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A method of space ensemble (SE) and time ensemble (TEs) correlation function technique applied on ground penetration radar (GPR) B-scan raw data proves to result in detailed information for tracking buried objects. These computations help in site allocations by time ensemble correlation functions (TESCs) and time stamps of objects scattering by space ensemble correlation functions (SECFs) which are precisely consistent with the simulation results. While these results are applied for given data stack, randomness in physical parameters of tested ground always occurs. An introduction of randomness to the physical parameters of tested models by creating stochastic collocation (SC) ensembles incorporating randomness to B-scan via successive A-scans, SC-SE, and SC-TE ensembles enables sensitivity analysis (SA) study of GPR raw data which gives a tool to change the physical properties of the ground in search for better ground matching. This method can be added to GPR machines or simulation software to enhance raw data analysis. A field experiment of small non-metallic objects' allocation was carried out as a platform for assessing the realistic performance of the method.

Two techniques are presented for characterisation of cloud-feeding coherent boundary-layer structures through analysis of large-eddy simulations of shallow cumulus clouds, contrasting conditions with and without ambient shear. The first technique is a generalisation of the two-point correlation function, where the correlation length-scale as well as the orientation can be extracted. The second technique identifies individual coherent structures and decomposes their vertical transport by the shape, size, and orientation of these objects. The bulk-correlation technique is shown to capture the elongation and orientation of coherence by ambient wind, but is unable to characterise individual coherent structures. Using the object-based approach, it is found that the individual structures dominating the vertical flux are plume-like in character (extending from the surface into cloud) rather than thermal-like, show small width/thickness asymmetry, and rise near-vertically in the absence of ambient wind. The planar stretching and tilting of boundary-layer structures caused by the introduction of ambient shear is also quantified, demonstrating the general applicability of the techniques for future study of other boundary-layer patterns.

In this paper, a novel space-time non-stationary three-dimensional (3D) wideband massive multiple-input multiple-output (MIMO) channel model is proposed. We then propose a ray-level process to model the spatial-temporal evolution of individual multipath components (MPCs), including near-field effects and (dis)appearance, and cluster-level large-scale fading. The proposed evolution process can flexibly control rays’ lifespans and smoothness of (dis)appearance in both space and time domains. In addition, we propose an improved Rayleigh-distance criterion to determine the most adequate wavefront for each cluster and ray. Existing models can easily implement the proposed criterion and make a more efficient use of computation resources. Also, a Gamma-Poisson mixture distribution is introduced to model the distribution of the number of clusters when multiple locations of the mobile station are considered. Key statistical properties of the channel, including the autocorrelation function (ACF), Doppler power spectral density (PSD), spatial cross-correlation function (S-CCF), and frequency correlation function (FCF), are derived and the impact of the ray-level evolution process on them is analyzed. We demonstrate the correctness of the derived statistical properties through numerical and simulation results.

This article presents a numerical study of the wave scattering from a modulated rough surface characterized by a modulated correlation function that shows zero crossings along the lag distance. The zero crossings imply the presence of multiscale roughness. In such a way, we treat the rough surface to include a baseband correlation length and a modulation length. The modulation ratio, the ratio of baseband correlation length, and the modulated length determine the degree of multiscale roughness. We then examine the dependence of bistatic scattering, both in level and angular trends, on the modulation length. The results indicate that as the modulation ratio increases, the scattering coefficients reduce in the incident plane. Comparing the model predictions with two independent sets of measurement data demonstrates a good agreement of the scattering coefficients between the experimental data and the model predictions with modulation effects. The proposed modulated rough surface concept offers higher flexibility to model the radar scattering of multiscale rough surface.

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Monthly Notices of the Royal Astronomical Society following peer review. The version of record Monthly Notices of the Royal Astronomical Society 510.1 (2022): 292-308 is available online at: https://academic.oup.com/mnras/article-abstract/510/1/292/6442269?redirectedFrom=fulltext#no-access-message, We study the clustering of H i intensity maps (IM) produced from simulations with a focus on baryonic acoustic oscillations (BAOs) and the effects induced by telescope beam smoothing and foreground cleaning. We start by creating an H i catalogue at z = 1.321 based on the Semi-Analytic Galaxy Evolution (SAGE) model applied to the UNIT simulations. With this catalogue, we investigate the relation between model H i and the dark matter haloes and we also study the abundance of H i, Omega rm{H small {rm I}}, predicted by this model. We then create synthetic H i IM with a nearest-grid-point approach. In order to simulate the telescope beam effect, a Gaussian smoothing is applied on the plane perpendicular to the line of sight. The effect of foreground removal methods is simulated by exponentially damping the largest wavelength Fourier modes on the radial direction. We study the anisotropic 2-point correlation function (2PCF) ζ(rpdbl, rpdbl) and how it is affected by the aforementioned observational effects. In order to better isolate the BAO signal, we study several 2PCF μ-wedges (with a restricted range of orientations μ) tailored to address the systematics effects and we compare them with different definitions of radial 2PCFs. Finally, we discuss our findings in the context of an SKA-like survey, finding a clear BAO signal in most of the estimators here proposed

The packing length p figures prominently in scaling predictions of the entanglement length and bulk modulus for polymer melts and solutions. p has been argued to scale as the ratio of chain displaced volume V and mean square end-to-end distance R2. This scaling works for several cases; however, it is not obvious how to apply it to chains with side groups, and the scaling must fail for sufficiently thin, stiff chains. In this work, we measure the packing length in simulations, without making any scaling assumptions, as the typical distance of closest approach of two polymer strands in a simulated bead-spring melt. We use the intermolecular correlation function to measure the distance up to which a given polymer strand dominates the local volume fraction. Using our measured packing length, we find good agreement of entanglement properties with Lin–Noolandi scaling for flexible polymers of different architectures.

