arXiv subjects

H. Eugene Stanley

Publications and source records attributed to H. Eugene Stanley.

At least 271 records · Page 15Linked to original sources

arXiv2001

Noise Effects on the Complex Patterns of Abnormal Heartbeats

Patients at high risk for sudden death often exhibit complex heart rhythms in which abnormal heartbeats are interspersed with normal heartbeats. We analyze such a complex rhythm in a single patient over a 12-hour period and show that the rhythm can be described by a theoretical model consisting of two interacting oscillators with stochastic elements. By varying the magnitude of the noise, we show that for an intermediate level of noise, the model gives best agreement with key statistical features of the dynamics.

cond-mat.stat-mech↗

arXiv2001

A Stochastic Model of Human Gait Dynamics

We present a stochastic model of gait rhythm dynamics, based on transitions between different ``neural centers'', that reproduces distinctive statistical properties of normal human walking. By tuning one model parameter, the hopping range, the model can describe alterations in gait dynamics from childhood to adulthood --- including a decrease in the correlation and volatility exponents with maturation. The model also generates time series with multifractal spectra whose broadness depends only on this parameter.

cond-mat.stat-mech↗

arXiv2001

Magnitude and Sign Correlations in Heartbeat Fluctuations

We propose an approach for analyzing signals with long-range correlations by decomposing the signal increment series into magnitude and sign series and analyzing their scaling properties. We show that signals with identical long-range correlations can exhibit different time organization for the magnitude and sign. We find that the magnitude series relates to the nonlinear properties of the original time series, while the sign series relates to the linear properties. We apply our approach to the heartbeat interval series and find that the magnitude series is long-range correlated, while the sign series is anticorrelated and that both magnitude and sign series may have clinical applications.

cond-mat.stat-mech↗

arXiv2001

Static and Dynamic Properties of Stretched Water

We present the results of molecular dynamics simulations of the extended simple point charge (SPC/E) model of water to investigate thethermodynamic and dynamic properties of stretched and supercooled water. We locate the liquid-gas spinodal, and confirm that the spinodal pressure increases monotonically with $T$, supporting thermodynamic scenarios for the phase behavior of supercooled water involving a ``non-reentrant'' spinodal. The dynamics at negative pressure show a minimum in the diffusion constant $D$ when the density is decreased at constant temperature, complementary to the known maximum of $D$ at higher pressures. We locate the loci of minima of $D$ relative to the spinodal, showing that the locus is inside the thermodynamicaly metastable regions of the phase-diagram. These dynamical results reflect the initial enhancement and subsequent breakdown of the tetrahedral structure and of the hydrogen bond network as the density decreases.

cond-mat↗

arXiv2001

Generic mechanism for generating a liquid-liquid phase transition

Recent experimental results indicate that phosphorus, a single-component system, can have two liquid phases: a high-density liquid (HDL) and a low-density liquid (LDL) phase. A first-order transition between two liquids of different densities is consistent with experimental data for a variety of materials, including single-component systems such as water, silica and carbon. Molecular dynamics simulations of very specific models for supercooled water, liquid carbon and supercooled silica, predict a LDL-HDL critical point, but a coherent and general interpretation of the LDL-HDL transition is lacking. Here we show that the presence of a LDL and a HDL can be directly related to an interaction potential with an attractive part and two characteristic short-range repulsive distances. This kind of interaction is common to other single-component materials in the liquid state (in particular liquid metals), and such potentials are often used to decribe systems that exhibit a density anomaly. However, our results show that the LDL and HDL phases can occur in systems with no density anomaly. Our results therefore present an experimental challenge to uncover a liquid-liquid transition in systems like liquid metals, regardless of the presence of the density anomaly.

cond-mat.stat-mech↗

arXiv2001

Percolation Threshold, Fisher Exponent, and Shortest Path Exponent for 4 and 5 Dimensions

