Some asymptotic results for nonlinear Hawkes processes

Hawkes process is a class of simple point processes with self-exciting and clustering properties. Hawkes process has been widely applied in finance, neuroscience, social networks, criminology, seismology, and many other fields. In this paper, we study fluctuations, large deviations and moderate deviations nonlinear Hawkes processes in a new asymptotic regime, the large intensity function and the small exciting function regime. It corresponds to the large baseline intensity asymptotics for the linear case, and can also be interpreted as the asymptotics for the mean process of Hawkes processes on a large network.     

Fluctuations in the Ising model on a sparse random graph

We compute the fluctuations of the magnetization and of the multi-overlaps for the dilute mean field ferromagnet, in the high temperature region. The rescaled magnetization tends to a centered Gaussian variable with variance diverging at the critical line. The rescaled multi-overlaps also tend to centered independent Gaussian variables, but their covariances remain finite at the critical line.     

Variable sinh-Gaussian solitons in nonlocal nonlinear Schrödinger equation

Based on the nonlocal nonlinear Schrödinger equation that governs phenomenologically the propagation of laser beams in nonlocal nonlinear media, we theoretically investigate the propagation of sinh-Gaussian beams (ShGBs). Mathematical expressions are derived to describe the beam propagation, the intensity distribution, the beam width, and the beam curvature radius of ShGBs. It is found that the propagation behavior of ShGBs is variable and closely related to the parameter of sinh function (PShF). If the PShF is small, the transverse pattern of ShGBs keeps invariant during propagation for a proper input power, which can be regarded as solitons. If the PShF is large, it varies periodically, which is similar to the evolution of temporal higher-order solitons in nonlinear optical fiber. Numerical simulations are carried out to illustrate the typical propagation characteristics.     

Electron dynamical response in InP semiconductors driven by fluctuating electric fields

The complexity of electron dynamics in low-doped n-type InP crystals operating under fluctuating electric fields is deeply explored and discussed. In this study, we employ a multi-particle Monte Carlo approach to simulate the non-linear transport of electrons inside the semiconductor bulk. All possible scattering events of hot electrons in the medium, the main details of the band structure, as well as the heating effects, are taken into account. The results presented in this study derive from numerical simulations of the electron dynamical response to the application of a sub-Thz electric field, fluctuating for the superimposition of an external source of Gaussian correlated noise. The electronic noise features are statistically investigated by computing the correlation function of the velocity fluctuations, its spectral density and the variance, i.e. the total noise power, for different values of amplitude and frequency of the driving field. Our results show the presence of a cooperative non-linear behavior of electrons, whose dynamics is strongly affected by the field fluctuations. Moreover, the electrons self-organize among different valleys, giving rise to the reduction of the intrinsic noise. This counterintuitive effect critically depends on the relationship among the characteristic times of the external fluctuations and the temporal scales of complex phenomena involved in the electron dynamical response. In particular, the correlation time of the electric field fluctuations appears to be crucial both for the noise reduction effect and the appearance of an anomalous diffusion effect.     

On local behaviour of the phase separation line in the 2D Ising model

Summary. The aim of this note is to discuss some statistical properties of the phase separation line in the 2D low-temperature Ising model. We prove the functional central limit theorem for the probability distributions describing fluctuations of the phase boundary in the direction orthogonal to its orientation. The limiting Gaussian measure corresponds to a scaled Brownian bridge with direction dependent parameters. Up to the temperature factor, the variances of local increments of this limiting process are inversely proportional to the stiffness. Received: 6 June 1997/In revised form: 20 August 1997     

圆形杂质对裂纹扩展的影响

在单轴拉伸载荷作用下，运用分布位错方法对无限大平面内含有一个裂纹和一个任意方向的杂质问题进行求解，得到了裂纹尖端的应力强度因子、应力场以及应变能密度.利用最小应变能密度因子准则来判断裂纹扩展方向.结果显示:软杂质对裂纹尖端应力强度因子、应变能密度和应力场有增强作用，而硬杂质则具有屏蔽作用.在 -30°<θ<30°范围内，杂质对裂纹扩展方向的影响较小，而在 -90°<θ<-30°或30°<θ<90°范围内，杂质对裂纹扩展方向的影响较大.软杂质对裂纹扩展有吸引作用，而硬杂质具有排斥作用.     

