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Mengzi Xie

Publications and source records attributed to Mengzi Xie.

9 recordsLinked to original sources

Exponential decay of mass for inertial coalescing particles with Hamiltonian noise

We study a system of $N$ inertial particles on a two-dimensional torus $\T^2$, evolving under a second-order stochastic dynamics with position-dependent friction $\lambda$ and noise amplitude $\sigma$, and undergoing coalescence at rate $R_0$ when their distance falls below a threshold $\delta$. In the joint small-mass / small-correlation limit $\mu(\eps)\to 0$, $\mu(\eps)/\eps\to\al\in(0,\infty)$, the empirical measure of the surviving particles converges to a stochastic continuity equation with inertial drift~$g_\al$. Assuming that $\sigma$ is tangent to the level sets of a Hamiltonian $H=h_1(x_1)\,h_2(x_2)$ satisfying mild non-degeneracy and convexity-type conditions, and that $\lambda$ and the amplitude $\rho$ of $\sigma$ along $\xi=\nabla^\perp H$ are aligned with $H$, we prove that the expected total mass decays exponentially in time, with an explicit rate depending on $\al$ and on the values of $\lambda$ and $\rho$ on the separatrix $\{H=0\}$. The proof rests on a cell-by-cell analysis of the sign of $\div\,g_\al$ on the level sets of $H$, showing that the inertial drift pushes trajectories toward the separatrix at a quantitative rate.

math.PR

The inertial It\^o drift and its applications to particle collision

The small mass $\mu$ limit of an inertial system driven by an Ornstein Uhlenbeck fluid force, with correlation time $\epsilon$ going to zero, leads to a first order system with an additional drift, which we call inertial-It\^{o}-drift, depending on the limit $\alpha$ of the ratio $\mu/\epsilon$; the drift being zero when $\alpha=0$, corresponding to the Stratonovich integral in the limit equation, as in the Wong-Zakai theory, when applied directly to the first-order system with Ornstein-Uhlenbeck driver. We discuss the application of this result to particles driven by Stokes force;\ we identify inertial centrifugal effects and the so-called turbophoretic effect, as examples of the inertial-It\^{o}-drift. We also analyze concentration effects and their link with the theory of particle collision in turbulent fluids.

math.PR

Parabolic scaling of a stochastic wave map with co-normal noise: limit and fluctuations

This paper investigates the parabolic scaling limit of a damped stochastic wave map from the real line into the two-dimensional sphere, perturbed by multiplicative Gaussian noise of co-normal type. We prove that under this rescaling, the solutions converge to those of the deterministic heat flow for harmonic maps, revealing a transition from stochastic hyperbolic to deterministic parabolic dynamics. We further analyze the fluctuations around this limit, proving a weak central limit theorem and identifying the limiting process as the solution to a linear stochastic partial differential equation. The study combines tools from geometric analysis, stochastic calculus, and functional analysis, offering insights into the interplay between geometry, noise, and scaling in nonlinear stochastic systems.

math.PR

The small-mass limit for some constrained wave equations with nonlinear conservative noise

We study the small-mass limit, also known as the Smoluchowski-Kramers diffusion approximation (see \cite{kra} and \cite{smolu}), for a system of stochastic damped wave equations, whose solution is constrained to live in the unitary sphere of the space of square-integrable functions on the interval $(0,L)$. The stochastic perturbation is given by a nonlinear multiplicative Gaussian noise, where the stochastic differential is understood in Stratonovich sense. Due to its particular structure, such noise not only conserves $\mathbb{P}$-a.s. the constraint, but also preserves a suitable energy functional. In the limit, we derive a deterministic system, that remains confined to the unit sphere of $L^2$, but includes additional terms. These terms depend on the reproducing kernel of the noise and account for the interaction between the constraint and the particular conservative noise we choose.

math.PR

Well-posedness and invariant measure for quasilinear parabolic SPDE on a bounded domain

We study quasilinear parabolic stochastic partial differential equations with general multiplicative noise on a bounded domain in $\mathbb{R}^{d}$, with homogeneous Dirichlet boundary condition. We establish the existence and uniqueness of solutions in a $L^{1}$ setting, and we prove a comparison result and an $L^{1}$-contraction property for the solutions. In addition, we show the existence of an invariant measure in case of non-degenerate diffusion. Finally, we show the uniqueness and ergodicity of the invariant measure in $L^{1}$, in case of bounded diffusion and additive noise.

math.PR

On the small-mass limit for stationary solutions of stochastic wave equations with state dependent friction

We investigate the convergence, in the small mass limit, of the stationary solutions of a class of stochastic damped wave equations, where the friction coefficient depends on the state and the noisy perturbation if of multiplicative type. We show that the Smoluchowski-Kramers approximation that has been previously shown to be true in any fixed time interval, is still valid in the long time regime. Namely we prove that the first marginals of any sequence of stationary solutions for the damped wave equation converge to the unique invariant measure of the limiting stochastic quasilinear parabolic equation. The convergence is proved with respect to the Wasserstein distance associated with the $H^{-1}$ norm.

math.PR

Inference of high quantiles of a heavy-tailed distribution from block data

In this paper we consider the estimation problem for high quantiles of a heavy-tailed distribution from block data when only a few largest values are observed within blocks. We propose estimators for high quantiles and prove that these estimators are asymptotically normal. Furthermore, we employ empirical likelihood method and adjusted empirical likelihood method to constructing the confidence intervals of high quantiles. Through a simulation study we also compare the performance of the normal approximation method and the adjusted empirical likelihood methods in terms of the coverage probability and length of the confidence intervals.

math.ST

Spectral Radii of Products of Random Rectangular Matrices

We consider m independent random rectangular matrices whose entries are independent and identically distributed standard complex Gaussian random variables. Assume the product of the m rectangular matrices is an n by n square matrix. The maximum absolute values of the n eigenvalues of the product matrix is called spectral radius. In this paper, we study the limiting spectral radii of the product when m changes with n and can even diverge. We give a complete description for the limiting distribution of the spectral radius. Our results reduce to those in Jiang and Qi [26] when the rectangular matrices are square ones.

math.PR