Functional-differential equations for $F_q$%-transforms of $q$-Gaussians

The Equation of State of a Gaussian Phantom Network with Defined Cross Link Functionality

A phantom network of Gaussian chains far from the point of gelation can be described as a gas of interacting particles represented by the cross links. The type of particles varies with the network functionality, whereas the type of interaction depends on the properties of the connecting chains. In a mean field approximation the Equation of State can be calculated using Mayer's cluster expansion. The resulting isothermal compressibility is compared for different cross link functionalities.

Almost Sure Uniform Convergence of a Random Gaussian Field Conditioned on a Large Linear Form to a Non Random Profile

We investigate the realizations of a random Gaussian field on a finite domain of ${\mathbb R}^d$ in the limit where a given linear functional of the field is large. We prove that if its variance is bounded, the field converges uniformly and almost surely to a non random profile depending only on the covariance and the considered linear functional of the field. This is a significant improvement of the weaker $L^2$-convergence in probability previously obtained in the case of conditioning on a large quadratic functional.

Generating functionals and Gaussian approximations for interruptible delay reactions

We develop a generating functional description of the dynamics of non-Markovian individual-based systems, in which delay reactions can be terminated before completion. This generalises previous work in which a path-integral approach was applied to dynamics in which delay reactions complete with certainty. We construct a more widely applicable theory, and from it we derive Gaussian approximations of the dynamics, valid in the limit of large, but finite population sizes. As an application of our theory we study predator-prey models with delay dynamics due to gestation or lag periods to reach the…

Large-Deviation Functions for Nonlinear Functionals of a Gaussian Stationary Markov Process

We introduce a general method, based on a mapping onto quantum mechanics, for investigating the large-T limit of the distribution P(r,T) of the nonlinear functional r[V] = (1/T)\int_0^T dT' V[X(T')], where V(X) is an arbitrary function of the stationary Gaussian Markov process X(T). For T tending to infinity at fixed r we find that P(r,T) behaves as exp[-theta(r) T], where theta(r) is a large deviation function. We present explicit results for a number of special cases, including the case V(X) = X θ(X) which is related to the cooling and the heating degree days relevant to weather derivatives.

广义正随机函数的遍历性质

Ergodic properties of functionals of Gaussian processes

研究广义正随机函数的一阶二阶矩及其在平稳随机游走中的遍历性，推导半占时和区间占时的精确解析表达式，并扩展至分数布朗运动，建立占时概率密度的标度形式。

Solvation in atomic liquids: connection between Gaussian field theory and density functional theory

For the problem of molecular solvation, formulated as a liquid submitted to the external potential field created by a molecular solute of arbitrary shape dissolved in that solvent, we draw a connection between the Gaussian field theory derived by David Chandler [Phys. Rev. E, 1993, 48, 2898] and classical density functional theory. We show that Chandler's results concerning the solvation of a hard core of arbitrary shape can be recovered by either minimising a linearised HNC functional using an auxiliary Lagrange multiplier field to impose a vanishing density inside the core, or by minimising …