Structural difference rule for amorphous alloy formation by ion mixing

We formulate a rule which establishes a sufficient condition that an amorphous binary alloy will be formed by ion mixing of multilayered samples when the two constituent metals are of different crystalline structure, regardless of their atomic sizes and electronegativities. The rule is supported by the experimental results we have obtained on six selected binary metal systems, as well as by the previous data reported in the literature. The amorphization mechanism is discussed in terms of the competition between two different structures resulting in frustration of the crystallization process

Sequential nature of damage annealing and activation in implanted GaAs

Rapid thermal processing of implanted GaAs reveals a definitive sequence in the damage annealing and the electrical activation of ions. Removal of implantation-induced damage and restoration of GaAs crystallinity occurs first. Irrespective of implanted species, at this stage the GaAs is n-type and highly resistive with almost ideal values of electron mobility. Electrical activation is achieved next when, in a narrow anneal temperature window, the material becomes n- or p-type, or remains semi-insulating, commensurate to the chemical nature of the implanted ion. Such a two-step sequence in the electrical doping of GaAs by ion implantation may be unique of GaAs and other compound semiconductors

Automatically Generating Natural Language Descriptions of Images by a Deep Hierarchical Framework.

Automatically generating an accurate and meaningful description of an image is very challenging. However, the recent scheme of generating an image caption by maximizing the likelihood of target sentences lacks the capacity of recognizing the human-object interaction (HOI) and semantic relationship between HOIs and scenes, which are the essential parts of an image caption. This article proposes a novel two-phase framework to generate an image caption by addressing the above challenges: 1) a hybrid deep learning and 2) an image description generation. In the hybrid deep-learning phase, a novel factored three-way interaction machine was proposed to learn the relational features of the human-object pairs hierarchically. In this way, the image recognition problem is transformed into a latent structured labeling task. In the image description generation phase, a lexicalized probabilistic context-free tree growing scheme is innovatively integrated with a description generator to transform the descriptions generation task into a syntactic-tree generation process. Extensively comparing state-of-the-art image captioning methods on benchmark datasets, we demonstrated that our proposed framework outperformed the existing captioning methods in different ways, such as significantly improving the performance of the HOI and relationships between HOIs and scenes (RHIS) predictions, and quality of generated image captions in a semantically and structurally coherent manner.\enlargethispage-8pt

Multiwavelength Observations of the BL Lacertae Object PKS 2155-304 with XMM-Newton

The optical-UV and X-ray instruments on-board XMM-Ndewton provide an excellent opportunity to perform simultaneous observations of violently variable objects over a broad wavelength range. The UV and X-ray bright BL Lac object PKS 2155-304 has been repeatedly observed with XMM-Ndewton about twice per year. In this paper, we present a detailed analysis of the simultaneous multiwavelength variability of the source from optical to X-rays, based on the currently available XMM-Ndewton observations. These observations probed the intra-day multiwavelength variability at optical-UV and X-ray wavelengths of the source. The UV variability amplitude is substantially smaller than the X-ray one, and the hardness ratios of the UV to X-rays correlates with the X-ray fluxes: the brighter the source, the flatter the UV-X-ray spectra. On 2000 May 30-31 the UV and X-ray light curves were weakly correlated, while the UV variations followed the X-ray ones with no detectable lags on 2000 November 19-21. On 2001 November 30 the source exhibited a major X-ray flare that was not detected in the optical. The intra-day UV and X-ray variability presented here is not similar to the inter-day UV and X-ray variability obtained from the previous coordinated extensive multiwavelength campaigns on the source, indicating that different ``modes'' of variability might be operating in PKS 2155-304 on different timescales or from epoch to epoch.Comment: Accepted by Ap

Tunneling dynamics of side chains and defects in proteins, polymer glasses, and OH-doped network glasses