The problem of modeling signals of various spatial coherence in radio engineering systems is considered. First, a mathematical model for spatially coherent signals in the form of stochastic differential equations is constructed, followed by its study in the Simulink environment. The following is a method for constructing a mathematical model for a more general case – partially coherent signals, and its accuracy is also evaluated. Based on the developed models, an algorithm for estimating the parameters of partially coherent signals is synthesized. Based on the obtained dependence of the sensitivity of the model to deviation from a priori data, conclusions are drawn about a sufficiently high accuracy of estimation using synthesized algorithms.

Electromagnetic scattering model from 3-D snowpack with arbitrary thickness is considered. A fully coherent model is presented through the usage of the Statistical S-Matrix Wave Propagation in Spectral Domain approach (SSWaP-SD). The computer-generated snow media is constructed using 3-D spatial exponential correlation function along with Lineal-Path function to preserve the connectivity of the snow particles as well. The SSWaP-SD in conjunction with a Method of Moments (MoM) code based on the discrete-dipole approximation (DDA) is chosen to leverage both the time-efficient computations of the DDA and the full-coherency of the SSWaP-SD method simultaneously. The SSWaP-SD depends on the discretization of the medium into thin slabs. Several realizations of a thin snow slab are solved numerically to form the statistics of the scattering matrix representing such a thin snow layer. For an arbitrarily thick snow layer, thin slabs of a snowpack are analyzed and a corresponding polarimetric N-port (representing different directions of scattering) S-matrix is generated. These S-matrices are cascaded using SSWaP-SD method to calculate the total forward and backward bistatic scattered fields in a fully coherent way. The simulation results of the backscattering from an arbitrary thick snow layer are presented and validated with measurements.

It is shown that modelling the first oxygen-oxygen peak in the neutron correlation function of a glass enables structural information about other correlations to be obtained, and the method is illustrated by application to a sodium silicate glass. The first O-O coordination number can be calculated from network theory, and sodium silicate crystal structures show that the mean O-O distance can be calculated from the Si-O distance, despite the distortion of the SiO4 tetrahedra. Modelling the O-O peak for a sodium silicate glass allows the Na-O bond length distribution to be determined. For a binary glass with 42.5 mol% Na2O, it is found that the Na-O coordination number is 4.8(2) with an average bond length of 2.45 Å, and the Na-O bond lengths are more widely distributed than in sodium silicate crystal structures. Sodium ions are bonded mostly to non-bridging oxygens (NBOs), and the Na-NBO coordination number may be four as in crystals. Sodium ions are also bonded to a smaller number of bridging oxygens (BOs). Contrary to previous reports, it is not concluded that Na-NBO bonds are shorter than Na-BO bonds, but instead that the Na-BO distribution is relatively narrow, whilst the Na-NBO distribution extends to both shorter and longer distance. The broad distribution of Na-O bond lengths arises from a relatively broad distribution of Na-NBO bond valences, subject to the overall requirement of charge balance.

We present a comparative study of the accuracy and precision of correlation function methods and full-field inference in cosmological data analysis. To do so, we examine a Bayesian hierarchical model that predicts log-normal fields and their two-point correlation function. Although a simplified analytic model, the log-normal model produces fields that share many of the essential characteristics of the present-day non-Gaussian cosmological density fields. We use three different statistical techniques: (i) a standard likelihood-based analysis of the two-point correlation function; (ii) a likelihood-free (simulation-based) analysis of the two-point correlation function; (iii) a field-level analysis, made possible by the more sophisticated data assimilation technique. We find that (a) standard assumptions made to write down a likelihood for correlation functions can cause significant biases, a problem that is alleviated with simulation-based inference; and (b) analysing the entire field offers considerable advantages over correlation functions, through higher accuracy, higher precision, or both. The gains depend on the degree of non-Gaussianity, but in all cases, including for weak non-Gaussianity, the advantage of analysing the full field is substantial., Comment: 6+8 pages, 4+5 figures. Matches MNRAS Letters published version. Appendices provide supplementary information, including calculations of Fisher matrices. Our code and data are publicly available at https://github.com/florent-leclercq/correlations_vs_field

Based on the basic-element expression method and correlation function theory in Extenics, combined with the knowledge of slope engineering, a method for evaluating the stability of complex slope is proposed. The evaluation process includes the selection of suitable evaluation indexes of slope stability, identificationof the classification standard for the slope stability, identificationof the weights of evaluation indexes by using the improved analytic hierarchy process,identificationof the classical domain, node domain and matter-element under evaluation,the calculation of the correlation of each stability class for each evaluation index, normalization of correlation,and so on. The selection rule of the slop stability evaluation indexes and selection of correlation function and optimal points are also discussed, which can provide reference for slope engineering designin construction industry.

Seismic demand and performance of bridges are highly dependent upon the level of irregularity. Although previous studies have proposed methodologies so as to quantify the irregularity of the bridges in terms of global regularity index, it still remains unclear how to determine the distribution of irregularity along a bridge, as well as to discover the irregularity sources. This research project is intended to develop a quantitative vector regularity criterion for single- and multiframe bridges based on the modified correlation function for spatial locations of scaled mode shapes of deck-alone and whole bridge. The proposed criterion calculates two types of regularity indices, namely, local (LRI) and global regularity indices (GRI). The GRI is a scalar value representing the overall regularity of the entire bridge, whereas the LRI highlights vector irregularity distribution along the bridge. Since the deck discontinuity due to the in-span hinges is one of the leading causes for irregularity, the proposed index has been employed in case of multiframe bridges as well. Furthermore, the current study aims to investigate the correlation between the proposed irregularity indicators and the nonlinear to linear demand ratio. Therefore, the appropriate analysis method can be chosen based on irregularity extent of bridges. Obtained results of the proposed indices reveal that in-span hinge is one of the main parameters affecting the distribution of local irregularity along a bridge. Therefore, multiframe bridges need to be investigated in detail so as to validate the special design requirements recommended by design codes.