We develop a method of constructing percolation clusters that allows us to build very large clusters using very little computer memory by limiting the maximum number of sites for which we maintain state information to a number of the order of the number of sites in the largest chemical shell of the cluster being created. The memory required to grow a cluster of mass s is of the order of $s^θ$ bytes where $θ$ ranges from 0.4 for 2-dimensional lattices to 0.5 for 6- (or higher)-dimensional lattices. We use this method to estimate $d_{\scriptsize min}$, the exponent relating the minimum path $\ell$ to the Euclidean distance r, for 4D and 5D hypercubic lattices. Analyzing both site and bond percolation, we find $d_{\scriptsize min}=1.607\pm 0.005$ (4D) and $d_{\scriptsize min}=1.812\pm 0.006$ (5D). In order to determine $d_{\scriptsize min}$ to high precision, and without bias, it was necessary to first find precise values for the percolation threshold, $p_c$: $p_c=0.196889\pm 0.000003$ (4D) and $p_c=0.14081\pm 0.00001$ (5D) for site and $p_c=0.160130\pm 0.000003$ (4D) and $p_c=0.118174\pm 0.000004$ (5D) for bond percolation. We also calculate the Fisher exponent, $τ$, determined in the course of calculating the values of $p_c$: $τ=2.313\pm 0.003$ (4D) and $τ=2.412\pm 0.004$ (5D).

cond-mat.stat-mech↗

arXiv2000

Thermodynamically Important Contacts in Folding of Model Proteins

We introduce a quantity, the entropic susceptibility, that measures the thermodynamic importance-for the folding transition-of the contacts between amino acids in model proteins. Using this quantity, we find that only one equilibrium run of a computer simulation of a model protein is sufficient to select a subset of contacts that give rise to the peak in the specific heat observed at the folding transition. To illustrate the method, we identify thermodynamically important contacts in a model 46-mer. We show that only about 50% of all contacts present in the protein native state are responsible for the sharp peak in the specific heat at the folding transition temperature, while the remaining 50% of contacts do not affect the specific heat.

cond-mat.stat-mech↗

arXiv2000

Identifying Business Sectors from Stock Price Fluctuations

Firms having similar business activities are correlated. We analyze two different cross-correlation matrices C constructed from (i) 30-min price fluctuations of 1000 US stocks for the 2-year period 1994-95 and (ii) 1-day price fluctuations of 422 US stocks for the 35-year period 1962-96. We find that the eigenvectors of C corresponding to the largest eigenvalues allow us to partition the set of all stocks into distinct subsets. These subsets are similar to conventionally-identified business sectors, and are stable for extended periods of time. Using a set of coupled stochastic differential equations, we argue how correlations between stocks might arise. Finally, we demonstrate that the sectors we identify are useful for the practical goal of finding an investment which earns a given return without exposure to unnecessary risk.

cond-mat.stat-mech↗

arXiv2000

Statistical Properties of Share Volume Traded in Financial Markets

We quantitatively investigate the ideas behind the often-expressed adage `it takes volume to move stock prices', and study the statistical properties of the number of shares traded $Q_{Δt}$ for a given stock in a fixed time interval $Δt$. We analyze transaction data for the largest 1000 stocks for the two-year period 1994-95, using a database that records every transaction for all securities in three major US stock markets. We find that the distribution $P(Q_{Δt})$ displays a power-law decay, and that the time correlations in $Q_{Δt}$ display long-range persistence. Further, we investigate the relation between $Q_{Δt}$ and the number of transactions $N_{Δt}$ in a time interval $Δt$, and find that the long-range correlations in $Q_{Δt}$ are largely due to those of $N_{Δt}$. Our results are consistent with the interpretation that the large equal-time correlation previously found between $Q_{Δt}$ and the absolute value of price change $| G_{Δt} |$ (related to volatility) are largely due to $N_{Δt}$.

cond-mat.stat-mech↗

arXiv2000

Thermodynamic and structural aspects of the potential energy surface of simulated water

