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Related papers: On measures strongly log-concave on a subspace

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The use of geometrical constraints opens many new perspectives in photonics and in fundamental studies of nonlinear waves. By implementing surface structures in vertical cavity surface emitting lasers as manifolds for curved space, we…

We investigate the existence of invariant measures for self-stabilizing diffusions. These stochastic processes represent roughly the behavior of some Brownian particle moving in a double-well landscape and attracted by its own law. This…

Probability · Mathematics 2009-03-16 Samuel Herrmann Julian Tugaut

We study topological properties of random metric spaces which arise by Lambda-coalescents. These are stochastic processes, which start with an infinite number of lines and evolve through multiple mergers in an exchangeable setting. We show…

Probability · Mathematics 2011-05-13 Holger F. Biehler , Peter Pfaffelhuber

We consider the inverse problem of the detection of a single body, immersed in a bounded container filled with a fluid which obeys the Stokes equations, from a single measurement of force and velocity on a portion of the boundary. We obtain…

Analysis of PDEs · Mathematics 2015-05-18 Andrea Ballerini

Caffarelli's contraction theorem bounds the derivative of the optimal transport map between a log-convex measure and a strongly log-concave measure. We show that an analogous phenomenon holds on the level of the trace: The trace of the…

Analysis of PDEs · Mathematics 2025-11-26 Guido De Philippis , Yair Shenfeld

We present a novel, log-radius profile representation for convex curves and define a new operation for combining the shape features of curves. Unlike the standard, angle profile-based methods, this operation accurately combines the shape…

Graphics · Computer Science 2015-06-25 Dongsung Huh

The space of smooth curves admits a beautiful compactification by the moduli space of Deligne-Mumford stable curves. In this paper, we undertake a systematic investigation of alternate modular compactifications of the space of smooth…

Algebraic Geometry · Mathematics 2009-12-02 David Ishii Smyth

This article deals with the realisation of constraints in underdamped Langevin dynamics via soft-constrained dynamics. Specifically, we study systems with a large (or small) parameter that controls the constraint mechanisms, e.g. the…

Probability · Mathematics 2026-04-03 Carsten Hartmann , Lara Neureither , Upanshu Sharma

For a real or complex one-dimensional map satisfying a weak hyperbolicity assumption, we study the existence and statistical properties of physical measures, with respect to geometric reference measures. We also study geometric properties…

Dynamical Systems · Mathematics 2014-06-12 Juan Rivera-Letelier , Weixiao Shen

Lie scale invariance is used to reduce the incompressible Navier-Stokes equations to non-linear ordinary equations. This yields a formulation in terms of logarithmic spirals as independent variables. We give the equations when the spirals…

Fluid Dynamics · Physics 2025-04-29 Richard Henriksen

We introduce a notion of vague convergence for random marked metric measure spaces. Our main result shows that convergence of the moments of order $k \ge 1$ of a random marked metric measure space is sufficient to obtain its vague…

Probability · Mathematics 2024-12-23 Félix Foutel-Rodier

Log-concave distributions are an attractive choice for modeling and inference, for several reasons: The class of log-concave distributions contains most of the commonly used parametric distributions and thus is a rich and flexible…

Methodology · Statistics 2010-10-05 Guenther Walther

We propose and develop a measurement scheme for quantum field theory (QFT) in curved spacetimes, in which the QFT of interest, the "system", is dynamically coupled to another, the "probe", in a compact spacetime region. Measurements of…

General Relativity and Quantum Cosmology · Physics 2019-04-16 Christopher J. Fewster

We show the existence of Lebesgue-equivalent conservative and ergodic $\sigma$-finite invariant measures for a wide class of one-dimensional random maps consisting of piecewise convex maps. We also estimate the size of invariant measures…

Dynamical Systems · Mathematics 2023-03-21 Tomoki Inoue , Hisayoshi Toyokawa

Spontaneous strain localization occurs during mechanical tests of a model amorphous solid simulated using molecular dynamics. The degree of localization depends upon the extent of structural relaxation prior to mechanical testing. In the…

Materials Science · Physics 2007-05-23 Yunfeng Shi , Michael L. Falk

Extending results of Harg{\'e} and Hu for the Gaussian measure, we prove inequalities for the covariance Cov$_\mu(f, g)$ where $\mu$ is a general product probability measure on $\mathbb{R}^d$ and $f,g: \mathbb{R}^d \to \mathbb{R}$ satisfy…

Probability · Mathematics 2023-02-13 Michel Bonnefont , Erwan Hillion , Adrien Saumard

Given a suitably normalized $X\in\mathbb{R}^n$ we observe that the function $\theta\mapsto\mathbb{E}|X\cdot\theta|$, defined for $\theta\in S^{n-1}$, admits surprisingly strong concentration far surpassing what is expected on account of…

Functional Analysis · Mathematics 2020-08-04 Erez Buchweitz

Existence of solution of the logarithmic Minkowski problem is proved for the case where the discrete measures on the unit sphere satisfy the subspace concentration condition with respect to some special proper subspaces. In order to…

Metric Geometry · Mathematics 2015-06-04 Karoly J. Boroczky , Pal Hegedus , Guangxian Zhu

We develop a general framework to study concavity properties of weighted marginals of $\beta$-concave functions on $\mathbb{R}^n$ via local methods. As a concrete implementation of our approach, we obtain a functional version of the…

Functional Analysis · Mathematics 2025-06-23 Dario Cordero-Erausquin , Alexandros Eskenazis

In this paper, we investigate a continuous time version of the Stochastic Langevin Monte Carlo method, introduced in [WT11], that incorporates a stochastic sampling step inside the traditional over-damped Langevin diffusion. This method is…

Machine Learning · Statistics 2023-01-10 Marelys Crespo Navas , Sébastien Gadat , Xavier Gendre