This work presents an efficient methodology for the optimum design of functionally graded structures using a Kriging-based approach. The method combines an adaptive Kriging framework with a hybrid particle swarm optimization (PSO) algorithm to improve the computational efficiency of the optimization process. In this approach, the surrogate model is used to replace the high-fidelity structural responses obtained by a NURBS-based isogeometric analysis. In addition, the impact of key factors on surrogate modelling, as the correlation function, the infill criterion used to update the surrogate model, and the constraint handling is assessed for accuracy, efficiency, and robustness. The design variables are related to the volume fraction distribution and the thickness. Displacement, fundamental frequency, buckling load, mass, and ceramic volume fraction are used as objective functions or constraints. The effectiveness and accuracy of the proposed algorithm are illustrated through a set of numerical examples. Results show a significant reduction in the computational effort over the conventional approach.

In this work, we investigate thermodynamic properties of the one-dimensional (1D) spin-crossover molecular chain being a subject of a constant external pressure. Effective compressible degenerate Ising model is used as a theoretical framework. Using transfer matrix formalism analytic results for the low spin -- high spin crossover were obtained. We derive the exact expressions for the fraction of molecules in the high spin state, correlation function and heat capacity. We provide analysis of parameters region where the spin crossover takes place and demonstrate how pressure changes location of the crossover., 9 pages, 5 figures, submitted to Low Temperature Physics

Consider a particle whose drift velocity fluctuates due to transitions among discrete states or due to diffusion in a confined moving fluid. At long times, the dynamics of the particle in the direction of transport can be described in terms of the average drift velocity and an effective diffusivity. For both types of fluctuations, we show that the effective diffusivity is the sum of the average intrinsic diffusivity and the time integral of the velocity correlation function of the deviation of the fluctuating velocity from its mean value. For nearest-neighbor interstate transitions and for one-dimensional diffusion in a perpendicular direction, the time integral can be found in closed form. Our analytical expressions for the effective diffusivity recover the classic results for Taylor dispersion in the laminar flow of viscous fluid and for cargo transport along microtubules by molecular motors.

This work develops a second-order approximation (SOA) model and a three-dimensional (3D) finite element (FE) model to calculate scattering-induced attenuation for elastic wave propagation in polycrystals with elongated grains of arbitrary crystal symmetry. The SOA model accounts for some degree of multiple scattering, whereas the 3D FE model includes all scattering possibilities. The SOA model incorporates the accurate geometric two-point correlation function obtained from the FE material systems to enable comparative studies between the two models. Also, the analytical Rayleigh and stochastic asymptotes are presented to provide explicit insights into propagation behaviors. Quantitative agreement is found between the FE and analytical models for all evaluated cases. In particular, the FE simulations support the SOA model prediction that grain shape does not exert influence on attenuation in the Rayleigh regime and its effect emerges as frequency increases to the stochastic regime showing anisotropy in attenuation. This attenuation anisotropy intensifies with the increase in frequency, but it exhibits a complicated behavior as frequency transits into the geometric regime. Wavefield fluctuations captured from the FE simulations are provided to help observe these complex scattering behaviors. The proportionality of attenuation to elastic scattering factors is also quantitatively evaluated.

SUMMARY We propose a new correlation function called the similarity coefficient (SC) based on the normal time–frequency transform (NTFT) to evaluate the similarity between two non-stationary seismic signals as a function of the delay time. The SC is defined in the time–frequency spectrum of the NTFT, and the instantaneous phase and amplitude of each frequency component in a signal are used to calculate the SC. Our simulation experiments demonstrate that the SC method can effectively recognize similar signals compared to the conventional normalized cross-correlation coefficient (NCC) under high background noise conditions. The SC presents good robustness in identifying similar signals and performs well in the case of an extremely low signal-to-noise ratio (SNR), which makes it suitable for detecting weak seismic signals concealed by noise. As a real application case, we use the SC method to detect quasi-Love (QL) surface waves. QL waves are scattered Love waves and are important indicators for lateral anisotropic gradients in the upper mantle. We detect the QL waves at 21 stations deployed across Japan after the 23 December 2004 Mw 8.1 Macquarie earthquake by using the SC method. Obvious QL waves are observed at 19 stations, and we locate the Love-to-Rayleigh scatterers by applying the delay times between the QL and main Love waves. Our results show that the QL wave scatterers were mostly generated in two areas: Mariana subduction and Papua New Guinea. The observations of QL waves suggest the presence of lateral gradients in anisotropy beneath those two areas. The spatial distribution of the 13 scatterers in the Mariana subduction zone agrees well with the Mariana Island Arc, and we infer that the Mariana slab may have melted and coupled with the surrounding mantle at depth.

This work presents scattering functions of conjugates consisting of a colloid particle and a self-avoiding polymer chain as a model for protein–polymer conjugates and nanoparticle–polymer conjugates in solution. The model is directly derived from the two-point correlation function with the inclusion of excluded volume effects. The dependence of the calculated scattering function on the geometric shape of the colloid and polymer stiffness is investigated. The model is able to describe the experimental scattering signature of the solutions of suspending hard particle–polymer conjugates and provide additional conformational information. This model explicitly elucidates the link between the global conformation of a conjugate and the microstructure of its constituent components.

