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We consider a process given as the solution of a stochastic differential equation with irregular, path dependent and time-inhomogeneous drift coefficient and additive noise. Explicit and optimal bounds for the Lebesgue density of that…

Probability · Mathematics 2015-08-04 David Baños , Paul Krühner

We introduce a natural equivalence relation on the space $\sH_0$ of horofunctions of a word hyperbolic group that take the value 0 at the identity. We show that there are only finitely many ergodic measures that are invariant under this…

Dynamical Systems · Mathematics 2008-07-15 Lewis Phylip Bowen

We study expansive measures for continuous flows without fixed points on compact metric spaces. We provide a new characterization of expansive measures through dynamical balls that, in contrast to the dynamical balls considered in [\emph{J.…

Dynamical Systems · Mathematics 2026-04-30 Eduardo Pedrosa , Elias Rego , Alexandre Trilles

We study the problem of classifying stationary measures and orbit closures for non-abelian action on a surface with a given smooth invariant measure. Using a result of Brown and Rodriguez Hertz, we show that under a certain finite…

Dynamical Systems · Mathematics 2020-06-11 Ping Ngai Chung

This paper studies limit measures of stationary measures of stochastic ordinary differential equations on the Euclidean space and tries to determine which invariant measures of an unperturbed system will survive. Under the assumption for…

Dynamical Systems · Mathematics 2022-01-28 Tianyuan Xu , Lifeng Chen , Jifa Jiang

We address the problem of optimal experimental design (OED) for Bayesian nonlinear inverse problems governed by PDEs. The goal is to find a placement of sensors, at which experimental data are collected, so as to minimize the uncertainty in…

Optimization and Control · Mathematics 2015-11-04 Alen Alexanderian , Noemi Petra , Georg Stadler , Omar Ghattas

We optimize the path of a mobile sensor to minimize the posterior uncertainty of a Bayesian inverse problem. Along its path, the sensor continuously takes measurements of the state, which is a physical quantity modeled as the solution of a…

Computational Engineering, Finance, and Science · Computer Science 2025-09-22 Nicole Aretz , Thomas Lynn , Karen Willcox , Sven Leyffer

We address the weak numerical solution of stochastic differential equations driven by independent Brownian motions (SDEs for short). This paper develops a new methodology to design adaptive strategies for determining automatically the…

Probability · Mathematics 2023-02-10 Carlos M. Mora , Juan Carlos Jimenez , Monica Selva

The method of Hessian measures is used to find the differential equation that defines the optimal shape of nonrotationally symmetric bodies with minimal resistance moving in a rare medium. The synthesis of optimal solutions is described. A…

Optimization and Control · Mathematics 2019-10-08 L. V. Lokutsievskiy , M. I. Zelikin

In many applications, it is often necessary to sample the mean value of certain quantity with respect to a probability measure {\mu} on the level set of a smooth function $\xi: \mathbb{R}^d\rightarrow \mathbb{R}^k$, $1\le k < d$. A…

Probability · Mathematics 2019-09-25 Wei Zhang

The sum of square roots is as follows: Given $x_1,\dots,x_n \in \mathbb{Z}$ and $a_1,\dots,a_n \in \mathbb{N}$ decide whether $ E=\sum_{i=1}^n x_i \sqrt{a_i} \geq 0$. It is a prominent open problem (Problem 33 of the Open Problems Project),…

Computational Geometry · Computer Science 2023-12-05 Friedrich Eisenbrand , Matthieu Haeberle , Neta Singer

Ergodic Optimization is the process of finding invariant probability measures that maximize the integral of a given function. It has been conjectured that "most" functions are optimized by measures supported on a periodic orbit, and it has…

Dynamical Systems · Mathematics 2015-03-17 Anthony Quas , Jason Siefken

Consider the following stochastic differential equation for $(X_t)_{t\ge 0}$ on $\mathbb R^d$ and its Euler-Maruyama (EM) approximation $(Y_{t_n})_{n\in \mathbb Z^+}$: \begin{align*} &d X_t=b( X_t) d t+\sigma(X_t) d B_t, \\ &…

Probability · Mathematics 2023-10-03 Xiang Li , Feng-Yu Wang , Lihu Xu

Avikainen provided a sharp upper bound of the difference $\mathbb{E}[|g(X)-g(\widehat{X})|^{q}]$ by the moments of $|X-\widehat{X}|$ for any one-dimensional random variables $X$ with bounded density and $\widehat{X}$, and function of…

Probability · Mathematics 2020-03-09 Dai Taguchi

Building on results developed in https://doi.org/10.48550/arXiv.2404.14902, where It\^{o}-SDEs with possibly degenerate and discontinuous dispersion coefficient and measurable drift were analyzed with respect to a given (sub-)invariant…

Probability · Mathematics 2024-05-21 Haesung Lee , Gerald Trutnau

We give a sufficient condition on nonlinearities of an SDE on a compact connected Riemannian manifold $M$ which implies that laws of all solutions converge weakly to the normalized Riemannian volume measure on $M$. This result is further…

Probability · Mathematics 2019-05-28 Lubomir Banas , Zdzislaw Brzezniak , Martin Ondrejat , Andreas Prohl

In this paper, we will focus - in dimension one - on the SDEs of the type dX_t=s(X_t)dB_t+b(X_t)dt where B is a fractional Brownian motion. Our principal motivation is to describe one of the simplest theory - from our point of view -…

Probability · Mathematics 2007-10-18 Ivan Nourdin

We are interested in the following two $\mathbb{R}^d$-valued stochastic differential equations (SDEs): \begin{gather*} d X_t=b(X_t)\,d t + \sigma\,d L_t, \quad X_0=x, %\label{BM-SDE} d Y_t=b(Y_t)\,d t + \sigma\,d B_t, \quad Y_0=y,…

Probability · Mathematics 2024-03-06 Changsong Deng , Rene L. Schilling , Lihu Xu

Consider a parabolic SPDE \[ \partial_t u = \Delta u + \sigma(u)\eta, \] on $(0\,,\infty)\times\mathbb{R}^d$, where $\eta$ is a centered, generalized Gaussian noise with $\text{Cov}[\eta(t\,,x)\,,\eta(s\,,y)]=\delta_0(t-s)\Lambda(x-y)$ for…

Probability · Mathematics 2026-03-20 Mathew Joseph , Davar Khoshnevisan , Kunwoo Kim , Carl Mueller

We establish high probability estimates on the eigenvalue locations of Brownian motion on the $N$-dimensional unitary group, as well as estimates on the number of eigenvalues lying in any interval on the unit circle. These estimates are…

Probability · Mathematics 2023-02-22 Arka Adhikari , Benjamin Landon