657 research outputs found

    Stable Attracting Sets in Dynamical Systems and in Their One-Step Discretizations

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    We consider a dynamical system described by a system of ordinary differential equations which possesses a compact attracting set Λ of arbitrary shape. Under the assumption of uniform asymptotic stability of Λ in the sense of Lyapunov, we show that discretized versions of the dynamical system involving one-step numerical methods have nearby attracting sets Λ(h), which are also uniformly asymptotically stable. Our proof uses the properties of a Lyapunov function which characterizes the stability of Λ

    Measurement-induced two-qubit entanglement in a bad cavity: Fundamental and practical considerations

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    An entanglement-generating protocol is described for two qubits coupled to a cavity field in the bad-cavity limit. By measuring the amplitude of a field transmitted through the cavity, an entangled spin-singlet state can be established probabilistically. Both fundamental limitations and practical measurement schemes are discussed, and the influence of dissipative processes and inhomogeneities in the qubits are analyzed. The measurement-based protocol provides criteria for selecting states with an infidelity scaling linearly with the qubit-decoherence rate.Comment: 13 pages, 7 figures, submitted to Phys. Rev.

    Stochastic contribution to the growth factor in the LCDM model

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    We study the effect of noise on the evolution of the growth factor of density perturbations in the context of the LCDM model. Stochasticity is introduced as a Wiener process amplified by an intensity parameter alpha. By comparing the evolution of deterministic and stochastic cases for different values of alpha we estimate the intensity level necessary to make noise relevant for cosmological tests based on large-scale structure data. Our results indicate that the presence of random forces underlying the fluid description can lead to significant deviations from the nonstochastic solution at late times for alpha>0.001.Comment: 6 pages, 1 figur

    Current-pulse-induced magnetic switching in standard and nonstandard spin-valves

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    Magnetization switching due to a current-pulse in symmetric and asymmetric spin valves is studied theoretically within the macrospin model. The switching process and the corresponding switching parameters are shown to depend significantly on the pulse duration and also on the interplay of the torques due to spin transfer and external magnetic field. This interplay leads to peculiar features in the corresponding phase diagram. These features in standard spin valves, where the spin transfer torque stabilizes one of the magnetic configurations (either parallel or antiparallel) and destabilizes the opposite one, differ from those in nonstandard (asymmetric) spin valves, where both collinear configurations are stable for one current orientation and unstable for the opposite one. Following this we propose a scheme of ultrafast current-induced switching in nonstandard spin valves, based on a sequence of two current pulses.Comment: 7 pages, 5 figures; to be published in Phys. Rev.

    Stochastic memory: memory enhancement due to noise

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    There are certain classes of resistors, capacitors and inductors that, when subject to a periodic input of appropriate frequency, develop hysteresis loops in their characteristic response. Here, we show that the hysteresis of such memory elements can also be induced by white noise of appropriate intensity even at very low frequencies of the external driving field. We illustrate this phenomenon using a physical model of memory resistor realized by TiO2\mathrm{TiO_2} thin films sandwiched between metallic electrodes, and discuss under which conditions this effect can be observed experimentally. We also discuss its implications on existing memory systems described in the literature and the role of colored noise.Comment: 5 pages, 4 figure

    Exact corrections for finite-time drift and diffusion coefficients

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    Real data are constrained to finite sampling rates, which calls for a suitable mathematical description of the corrections to the finite-time estimations of the dynamic equations. Often in the literature, lower order discrete time approximations of the modeling diffusion processes are considered. On the other hand, there is a lack of simple estimating procedures based on higher order approximations. For standard diffusion models, that include additive and multiplicative noise components, we obtain the exact corrections to the empirical finite-time drift and diffusion coefficients, based on It\^o-Taylor expansions. These results allow to reconstruct the real hidden coefficients from the empirical estimates. We also derive higher-order finite-time expressions for the third and fourth conditional moments, that furnish extra theoretical checks for that class of diffusive models. The theoretical predictions are compared with the numerical outcomes of some representative artificial time-series.Comment: 18 pages, 5 figure

    Analysis of stochastic time series in the presence of strong measurement noise

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    A new approach for the analysis of Langevin-type stochastic processes in the presence of strong measurement noise is presented. For the case of Gaussian distributed, exponentially correlated, measurement noise it is possible to extract the strength and the correlation time of the noise as well as polynomial approximations of the drift and diffusion functions from the underlying Langevin equation.Comment: 12 pages, 10 figures; corrected typos and reference

    Algebraic structure of stochastic expansions and efficient simulation

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    We investigate the algebraic structure underlying the stochastic Taylor solution expansion for stochastic differential systems.Our motivation is to construct efficient integrators. These are approximations that generate strong numerical integration schemes that are more accurate than the corresponding stochastic Taylor approximation, independent of the governing vector fields and to all orders. The sinhlog integrator introduced by Malham & Wiese (2009) is one example. Herein we: show that the natural context to study stochastic integrators and their properties is the convolution shuffle algebra of endomorphisms; establish a new whole class of efficient integrators; and then prove that, within this class, the sinhlog integrator generates the optimal efficient stochastic integrator at all orders.Comment: 19 page
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