Discrete fracture network (DFN) is an effective means of describing the coupling of heat flow in an underground fractured rock mass. In this paper, an improved DFN is proposed by introducing the correlation function of fracture trace length and aperture, which is more consistent with the real fracture data. Next, based on the improved model, the influence of fracture roughness on the fluid flow and heat transmission was evaluated, and the relationship between the fracture aperture and the joint roughness coefficient (JRC) is established. Finally, based on the exponential function between confining pressure and aperture, the influence of confining pressure on the heat‐flow coupling process is considered in the improved model. Besides, the reliability of the model was verified by comparing with the analytical solution of the two‐dimensional single‐fracture heat‐flow coupling problem. The results show that under the same conditions, considering the correlation between the geometric parameters of the fracture, the seepage and heat transfer rates of the model increased, the outlet boundary flow reached the maximum value, and the average outlet temperature dropped rapidly. However, the fracture roughness reduces the outlet flow rate and the decline rate of average temperature. The confining pressure will lead to a decrease of about 3.5% in the outlet flow of the model, which is consistent with the seepage law in practical engineering. The model presented in this paper is an effective supplement to the two‐dimensional fracture network heat‐flow coupling model and can provide a theoretical basis and a numerical calculation tool for related underground rock mass engineering.

It has been a vital issue to ensure both the accuracy and efficiency of computational models for analyzing the ballistic impact response of fiber-reinforced composite plates (FRCP). In this paper, a machine learning (ML) model is established in an effort to bridge the ballistic impact protective performance and the characteristics of microstructure for unidirectional FRCP (UD-FRCP), where the microstructure of the UD-FRCP is characterized by the two-point correlation function. The results showed that the ML model, after trained by 175 cases, could reasonably predict the ballistic impact energy absorption of the UD-FRCP with a maximum error of 13%, indicating that the model can ensure both computational accuracy and efficiency. Besides, the model’s critical parameter sensitivities are investigated, and three typical ML algorithms are analyzed, showing that the gradient boosting regression algorithm has the highest accuracy among these algorithms for the ballistic impact problem of UD-FRCP. The study proposes an effective solution for the traditional difficulty of the ballistic impact simulation of composites with both high efficiency and accuracy.

Coarse-grained descriptions of dislocation motion in crystalline metals inherently represent a loss of information regarding dislocation-dislocation interactions. In the present work, we consider a coarse-graining framework capable of re-capturing these interactions by means of the dislocation-dislocation correlation functions. The framework depends on a coarse-graining length to define slip-system-specific dislocation densities. Following a statistical definition of this coarse-graining process, we define a spatial correlation function which will allow relative positions of dislocation pairs, and thus the strength of their interactions at short range, to be recaptured into a mean field description of dislocation dynamics. Through a statistical homogeneity argument, we present a method of evaluating this correlation function from discrete dislocation dynamics simulations. Finally, results of this evaluation are shown in the form of self-correlation of dislocation densities on the same slip-system. These correlation functions are seen to depend weakly on plastic strain (and, in turn, the total dislocation density), but are seen to depend strongly on the coarse-graining length. Implications of these correlation functions in regard to continuum dislocation dynamics as well as future directions of investigation are also discussed., Comment: 51 pages, 8 figures, submitted to Materials Theory

We present a new statistical analysis of the large-scale stellar mass distribution in the Sloan Digital Sky Survey (data release 7). A set of volume-limited samples shows that the stellar mass of galaxies is concentrated in a range of galaxy luminosities that is very different from the range selected by the usual analysis of galaxy positions. Nevertheless, the two-point correlation function is a power-law with the usual exponent $\gamma=1.71$--$1.82$, which varies with luminosity. The mass concentration property allows us to make a meaningful analysis of the angular distribution of the full flux-limited sample. With this analysis, after suppressing the shot noise, we extend further the scaling range and thus obtain $\gamma=1.83$ and a clustering length \redc{$r_0= 5.8$--$7.0\,h^{-1}$Mpc.} Fractional statistical moments of the coarse-grained stellar mass density exhibit multifractal scaling. Our results support a multifractal model with a transition to homogeneity at about $10\,h^{-1}$Mpc., Comment: 19 pages, 6 figures; new results: shot noise suppression, fractional moments, analysis of VL samples; to be published in Advances in Astronomy

Quasielastic neutron scattering (QENS) allows measurement of the molecular displacements in time and space, from pico- to tens of nanoseconds and from Ångstroms to nanometers, respectively. The method probes dynamics from fast vibrational modes down to slow diffusive motion. Every scattering experiment leads to a dynamic structure factor $$S\left( {\vec Q,\omega } \right)$$ S Q → , ω or its spatial and temporal Fourier transform (van Hove correlation function $$G\left( {\vec r,t} \right)$$ G r → , t ). This shows exactly where the atoms are and how they move. In this manuscript the basics of the QENS method are presented and a few examples highlighting the potentials of QENS are given: (i) diffusion of liquids and gases in nano- and mesoporous materials; (ii) hydrogen dynamics in a high temperature polymer electrolyte fuel cell (HT-PEFC) and (iii) influence of the surface interactions on polymer dynamics in nanopores.

Understanding the nature of active sites is a non-trivial task, especially when the catalyst is sensitively affected by chemical reactions and environmental conditions. The challenge lies on capturing explicitly the dynamics of catalyst evolution during reactions. Despite the complexity of catalyst reconstruction, we can untangle them into several elementary processes, of which surface diffusion is of prime importance. By applying density functional theory–kinetic Monte Carlo (DFT–KMC) simulation employed with cluster expansion (CE), we investigated the microscopic mechanism of surface diffusion of Cu with defects such as steps and kinks. Based on the result, the energetics obtained from CE have shown good agreement with DFT calculations. Various diffusion events during the step fluctuations are discussed as well. Aside from the adatom attachment, the diffusion along the step edge is found to be the dominant mass transport mechanism, indicated by the lowest activation energy. We also calculated time correlation functions at 300, 400, and 500 K. However, the time exponent in the correlation function does not strictly follow the power law behavior due to the limited step length, which inhibits variation in the kink density.

