596 research outputs found

    UV-induced modification of stress distribution in optical fibers and its contribution to Bragg grating birefringence

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    This paper discusses the importance of stress-induced contributions to the photo-induced birefringence observed in fiber Bragg gratings. Optical tomography measurements are performed in exposed and unexposed fibers to extract the stress profiles induced by UV-writing of fiber Bragg gratings for various exposure levels. A photoelastic analysis and a high-order isoparametric finite elements method are then used to calculate the birefringence caused by stress profile modifications. The results are compared to the birefringence directly measured by spectral analysis of a chirped fiber grating with multiple phase-shifts. We can therefore estimate the fraction of the photo-induced birefringence due to stress-induced anisotropy following UV exposure. © 2008 Optical Society of America

    A Quasi-Classical Model of Intermediate Velocity Particle Production in Asymmetric Heavy Ion Reactions

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    The particle emission at intermediate velocities in mass asymmetric reactions is studied within the framework of classical molecular dynamics. Two reactions in the Fermi energy domain were modelized, 58^{58}Ni+C and 58^{58}Ni+Au at 34.5 MeV/nucleon. The availability of microscopic correlations at all times allowed a detailed study of the fragment formation process. Special attention was paid to the physical origin of fragments and emission timescales, which allowed us to disentangle the different processes involved in the mid-rapidity particle production. Consequently, a clear distinction between a prompt pre- equilibrium emission and a delayed aligned asymmetric breakup of the heavier partner of the reaction was achieved.Comment: 8 pages, 7 figures. Final version: figures were redesigned, and a new section discussing the role of Coulomb in IMF production was include

    Calibration of Plastic Phoswich Detectors for Charged Particle Detection

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    The response of an array of plastic phoswich detectors to ions of 1≤Z≤181\le Z\le 18 has been measured from E/AE/A=12 to 72 MeV. The detector response has been parameterized by a three parameter fit which includes both quenching and high energy delta-ray effects. The fits have a mean variation of ≤4%\le 4\% with respect to the data.Comment: 17 pages, 5 figure

    Clear Experimental Signature of Charge-Orbital density wave in Nd1−x_{1-x}Ca1+x_{1+x}MnO4_{4}

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    Single Crystals of Nd1−x_{1-x}Ca1+x_{1+x}MnO4_{4} have been prepared by the travelling floating-zone method, and possible evidence of a charge -orbital density wave in this material presented earlier [PRB68,092405 (2003)] using High Resolution Electron Microscopy [HRTEM] and Electron Diffraction [ED]. In the current note we present direct evidence of charge-orbital ordering in this material using heat capacity measurements. Our heat capacity measurements indicate a clear transition consistent with prior observation. We find two main transitions, one at temperature TH=310−314T_{_H}=310-314 K, and other at TA=143T_{_A}=143 K. In addition, we may also conclude that there is a strong electron-phonon coupling in this material.Comment: 7 pages, 8 figure

    Variational Deep Semantic Hashing for Text Documents

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    As the amount of textual data has been rapidly increasing over the past decade, efficient similarity search methods have become a crucial component of large-scale information retrieval systems. A popular strategy is to represent original data samples by compact binary codes through hashing. A spectrum of machine learning methods have been utilized, but they often lack expressiveness and flexibility in modeling to learn effective representations. The recent advances of deep learning in a wide range of applications has demonstrated its capability to learn robust and powerful feature representations for complex data. Especially, deep generative models naturally combine the expressiveness of probabilistic generative models with the high capacity of deep neural networks, which is very suitable for text modeling. However, little work has leveraged the recent progress in deep learning for text hashing. In this paper, we propose a series of novel deep document generative models for text hashing. The first proposed model is unsupervised while the second one is supervised by utilizing document labels/tags for hashing. The third model further considers document-specific factors that affect the generation of words. The probabilistic generative formulation of the proposed models provides a principled framework for model extension, uncertainty estimation, simulation, and interpretability. Based on variational inference and reparameterization, the proposed models can be interpreted as encoder-decoder deep neural networks and thus they are capable of learning complex nonlinear distributed representations of the original documents. We conduct a comprehensive set of experiments on four public testbeds. The experimental results have demonstrated the effectiveness of the proposed supervised learning models for text hashing.Comment: 11 pages, 4 figure

    Zero-Shot Hashing via Transferring Supervised Knowledge

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    Hashing has shown its efficiency and effectiveness in facilitating large-scale multimedia applications. Supervised knowledge e.g. semantic labels or pair-wise relationship) associated to data is capable of significantly improving the quality of hash codes and hash functions. However, confronted with the rapid growth of newly-emerging concepts and multimedia data on the Web, existing supervised hashing approaches may easily suffer from the scarcity and validity of supervised information due to the expensive cost of manual labelling. In this paper, we propose a novel hashing scheme, termed \emph{zero-shot hashing} (ZSH), which compresses images of "unseen" categories to binary codes with hash functions learned from limited training data of "seen" categories. Specifically, we project independent data labels i.e. 0/1-form label vectors) into semantic embedding space, where semantic relationships among all the labels can be precisely characterized and thus seen supervised knowledge can be transferred to unseen classes. Moreover, in order to cope with the semantic shift problem, we rotate the embedded space to more suitably align the embedded semantics with the low-level visual feature space, thereby alleviating the influence of semantic gap. In the meantime, to exert positive effects on learning high-quality hash functions, we further propose to preserve local structural property and discrete nature in binary codes. Besides, we develop an efficient alternating algorithm to solve the ZSH model. Extensive experiments conducted on various real-life datasets show the superior zero-shot image retrieval performance of ZSH as compared to several state-of-the-art hashing methods.Comment: 11 page

    Enhanced Fusion-Evaporation Cross Sections in Neutron-Rich 132^{132}Sn on 64^{64}Ni

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    Evaporation residue cross sections have been measured with neutron-rich radioactive 132^{132}Sn beams on 64^{64}Ni in the vicinity of the Coulomb barrier. The average beam intensity was 2×1042\times 10^{4} particles per second and the smallest cross section measured was less than 5 mb. Large subbarrier fusion enhancement was observed. Coupled-channels calculations taking into account inelastic excitation and neutron transfer underpredict the measured cross sections below the barrier.Comment: 4 pages including 1 table and 3 figure

    Fragment Production in Non-central Collisions of Intermediate Energy Heavy Ions

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    The defining characteristics of fragment emission resulting from the non-central collision of 114Cd ions with 92Mo target nuclei at E/A = 50 MeV are presented. Charge correlations and average relative velocities for mid-velocity fragment emission exhibit significant differences when compared to standard statistical decay. These differences associated with similar velocity dissipation are indicative of the influence of the entrance channel dynamics on the fragment production process

    Nature of ege_g Electron Order in La1−x_{1-x}Sr1+x_{1+x}MnO4_4

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    Synchrotron x-ray scattering measurements of the low-temperature structure of the single-layer manganese oxide La1−x_{1-x}Sr1+x_{1+x}MnO4_4, over the doping range 0.33≤x≤0.670.33 \le x \le 0.67, indicate the existence of three distinct regions: a disordered phase (x<0.4x < 0.4), a charge-ordered phase (x≥0.5x \ge 0.5), and a mixed phase (0.4≤x0.50.4 \le x 0.5, the modulation vector associated with the charge order is incommensurate with the lattice and depends linearly on the concentration of ege_g electrons. The primary superlattice reflections are strongly suppressed along the modulation direction and the higher harmonics are weak, implying the existence of a largely transverse and nearly sinusoidal structural distortion, consistent with a charge density wave of the ege_g electrons.Comment: 4 pages, 4 figure
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