Power-law Distribution Of Waiting Times Research Articles

Tempered fractional order compartment models and applications in biology

<p style='text-indent:20px;'>Compartment models with classical derivatives have diverse applications and attracted a lot of interest among scientists. To model the dynamical behavior of the particles that existed in the system for a long period of time with little chance to be removed, a power-law waiting time technique was introduced in the most recent work of Angstmann et al. [<xref ref-type="bibr" rid="b2">2</xref>]. The divergent first moment makes the power-law waiting time distribution less physical because of the finite lifespan of the particles. In this work, we take the tempered power-law function as the waiting time distribution, which has finite first moment while keeping the power-law properties. From the underlying physical stochastic process with the exponentially truncated power-law waiting time distribution, we build the tempered fractional compartment model. As an application, the tempered fractional SEIR epidemic model is proposed to simulate the real data of confirmed cases of pandemic AH1N1/09 influenza from Bogotá D.C. (Colombia). Some analysis and numerical simulations are carried out around the equilibrium behavior.</p>

Bayesian inference of Lévy walks via hidden Markov models

The Lévy walk (LW) is a non-Brownian random walk model that has been found to describe anomalous dynamic phenomena in diverse fields ranging from biology over quantum physics to ecology. Recurrently occurring problems are to examine whether observed data are successfully quantified by a model classified as LWs or not and extract the best model parameters in accordance with the data. Motivated by such needs, we propose a hidden Markov model for LWs and computationally realize and test the corresponding Bayesian inference method. We introduce a Markovian decomposition scheme to approximate a renewal process governed by a power-law waiting time distribution. Using this, we construct the likelihood function of LWs based on a hidden Markov model and the forward algorithm. With the LW trajectories simulated at various conditions, we perform the Bayesian inference for parameter estimation and model classification. We show that the power-law exponent of the flight-time distribution can be successfully extracted even at the condition that the mean-squared displacement does not display the expected scaling exponent due to the noise or insufficient trajectory length. It is also demonstrated that the Bayesian method performs remarkably inferring the LW trajectories from given unclassified trajectory data set if the noise level is moderate.

Comparison of negative skewed space fractional models with time nonlocal approaches for stream solute transport modeling

Continuous time random walks (CTRW), multi-rate mass transfer (MRMT), and fractional advection-dispersion equations (FADEs) are three promising models of anomalous transport as commonly found in natural streams. Although these paradigms are mathematically related, understanding their advantages and limitations poses a challenge for model selection. In this paper, we quantitatively evaluate the advection-dispersion equation (ADE), fractional-mobile-immobile (FMIM), fractional-in-space ADE (sFADE), fractional in space transient storage (FSTS), truncated time-fractional model (TTFM), and CTRW models with truncated power-law waiting time distribution (CTRW-TPL) by fitting them first to synthetic data. We then applied these models to observations from tracer experiments conducted in several rivers. Based on the extensive analysis, we conclude that the performance of the FSTS model (in particular, the model with negative skewness β=-1) is comparable or superior to the other nonlocal models evaluated in the paper; therefore, the model represents an alternative to existing models for simulating stream solute transport for spatially-homogeneous flows.

Augmented upwind numerical schemes for a fractional advection-dispersion equation in fractured groundwater systems

The anomalous transport of particles within non-linear systems cannot be captured accurately with the classical advection-dispersion equation, due to its inability to incorporate non-linearity of geological formations in the mathematical formulation. Fortunately, fractional differential operators have been recognised as appropriate mathematical tools to describe such natural phenomena. The classical advection-dispersion equation is adapted to a fractional model by replacing the time differential operator by a time fractional derivative to include the power-law waiting time distribution. The advection component is adapted by replacing the local differential by a fractional space derivative to account for mean-square displacement from normal to super-advection. Due to the complexity of this new model, new numerical schemes are suggested, including an upwind Crank-Nicholson and weighted upwind-downwind scheme. Both numerical schemes are used to solve the modified fractional advection-dispersion model and the conditions of their stability established.

