25,082 research outputs found

    Dynamic Atomic Snapshots

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    Snapshots are useful tools for monitoring big distributed and parallel systems. In this paper, we adapt the well-known atomic snapshot abstraction to dynamic models with an unbounded number of participating processes. Our dynamic snapshot specification extends the API to allow changing the set of processes whose values should be returned from a scan operation. We introduce the ephemeral memory model, which consists of a dynamically changing set of nodes; when a node is removed, its memory can be immediately reclaimed. In this model, we present an algorithm for wait-free dynamic atomic snapshots

    Disorder Correlation Frequency Controlled Diffusion in the Jaynes-Cummings-Hubbard Model

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    We investigate time-dependent stochastic disorder in the one-dimensional Jaynes-Cummings-Hubbard model and show that it gives rise to diffusive behaviour. We find that disorder correlation frequency is effective in controlling the level of diffusivity. In the defectless system the mean squared displacement (MSD), which is a measure of the diffusivity, increases with increasing disorder frequency. Contrastingly, when static defects are present the MSD increases with disorder frequency only at lower frequencies; at higher frequencies, increasing disorder frequency actually reduces the MSD

    Learning from Ontology Streams with Semantic Concept Drift

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    Data stream learning has been largely studied for extracting knowledge structures from continuous and rapid data records. In the semantic Web, data is interpreted in ontologies and its ordered sequence is represented as an ontology stream. Our work exploits the semantics of such streams to tackle the problem of concept drift i.e., unexpected changes in data distribution, causing most of models to be less accurate as time passes. To this end we revisited (i) semantic inference in the context of supervised stream learning, and (ii) models with semantic embeddings. The experiments show accurate prediction with data from Dublin and Beijing

    Quantum Monte Carlo and exact diagonalization study of a dynamic Hubbard model

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    A one-dimensional model of electrons locally coupled to spin-1/2 degrees of freedom is studied by numerical techniques. The model is one in the class of dynamicdynamic HubbardHubbard modelsmodels that describe the relaxation of an atomic orbital upon double electron occupancy due to electron-electron interactions. We study the parameter regime where pairing occurs in this model by exact diagonalization of small clusters. World line quantum Monte Carlo simulations support the results of exact diagonalization for larger systems and show that kinetic energy is lowered when pairing occurs. The qualitative physics of this model and others in its class, obtained through approximate analytic calculations, is that superconductivity occurs through hole undressing even in parameter regimes where the effective on-site interaction is strongly repulsive. Our numerical results confirm the expected qualitative behavior, and show that pairing will occur in a substantially larger parameter regime than predicted by the approximate low energy effective Hamiltonian.Comment: Some changes made in response to referees comments. To be published in Phys.Rev.

    Structural disjoining potential for grain boundary premelting and grain coalescence from molecular-dynamics simulations

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    We describe a molecular dynamics framework for the direct calculation of the short-ranged structural forces underlying grain-boundary premelting and grain-coalescence in solidification. The method is applied in a comparative study of (i) a Sigma 9 120 degress twist and (ii) a Sigma 9 {411} symmetric tilt boundary in a classical embedded-atom model of elemental Ni. Although both boundaries feature highly disordered structures near the melting point, the nature of the temperature dependence of the width of the disordered regions in these boundaries is qualitatively different. The former boundary displays behavior consistent with a logarithmically diverging premelted layer thickness as the melting temperature is approached from below, while the latter displays behavior featuring a finite grain-boundary width at the melting point. It is demonstrated that both types of behavior can be quantitatively described within a sharp-interface thermodynamic formalism involving a width-dependent interfacial free energy, referred to as the disjoining potential. The disjoining potential for boundary (i) is calculated to display a monotonic exponential dependence on width, while that of boundary (ii) features a weak attractive minimum. The results of this work are discussed in relation to recent simulation and theoretical studies of the thermodynamic forces underlying grain-boundary premelting.Comment: 24 pages, 8 figures, 1 tabl

    Stone-Wales Transformation Paths in Fullerene C60

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    The mechanisms of formation of a metastable defect isomer of fullerene C60 due to the Stone-Wales transformation are theoretically studied. It is demonstrated that the paths of the "dynamic" Stone-Wales transformation at a high sufficient for overcoming potential barriers) temperature can differ from the two "adiabatic" transformation paths discussed in the literature. This behavior is due to the presence of a great near-flat segment of the potential-energy surface in the neighborhood of metastable states. Besides, the sequence of rupture and formation of interatomic bonds is other than that in the case of the adiabatictransformation.Comment: 10 pages, 6 figure
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