A synthetic inflow turbulence generator was implemented in the idealised Weather Research and Forecasting large eddy simulation (WRF-LES v3.6.1) model under neutral atmospheric conditions. This method is based on an exponential correlation function and generates a series of two-dimensional slices of data which are correlated both in space and in time. These data satisfy a spectrum with a near “-5/3” inertial subrange, suggesting its excellent capability for high Reynolds number atmospheric flows. It is more computationally efficient than other synthetic turbulence generation approaches, such as three-dimensional digital filter methods. A WRF-LES simulation with periodic boundary conditions was conducted to provide prior mean profiles of first and second moments of turbulence for the synthetic turbulence generation method, and the results of the periodic case were also used to evaluate the inflow case. The inflow case generated similar turbulence structures to those of the periodic case after a short adjustment distance. The inflow case yielded a mean velocity profile and second-moment profiles that agreed well with those generated using periodic boundary conditions, after a short adjustment distance. For the range of the integral length scales of the inflow turbulence (±40 %), its effect on the mean velocity profiles is negligible, whereas its influence on the second-moment profiles is more visible, in particular for the smallest integral length scales, e.g. those with the friction velocity of less than 4 % error of the reference data at x/H=7. This implementation enables a WRF-LES simulation of a horizontally inhomogeneous case with non-repeated surface land-use patterns and can be extended so as to conduct a multi-scale seamless nesting simulation from a meso-scale domain with a kilometre-scale resolution down to LES domains with metre-scale resolutions.

A problem related to the development of instability of a homogeneous state in an ensemble of screw dislocations under plastic deformation of metals is considered . The study of the development of instability and structure formation in the dislocation ensemble is carried out on the basis of the method developed for charged particles in plasma and associated with the correlation interaction of electrons and positively charged ions. Accordingly, the screw dislocation ensemble is represented as a system of dislocations with an opposite Burgers vector, i.e., as a plasma-like medium with opposite dislocation charges. The total dislocation charge of the dislocation ensemble is equal to zero due to the law of conservation of the Burgers vector. In this situation, the elastic field of dislocations is “cut off”. The stress field of a single dislocation is shielded by a uniformly distributed dislocation “background” and is characterized by a certain effective potential. It is found that at long distances it decreases exponentially. Therefore, the value in the argument of the falling potential can be considered as the radius of screening of the elastic field of dislocations. It is shown that the screening radius is equal to the correlation radius, which makes it possible to construct a two-particle correlation function and find the energy of the correlation interaction of dislocations. A system of kinetic equations for a dislocation ensemble is formulated, taking into account the elastic and correlation interaction of dislocations, as well as the processes of their generation and annihilation. The criterion of instability of the homogeneous distribution of dislocations for the formulated system of equations is established. The instability criterion is met under the condition that the dislocation density exceeds a certain critical value that depends on the square of the flow stress and material constants (such as the Burgers vector modulus and shear modulus, as well as indirectly, the packing defect energy). In the framework of linear analysis, it is shown that when one system of sliding screw dislocations is taken into account, a one – dimensional periodic dislocation dissipative structure is formed at the moment of instability occurrence, and when multiple sliding is taken into account, solutions appear in the form of various variants of polyhedral lattices (cellular structures). It is established that the characteristic size of the cellular structure coincides with the experimental dependence both qualitatively and quantitatively ( the cell size is proportional to the square root of the dislocation density, and the proportionality coefficient is about ten). It is shown that the origin of spatially inhomogeneous dislocation structures, based on correlation instability, depends mainly on the features of the elastic interaction of dislocations and is not critical to the choice of the mechanisms of their kinetics (i.e., the mechanisms of generation, annihilation, and runoff of dislocations).

We prove a theorem describing the limiting fine-scale statistics of orbits of a point in hyperbolic space under the action of a discrete subgroup. Similar results have been proved only in the lattice case, with two recent infinite-volume exceptions by Zhang for Apollonian circle packings and certain Schottky groups. Our results hold for general Zariski dense, non-elementary, geometrically finite subgroups in any dimension. Unlike in the lattice case, orbits of geometrically finite subgroups do not necessarily equidistribute on the whole boundary of hyperbolic space. But rather, they may equidistribute on a fractal subset. Understanding the behaviour of these orbits near the boundary is central to Patterson-Sullivan theory and much further work. Our theorem characterizes the higher order spatial statistics and thus addresses a very natural question. As a motivating example our work applies to sphere packings (in any dimension) which are invariant under the action of such discrete subgroups. At the end of the paper we show how this statistical characterization can be used to prove convergence of moments and to write down the limiting formula for the two-point correlation function and nearest neighbor distribution. Moreover we establish an formula for the 2 dimensional limiting gap distribution (and cumulative gap distribution) which was not known previously even in the lattice case., 33 pages, 1 figure; Accepted for Publication in Mathematical Proceedings of the Cambridge Philosophical Society

We explain how the axioms of Conformal Field Theory are used to make predictions about critical exponents of continuous phase transitions in three dimensions, via a procedure called the conformal bootstrap. The method assumes conformal invariance of correlation functions, and imposes some relations between correlation functions of different orders. Numerical analysis shows that these conditions are incompatible unless the critical exponents take particular values, or more precisely that they must belong to a small island in the parameter space., Comment: 16 pages, 3 figures, accepted for publication by C.R.Physique

Fluctuating hydrodynamics (FH) is one of the theories that describes the dynamics of the fluctuations for fluids at mesoscopic scales. However, it is only valid for Markovian processes. Here we extend this approach for a viscoelastic liquid by using a generalized Langevin equation (GLE). We obyain general analytic expressions for the density fluctuations correlation function, the dynamic structure factor and the light scattering spectrum. In particular, we calculate the intermediate scattering function when the time memory and the noise correlation function are power-laws. We find that the difference in values of this quantity as functions of the viscoelasticity may be ∼62% and might be measurable.

