The subordinated processes controlled by a family of subordinators and corresponding Fokker-Planck type equations

In this work, we consider subordinated processes controlled by a family of subordinators which consist of a power function of a time variable and a negative power function of an α-stable random variable. The effect of parameters in the subordinators on the subordinated process is discussed. By suitable variable substitutions and the Laplace transform technique, the corresponding fractional Fokker–Planck-type equations are derived. We also compute their mean square displacements in a free force field. By choosing suitable ranges of parameters, the resulting subordinated processes may be subdiffusive, normal diffusive or superdiffusive

Memory of past random wave conditions in submarine groundwater discharge

Submarine groundwater discharge (SGD) is an integral part of the hydrological cycle and represents an important aspect of land-ocean interactions. We used a numerical model to simulate flow and salt transport in a nearshore groundwater aquifer under varying wave conditions based on yearlong random wave data sets, including storm surge events. The results showed significant flow asymmetry with rapid response of influxes and retarded response of effluxes across the seabed to the irregular wave conditions. While a storm surge immediately intensified seawater influx to the aquifer, the subsequent return of intruded seawater to the sea, as part of an increased SGD, was gradual. Using functional data analysis, we revealed and quantified retarded, cumulative effects of past wave conditions on SGD including the fresh groundwater and recirculating seawater discharge components. The retardation was characterized well by a gamma distribution function regardless of wave conditions. The relationships between discharge rates and wave parameters were quantifiable by a regression model in a functional form independent of the actual irregular wave conditions. This statistical model provides a useful method for analyzing and predicting SGD from nearshore unconfined aquifers affected by random waves

Calculating the Fickian diffusivity for a lattice-based random walk with agents and obstacles of different shapes and sizes

Random walk models are often used to interpret experimental observations of the motion of biological cells and molecules. A key aim in applying a random walk model to mimic an in vitro experiment is to estimate the Fickian diffusivity (or Fickian diffusion coefficient),D. However, many in vivo experiments are complicated by the fact that the motion of cells and molecules is hindered by the presence of obstacles. Crowded transport processes have been modeled using repeated stochastic simulations in which a motile agent undergoes a random walk on a lattice that is populated by immobile obstacles. Early studies considered the most straightforward case in which the motile agent and the obstacles are the same size. More recent studies considered stochastic random walk simulations describing the motion of an agent through an environment populated by obstacles of different shapes and sizes. Here, we build on previous simulation studies by analyzing a general class of lattice-based random walk models with agents and obstacles of various shapes and sizes. Our analysis provides exact calculations of the Fickian diffusivity, allowing us to draw conclusions about the role of the size, shape and density of the obstacles, as well as examining the role of the size and shape of the motile agent. Since our analysis is exact, we calculateDdirectly without the need for random walk simulations. In summary, we find that the shape, size and density of obstacles has a major influence on the exact Fickian diffusivity. Furthermore, our results indicate that the difference in diffusivity for symmetric and asymmetric obstacles is significant.

Structural origin of set-reset processes in Ge15Te83Si2 glass investigated using in situ Raman scattering and transmission electron microscopy

We report here that the structural origin of an easily reversible Ge15Te83Si2 glass can be a promising candidate for phase change random access memories. In situ Raman scattering studies on Ge15Te83Si2 sample, undertaken during the amorphous set and reset processes, indicate that the degree of disorder in the glass is reduced from off to set state. It is also found that the local structure of the sample under reset condition is similar to that in the amorphous off state. Electron microscopic studies on switched samples indicate the formation of nanometric sized particles of c-SiTe2 structure. ©2009 American Institute of Physics

