Diffusive foam wetting process in microgravity

We report the experimental study of aqueous foam wetting in microgravity. The liquid fraction $\ell$ along the bubble edges is measured and is found to be a relevant dynamical parameter during the capillary process. The penetration of the liquid in the foam, the foam inflation, and the rigidity loss are shown all to obey strict diffusion processes.Comment: 4 pages, 6 figures, submitted to Phys. Rev. Let

Cross-correlations between volume change and price change

In finance, one usually deals not with prices but with growth rates $R$, defined as the difference in logarithm between two consecutive prices. Here we consider not the trading volume, but rather the volume growth rate $\tilde R$, the difference in logarithm between two consecutive values of trading volume. To this end, we use several methods to analyze the properties of volume changes $|\tilde R|$, and their relationship to price changes $|R|$. We analyze $14,981$ daily recordings of the S\&P 500 index over the 59-year period 1950--2009, and find power-law {\it cross-correlations\/} between $|R|$ and $|\tilde R|$ using detrended cross-correlation analysis (DCCA). We introduce a joint stochastic process that models these cross-correlations. Motivated by the relationship between $| R|$ and $|\tilde R|$, we estimate the tail exponent ${\tilde\alpha}$ of the probability density function $P(|\tilde R|) \sim |\tilde R|^{-1 -\tilde\alpha}$ for both the S\&P 500 index as well as the collection of 1819 constituents of the New York Stock Exchange Composite index on 17 July 2009. As a new method to estimate $\tilde\alpha$, we calculate the time intervals $\tau_q$ between events where $\tilde R>q$. We demonstrate that $\bar\tau_q$, the average of $\tau_q$, obeys $\bar \tau_q \sim q^{\tilde\alpha}$. We find $\tilde \alpha \approx 3$. Furthermore, by aggregating all $\tau_q$ values of 28 global financial indices, we also observe an approximate inverse cubic law.Comment: 7 pages, 5 figure

Contour lines of the discrete scale invariant rough surfaces

We study the fractal properties of the 2d discrete scale invariant (DSI) rough surfaces. The contour lines of these rough surfaces show clear DSI. In the appropriate limit the DSI surfaces converge to the scale invariant rough surfaces. The fractal properties of the 2d DSI rough surfaces apart from possessing the discrete scale invariance property follow the properties of the contour lines of the corresponding scale invariant rough surfaces. We check this hypothesis by calculating numerous fractal exponents of the contour lines by using numerical calculations. Apart from calculating the known scaling exponents some other new fractal exponents are also calculated.Comment: 9 Pages, 12 figure

Estimation of the charge carrier localization length from Gaussian fluctuations in the magneto-thermopower of La_{0.6}Y_{0.1}Ca_{0.3}MnO_3

The magneto-thermoelectric power (TEP) $\Delta S(T,H)$ of perovskite type manganise oxide $La_{0.6}Y_{0.1}Ca_{0.3}MnO_3$ is found to exhibit a sharp peak at some temperature $T^{*}=170K$. By approximating the true shape of the measured magneto-TEP in the vicinity of $T^{*}$ by a linear triangle of the form $\Delta S(T,H)\simeq S_p(H)\pm B^{\pm}(H)(T^{*}-T)$, we observe that $B ^{-}(H)\simeq 2B ^{+}(H)$. We adopt the electron localization scenario and introduce a Ginzburg-Landau (GL) type theory which incorporates the two concurrent phase transitions, viz., the paramagnetic-ferromagnetic transition at the Curie point $T_C$ and the "metal-insulator" (M-I) transition at $T_{MI}$. The latter is characterized by the divergence of the field-dependent charge carrier localization length $\xi (T,H)$ at some characteristic field $H_0$. Calculating the average and fluctuation contributions to the total magnetization and the transport entropy related magneto-TEP $\Delta S(T,H)$ within the GL theory, we obtain a simple relationship between $T^{*}$ and the above two critical temperatures ($T_{C}$ and $T_{MI}$). The observed slope ratio $B ^{-}(H)/B ^{+}(H)$ is found to be governed by the competition between the electron-spin exchange $JS$ and the induced magnetic energy $M_sH_0$. The comparison of our data with the model predictions produce $T_{C}=195K$, $JS=40meV$, $M_0=0.4M_s$, $\xi_0=10\AA$, and $n_e/n_i=2/3$ for the estimates of the Curie temperature, the exchange coupling constant, the critical magnetization, the localization length, and the free-to-localized carrier number density ratio, respectively.Comment: 6 pages (REVTEX), 2 PS figures (epsf.sty); submitted to Phys.Rev.