Direct Estimation of Linear Functionals from Indirect Noisy Observations

The authors study the efficiency of the linear-functional strategy, as introduced by Anderssen in 1986, for inverse problems with observations blurred by Gaussian white noise with known intensity δ. The optimal accuracy is presented and it is shown how this can be achieved by a linear-functional strategy based on the noisy observations. This optimal linear-functional strategy is obtained from Tikhonov regularization of some dual problem. Next, the situation is treated when only a finite number of noisy observations, given beforehand, is available. Under appropriate smoothness assumptions best possible accuracy still can be attained if the number of observations corresponds to the noise intensity in a proper way. It is also shown that, at least asymptotically, this number of observations cannot be reduced.     

Non‐Gaussian invariant measures for the Majda model of decaying turbulent transport

The problem of turbulent transport of a scalar field by a random velocity field is considered. The scalar field amplitude exhibits rare but very large fluctuations whose typical signature are fatter than Gaussian tails for the probability distribution of the scalar. The existence of such large fluctuations is related to clustering phenomena of the Lagrangian paths within the flow. This suggests an approach to turn the large deviation problem for the scalar field into a small deviation, or small ball, problem for some appropriately defined process measuring the spreading with time of the Lagrangian paths. Here, such a methodology is applied to a model proposed by Majda consisting of a white‐in‐time linear shear flow and some generalizations of it where the velocity field has finite, or even infinite, correlation time. The non‐Gaussian invariant measure for the (reduced) scalar field is derived and, in particular, it is shown that the one‐point distribution of the scalar has stretched exponential tails, with a stretching exponent depending of the parameters in the model. Different universality classes for the scalar behavior are identified which, all other parameters being kept fixed, display a one‐to‐one correspondence with a exponent measuring time persistence effects in the velocity field. © 2001 John Wiley & Sons, Inc.     

Model selection for Gaussian latent block clustering with the integrated classification likelihood

Block clustering aims to reveal homogeneous block structures in a data table. Among the different approaches of block clustering, we consider here a model-based method: the Gaussian latent block model for continuous data which is an extension of the Gaussian mixture model for one-way clustering. For a given data table, several candidate models are usually examined, which differ for example in the number of clusters. Model selection then becomes a critical issue. To this end, we develop a criterion based on an approximation of the integrated classification likelihood for the Gaussian latent block model, and propose a Bayesian information criterion-like variant following the same pattern. We also propose a non-asymptotic exact criterion, thus circumventing the controversial definition of the asymptotic regime arising from the dual nature of the rows and columns in co-clustering. The experimental results show steady performances of these criteria for medium to large data tables.     

Entropic optimal transport is maximum-likelihood deconvolution

We give a statistical interpretation of entropic optimal transport by showing that performing maximum-likelihood estimation for Gaussian deconvolution corresponds to calculating a projection with respect to the entropic optimal transport distance. This structural result gives theoretical support for the wide adoption of these tools in the machine learning community.     

The effect of Gaussian white noise on the fractality of fluctuations in the plasma of a symmetrical discharge

In this work we investigate the influence of white Gaussian noise on the fluctuations in the plasma of a symmetrical discharge using multifractal detrended fluctuation analysis. We observe that in the range of noise intensity used in our study, the multifractality strength is increased by the noise, at all values of the inter-anode voltage, both for original and filtered time-series. This is interpreted as a new positive influence of noise because this effect can be understood as an increasing in the predictability on the dynamics in a time-series. A constructive influence of noise can appear only for fluctuations with underlying chaotic dynamics. The shuffling analysis demonstrates that the multifractality is purely a consequence of the correlations of the fluctuations. The noise influence is also observed in the change of the position of the maximum in the singularity spectra. The multifractal detrended cross correlation between light intensity and current intensity demonstrates that the fluctuations in both parameters are generated by the same physical processes though they are very different in nature: one is a local parameter and the other is a global one.     

Gradient-consistent non-linear model of the generation of ultrasound in the propagation of seismic waves

The equations of the propagation of weak non-linear waves are obtained by a detailed analysis of the gradient-consistent micropolar model of a granular continuous medium. The high-frequency mode of oscillation is associated with ultrasonic waves, and the low-frequency mode is associated with the usual seismic waves in rocks. The evolution equations that include the case of long-wave-short-wave resonance are obtained by an asymptotic consideration. This resonance corresponds to the case of the generation of ultrasound (noise) by travelling seismic waves.     

