Uncovering the evolution of nonstationary stochastic variables: The example of asset volume-price fluctuations.

We present a framework for describing the evolution of stochastic observables having a nonstationary distribution of values. The framework is applied to empirical volume-prices from assets traded at the New York Stock Exchange, about which several remarks are pointed out from our analysis. Using Kullback-Leibler divergence we evaluate the best model out of four biparametric models commonly used in the context of financial data analysis. In our present data sets we conclude that the inverse Γ distribution is a good model, particularly for the distribution tail of the largest volume-price fluctuations. Extracting the time series of the corresponding parameter values we show that they evolve in time as stochastic variables themselves. For the particular case of the parameter controlling the volume-price distribution tail we are able to extract an Ornstein-Uhlenbeck equation which describes the fluctuations of the highest volume-prices observed in the data. Finally, we discuss how to bridge the gap from the stochastic evolution of the distribution parameters to the stochastic evolution of the (nonstationary) observable and put our conclusions into perspective for other applications in geophysics and biology.

From empirical data to time-inhomogeneous continuous Markov processes.

We present an approach for testing for the existence of continuous generators of discrete stochastic transition matrices. Typically, existing methods to ascertain the existence of continuous Markov processes are based on the assumption that only time-homogeneous generators exist. Here a systematic extension to time inhomogeneity is presented, based on new mathematical propositions incorporating necessary and sufficient conditions, which are then implemented computationally and applied to numerical data. A discussion concerning the bridging between rigorous mathematical results on the existence of generators to its computational implementation is presented. Our detection algorithm shows to be effective in more than 60% of tested matrices, typically 80% to 90%, and for those an estimate of the (nonhomogeneous) generator matrix follows. We also solve the embedding problem analytically for the particular case of three-dimensional circulant matrices. Finally, a discussion of possible applications of our framework to problems in different fields is briefly addressed.

Record-breaking events during the compressive failure of porous materials.

An accurate understanding of the interplay between random and deterministic processes in generating extreme events is of critical importance in many fields, from forecasting extreme meteorological events to the catastrophic failure of materials and in the Earth. Here we investigate the statistics of record-breaking events in the time series of crackling noise generated by local rupture events during the compressive failure of porous materials. The events are generated by computer simulations of the uniaxial compression of cylindrical samples in a discrete element model of sedimentary rocks that closely resemble those of real experiments. The number of records grows initially as a decelerating power law of the number of events, followed by an acceleration immediately prior to failure. The distribution of the size and lifetime of records are power laws with relatively low exponents. We demonstrate the existence of a characteristic record rank k(*), which separates the two regimes of the time evolution. Up to this rank deceleration occurs due to the effect of random disorder. Record breaking then accelerates towards macroscopic failure, when physical interactions leading to spatial and temporal correlations dominate the location and timing of local ruptures. The size distribution of records of different ranks has a universal form independent of the record rank. Subsequences of events that occur between consecutive records are characterized by a power-law size distribution, with an exponent which decreases as failure is approached. High-rank records are preceded by smaller events of increasing size and waiting time between consecutive events and they are followed by a relaxation process. As a reference, surrogate time series are generated by reshuffling the event times. The record statistics of the uncorrelated surrogates agrees very well with the corresponding predictions of independent identically distributed random variables, which confirms that temporal and spatial correlation in the crackling noise is responsible for the observed unique behavior. In principle the results could be used to improve forecasting of catastrophic failure events, if they can be observed reliably in real time.

Modeling the functional network of primary intercellular Ca2+ wave propagation in astrocytes and its application to study drug effects.

We introduce a simple procedure of multivariate signal analysis to uncover the functional connectivity among cells composing a living tissue and describe how to apply it for extracting insight on the effect of drugs in the tissue. The procedure is based on the covariance matrix of time resolved activity signals. By determining the time-lag that maximizes covariance, one derives the weight of the corresponding connection between cells. Introducing simple constraints, it is possible to conclude whether pairs of cells are functionally connected and in which direction. After testing the method against synthetic data we apply it to study intercellular propagation of Ca(2+) waves in astrocytes following an external stimulus, with the aim of uncovering the functional cellular connectivity network. Our method proves to be particularly suited for this type of networking signal propagation where signals are pulse-like and have short time-delays, and is shown to be superior to standard methods, namely a multivariate Granger algorithm. Finally, based on the statistical analysis of the connection weight distribution, we propose simple measures for assessing the impact of drugs on the functional connectivity between cells.

Uncovering wind turbine properties through two-dimensional stochastic modeling of wind dynamics.

