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Consider a dominant rational self-map $f$ on a smooth projective variety $X$ defined over $\overline{\mathbb{Q}}$. We prove that \begin{align} \lim_{n \to \infty} \frac{h_{Y}(f^{n}(x))}{h_{H}(f^{n}(x)) } = 0, \end{align} where $h_{Y}$ is a…

Algebraic Geometry · Mathematics 2025-07-08 Yohsuke Matsuzawa

In this paper, we propose a control design methodology for a linearized continuum traffic model in the congested regime. The continuum traffic flow on a highway is modeled using a linearized quasilinear hyperbolic partial differential…

Optimization and Control · Mathematics 2019-11-11 Stephen Chen , Huan Yu , Miroslav Krstic

We consider a random walk $(Y_N)_{N\geq 0}$ on $\mathbb{R}^2$ generated by successively applying independent random isometries, drawn from a fixed measure $\mu$, to the point $0$. When the support of $\mu$ is finite and includes an…

Probability · Mathematics 2026-01-26 Reuben Drogin , Felipe Hernández

Many interesting physical theories have analytic classical actions. We show how Feynman's path integral may be defined non-perturbatively, for such theories, without a Wick rotation to imaginary time. We start by introducing a class of…

High Energy Physics - Theory · Physics 2023-05-17 Job Feldbrugge , Neil Turok

Optimal Transport (OT) problems are a cornerstone of many applications, but solving them is computationally expensive. To address this problem, we propose UNOT (Universal Neural Optimal Transport), a novel framework capable of accurately…

Machine Learning · Computer Science 2026-02-11 Jonathan Geuter , Gregor Kornhardt , Ingimar Tomasson , Vaios Laschos

We consider a nonlinear control system depending on two controls u and v, with dynamics affine in the (unbounded) derivative of u, and v appearing initially only in the drift term. Recently, motivated by applications to optimization…

Optimization and Control · Mathematics 2017-06-02 Monica Motta , Caterina Sartori

In this article we show a robustness theorem for controlled stochastic differential equations driven by approximations of Brownian motion. Often, Brownian motion is used as an idealized model of a diffusion where approximations such as…

Optimization and Control · Mathematics 2023-12-07 Somnath Pradhan , Zachary Selk , Serdar Yüksel

We derive a universal nonperturbative bound on the distance between unitary evolutions generated by time-dependent Hamiltonians in terms of the difference of their integral actions. We apply our result to provide explicit error bounds for…

Quantum Physics · Physics 2022-06-15 Daniel Burgarth , Paolo Facchi , Giovanni Gramegna , Kazuya Yuasa

In this paper, uniformly unconditionally stable first and second order finite difference schemes are developed for kinetic transport equations in the diffusive scaling. We first derive an approximate evolution equation for the macroscopic…

Numerical Analysis · Mathematics 2022-11-10 Guoliang Zhang , Hongqiang Zhu , Tao Xiong

In this work, a boundary control problem for the following generalized Burgers-Huxley (GBH) equation: $$u_t=\nu u_{xx}-\alpha u^{\delta}u_x+\beta u(1-u^{\delta})(u^{\delta}-\gamma), $$ where $\nu,\alpha,\beta>0,$ $1\leq\delta<\infty$,…

Analysis of PDEs · Mathematics 2023-11-14 Shri Lal Raghudev Ram Singh , Manil T. Mohan

We study fundamental theoretical aspects of probabilistic roadmaps (PRM) in the finite time (non-asymptotic) regime. In particular, we investigate how completeness and optimality guarantees of the approach are influenced by the underlying…

Data Structures and Algorithms · Computer Science 2019-09-24 Matthew Tsao , Kiril Solovey , Marco Pavone

We study the fundamental computational problem of approximating optimal transport (OT) equations using neural differential equations (Neural ODEs). More specifically, we develop a novel framework for approximating unbalanced optimal…

Numerical Analysis · Mathematics 2026-05-21 Minh-Nhat Phung , Minh-Binh Tran

Deep reinforcement learning (DRL) allows a system to interact with its environment and take actions by training an efficient policy that maximizes self-defined rewards. In autonomous driving, it can be used as a strategy for high-level…

Robotics · Computer Science 2024-07-02 Xibo Li , Shruti Patel , Christof Büskens

We study time-dependent density fluctuations in the stationary state of driven diffusive systems with two conserved densities $\rho_\lambda$. Using Monte-Carlo simulations of two coupled single-lane asymmetric simple exclusion processes we…

Statistical Mechanics · Physics 2016-08-08 V. Popkov , J. Schmidt , G. M. Schütz

The Universal Approximation Theorem (UAT) guarantees universal function approximation but does not explain how residual models distribute approximation across layers. We reframe residual networks as a layer-wise approximation process that…

Machine Learning · Computer Science 2026-04-28 Wei Wang , Xiao-Yong Wei , Qing Li

We propose a novel method to generate a small set of ruled surfaces that do not collide with the input shape for linear hot-wire rough machining. Central to our technique is a new observation: the ruled surfaces constructed by vertical…

Computational Geometry · Computer Science 2025-09-03 Zheng Zhang , Kang Wu , Yi-Fei Li , Xu Liu , Xiang Wang , Ligang Liu , Xiao-Ming Fu

The Central Limit Theorem (CLT) establishes that sufficiently large sequences of independent and identically distributed random variables converge in probability to a normal distribution. This makes the CLT a fundamental building block of…

Logic in Computer Science · Computer Science 2026-03-10 Henning Basold , Oisín Flynn-Connolly , Chase Ford , Hao Wang

We study the center problem for the class $\mathcal E_\Gamma$ of Abel differential equations $\frac{dv}{dt}=a_1 v^2+a_2 v^3$, $a_1,a_2\in L^\infty ([0,T])$, such that images of Lipschitz paths $\tilde A:=\bigl(\int_0^\cdot a_1(s)ds,…

Classical Analysis and ODEs · Mathematics 2019-02-20 Alexander Brudnyi

Understanding and adhering to soft constraints is essential for safe and socially compliant autonomous driving. However, such constraints are often implicit, context-dependent, and difficult to specify explicitly. In this work, we present…

Robotics · Computer Science 2025-08-07 Longling Geng , Huangxing Li , Viktor Lado Naess , Mert Pilanci

We study solutions to backward differential equations that are driven hybridly by a deterministic discontinuous rough path $W$ of finite $q$-variation for $q \in [1, 2)$ and by Brownian motion $B$. To distinguish between integration of…

Probability · Mathematics 2025-05-28 Dirk Becherer , Yuchen Sun