On Random Planar Curves and Their Scaling Limits

Planar curves arise naturally as interfaces between two regions of the plane. An important part of statistical physics is the study of lattice models. This thesis is about the interfaces of 2D lattice models. The scaling limit is an infinite system limit which is taken by letting the lattice mesh decrease to zero. At criticality, the scaling limit of an interface is one of the SLE curves (Schramm-Loewner evolution), introduced by Oded Schramm. This family of random curves is parametrized by a real variable, which determines the universality class of the model. The first and the second paper of this thesis study properties of SLEs. They contain two different methods to study the whole SLE curve, which is, in fact, the most interesting object from the statistical physics point of view. These methods are applied to study two symmetries of SLE: reversibility and duality. The first paper uses an algebraic method and a representation of the Virasoro algebra to find common martingales to different processes, and that way, to confirm the symmetries for polynomial expected values of natural SLE data. In the second paper, a recursion is obtained for the same kind of expected values. The recursion is based on stationarity of the law of the whole SLE curve under a SLE induced flow. The third paper deals with one of the most central questions of the field and provides a framework of estimates for describing 2D scaling limits by SLE curves. In particular, it is shown that a weak estimate on the probability of an annulus crossing implies that a random curve arising from a statistical physics model will have scaling limits and those will be well-described by Loewner evolutions with random driving forces.

Stationary processes for object detection and non-rigid structure-from-motion

Stationary processes are random variables whose value is a signal and whose distribution is invariant to translation in the domain of the signal. They are intimately connected to convolution, and therefore to the Fourier transform, since the covariance matrix of a stationary process is a Toeplitz matrix, and Toeplitz matrices are the expression of convolution as a linear operator. This thesis utilises this connection in the study of i) efficient training algorithms for object detection and ii) trajectory-based non-rigid structure-from-motion.

First passage probability during random vibration

The probability that a random process crosses an arbitrary level for the first time is expressed as a Gram—Charlier series, the leading term of which is the Poisson approximation. The coefficients of this series are related to the moments of the number of level crossings. The results are applicable to both stationary and non-stationary processes. Some numerical results are presented for the response process of a linear single-degree-of-freedom oscillator under Gaussian white noise excitation.

Probability Distribution of the Eigenvalues of the Random String Equation

The probability distribution of the eigenvalues of a second-order stochastic boundary value problem is considered. The solution is characterized in terms of the zeros of an associated initial value problem. It is further shown that the probability distribution is related to the solution of a first-order nonlinear stochastic differential equation. Solutions of this equation based on the theory of Markov processes and also on the closure approximation are presented. A string with stochastic mass distribution is considered as an example for numerical work. The theoretical probability distribution functions are compared with digital simulation results. The comparison is found to be reasonably good.

Search on a hypercubic lattice using a quantum random walk. I. d > 2

Random walks describe diffusion processes, where movement at every time step is restricted to only the neighboring locations. We construct a quantum random walk algorithm, based on discretization of the Dirac evolution operator inspired by staggered lattice fermions. We use it to investigate the spatial search problem, that is, to find a marked vertex on a d-dimensional hypercubic lattice. The restriction on movement hardly matters for d > 2, and scaling behavior close to Grover's optimal algorithm (which has no restriction on movement) can be achieved. Using numerical simulations, we optimize the proportionality constants of the scaling behavior, and demonstrate the approach to that for Grover's algorithm (equivalent to the mean-field theory or the d -> infinity limit). In particular, the scaling behavior for d = 3 is only about 25% higher than the optimal d -> infinity value.

Processing and fiber content effects on the machinability of compression moulded random direction short GFRP composites

The random direction short Glass Fiber Reinforced Plastics (GFRP) have been prepared by two compression moulding processes, namely the Preform and Sheet Moulding Compound (SMC) processes. Cutting force analysis and surface characterization are conducted on the random direction short GFRPs with varying fiber contents (25 similar to 40%). Edge trimming experiments are preformed using carbide inserts with varing the depth of cut and cutting speed. Machining characteristics of the Preform and SMC processed random direction short GFRPs are evaluated in terms of cutting forces, surface quality, and tool wear. It is found that composite primary processing and fiber contents are major contributing factors influencing the cutting force magnitudes and surface textures. The SMC composites show better surface finish over the Preform composites due to less delamination and fiber pullouts. Moreover, matrix damage and fiber protrusions at the machined edge are reduced by increasing fiber content in the random direction short GFRP composites.

Supercritical age-dependent branching Markov processes and their scaling limits

This paper studies the long-time behavior of the empirical distribution of age and normalized position of an age-dependent supercritical branching Markov process. The motion of each individual during its life is a random function of its age. It is shown that the empirical distribution of the age and the normalized position of all individuals alive at time t converges as t -> infinity to a deterministic product measure.