Well-posedness and numerical algorithm for the tempered fractional differential equations

Trapped dynamics widely appears in nature, e.g., the motion of particles in viscous cytoplasm. The famous continuous time random walk (CTRW) model with power law waiting time distribution (having diverging first moment) describes this phenomenon. Because of the finite lifetime of biological particles, sometimes it is necessary to temper the power law measure such that the waiting time measure has convergent first moment. Then the time operator of the Fokker-Planck equation corresponding to the CTRW model with tempered waiting time measure is the so-called tempered fractional derivative. This paper focus on discussing the properties of the time tempered fractional derivative, and studying the well-posedness and the Jacobi-predictor-corrector algorithm for the tempered fractional ordinary differential equation. By adjusting the parameter of the proposed algorithm, high convergence order can be obtained and the computational cost linearly increases with time. The numerical results shows that our algorithm converges with order $ N_I $, where $ N_I $ is the number of used interpolating points.

Retraction

Trapped dynamics widely appears in nature, e.g., the motion of particles in viscous cytoplasm. The famous continuous time random walk (CTRW) model with power law waiting time distribution ({\em having diverging first moment}) describes this phenomenon. Because of the finite lifetime of biological particles, sometimes it is necessary to temper the power law measure such that the waiting time measure has convergent first moment. Then the time operator of the Fokker-Planck equation corresponding to the CTRW model with tempered waiting time measure is the so-called tempered fractional derivative. This paper focus on discussing the properties of the time tempered fractional derivative, and studying the well-posedness and the Jacobi-predictor-corrector algorithm for the tempered fractional ordinary differential equation. By adjusting the parameter of the proposed algorithm, any desired convergence order can be obtained and the computational cost linearly increases with time. And the effectiveness of the algorithm is numerically confirmed.

Biased continuous-time random walks for ordinary and equilibrium cases: facilitation of diffusion, ergodicity breaking and ageing.

We examine renewal processes with power-law waiting time distributions (WTDs) and non-zero drift via computing analytically and by computer simulations their ensemble and time averaged spreading characteristics. All possible values of the scaling exponent α are considered for the WTD ψ(t) ∼ 1/t1+α. We treat continuous-time random walks (CTRWs) with 0 < α < 1 for which the mean waiting time diverges, and investigate the behaviour of the process for both ordinary and equilibrium CTRWs for 1 < α < 2 and α > 2. We demonstrate that in the presence of a drift CTRWs with α < 1 are ageing and non-ergodic in the sense of the non-equivalence of their ensemble and time averaged displacement characteristics in the limit of lag times much shorter than the trajectory length. In the sense of the equivalence of ensemble and time averages, CTRW processes with 1 < α < 2 are ergodic for the equilibrium and non-ergodic for the ordinary situation. Lastly, CTRW renewal processes with α > 2-both for the equilibrium and ordinary situation-are always ergodic. For the situations 1 < α < 2 and α > 2 the variance of the diffusion process, however, depends on the initial ensemble. For biased CTRWs with α > 1 we also investigate the behaviour of the ergodicity breaking parameter. In addition, we demonstrate that for biased CTRWs the Einstein relation is valid on the level of the ensemble and time averaged displacements, in the entire range of the WTD exponent α.

Direct and inverse problems in dispersive time-of-flight photocurrent revisited

Using the fact that the continuous time random walk (CTRW) scheme is a random process subordinated to a simple random walk under the operational time given by the number of steps taken by the walker up to a given time, we revisit the problem of strongly dispersive transport in disordered media, which first lead Scher and Montroll to introducing the power law waiting time distributions. Using a subordination approach permits to disentangle the complexity of the problem, separating the solution of the boundary value problem (which is solved on the level of normal diffusive transport) from the influence of the waiting times, which allows for the solution of the direct problem in the whole time domain (including short times, out of reach of the initial approach), and simplifying strongly the analysis of the inverse problem. This analysis shows that the current traces do not contain information sufficient for unique restoration of the waiting time probability densities, but define a single-parametric family of functions that can be restored, all leading to the same photocurrent forms. The members of the family have the power-law tails which differ only by a prefactor, but may look astonishingly different at their body. The same applies to the multiple trapping model, mathematically equivalent to a special limiting case of CTRW.

A model of return intervals between earthquake events

Application of the diffusion entropy analysis and the standard deviation analysis to the time sequence of the southern California earthquake events from 1976 to 2002 uncovered scaling behavior typical for anomalous diffusion. However, the origin of such behavior is still under debate. Some studies attribute the scaling behavior to the correlations in the return intervals, or waiting times, between aftershocks or mainshocks. To elucidate a nature of the scaling, we applied specific reshulffling techniques to eliminate correlations between different types of events and then examined how it affects the scaling behavior. We demonstrate that the origin of the scaling behavior observed is the interplay between mainshock waiting time distribution and the structure of clusters of aftershocks, but not correlations in waiting times between the mainshocks and aftershocks themselves. Our findings are corroborated by numerical simulations of a simple model showing a very similar behavior. The mainshocks are modeled by a renewal process with a power-law waiting time distribution between events, and aftershocks follow a nonhomogeneous Poisson process with the rate governed by Omori's law.

