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The goal of this paper is to exhibit and analyze an algorithm that takes a given closed orientable hyperbolic surface and outputs an explicit Dirichlet domain. The input is a fundamental polygon with side pairings. While grounded in…

Computational Geometry · Computer Science 2022-12-06 Vincent Despré , Benedikt Kolbe , Hugo Parlier , Monique Teillaud

We present some new bounds for the first Robin eigenvalue with a negative boundary parameter. These include the constant volume problem, where the bounds are based on the shrinking coordinate method, and a proof that in the fixed perimeter…

Spectral Theory · Mathematics 2018-11-26 Pedro R. S. Antunes , Pedro Freitas , David Krejcirik

We give meaning to linear and semi-linear (possibly degenerate) parabolic partial differential equations with (affine) linear rough path noise and establish stability in a rough path metric. In the case of enhanced Brownian motion (Brownian…

Probability · Mathematics 2013-01-17 Peter Friz , Harald Oberhauser

We give short proofs of two classical results about the position of the extremal particle in a branching Brownian motion, one concerning the median position and another the almost sure behaviour.

Probability · Mathematics 2013-10-04 Matthew I. Roberts

We construct quantum effective action in spacetime with branes/boundaries. This construction is based on the reduction of the underlying Neumann type boundary value problem for the propagator of the theory to that of the much more…

High Energy Physics - Theory · Physics 2008-11-26 A. O. Barvinsky , D. V. Nesterov

We discuss a method of parameter reduction in complex models known as the Manifold Boundary Approximation Method (MBAM). This approach, based on a geometric interpretation of statistics, maps the model reduction problem to a geometric…

Data Analysis, Statistics and Probability · Physics 2016-05-30 Mark K. Transtrum

The Material Point Method (MPM) is a hybrid Eulerian-Lagrangian approach capable of simulating large deformation problems of history-dependent materials. While the MPM can represent complex and evolving material domains by using Lagrangian…

Geophysics · Physics 2019-10-01 Ezra Y. S. Tjung , Shyamini Kularathna , Krishna Kumar , Kenichi Soga

Excursion reflected Brownian motion (ERBM) is a strong Markov process defined in a finitely connected domain $D \subset \C$ that behaves like a Brownian motion away from the boundary of $D$ and picks a point according to harmonic measure…

Probability · Mathematics 2011-12-21 Shawn Drenning

This is the second in a series of three papers in which we initiate the study of very rough solutions to the initial value problem for the Einstein vacuum equations expressed relative to wave coordinates. By very rough we mean solutions…

Analysis of PDEs · Mathematics 2016-09-07 S. Klainerman , I. Rodnianski

We develop a rigorous mathematical framework for the weak formulation of cracked beams and shallow arches problems. First, we discuss the crack modeling by means of massless rotational springs. Then we introduce Hilbert spaces, which are…

Analysis of PDEs · Mathematics 2022-07-13 Semion Gutman , Junhong Ha , Sudeok Shon

In this paper, we investigate the behavior of the eigenvalues of a magnetic Aharonov-Bohm operator with half-integer circulation and Dirichlet boundary conditions in a bounded planar domain. We establish a sharp relation between the rate of…

Analysis of PDEs · Mathematics 2016-06-01 Laura Abatangelo , Veronica Felli , Benedetta Noris , Manon Nys

Using sharp global heat kernel bounds and geodesic comparison geometry, we show that the Dalang condition for well-posedness of the parabolic Anderson model with measure-valued initial conditions, first introduced on Euclidean space, holds…

Probability · Mathematics 2026-03-31 Hongyi Chen , Robert Neel , Cheng Ouyang

We establish strong uniqueness for a class of degenerate SDEs of weak H{\"o}rmander type under suitable H{\"o}lder regularity conditions for the associated drift term. Our approach relies on the Zvonkin transform which requires to exhibit…

Probability · Mathematics 2020-09-30 Paul-Eric Chaudru de Raynal , Igor Honoré , Stephane Menozzi

In this paper, we study discrete approximation of reflected Brownian motions on domains in Euclidean space. Our approximation is given by a sequence of Markov chains on partitions of the domain, where we allow uneven or random partitions.…

Probability · Mathematics 2025-04-09 Masanori Hino , Arata Maki , Kouhei Matsuura

In this article we obtain new rigidity results for spacelike submanifolds of arbitrary codimension in Generalized Robertson-Walker spacetimes. Namely, under appropriate assumptions such as parabolicity we prove by means of some maximum…

General Relativity and Quantum Cosmology · Physics 2024-01-31 José A. S. Pelegrín

This article develops direct and inverse estimates for certain finite dimensional spaces arising in kernel approximation. Both the direct and inverse estimates are based on approximation spaces spanned by local Lagrange functions which are…

Numerical Analysis · Mathematics 2017-09-08 Thomas Hangelbroek , Francis J. Narcowich , Christian Rieger , Joseph D. Ward

We introduce a constrained optimal transport problem where origins $x$ can only be transported to destinations $y\geq x$. Our statistical motivation is to describe the sharp upper bound for the variance of the treatment effect $Y-X$ given…

Optimization and Control · Mathematics 2021-06-22 Marcel Nutz , Ruodu Wang

In this paper, we investigate an optimal design problem motivated by some issues arising in population dynamics. In a nutshell, we aim at determining the optimal shape of a region occupied by resources for maximizing the survival ability of…

Analysis of PDEs · Mathematics 2017-09-08 Fabien Caubet , Thibaut Deheuvels , Yannick Privat

We show that the de Rham Hilbert complex with mixed boundary conditions on bounded strong Lipschitz domains is closed and compact. The crucial results are compact embeddings which follow by abstract arguments using functional analysis…

Analysis of PDEs · Mathematics 2022-03-14 Dirk Pauly , Michael Schomburg

Using rough path techniques, we provide a priori estimates for the output of Deep Residual Neural Networks in terms of both the input data and the (trained) network weights. As trained network weights are typically very rough when seen as…

Machine Learning · Computer Science 2023-02-22 Christian Bayer , Peter K. Friz , Nikolas Tapia
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