Simulations on a Lennard-Jones computer glass are performed to study effects arising from defects in glasses at low temperatures. The numerical analysis reveals that already a low concentration of defects may dramatically change the low temperature properties by giving rise to extrinsic double-well potentials (DWP's). The main characteristics of these extrinsic DWP's are (i) high barrier heights, (ii) high probability that a defect is indeed connected with an extrinsic DWP, (iii) highly localized dynamics around this defect, and (iv) smaller deformation potential coupling to phonons. Designing an extension of the Standard Tunneling Model (STM) which parametrizes this picture and comparing with ultrasound experiments on the wet network glass $a$-B$_2$O$_3$ shows that effects of OH-impurities are accurately accounted for. This model is then applied to organic polymer glasses and proteins. It is suggested that side groups may act similarly like doped impurities inasmuch as extrinsic DWP's are induced, which possess a distribution of barriers peaked around a high barrier height. This compares with the structurlessly distributed barrier heights of the intrinsic DWP's, which are associated with the backbone dynamics. It is shown that this picture is consistent with elastic measurements on polymers, and can explain anomalous nonlogarithmic line broadening recently observed in hole burning experiments in PMMA.Comment: 34 pages, Revtex, 9 eps-figures, accepted for publication in J. Chem. Phy

Random matrices: Universality of local eigenvalue statistics up to the edge

This is a continuation of our earlier paper on the universality of the eigenvalues of Wigner random matrices. The main new results of this paper are an extension of the results in that paper from the bulk of the spectrum up to the edge. In particular, we prove a variant of the universality results of Soshnikov for the largest eigenvalues, assuming moment conditions rather than symmetry conditions. The main new technical observation is that there is a significant bias in the Cauchy interlacing law near the edge of the spectrum which allows one to continue ensuring the delocalization of eigenvectors.Comment: 24 pages, no figures, to appear, Comm. Math. Phys. One new reference adde

Semantic analysis of field sports video using a petri-net of audio-visual concepts

The most common approach to automatic summarisation and highlight detection in sports video is to train an automatic classifier to detect semantic highlights based on occurrences of low-level features such as action replays, excited commentators or changes in a scoreboard. We propose an alternative approach based on the detection of perception concepts (PCs) and the construction of Petri-Nets which can be used for both semantic description and event detection within sports videos. Low-level algorithms for the detection of perception concepts using visual, aural and motion characteristics are proposed, and a series of Petri-Nets composed of perception concepts is formally defined to describe video content. We call this a Perception Concept Network-Petri Net (PCN-PN) model. Using PCN-PNs, personalized high-level semantic descriptions of video highlights can be facilitated and queries on high-level semantics can be achieved. A particular strength of this framework is that we can easily build semantic detectors based on PCN-PNs to search within sports videos and locate interesting events. Experimental results based on recorded sports video data across three types of sports games (soccer, basketball and rugby), and each from multiple broadcasters, are used to illustrate the potential of this framework

Finite-Temperature Auxiliary-Field Quantum Monte Carlo for Bose-Fermi Mixtures

We present a quantum Monte Carlo (QMC) technique for calculating the exact finite-temperature properties of Bose-Fermi mixtures. The Bose-Fermi Auxiliary-Field Quantum Monte Carlo (BF-AFQMC) algorithm combines two methods, a finite-temperature AFQMC algorithm for bosons and a variant of the standard AFQMC algorithm for fermions, into one algorithm for mixtures. We demonstrate the accuracy of our method by comparing its results for the Bose-Hubbard and Bose-Fermi-Hubbard models against those produced using exact diagonalization for small systems. Comparisons are also made with mean-field theory and the worm algorithm for larger systems. As is the case with most fermion Hamiltonians, a sign or phase problem is present in BF-AFQMC. We discuss the nature of these problems in this framework and describe how they can be controlled with well-studied approximations to expand BF-AFQMC's reach. The new algorithm can serve as an essential tool for answering many unresolved questions about many-body physics in mixed Bose-Fermi systems.Comment: 19 pages, 6 figure

Fluctuations of Matrix Entries of Regular Functions of Wigner Matrices

We study the fluctuations of the matrix entries of regular functions of Wigner random matrices in the limit when the matrix size goes to infinity. In the case of the Gaussian ensembles (GOE and GUE) this problem was considered by A.Lytova and L.Pastur in J. Stat. Phys., v.134, 147-159 (2009). Our results are valid provided the off-diagonal matrix entries have finite fourth moment, the diagonal matrix entries have finite second moment, and the test functions have four continuous derivatives in a neighborhood of the support of the Wigner semicircle law.Comment: minor corrections; the manuscript will appear in the Journal of Statistical Physic