Effects of the Tempered Aging and the Corresponding Fokker–Planck Equation

In the renewal processes, if the waiting time probability density function is a tempered power-law distribution, then the process displays a transition dynamics; and the transition time depends on the parameter $\lambda$ of the exponential cutoff. In this paper, we discuss the aging effects of the renewal process with the tempered power-law waiting time distribution. By using the aging renewal theory, the $p$-th moment of the number of renewal events $n_a(t_a, t)$ in the interval $(t_a, t_a+t)$ is obtained for both the weakly and strongly aged systems; and the corresponding surviving probabilities are also investigated. We then further analyze the tempered aging continuous time random walk and its Einstein relation, and the mean square displacement is attained. Moreover, the tempered aging diffusion equation is derived.

A Mathematical Model for the Proliferation, Accumulation and Spread of Pathogenic Proteins Along Neuronal Pathways with Locally Anomalous Trapping

There is growing evidence that many neurodegenerative disease processes involve the proliferation, accumulation and spread of pathogenic proteins. The transport of proteins in the brain is typically hindered on small scales by micro-domain traps and binding sites but it may be enhanced on larger scales by neuronal pathways identified as white matter transport networks. We have introduced a mathematical network model to simulate a pathogenic protein neurodegenerative disease in the brain taking into account the anomalous transport. The proliferation and accumulation of pathogenic proteins is modelled using a set of reaction kinetics equations on the nodes of a network. Transport of the proteins on the network is modelled as a continuous time random walk with power law distributed waiting times on the nodes. This power law waiting time distribution is shown to be consistent with anomalously slowed diffusion on local scales but transport is enhanced on larger scales by the jumps between nodes. The model reveals that the disease spreads as a propagating front throughout the brain. The anomalous behaviour leads to a lessor variation in the concentration of pathogenic proteins. The enhanced transport on the network ensures that the approach to equilibrium is dominated by the short time behaviour of the waiting time density, hence the effects of subdiffusion are not as pronounced as in a spatial continuum.

Aging phenomena, probability distribution functions and numerical implementations for Lévy walks

Lévy walks are non-Markovian stochastic processes, whose explosion of space with time is faster than regular Brownian motion but slower than ballistic motion. More concretely, they correspond to a random walk process with jump distribution , where is a power law waiting-time distribution. In this paper, we first investigate the probability distribution functions of Lévy walks, then discuss their aging phenomena, forward waiting-time probability distribution and numerical implementations.

Anomalous diffusion of volcanic earthquakes

Volcanic seismicity at Mt. Etna is studied. It is found that the associated stochastic process exhibits a subdiffusive phenomenon. The jump probability distribution well obeys an exponential law, whereas the waiting-time distribution follows a power law in a wide range. Although these results would seem to suggest that the phenomenon could be described by a temporally fractional kinetic theory based on the viewpoint of continuous-time random walks, the exponent of the power-law waiting-time distribution actually lies outside of the range allowed in the theory. In addition, there exists the aging phenomenon in the event-time averaged mean squared displacement, in contrast to the picture of the fractional Brownian motion. Comments are also made on possible relevances of random walks on fractals as well as nonlinear kinetics. Thus, problems of volcanic seismicity are highly challenging for science of complex systems.

Nonergodicity, fluctuations, and criticality in heterogeneous diffusion processes.

We study the stochastic behavior of heterogeneous diffusion processes with the power-law dependence D(x) ∼ |x|(α) of the generalized diffusion coefficient encompassing sub- and superdiffusive anomalous diffusion. Based on statistical measures such as the amplitude scatter of the time-averaged mean-squared displacement of individual realizations, the ergodicity breaking and non-Gaussianity parameters, as well as the probability density function P(x,t), we analyze the weakly nonergodic character of the heterogeneous diffusion process and, particularly, the degree of irreproducibility of individual realizations. As we show, the fluctuations between individual realizations increase with growing modulus |α| of the scaling exponent. The fluctuations appear to diverge when the critical value α = 2 is approached, while for even larger α the fluctuations decrease, again. At criticality, the power-law behavior of the mean-squared displacement changes to an exponentially fast growth, and the fluctuations of the time-averaged mean-squared displacement do not converge for increasing number of realizations. From a systematic comparison we observe some striking similarities of the heterogeneous diffusion process with the familiar subdiffusive continuous time random walk process with power-law waiting time distribution and diverging characteristic waiting time.

