895 research outputs found

    Memory beyond memory in heart beating: an efficient way to detect pathological conditions

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    We study the long-range correlations of heartbeat fluctuations with the method of diffusion entropy. We show that this method of analysis yields a scaling parameter δ\delta that apparently conflicts with the direct evaluation of the distribution of times of sojourn in states with a given heartbeat frequency. The strength of the memory responsible for this discrepancy is given by a parameter ϵ2\epsilon^{2}, which is derived from real data. The distribution of patients in the (δ\delta, ϵ2\epsilon^{2})-plane yields a neat separation of the healthy from the congestive heart failure subjects.Comment: submitted to Physical Review Letters, 5 figure

    Finite-sample frequency distributions originating from an equiprobability distribution

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    Given an equidistribution for probabilities p(i)=1/N, i=1..N. What is the expected corresponding rank ordered frequency distribution f(i), i=1..N, if an ensemble of M events is drawn?Comment: 4 pages, 4 figure

    Ultracold atoms in radio-frequency-dressed potentials beyond the rotating wave approximation

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    We study dressed Bose-Einstein condensates in an atom chip radio-frequency trap. We show that in this system sufficiently strong dressing can be achieved to cause the widely used rotating wave approximation (RWA) to break down. We present a full calculation of the atom - field coupling which shows that the non-RWA contributions quantitatively alter the shape of the emerging dressed adiabatic potentials. The non-RWA contributions furthermore lead to additional allowed transitions between dressed levels. We use RF spectroscopy of Bose-Einstein condensates trapped in the dressed state potentials to directly observe the transition from the RWA to the beyond-RWA regime.Comment: 6 pages, 4 figure

    L\'{e}vy scaling: the Diffusion Entropy Analysis applied to DNA sequences

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    We address the problem of the statistical analysis of a time series generated by complex dynamics with a new method: the Diffusion Entropy Analysis (DEA) (Fractals, {\bf 9}, 193 (2001)). This method is based on the evaluation of the Shannon entropy of the diffusion process generated by the time series imagined as a physical source of fluctuations, rather than on the measurement of the variance of this diffusion process, as done with the traditional methods. We compare the DEA to the traditional methods of scaling detection and we prove that the DEA is the only method that always yields the correct scaling value, if the scaling condition applies. Furthermore, DEA detects the real scaling of a time series without requiring any form of de-trending. We show that the joint use of DEA and variance method allows to assess whether a time series is characterized by L\'{e}vy or Gauss statistics. We apply the DEA to the study of DNA sequences, and we prove that their large-time scales are characterized by L\'{e}vy statistics, regardless of whether they are coding or non-coding sequences. We show that the DEA is a reliable technique and, at the same time, we use it to confirm the validity of the dynamic approach to the DNA sequences, proposed in earlier work.Comment: 24 pages, 9 figure

    Renewal processes and fluctuation analysis of molecular motor stepping

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    We model the dynamics of a processive or rotary molecular motor using a renewal processes, in line with the work initiated by Svoboda, Mitra and Block. We apply a functional technique to compute different types of multiple-time correlation functions of the renewal process, which have applications to bead-assay experiments performed both with processive molecular motors, such as myosin V and kinesin, and rotary motors, such as F1-ATPase
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