Relations between the thermodynamics and dynamics of supercooled liquids approaching a glass transition have been proposed over many years. The potential energy surface of model liquids has been increasingly studied since it provides a connection between the configurational component of the partition function on one hand, and the system dynamics on the other. This connection is most obvious at low temperatures, where the motion of the system can be partitioned into vibrations within a basin of attraction and infrequent inter-basin transitions. In this work, we present a description of the potential energy surface properties of supercooled liquid water. The dynamics of this model has been studied in great details in the last years. Specifically, we locate the minima sampled by the liquid by ``quenches'' from equilibrium configurations generated via molecular dynamics simulations. We calculate the temperature and density dependence of the basin energy, degeneracy, and shape. The temperature dependence of the energy of the minima is qualitatively similar to simple liquids, but has anomalous density dependence. The unusual density dependence is also reflected in the configurational entropy, the thermodynamic measure of degeneracy. Finally, we study the structure of simulated water at the minima, which provides insight on the progressive tetrahedral ordering of the liquid on cooling.

cond-mat.soft↗

arXiv2000

Scale Invariance in the Nonstationarity of Physiological Signals

We introduce a segmentation algorithm to probe temporal organization of heterogeneities in human heartbeat interval time series. We find that the lengths of segments with different local values of heart rates follow a power-law distribution. This scale-invariant structure is not a simple consequence of the long-range correlations present in the data. We also find that the differences in mean heart rates between consecutive segments display a common functional form, but with different parameters for healthy individuals and for patients with heart failure. This finding may provide information into the way heart rate variability is reduced in cardiac disease.

cond-mat.stat-mech↗

arXiv2000

Hierarchical organization of cities and nations

Universality in the behavior of complex systems often reveals itself in the form of scale-invariant distributions that are essentially independent of the details of the microscopic dynamics. A representative paradigm of complex behavior in nature is cooperative evolution. The interaction of individuals gives rise to a wide variety of collective phenomena that strongly differ from individual dynamics---such as demographic evolution, cultural and technological development, and economic activity. A striking example of such cooperative phenomena is the formation of urban aggregates which, in turn, can be considered to cooperate in giving rise to nations. We find that population and area distributions of nations follow an inverse power-law behavior, as is known for cities. The exponents, however, are radically different in the two cases ($μ\approx 1$ for nations, $μ\approx 2$ for cities). We interpret these findings by developing growth models for cities and for nations related to basic properties of partition of the plane. These models allow one to understand the empirical findings without resort to the introduction of complex socio-economic factors.

cond-mat.stat-mech↗

arXiv2000

Systems with Correlations in the Variance: Generating Power-Law Tails in Probability Distributions

We study how the presence of correlations in physical variables contributes to the form of probability distributions. We investigate a process with correlations in the variance generated by (i) a Gaussian or (ii) a truncated Lévy distribution. For both (i) and (ii), we find that due to the correlations in the variance, the process ``dynamically'' generates power-law tails in the distributions, whose exponents can be controlled through the way the correlations in the variance are introduced. For (ii), we find that the process can extend a truncated distribution {\it beyond the truncation cutoff}, which leads to a crossover between a Lévy stable power law and the present ``dynamically-generated'' power law. We show that the process can explain the crossover behavior recently observed in the $S&P500$ stock index.

cond-mat.stat-mech↗

arXiv2000

Flow Between Two Sites on a Percolation Cluster

We study the flow of fluid in porous media in dimensions $d=2$ and 3. The medium is modeled by bond percolation on a lattice of $L^d$ sites, while the flow front is modeled by tracer particles driven by a pressure difference between two fixed sites (``wells'') separated by Euclidean distance $r$. We investigate the distribution function of the shortest path connecting the two sites, and propose a scaling {\it Ansatz} that accounts for the dependence of this distribution (i) on the size of the system, $L$, and (ii) on the bond occupancy probability, $p$. We confirm by extensive simulations that the {\it Ansatz} holds for $d=2$ and 3, and calculate the relevant scaling parameters. We also study two dynamical quantities: the minimal traveling time of a tracer particle between the wells and the length of the path corresponding to the minimal traveling time ``fastest path'', which is not identical to the shortest path. A scaling {\it Ansatz} for these dynamical quantities also includes the effect of finite system size $L$ and off-critical bond occupation probability $p$. We find that the scaling form for the distribution functions for these dynamical quantities for $d=2$ and 3 is similar to that for the shortest path but with different critical exponents. The scaling form is represented as the product of a power law and three exponential cutoff functions. We summarize our results in a table which contains estimates for all parameters which characterize the scaling form for the shortest path and the minimal traveling time in 2 and 3 dimensions; these parameters are the fractal dimension, the power law exponent, and the constants and exponents that characterize the exponential cutoff functions.