Using a method for stochastic data analysis borrowed from statistical physics, we analyze synthetic data from a Markov chain model that reproduces measurements of wind speed and power production in a wind park in Portugal. We show that our analysis retrieves indeed the power performance curve, which yields the relationship between wind speed and power production, and we discuss how this procedure can be extended for extracting unknown functional relationships between pairs of physical variables in general. We also show how specific features, such as the rated speed of the wind turbine or the descriptive wind speed statistics, can be related to the equations describing the evolution of power production and wind speed at single wind turbines.

Continuous damage fiber bundle model for strongly disordered materials.

We present an extension of the continuous damage fiber bundle model to describe the gradual degradation of highly heterogeneous materials under an increasing external load. The breaking of a fiber in the model is preceded by a sequence of partial failure events occurring at random threshold values. In order to capture the subsequent propagation and arrest of cracks, furthermore, the disorder of the number of degradation steps of material constituents, the failure thresholds of single fibers, are sorted into ascending order and their total number is a Poissonian distributed random variable over the fibers. Analytical and numerical calculations showed that the failure process of the system is governed by extreme value statistics, which has a substantial effect on the macroscopic constitutive behavior and on the microscopic bursting activity as well.

Local load sharing fiber bundles with a lower cutoff of strength disorder.

We study the failure properties of fiber bundles with a finite lower cutoff of the strength disorder varying the range of interaction between the limiting cases of completely global and completely local load sharing. Computer simulations revealed that at any range of load redistribution there exists a critical cutoff strength where the macroscopic response of the bundle becomes perfectly brittle, i.e., linearly elastic behavior is obtained up to global failure, which occurs catastrophically after the breaking of a small number of fibers. As an extension of recent mean field studies [Phys. Rev. Lett. 95, 125501 (2005)], we demonstrate that approaching the critical cutoff, the size distribution of bursts of breaking fibers shows a crossover to a universal power law form with an exponent 3/2 independent of the range of interaction.

Failure process of a bundle of plastic fibers.

We present an extension of fiber bundle models considering that failed fibers still carry a fraction 0 < or = alpha < or = 1 of their failure load. The value of alpha interpolates between the perfectly brittle failure (alpha = 0) and perfectly plastic behavior (alpha = 1) of fibers. We show that the finite load bearing capacity of broken fibers has a substantial effect on the failure process of the bundle. In the case of global load sharing it is found that for alpha --> 1 the macroscopic response of the bundle becomes perfectly plastic with a yield stress equal to the average fiber strength. On the microlevel, the size distribution of avalanches has a crossover from a power law of exponent approximately 2.5 to a faster exponential decay. For localized load sharing, computer simulations revealed a sharp transition at a well-defined value alpha(c) from a phase where macroscopic failure occurs due to localization as a consequence of local stress enhancements, to another one where the disordered fiber strength dominates the damage process. Analyzing the microstructure of damage, the transition proved to be analogous to percolation. At the critical point alpha(c), the spanning cluster of damage is found to be compact with a fractal boundary. The distribution of bursts of fiber breakings shows a power-law behavior with a universal exponent approximately 1.5 equal to the mean-field exponent of fiber bundles of critical strength distributions. The model can be relevant to understand the shear failure of glued interfaces where failed regions can still transmit load by remaining in contact.

Laser electron accelerators for radiation medicine: a feasibility study.

Table-top laser wakefield accelerators (LWFAs), proposed theoretically in 1979, have now generated individual electron bunches in the laboratory with a significant number of electrons having energies up to 10 MeV and beyond with the maximum energy reaching tens of MeV and charge per laser pulse of > 1 nC. The attained electron beam properties have stimulated a discussion about the possible applications of LWFAs to medical radiation treatment, either directly or via conversion to x-rays. Our purpose in this paper is to analyze whether or not such applications are feasible, or can be made feasible with existing laser technology. Clinical electron beam applications require the selection of specific electron energies in the range of 6-25 MeV with a narrow energy bin (deltaE <5 MeV) for depth control, and a beam expansion to as much as 25 cm x 25 cm for various tumor radiation treatments. As a result, we show that present LWFA sources provide a dose rate that falls short of the requirements for clinical application by at least an order of magnitude. We then use particle simulations to evaluate the feasibility of developing an improved LWFA-based medical accelerator. Current LWFA sources require such high peak intensity that laser repetition rate is restricted to < or = 10 Hz. A scheme to lower the threshold and increase the repetition rate of efficient LWFA thus appears essential. We analyze one such scheme. We show that by "seeding" the primary laser pulse with a second, hundred-fold less intense pulse that is shifted downward in frequency by approximately the plasma frequency omegap, LWFA produces a yield of clinically useful electrons per pulse comparable to that provided by an unseeded source, except that the primary pulse energy is now more than one order of magnitude lower than that in current LWFAs. This enables a repetition rate of approximately 100 Hz or more using existing laser technology, and thus dose rates (several Gy/min) in the range required for medical radiation applications.