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We prove the Ramsey property for classes of ordered structures with closures and given local properties. This generalises earlier results: the Ne\v{s}et\v{r}il-R\"odl Theorem, the Ramsey property of partial orders and metric spaces as well…

Combinatorics · Mathematics 2019-09-04 Jan Hubička , Jaroslav Nešetřil

We study the electronic instabilities in a 2D Hubbard model where one of the dimensions has a finite width, so that it can be considered as a large array of coupled chains. The finite transverse size of the system gives rise to a discrete…

Strongly Correlated Electrons · Physics 2009-11-13 E. Perfetto , J. Gonzalez

Normalization Layers (NLs) are widely used in modern deep-learning architectures. Despite their apparent simplicity, their effect on optimization is not yet fully understood. This paper introduces a spherical framework to study the…

Machine Learning · Computer Science 2022-05-20 Simon Roburin , Yann de Mont-Marin , Andrei Bursuc , Renaud Marlet , Patrick Pérez , Mathieu Aubry

Information-theoretic quantities such as Renyi entropies show a remarkable universality in their late-time behaviour across a variety of chaotic many-body systems. Understanding how such common features emerge from very different…

Statistical Mechanics · Physics 2026-02-02 Shreya Vardhan , Sanjay Moudgalya

Townsend's attached eddy hypothesis models the logarithmic region of high Reynolds number wall turbulence as a random superposition of wall-attached, geometrically self-similar eddies whose sizes obey a scale-invariant population law.…

Fluid Dynamics · Physics 2026-04-21 Karthik Duraisamy

Recently it has been established that asymptotic incoherence can be used to facilitate subsampling, in order to optimize reconstruction quality, in a variety of continuous compressed sensing problems, and the coherence structure of certain…

Information Theory · Computer Science 2016-10-25 Alex Jones , Ben Adcock , Anders Hansen

It was conjectured that any neural network of any structure and arbitrary differentiable transfer functions at the nodes cannot learn the following problem sample efficiently when trained with gradient descent: The instances are the rows of…

Machine Learning · Computer Science 2020-10-20 Manfred K. Warmuth , Wojciech Kotłowski , Ehsan Amid

The classical dynamics and pulse propagation are presented for a series of lattice-like structures whose spatial dimensionality ranges from one to four: four representing a hyper lattice. The lattices are connected one-dimensional wave…

Mathematical Physics · Physics 2017-03-08 Joseph W. Dickey

Networks with nodes embedded in a metric space have gained increasing interest in recent years. The effects of spatial embedding on the networks' structural characteristics, however, are rarely taken into account when studying their…

Physics and Society · Physics 2016-07-06 Marc Wiedermann , Jonathan F. Donges , Jürgen Kurths , Reik V. Donner

We study the class of nonholonomic mechanical systems formed by a heavy symmetric ball that rolls without sliding on a surface of revolution, which is either at rest or rotates about its (vertical) figure axis with uniform angular velocity.…

Mathematical Physics · Physics 2022-10-05 Marco Dalla Via , Francesco Fassò , Nicola Sansonetto

Robust and semiparametric statistics are of the same historical origin and largely employ the same locally asymptotically normal framework. In our talk, we consider he following more intrinsic connections of both fields: 1) Robust influence…

Statistics Theory · Mathematics 2013-06-25 Helmut Rieder

Modern neural networks exhibit a striking property: basins of attraction in the loss landscape are often connected by low-loss paths, yet optimization dynamics generally remain confined to a single convex basin and rarely explore…

Machine Learning · Computer Science 2026-03-13 Luca Di Carlo , Chase Goddard , David J. Schwab

Consider a random hypergraph on a set of N vertices in which, for k between 1 and N, a Poisson(N beta_k) number of hyperedges is scattered randomly over all subsets of size k. We collapse the hypergraph by running the following algorithm to…

Probability · Mathematics 2007-05-23 Christina Goldschmidt , James Norris

A tiling of $\mathbb{R}^d$ is repulsive if no $r$-patch can repeat arbitrarily close to itself, relative to $r$. This is a characteristic property of aperiodic order, for a non repulsive tiling has arbitrarily large local periodic patterns.…

Metric Geometry · Mathematics 2014-10-29 J. Savinien

We reconstruct entanglement thermodynamics by means of Hessian geometry, since this method exactly generalizes thermodynamics into much wider exponential family cases including quantum entanglement. Starting with the correct first law of…

High Energy Physics - Theory · Physics 2015-08-12 Hiroaki Matsueda

We deal with the solution of the forward problem for high-dimensional parabolic PDEs with random feature (projection) neural networks (RFNNs). We first prove that there exists a single-hidden layer neural network with randomized…

Numerical Analysis · Mathematics 2025-11-04 Kyriakos Georgiou , Gianluca Fabiani , Constantinos Siettos , Athanasios N. Yannacopoulos

High-dimensional sparse modeling via regularization provides a powerful tool for analyzing large-scale data sets and obtaining meaningful, interpretable models. The use of nonconvex penalty functions shows advantage in selecting important…

Methodology · Statistics 2016-05-12 Zemin Zheng , Yingying Fan , Jinchi Lv

We prove that singularities of area minimizing hypersurfaces can be perturbed away in ambient dimensions 9 and 10.

Differential Geometry · Mathematics 2026-03-17 Otis Chodosh , Christos Mantoulidis , Felix Schulze

Two-dimensional random tilings of rhombi can be seen as projections of two-dimensional membranes embedded in hypercubic lattices of higher dimensional spaces. Here, we consider tilings projected from a $D$-dimensional space. We study the…

Statistical Mechanics · Physics 2016-08-31 N. Destainville , M. Widom , R. Mosseri , F. Bailly

In one dimension, any disorder is traditionally believed to localize all states. We show that this paradigm breaks down under hyperuniform disorder, which suppresses long-wavelength fluctuations and interpolates between random and periodic…

Disordered Systems and Neural Networks · Physics 2025-09-30 Junmo Jeon , Harukuni Ikeda , Shiro Sakai