cond-mat.stat-mech↗

arXiv2000

Classes of behavior of small-world networks

Small-world networks are the focus of recent interest because they appear to circumvent many of the limitations of either random networks or regular lattices as frameworks for the study of interaction networks of complex systems. Here, we report an empirical study of the statistical properties of a variety of diverse real-world networks. We present evidence of the occurrence of three classes of small-world networks: (a) scale-free networks, characterized by a vertex connectivity distribution that decays as a power law; (b) broad-scale networks, characterized by a connectivity distribution that has a power-law regime followed by a sharp cut-off; (c) single-scale networks, characterized by a connectivity distribution with a fast decaying tail. Moreover, we note for the classes of broad-scale and single-scale networks that there are constraints limiting the addition of new links. Our results suggest that the nature of such constraints may be the controlling factor for the emergence of different classes of networks.

cond-mat.stat-mech↗

arXiv1999

Economic Fluctuations and Diffusion

Stock price changes occur through transactions, just as diffusion in physical systems occurs through molecular collisions. We systematically explore this analogy and quantify the relation between trading activity - measured by the number of transactions $N_{Δt}$ - and the price change $G_{Δt}$, for a given stock, over a time interval $[t, t+Δt]$. To this end, we analyze a database documenting every transaction for 1000 US stocks over the two-year period 1994-1995. We find that price movements are equivalent to a complex variant of diffusion, where the diffusion coefficient fluctuates drastically in time. We relate the analog of the diffusion coefficient to two microscopic quantities: (i) the number of transactions $N_{Δt}$ in $Δt$, which is the analog of the number of collisions and (ii) the local variance $w^2_{Δt}$ of the price changes for all transactions in $Δt$, which is the analog of the local mean square displacement between collisions. We study the distributions of both $N_{Δt}$ and $w_{Δt}$, and find that they display power-law tails. Further, we find that $N_{Δt}$ displays long-range power-law correlations in time, whereas $w_{Δt}$ does not. Our results are consistent with the interpretation that the pronounced tails of the distribution of $G_{Δt} are due to $w_{Δt}$, and that the long-range correlations previously found for $| G_{Δt} |$ are due to $N_{Δt}$.

cond-mat.stat-mech↗

arXiv1999

Sleep-Wake Differences in Scaling Behavior of the Human Heartbeat: Analysis of Terrestrial and Long-Term Space Flight Data

We compare scaling properties of the cardiac dynamics during sleep and wake periods for healthy individuals, cosmonauts during orbital flight, and subjects with severe heart disease. For all three groups, we find a greater degree of anticorrelation in the heartbeat fluctuations during sleep compared to wake periods. The sleep-wake difference in the scaling exponents for the three groups is comparable to the difference between healthy and diseased individuals. The observed scaling differences are not accounted for simply by different levels of activity, but appear related to intrinsic changes in the neuroautonomic control of the heartbeat.

cond-mat.stat-mech↗

arXiv1999

Dependence of Conductance on Percolation Backbone Mass

On two-dimensional percolation clusters at the percolation threshold, we study $<σ(M_B,r)>$, the average conductance of the backbone, defined by two points separated by Euclidean distance $r$, of mass $M_B$. We find that with increasing $M_B$ and for fixed r, $<σ(M_B,r)>$ asymptotically {\it decreases} to a constant, in contrast with the behavior of homogeneous sytems and non-random fractals (such as the Sierpinski gasket) in which conductance increases with increasing $M_B$. We explain this behavior by studying the distribution of shortest paths between the two points on clusters with a given $M_B$. We also study the dependence of conductance on $M_B$ slightly above the percolation threshold.

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