One of the standard methods used to measure the hydrodynamic diameter of nanoparticles is photon correlation spectroscopy, especially dynamic light scattering (DLS). In principle, this technique is to analyze correlation function of the scattered light from the nanoparticles undergoing Brownian motion in solution and to calculate the diffusion coefficient from the correlation function which is converted into the hydrodynamic diameter. However, when using this technique, one needs to pay careful attention to interaction effects (i.e., particle-particle and particle-solvent interactions) on the diffusion coefficient of the particles in solution. If not, then incorrect information can be obtained on the self-diffusion coefficients of nanoparticles. In order to facilitate a strict procedure for obtaining real size of the nanoparticles in solution, we used 20 nm, 50 nm and 100 nm-nominal polystyrene latex (PSL) nanoparticle solutions for DLS measurement. We represented that a rigorous scrutinizing the concentration dependence of the diffusion coefficient of the PSL nanoparticles made it possible to separate the interaction effect from the diffusion phenomena of the PSL nanoparticles suspended in water and to give real size of the PSL nanoparticles.

We consider the extinction regime in the spatial stochastic logistic model in R d (a.k.a. Bolker–Pacala–Dieckmann–Law model of spatial populations) using the first-order perturbation beyond the mea...

The center line slope (CLS) observable has become a popular method for characterizing spectral diffusion dynamics in two-dimensional (2D) correlation spectroscopy because of its ease of implementation, robustness, and clear theoretical relationship to the frequency-frequency correlation function (FFCF). The FFCF relates the frequency fluctuations of an ensemble of chromophores to coupled bath modes of the chemical system and is used for comparison to molecular dynamics simulations and for calculating 2D spectra. While in the appropriate limits, the CLS can be shown to be the normalized FFCF, from which the full FFCF can be obtained, in practice the assumptions that relate the CLS to the normalized FFCF are frequently violated. These violations are due to the presence of homogeneous broadening and motional narrowing. The generalized problem of relating the CLS to the FFCF is reanalyzed by introducing a new set of dimensionless parameters for both the CLS and FFCF. A large data set was generated of CLS parameters derived from numerically modeled 2D line shapes with known FFCF parameters. This data set was used to train feedforward artificial neural networks that act as functions, which take the CLS parameters as inputs and return FFCF parameters. These neural networks were deployed in an algorithm that is able to quickly and accurately determine FFCF parameters from experimental CLS parameters and the fwhm of the absorption line shape. The method and necessary inputs to accurately obtain the FFCF from the CLS are presented.

This paper considers a single-input single-output linear dynamic system, whose input and output are corrupted by Gaussian white measurement noises with zero means and unknown variances; the parameter estimation of such a system is a typical errors-in-variables (EIV) system identification problem. This paper proposes the correlation function-based two-step identification methods for the EIV systems. In order to obtain the unbiased parameter estimates of the EIV system, we derive the correlation function equation by using the correlation analysis method and adopt the least squares method and the instrumental variable method to recursively compute the parameter estimates of the model, resulting in the unbiased parameter estimates of the EIV systems. Finally, a numerical simulation example is given to demonstrate the effectiveness of the proposed algorithms.

The flow dynamics of binary particle mixtures in the fluidized bed needs to be monitored in order to optimize the related industrial processes. In this paper, electrostatic sensing and high-speed imaging are applied to measure the velocities of polyethylene and sand particles in the binary particle mixtures in fluidization. Experimental studies were conducted on a lab-scale cold circulating fluidized bed. Correlation function between electrostatic signals from upstream and downstream electrodes placed along the riser shows two peaks that represent transit times for the two types of particles. To verify the above results, high-speed imaging was adopted to capture the flow images of particle mixtures. Particle Image Velocimetry and Particle Tracking Velocimetry algorithms were utilized to process the resulted images in order to measure the velocities of polyethylene and sand particles. The reasons for two-peak correlation functions are illustrated based on the frequency spectrums of the mono-solid-phase electrostatic signals and the velocity difference between polyethylene and sand particles. Finally, comparisons on the velocities obtained from electrostatic sensing and high-speed imaging demonstrate the electrostatic sensor can roughly estimate the particle velocity of binary particle mixtures in the near wall region of the circulating fluidized bed.

Continuous Markov processes widely used as a tool for modeling random phenomena in numerous applications, can be defined as solutions of generally nonlinear stochastic differential equations (SDEs) with certain drift and diffusion coefficients which together governs the process’ probability density and correlation functions. Usually it is assumed that the diffusion coefficient does not depend on the process' current value. Sometimes, in particular for presentation of non- Gaussian real processes this assumption becomes undesirable, leads generally to complexity of the correlation function estimation. We consider its analysis for the process with arbitrary pair of the drift and diffusion coefficients providing the given stationary probability distribution of the considered process.

Soil properties (or parameters herein) vary randomly in space because of different depositional conditions. The knowledge of the spatial variability characteristics of unsaturated soils can be critical to the reliability assessment of geological and geotechnical engineering problems such as the stability analysis of unsaturated soil slopes and the seepage analysis of earth dams. To investigate the spatial variability characteristics of unsaturated soils, the soil parameters, including physical, deformation, and hydraulic properties, are measured through laboratory tests in this study. It is found that the variability of the physical parameters is smaller than that of the deformation parameters, and smaller than that of the hydraulic parameters. Five existing methods are adopted to evaluate the horizontal and vertical auto-correlation distances that measure the spatial variability, and it is found that the space average method and the correlation function method are more suitable for evaluating the auto-correlation distances when the number of test data is small. To further explore the spatial variability characteristics, the Wilcoxon rank analysis is conducted, and the results show that the auto-correlation distance is an inherent property of soils and there is little difference among the results obtained based on the physical, deformation, and hydraulic parameters of the unsaturated soils.