Targeting Bayes factors with direct-path non-equilibrium thermodynamic integration

Thermodynamic integration (TI) for computing marginal likelihoods is based on an inverse annealing path from the prior to the posterior distribution. In many cases, the resulting estimator suffers from high variability, which particularly stems from the prior regime. When comparing complex models with differences in a comparatively small number of parameters, intrinsic errors from sampling fluctuations may outweigh the differences in the log marginal likelihood estimates. In the present article, we propose a TI scheme that directly targets the log Bayes factor. The method is based on a modified annealing path between the posterior distributions of the two models compared, which systematically avoids the high variance prior regime. We combine this scheme with the concept of non-equilibrium TI to minimise discretisation errors from numerical integration. Results obtained on Bayesian regression models applied to standard benchmark data, and a complex hierarchical model applied to biopathway inference, demonstrate a significant reduction in estimator variance over state-of-the-art TI methods.     

Effect of two photon absorption on nonlinear pulse propagation in gain medium

The effects of two photon absorption (TPA) and gain dispersion on soliton propagation in amplified medium are investigated. For finite gain bandwidth, the effect of gain dispersion becomes significant along with TPA and is treated as perturbation in fundamental soliton propagation. Including these perturbing effects an analytical expression of integrated intensity is formulated applying a completely new methodology by adopting Rayleigh’s dissipation function in the framework of variational approach. With classical analogy, the Euler–Lagrange equation in non-conservative system is used to solve the problem analytically. In order to justify the analytical prediction a numerical verification is made by split-step beam propagation method following Ginzburg–Landau equation.     

Buckling analysis of a ring under the action of internal pressure in a cylindrical shell

Buckling analysis of a thin cylindrical shell stiffened by rings with T-shaped cross section under the action of uniform internal pressure in the shell is performed. An annular plate stiffened over the outer edge by a circular beam is used as the ring model. The classical ring model, which is a beam with a T-shaped cross section, is inappropriate in this problem, since in the case of the loss of stability, buckling deformations are localized on the ring surface. The beam model does not allow one to find the critical pressure that corresponds to such a loss of stability. In the first approximation, the problem of the loss of stability of the annular plate connected with the shell is reduced to solving the boundary value problem for finding eigenvalues of the annular plate bending equation. Approximate formulas for determining critical pressure are obtained under the assumption that the plate width is much smaller than its inner radius. The results found using the Rayleigh method and the shooting method differ slightly from each other. It has been demonstrated that the critical pressure for rings with rectangular cross section is higher than that for rings with a T-shaped cross section.     

纯弯曲矩形截面梁Ⅰ型单边裂纹端部的应力应变场及裂纹失稳扩展临界应力的计算

本文应用文[1]的分析方法,研究了纯弯曲矩形载面梁Ⅰ型单边裂纹端部的应力应变场,给出了裂纹尖端的应力应变分量和计算裂纹端部弹性变形区和变形强化区宽度的公式以及计算裂纹失稳扩展临界应力的方程组。最后用计算实例对裂纹失稳扩展临界应力方程组进行了验证,最大误差不超过0.18%.     

Bose condensation: The viscosity critical dimension and developed turbulence

We propose a model for studying the mutual influence of critical fluctuations in the vicinity of the critical point of phase transition to a superfluid state and the velocity fluctuations in the developed turbulence regime. We demonstrate the presence of two different regimes: the turbulence regime and the equilibrium regime. We show that the standard critical behavior can break in the turbulence regime. The viscosity becomes an infrared-irrelevant parameter in the equilibrium regime. We justify the assumption that the viscosity critical dimension in this regime is determined by critical indices of the critical behavior statistical model, which are currently known with sufficient accuracy.     

Mean field analysis of neural networks: A central limit theorem

We rigorously prove a central limit theorem for neural network models with a single hidden layer. The central limit theorem is proven in the asymptotic regime of simultaneously (A) large numbers of hidden units and (B) large numbers of stochastic gradient descent training iterations. Our result describes the neural network’s fluctuations around its mean-field limit. The fluctuations have a Gaussian distribution and satisfy a stochastic partial differential equation. The proof relies upon weak convergence methods from stochastic analysis. In particular, we prove relative compactness for the sequence of processes and uniqueness of the limiting process in a suitable Sobolev space.     

矩形截面梁中波传播的精确分析

将傅立叶级数方法推广应用于矩形截面梁中波传播的精确分析．不仅试着直接从三维弹性动力学方程出发,导出了矩形截面梁中波传播的一般解析解,而且给出了弹性波在自由矩形截面梁中的传播特性．波传播精确模型的提出,为实现梁波的耦合控制奠定了坚实基础．