two degenerate geometries, due to a thermal flip motion between the mirror configurations. This leads to an apparently symmetric STM image, although the ground state atomic structure is nonsymmetric.Comment: 5 pages including 3 figures. related publications can be found at http://www.fhi-berlin.mpg.de/th/paper.htm

Low Loss Metamaterials Based on Classical Electromagnetically Induced Transparency

We demonstrate theoretically that electromagnetically induced transparency can be achieved in metamaterials, in which electromagnetic radiation is interacting resonantly with mesoscopic oscillators rather than with atoms. We describe novel metamaterial designs that can support full dark resonant state upon interaction with an electromagnetic beam and we present results of its frequency-dependent effective permeability and permittivity. These results, showing a transparency window with extremely low absorption and strong dispersion, are confirmed by accurate simulations of the electromagnetic field propagation in the metamaterial

Uncertainty quantification and its properties for hidden Markov models with application to condition based maintenance

Condition-based maintenance (CBM) can be viewed as a transformation of data gathered from a piece of equipment into information about its condition, and further into decisions on what to do with the equipment. Hidden Markov model (HMM) is a useful framework to probabilistically model the condition of complex engineering systems with partial observability of the underlying states. Condition monitoring and prediction of such type of system requires accurate knowledge of HMM that describes the degradation of such a system with data collected from the sensors mounted on it, as well as understanding of the uncertainty of the HMMs identified from the available data. To that end, this thesis proposes a novel HMM estimation scheme based on the principles of Bayes theorem. The newly proposed Bayesian estimation approach for estimating HMM parameters naturally yields information about model parametric uncertainties via posterior distributions of HMM parameters emanating from the estimation process. In addition, a novel condition monitoring scheme based on uncertain HMMs of the degradation process is proposed and demonstrated on a large dataset obtained from a semiconductor manufacturing facility. Portion of the data was used to build operating mode specific HMMs of machine degradation via the newly proposed Bayesian estimation process, while the remainder of the data was used for monitoring of machine condition using the uncertain degradation HMMs yielded by Bayesian estimation. Comparison with a traditional signature-based statistical monitoring method showed that the newly proposed approach effectively utilizes the fact that its parameters are uncertain themselves, leading to orders of magnitude fewer false alarms. This methodology is further extended to address the practical issue that maintenance interventions are usually imperfect. We propose both a novel non-ergodic and non-homogeneous HMM that assumes imperfect maintenances and a novel process monitoring method capable of monitoring the hidden states considering model uncertainty. Significant improvement in both the log-likelihood of estimated HMM parameters and monitoring performance were observed, compared to those obtained using degradation HMMs that always assumed perfect maintenance. Finally, behavior of the posterior distribution of parameters of unidirectional non- ergodic HMMs modeling in this thesis for degradation was theoretically analyzed in terms of their evolution as more data become available in the estimation process. The convergence problem is formulated as a Bernstein-von Mises theorem (BvMT), and under certain regularity conditions, the sequence of posterior distributions is proven to converge to a Gaussian distribution with variance matrix being the inverse of the Fisher information matrix. An example of a unidirectional HMM is presented for which the regularity conditions are verified, and illustrations of expected theoretical results are given using simulation. The understanding of such convergence of posterior distributions enables one to determine when Bayesian estimation of degradation HMMs is justified and converges toward true model parameters, as well as how much data one then needs to achieve desired accuracy of the resulting model. Understanding of these issues is of utmost important if HMMs are to be used for degradation modeling and monitoring.Operations Research and Industrial Engineerin

Tip-enhanced Raman spectroscopy of strained semiconductor nanostructures

Raman spectroscopy can serve as a powerful tool to probe the vibrational modes of solid state materials. By taking advantage of the enhanced electric fields caused by the surface-enhanced plasmon resonance of a noble metal coated atomic force microscopy tip, tip-enhanced Raman spectroscopy can dramatically increase local signal intensity and measurement spatial resolution. In this dissertation, work is presented on conventional and tip-enhanced Raman measurements of various semiconductor nanostructures with a specific focus on analyzing strain and strain related properties in these material systems. We use tip-enhanced Raman to study Ge-Si₀.₅Ge₀.₅ core-shell nanowires where we observe two distinct Ge-Ge mode Raman peaks that are affected by strain in the core-shell structure. Tip-enhanced measurements show dramatically increased sensitivity to the modes at the interface between the core and shell and a shift in position of this mode due to plasmonic field localization at the tip apex and the resulting change in phonon self-energy caused by increased coupling between phonons and intervalence-band carrier transitions. We also use tip-enhanced Raman spectroscopy to characterize unstrained and strained MoS₂ and show spatial resolution of approximately 100 nm in the measurements. The strain dependence of the second order Raman modes in MoS₂ reveals changes in the electronic band structure in strained MoS₂ that are manifested through changes in the Raman peak positions and peak area ratios, which are corroborated through density functional theory calculations. Finally, we use conventional Raman spectroscopy to probe uniaxially strained monolayer and three-layer WSe₂. Using mechanical modeling of strain in atomically thin WSe₂ on a stretched elastic substrate, we confirm complete transfer of strain from the substrate to the WSe₂ flakes and analyze the evolution of the Raman spectra with applied uniaxial strain above 1 percent. These studies enable us to experimentally determine the strain induced Raman shift for various Raman modes and to calculate the Grüneisen parameter and strain deformation potential for the first order in-plane Raman mode, with experimental values confirmed with theoretical values calculated using density functional theory.Electrical and Computer Engineerin

Managed Bumblebees Outperform Honeybees in Increasing Peach Fruit Set in China: Different Limiting Processes with Different Pollinators

© 2015 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. http://creativecommons.org/licenses/by/4.0/ The file attached is the published version of the article

Spatial-Temporal Deep Embedding for Vehicle Trajectory Reconstruction from High-Angle Video

Spatial-temporal Map (STMap)-based methods have shown great potential to process high-angle videos for vehicle trajectory reconstruction, which can meet the needs of various data-driven modeling and imitation learning applications. In this paper, we developed Spatial-Temporal Deep Embedding (STDE) model that imposes parity constraints at both pixel and instance levels to generate instance-aware embeddings for vehicle stripe segmentation on STMap. At pixel level, each pixel was encoded with its 8-neighbor pixels at different ranges, and this encoding is subsequently used to guide a neural network to learn the embedding mechanism. At the instance level, a discriminative loss function is designed to pull pixels belonging to the same instance closer and separate the mean value of different instances far apart in the embedding space. The output of the spatial-temporal affinity is then optimized by the mutex-watershed algorithm to obtain final clustering results. Based on segmentation metrics, our model outperformed five other baselines that have been used for STMap processing and shows robustness under the influence of shadows, static noises, and overlapping. The designed model is applied to process all public NGSIM US-101 videos to generate complete vehicle trajectories, indicating a good scalability and adaptability. Last but not least, the strengths of the scanline method with STDE and future directions were discussed. Code, STMap dataset and video trajectory are made publicly available in the online repository. GitHub Link: shorturl.at/jklT0