652 research outputs found

    Strain-engineered magnetic order in (LaMnO3_{3})n_n/(SrMnO3_{3})2n_{2n} superlattices

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    Using first-principles calculations based on the density functional theory, we show a strong strain dependence of magnetic order in (LaMnO3_{3})n_n/(SrMnO3_{3})2n_{2n} (001) superlattices with n=1,2n=1,2. The epitaxial strain lifts the degeneracy of Mn ege_{g} orbitals, thus inducing an inherent orbital order, which in turn strongly affects the ferromagnetic double exchange of itinerant ege_{g} electrons, competing with the antiferromagnetic superexchange of localized t2gt_{2g} electrons. For the case of tensile strain induced by SrTiO3_3 (001) substrate, we find that the ground state is A-type antiferromagnetic and dx2−y2d_{x^2-y^2} orbital ordered, which is in excellent agreement with recent experiments [S. J. May {\it et al.}, Nature Materials {\bf 8}, 892 (2009)]. Instead, for the case of compressive strain induced by LaAlO3_3 (001) substrate, we predict that the ground state is C-type antiferromagnetic and d3z2−r2d_{3z^2-r^2} orbital ordered.Comment: The paper is accepted for publication in Phys. Rev.

    Word Embedding based Correlation Model for Question/Answer Matching

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    With the development of community based question answering (Q&A) services, a large scale of Q&A archives have been accumulated and are an important information and knowledge resource on the web. Question and answer matching has been attached much importance to for its ability to reuse knowledge stored in these systems: it can be useful in enhancing user experience with recurrent questions. In this paper, we try to improve the matching accuracy by overcoming the lexical gap between question and answer pairs. A Word Embedding based Correlation (WEC) model is proposed by integrating advantages of both the translation model and word embedding, given a random pair of words, WEC can score their co-occurrence probability in Q&A pairs and it can also leverage the continuity and smoothness of continuous space word representation to deal with new pairs of words that are rare in the training parallel text. An experimental study on Yahoo! Answers dataset and Baidu Zhidao dataset shows this new method's promising potential.Comment: 8 pages, 2 figure

    Solar Radio Bursts with Spectral Fine Structures in Preflares

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    A good observation of preflare activities is important for us to understand the origin and triggering mechanism of solar flares, and to predict the occurrence of solar flares. This work presents the characteristics of microwave spectral fine structures as preflare activities of four solar flares observed by Ond\v{r}ejov radio spectrograph in the frequency range of 0.8--2.0 GHz. We found that these microwave bursts which occurred 1--4 minutes before the onset of flares have spectral fine structures with relatively weak intensities and very short timescales. They include microwave quasi-periodic pulsations (QPP) with very short period of 0.1-0.3 s and dot bursts with millisecond timescales and narrow frequency bandwidths. Accompanying these microwave bursts, there are filament motions, plasma ejection or loop brightening on the EUV imaging observations and non-thermal hard X-ray emission enhancements observed by RHESSI. These facts may reveal certain independent non-thermal energy releasing processes and particle acceleration before the onset of solar flares. They may be conducive to understand the nature of solar flares and predict their occurrence
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