Properties and Moving Time Average for Lévy Walks with Power-Law Waiting-Time Distributions

Lévy walks are a natural model for the description of sub-ballistic, superdiffusive motion. The waiting times and jump lengths of Lévy walks are coupled in the form . The-coupling introduces a time cost for each jump in the form of the generalized velocity , such that long jumps get penalized by a higher time cost. In this paper, we firstly investigate the properties of Lévy walks with power-law waiting-time distributions; then discuss its moving time average.

Linear response, fluctuation-dissipation, and finite-system-size effects in superdiffusion

Lévy walks (LWs) are a popular stochastic tool to model anomalous diffusion and have recently been used to describe a variety of phenomena. We study the linear response behavior of this generic model of superdiffusive LWs in finite systems to an external force field under both stationary and nonstationary conditions. These finite-size LWs are based on power-law waiting time distributions with a finite-time regularization at τ(c), such that the physical requirements are met to apply linear response theory and derive the power spectrum with the correct short frequency limit, without the introduction of artificial cutoffs. We obtain the generalized Einstein relation for both ensemble and time averages over the entire process time and determine the turnover to normal Brownian motion when the full system is explored. In particular, we obtain an exact expression for the long time diffusion constant as a function of the scaling exponent of the waiting time density and the characteristic time scale τ(c).

Spreading dynamics following bursty human activity patterns

We study the susceptible-infected model with power-law waiting time distributions P(τ)~τ^{-α}, as a model of spreading dynamics under heterogeneous human activity patterns. We found that the average number of new infections n(t) at time t decays as a power law in the long-time limit, n(t)~t^{-β}, leading to extremely slow prevalence decay. We also found that the exponent in the spreading dynamics β is related to that in the waiting time distribution α in a way depending on the interactions between agents but insensitive to the network topology. These observations are well supported by both the theoretical predictions and the long prevalence decay time in real social spreading phenomena. Our results unify individual activity patterns with macroscopic collective dynamics at the network level.

Non-Markovian Model for Transport and Reactions of Particles in Spiny Dendrites

Motivated by the experiments [Santamaria, Neuron 52, 635 (2006)10.1016/j.neuron.2006.10.025] that indicated the possibility of subdiffusive transport of molecules along dendrites of cerebellar Purkinje cells, we develop a mesoscopic model for transport and chemical reactions of particles in spiny dendrites. The communication between spines and a parent dendrite is described by a non-Markovian random process and, as a result, the overall movement of particles can be subdiffusive. A system of integrodifferential equations is derived for the particles densities in dendrites and spines. This system involves the spine-dendrite interaction term which describes the memory effects and nonlocality in space. We consider the impact of power-law waiting time distributions on the transport of biochemical signals and mechanism of the accumulation of plasticity-inducing signals inside spines.

Continuous-time random walks in an oscillating field: Field-induced dispersion and the death of linear response

Abstract We discuss the response of continuous-time random walks to an oscillating external field within the generalized master equation approach. We concentrate on the time dependence of the first two moments of the walker’s displacement and show that for power-law waiting-time distributions with 0 α 1 (corresponding to a semi-Markovian situation displaying aging) the mean particle position tends to a constant, while the response to the external perturbation dies out. The oscillating field is shown to lead to an additional new contribution to the dispersion of the particle’s position which is proportional to the square of its amplitude and grows with time.

Field-Induced Dispersion in Subdiffusion

We discuss the response of continuous-time random walks to an oscillating external field within the generalized master equation approach. We concentrate on the time dependence of the two first moments of the walker's displacement. We show that for power-law waiting-time distributions with 0<alpha<1 corresponding to a semi-Markovian situation showing nonstationarity, the mean particle position tends to a constant; namely, the response to the external perturbation dies out. On the other hand, the oscillating field leads to a new additional contribution to the dispersion of the particle position, proportional to the square of its amplitude and growing with time. These new effects, amenable to experimental observation, result directly from the nonstationary property of the system.