Low electric field, easily reversible electrical set and reset processes in a Ge15Te83Si2 glass for phase change memory applications

We report here an easily reversible set-reset process in a new Ge15Te83Si2 glass that could be a promising candidate for phase change random access memory applications. The I-V characteristics of the studied sample show a comparatively low threshold electric field (E-th) of 7.3 kV/cm. Distinct differences in the type of switching behavior are achieved by means of controlling the on state current. It enables the observation of a threshold type for less than 0.7 mA beyond memory type (set) switching. The set and reset processes have been achieved with a similar magnitude of 1 mA, and with a triangular current pulse for the set process and a short duration rectangular pulse of 10 msec width for the reset operation. Further, a self-resetting effect is seen in this material upon excitation with a saw-tooth/square pulse, and their response of leading and trailing edges are discussed. About 6.5 x 10(4) set-reset cycles have been undertaken without any damage to the device. (C) 2011 American Institute of Physics. doi: 10.1063/1.3574659]

Thermal degradation processes in polysulfide copolymers investigated by direct pyrolysis mass spectrometry and flash pyrolysis-gas chromatography/mass spectrometry

This is the first report on the analysis of random block polysulfide copolymers containing different amounts of repeating units in the copolymer backbone, which has been studied by direct pyrolysis mass spectrometry (DPMS) and by pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS). The homopolymers such as poly(ethylene sulfide) (PES), poly(styrene sulfide) (PSS), and two random copolymers, viz., poly(ethylene sulfide(x)-co-styrene sulfide(y)) [copolymer I (x = y = 0.5) and copolymer II (x = 0.74, y = 0.26)] were investigated by both DPMS and Py-GC/MS (except copolymer II) techniques. In the case of copolymer I, the thermal degradation products of SE1, SE2, S-2, and S2E (S = styrene sulfide, E = ethylene sulfide) were detected in DPMS, whereas the formation of SE1 and SE2 were observed by Py-GC/MS technique. However, for copolymer II, SE3 was also found along with SE1, SE2, S-2, and S2E in DPMS. The formation of additional product (SE3) observed in copolymer II could be due to an increase in the block length formed during copolymerization. Further, a comparative study on thermal degradation of PES, poly(ethylene disulfide) (PEDS), and poly(ethylene tetrasulfide) (PETS) were investigated by Py-GC/MS. The pyrolysis products detected by both DPMS and Py-GC/MS indicates that the thermal decomposition of these polymers yield cyclic sulfides through an intramolecular exchange or by backbiting processes. The linear products with thiol and vinyl groups were also observed by Py-GC/MS along with the cyclic products via carbon hydrogen transfer reaction.

Percolation and Connectivity in AB Random Geometric Graphs

Given two independent Poisson point processes ©(1);©(2) in Rd, the AB Poisson Boolean model is the graph with points of ©(1) as vertices and with edges between any pair of points for which the intersection of balls of radius 2r centred at these points contains at least one point of ©(2). This is a generalization of the AB percolation model on discrete lattices. We show the existence of percolation for all d ¸ 2 and derive bounds for a critical intensity. We also provide a characterization for this critical intensity when d = 2. To study the connectivity problem, we consider independent Poisson point processes of intensities n and cn in the unit cube. The AB random geometric graph is de¯ned as above but with balls of radius r. We derive a weak law result for the largest nearest neighbour distance and almost sure asymptotic bounds for the connectivity threshold.

Percolation and connectivity in AB random geometric graphs

Given two independent Poisson point processes Phi((1)), Phi((2)) in R-d, the AB Poisson Boolean model is the graph with the points of Phi((1)) as vertices and with edges between any pair of points for which the intersection of balls of radius 2r centered at these points contains at least one point of Phi((2)). This is a generalization of the AB percolation model on discrete lattices. We show the existence of percolation for all d >= 2 and derive bounds fora critical intensity. We also provide a characterization for this critical intensity when d = 2. To study the connectivity problem, we consider independent Poisson point processes of intensities n and tau n in the unit cube. The AB random geometric graph is defined as above but with balls of radius r. We derive a weak law result for the largest nearest-neighbor distance and almost-sure asymptotic bounds for the connectivity threshold.