Redshift-space clustering distortions provide one of the most powerful probes to test the gravity theory on the largest cosmological scales. We perform a systematic validation study of the state-of-the-art statistical methods currently used to constrain the linear growth rate from redshift-space distortions in the galaxy two-point correlation function. The numerical pipelines are tested on mock halo catalogues extracted from large N-body simulations of the standard cosmological framework. We consider both the monopole and quadrupole multipole moments of the redshift-space two-point correlation function, as well as the radial and transverse clustering wedges, in the comoving scale range $1030$ \Mpch, the discrepancy is reduced below $5\%$. At higher redshifts, we find instead an overall good agreement between measurements and model predictions. Though this accuracy is good enough for clustering analyses in current redshift surveys, the models have to be further improved not to introduce significant systematics in RSD constraints from next generation galaxy surveys. The effect of redshift errors is degenerate with the one of small-scale random motions, and can be marginalised over in the statistical analysis, not introducing any statistically significant bias in the linear growth constraints, especially at $z\geq1$., Comment: 17 pages, 14 figures, 1 table

Recent studies have demonstrated that {\em secondary} non-Gaussianity induced by gravity will be detected with a high signal-to-noise (S/N) by future and even by on-going weak lensing surveys. One way to characterise such non-Gaussianity is through the detection of a non-zero three-point correlation function of the lensing convergence field, or of its harmonic transform, the bispectrum. A recent study analysed the properties of the squeezed configuration of the bispectrum, when two wavenumbers are much larger than the third one. We extend this work by estimating the amplitude of the (reduced) bispectrum in four generic configurations, i.e., {\em squeezed, equilateral, isosceles} and {\em folded}, and for four different source redshifts $z_s=0.5,1.0,1.5,2.0$, by using an ensemble of all-sky high-resolution simulations. We compare these results against theoretical predictions. We find that, while the theoretical expectations based on widely used fitting functions can predict the general trends of the reduced bispectra, a more accurate theoretical modelling will be required to analyse the next generation of all-sky weak lensing surveys. The disagreement is particularly pronounced in the squeezed limit., Comment: 12 pages, 2 figures

High-speed (HS) atomic force microscopy (AFM) is a prominent imaging technology that observes large-scale structural dynamics of biomolecules near the physiological condition, but the AFM data are limited to the surface shape of specimens. Rigid-body fitting methods were developed to obtain molecular structures that fit to an AFM image, without accounting for conformational changes. Here, we developed a method to fit flexibly a three-dimensional (3D) biomolecular structure into an AFM image. First, we describe a method to produce a pseudo-AFM image from a given 3D structure in a differentiable form. Then, using a correlation function between the experimental AFM image and the computational pseudo-AFM image, we developed a flexible fitting molecular dynamics (MD) simulation method by which we obtain protein structures that well fit to the given AFM image. We first test it with a twin experiment; using an AFM image produced from a protein structure different from its native conformation as a reference, we performed the flexible fitting MD simulations to sample conformations that fit well the reference AFM image, and the method was confirmed to work well. Then, parameter dependence in the protocol was discussed. Finally, we applied the method to a real experimental HS-AFM image for a flagellar protein FlhA, demonstrating its applicability. We also test the rigid-body fitting of a molecular structure to an AFM image. Our method will be a general tool for dynamic structure modeling based on HS-AFM images and is publicly available through the CafeMol software.

We present the derivation of a new model to describe neutron spin echo spectroscopy and quasi-elastic neutron scattering data on liposomes. We compare the new model with existing approaches and benchmark it with experimental data. The analysis indicates the importance of including all major contributions in the modeling of the intermediate scattering function. Simultaneous analysis of the experimental data on lipids with full contrast and tail contrast matched samples reveals highly confined lipid tail motion. A comparison of their dynamics demonstrates the statistical independence of tail-motion and height-height correlation of the membrane. A more detailed analysis indicates that the lipid tail relaxation is confined to a potential with cylindrical symmetry, in addition to the undulation and diffusive motion of the liposome. Despite substantial differences in the chemistry of the fatty acid tails, the observation indicates a universal behavior. The analysis of partially deuterated systems confirms the strong contribution of the lipid tail to the intermediate scattering function. Within the time range from 5 to 100 ns, the intermediate scattering function can be described by the height-height correlation function. The existence of the fast-localized tail motion and the contribution of slow translational diffusion of liposomes determine the intermediate scattering function for t5 ns and t100 ns, respectively. Taking into account the limited time window lowers the bending moduli by a factor of 1.3 (DOPC) to 2 (DMPC) compared to the full range.

We study the single-file dynamics of three classes of active particles: run-and-tumble particles, active Brownian particles and active Ornstein-Uhlenbeck particles. At high activity values, the particles, interacting via purely repulsive and short-ranged forces, aggregate into several motile and dynamical clusters of comparable size, and do not display bulk phase-segregation. In this dynamical steady-state, we find that the cluster size distribution of these aggregates is a scaled function of the density and activity parameters across the three models of active particles with the same scaling function. The velocity distribution of these motile clusters is non-Gaussian. We show that the effective dynamics of these clusters can explain the observed emergent scaling of the mean-squared displacement of tagged particles for all the three models with identical scaling exponents and functions. Concomitant with the clustering seen at high activities, we observe that the static density correlation function displays rich structures, including multiple peaks that are reminiscent of particle clustering induced by effective attractive interactions, while the dynamical variant shows non-diffusive scaling. Our study reveals a universal scaling behavior in the single-file dynamics of interacting active particles., Accepted for publication in Soft Matter

Complex random variables and processes with a vanishing pseudo-correlation are called proper. There is a class of stationary proper complex random processes that have a stable correlation function. In the present article we consider real stationary Gaussian processes with a stable correlation function. It is shown that the trajectories of stationary Gaussian proper complex random processes with zero mean belong to the Orlich space generated by the function $U(x) = e^{x^2/2}-1$. Estimates are obtained for the distribution of semi-norms of sample functions of Gaussian proper complex random processes with a stable correlation function, defined on the compact $\mathbb{T} = [0,T]$, in Hölder spaces.