Influence of a low magnetic field on the thermal diffusivity of Bi-2212

The thermal diffusivity of a Bi-2212 polycrystalline sample has been measured under a 1T magnetic field applied perpendicularly to the heat flux. The magnetic contribution to the heat carrier mean free path has been extracted and is found to behave as a simple power law. This behavior can be attributed to a percolation process of electrons in the vortex lattice created by the magnetic field.Comment: 10 pages, 3 figures; to be published in Phys. Rev.

Antipersistent binary time series

Completely antipersistent binary time series are sequences in which every time that an $N$-bit string $\mu$ appears, the sequence is continued with a different bit than at the last occurrence of $\mu$. This dynamics is phrased in terms of a walk on a DeBruijn graph, and properties of transients and cycles are studied. The predictability of the generated time series for an observer who sees a longer or shorter time window is investigated also for sequences that are not completely antipersistent.Comment: 6 pages, 6 figure

Effect of nonstationarities on detrended fluctuation analysis

Detrended fluctuation analysis (DFA) is a scaling analysis method used to quantify long-range power-law correlations in signals. Many physical and biological signals are ``noisy'', heterogeneous and exhibit different types of nonstationarities, which can affect the correlation properties of these signals. We systematically study the effects of three types of nonstationarities often encountered in real data. Specifically, we consider nonstationary sequences formed in three ways: (i) stitching together segments of data obtained from discontinuous experimental recordings, or removing some noisy and unreliable parts from continuous recordings and stitching together the remaining parts -- a ``cutting'' procedure commonly used in preparing data prior to signal analysis; (ii) adding to a signal with known correlations a tunable concentration of random outliers or spikes with different amplitude, and (iii) generating a signal comprised of segments with different properties -- e.g. different standard deviations or different correlation exponents. We compare the difference between the scaling results obtained for stationary correlated signals and correlated signals with these three types of nonstationarities.Comment: 17 pages, 10 figures, corrected some typos, added one referenc

An attempt to observe economy globalization: the cross correlation distance evolution of the top 19 GDP's

Economy correlations between the 19 richest countries are investigated through their Gross Domestic Product increments. A distance is defined between increment correlation matrix elements and their evolution studied as a function of time and time window size. Unidirectional and Bidirectional Minimal Length Paths are generated and analyzed for different time windows. A sort of critical correlation time window is found indicating a transition for best observations. The mean length path decreases with time, indicating stronger correlations. A new method for estimating a realistic minimal time window to observe correlations and deduce macroeconomy conclusions from such features is thus suggested.Comment: to be published in the Dyses05 proceedings, in Int. J. Mod Phys C 15 pages, 5 figures, 1 tabl

Time correlations and 1/f behavior in backscattering radar reflectivity measurements from cirrus cloud ice fluctuations

The state of the atmosphere is governed by the classical laws of fluid motion and exhibits correlations in various spatial and temporal scales. These correlations are crucial to understand the short and long term trends in climate. Cirrus clouds are important ingredients of the atmospheric boundary layer. To improve future parameterization of cirrus clouds in climate models, it is important to understand the cloud properties and how they change within the cloud. We study correlations in the fluctuations of radar signals obtained at isodepths of winter and fall cirrus clouds. In particular we focus on three quantities: (i) the backscattering cross-section, (ii) the Doppler velocity and (iii) the Doppler spectral width. They correspond to the physical coefficients used in Navier Stokes equations to describe flows, i.e. bulk modulus, viscosity, and thermal conductivity. In all cases we find that power-law time correlations exist with a crossover between regimes at about 3 to 5 min. We also find that different type of correlations, including 1/f behavior, characterize the top and the bottom layers and the bulk of the clouds. The underlying mechanisms for such correlations are suggested to originate in ice nucleation and crystal growth processes.Comment: 33 pages, 9 figures; to appear in the Journal of Geophysical Research - Atmosphere