49,522 research outputs found

    Redistribution of particle and anti-particle entanglement in non-inertial frames

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    We analyse the entanglement tradeoff between particle and anti-particle modes of a Dirac field from the perspective of inertial and uniformly accelerated observers. Our results show that a redistribution of entanglement between particle and anti-particle modes plays a key role in the survival of fermionic field entanglement in the infinite acceleration limit.Comment: 10 pages, 5 figures, revtex4. Added journal referenc

    Boxy/peanut bulges : formation, evolution and properties

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    We discuss the formation and evolution of boxy/peanut bulges (B/Ps) and present new simulations results. Orbital structure studies show that B/Ps are parts of bars seen edge-on, they have their origin in vertical instabilities of the disc material and they are somewhat shorter in extent than bars. When the bar forms it is vertically thin, but after a time of the order of a Gyr it experiences a vertical instability and buckles. At that time the strength of the bar decreases, its inner part becomes thicker, so that, seen edge-on, it acquires a peanut or boxy shape. A second buckling episode is seen in simulations with strong bars, accompanied by a further thickening of the B/P and a weakening of the bar. Quantitatively, this evolution depends considerably on the properties of the halo and particularly on the extent of its core. This influences the amount of angular momentum exchanged within the galaxy, emitted by near-resonant material in the bar region and absorbed by near-resonant material in the halo and in the outer disc. Haloes with small cores generally harbour stronger bars and B/Ps and they often witness double buckling.Comment: 7 pages, 3 figures, contribution to the conference "Chaos in Astronomy", Athens, sept. 2007, eds. G. Contopoulos & P.A. Patsi

    Boxy/Peanut bulges, vertical buckling and galactic bars

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    Boxy/peanut bulges in disk galaxies have been associated to stellar bars. In this talk, we discuss the different properties of such bulges and their relation with the corresponding bar, using a very large sample of a few hundred numerical N-body simulations. We present and inter-compare various methods of measuring the boxy/peanut bulge properties, namely its strength, shape and possible asymmetry. Some of these methods can be applied to both simulations and observations. Our final goal is to get correlations that will allow us to obtain information on the boxy/peanut bulge for a galaxy viewed face-on as well as information on the bars of galaxies viewed edge-on.Comment: 4 pages. To appear in the proceedings of IAU Symposium 245 "Formation and Evolution of Galaxy Bulges", M. Bureau, E. Athanassoula, and B. Barbuy, ed

    Quantum stochastic walks on networks for decision-making

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    Recent experiments report violations of the classical law of total probability and incompatibility of certain mental representations when humans process and react to information. Evidence shows promise of a more general quantum theory providing a better explanation of the dynamics and structure of real decision-making processes than classical probability theory. Inspired by this, we show how the behavioral choice-probabilities can arise as the unique stationary distribution of quantum stochastic walkers on the classical network defined from Luce''s response probabilities. This work is relevant because (i) we provide a very general framework integrating the positive characteristics of both quantum and classical approaches previously in confrontation, and (ii) we define a cognitive network which can be used to bring other connectivist approaches to decision-making into the quantum stochastic realm. We model the decision-maker as an open system in contact with her surrounding environment, and the time-length of the decision-making process reveals to be also a measure of the process'' degree of interplay between the unitary and irreversible dynamics. Implementing quantum coherence on classical networks may be a door to better integrate human-like reasoning biases in stochastic models for decision-making
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