Analytical and numerical models of nucleation and growth transformations usually suppose that nuclei are located uniform randomly, i.e., according to a Poisson point process, within the matrix. Nonetheless, nucleation might be prevented or made more difficult if a new nucleus tries to form very close to another already existent nucleus. In these circumstances, it is better to locate the nuclei according to a point process in which there is an exclusion zone around each nucleus. The 3D Sequential point process is a convenient point process to model such a situation. By changing the nuclei density, the Sequential point process can generate arrangements of nuclei in space with distinct characteristics. In this work, we compare 3D computer simulations with nuclei generated by the Sequential point process with nuclei generated by a Poisson point process. Stereological parameters, as well as the correction function (obtained from the two-point correlation function), characterize the progress of the transformation. The 3D Sequential point process can produce a range of outcomes. Transformation kinetics behavior changes from close to a transformation nucleated according to a homogeneous Poisson point process to a transformation close to a periodic arrangement of nuclei. Keywords: Phase transformations, Computer simulation, Point process, Microstructure, Exclusion zone

Due to the difficulties in actual measurement of sea clutter and uncertainties of experimental data, the electromagnetic (EM) scattering model becomes a better alternative means to acquire the sea clutter. However, the EM scattering model still faces the problems of huge memory consumption and low-computational efficiency when dealing with the large size of sea surface or the long time case. Thus, this paper presents a statistical model to simulate the temporal-spatial correlated three-dimensional (3D) sea clutter, which is based on the statistical properties obtained from the EM scattering model, such as probability density function and correlation function. The comparisons show that the texture feature, autocorrelation function, and PDF of the sea clutter simulated by the statistical model have a good agreement with the results given by the EM model. Furthermore, the statistical model is with high efficiency and can be used to simulate the large scene or long time temporal-spatial correlated 3D sea clutter.

In this paper we prove a wall-crossing formula, a crucial ingredient needed to prove that the correlation function of gauged linear sigma model is independent of the choice of perturbations., This article is split from 1602.07638. Submitted and revised version. 48 pages

The effective diffusivity and the effective Thiele modulus of reactive porous matrices are determined by using a hybrid discrete and continuum model. The model describes static heterogeneity with weak noise on both morphology and topology of the matrix. Variations in diffusivity with respect to pore size (radius and length) and network connectivity up to second order are analyzed to assess the effect of stochastic media on catalytic reaction and transition of a single species. The porous medium is simulated by several building blocks (BB) which are regular in topology and morphology. A methodology is presented to construct a BB such that it fits the true matrix. Permutation of several regular pore networks in series constructs the porous media. Local mass balances over each BB yields model equations for reaction and transport in the matrix. Correlated random walk theory is used in each BB in order to relate the diffusivity to the coordination number. The Gaussian correlation function is assumed to model the autocorrelation of independent variables which are used to characterize the correlated porous media. The contribution of the fluctuating parameters in the mass conservation of the matrix yields a new closure equation in which ensemble average concentration of the reactant depends on different cross-correlations. The model is stable as long as the Thiele modulus at the correlation length scale is small. It predicts that geometrical heterogeneities lead to correction in effective diffusivity while the reaction rate is unaffected due to small Thiele modulus at correlation length scale. The model is verified by assessing the Thiele modulus of a pore network under Knudsen regime during a first order catalytic reaction; a good agreement was found especially for moderate Thiele modulus of correlated network. However, it fails to simulate random networks. Our systematic study revealed that the pore radius statistics impact significantly the diffusivity and the Thiele modulus while the topological parameters are important in weakly connected networks. The model predictions show that the diffusion constant decreases sharply as pore radius variance increases but increases smoothly with Thiele modulus.

A detailed theoretical and experimental study on the effect of the superposition of uncorrelated speckle patterns with polarization diversity on the spatial statistics of the superposed speckle pattern is presented. It is shown that depending on the mutual orientation of the polarization vectors of the constituent speckle patterns, the maximum degree of coherence (DoC) and degree of polarization (DoP) of the superposed speckle pattern changes between a maximum and minimum value in a sinusoidal fashion. Moreover, the average intensity ratio of the constituent speckle patterns is also found to be affecting these variations. A study of the change in the visibility of the two-point intensity correlation function also reveals a sinusoidal nature of the variation and its dependence on the ratio of the average intensity, which are found to be similar to the variations of the maximum DoC and DoP. A detailed study on the changes in the normalized probability density function is also performed for better understanding of the effect on the spatial statistics.

We present a new partially coherent source with spatiotemporal coupling. The stochastic light, which we call a spatiotemporal (ST) non-uniformly correlated (NUC) beam, combines space and time in an inhomogeneous (shift- or space-variant) correlation function. This results in a source that self-focuses at a controllable location in space-time, making these beams potentially useful in applications such as optical trapping, optical tweezing, and particle manipulation. We begin by developing the mutual coherence function for an ST NUC beam. We then examine its free-space propagation characteristics by deriving an expression for the mean intensity at any plane $$z \ge 0$$ z ≥ 0 . To validate the theoretical work, we perform Monte Carlo simulations, in which we generate statistically independent ST NUC beam realizations and compare the sample statistical moments to the corresponding theory. We observe excellent agreement amongst the results.

On a class of four-dimensional Lifshitz spacetimes with critical exponent z=2, including a hyperbolic and a spherical Lifshitz topological black hole, we consider a real Klein-Gordon field. Using a mode decomposition, we split the equation of motion into a radial and into an angular component. As first step, we discuss under which conditions on the underlying parameters we can impose to the radial equation boundary conditions of Robin type and whether bound state solutions do occur. Subsequently, we show that, whenever bound states are absent, one can associate to each admissible boundary condition a ground and a KMS state whose associated two-point correlation function is of local Hadamard form.