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Given a n-dimensional lamination endowed with a Riemannian metric, we introduce the notion of a multiplicative cocycle of rank d, where n and d are arbitrary positive integers. The holonomy cocycle of a foliation and its exterior powers as…

Dynamical Systems · Mathematics 2015-04-30 Viet-Anh Nguyen

Here, we study the coalescence of two droplets that are moving in the same direction on a soft surface; the motion of the droplets is caused by a gradient in the surface stiffness. As reference, stationary coalescence of the same droplets…

Soft Condensed Matter · Physics 2026-05-19 Divyansh Tripathi , Vimal Kishore , Panagiotis E. Theodorakis , Swarn Lata Singh

Stochastic dynamics is generated by a matrix of transition probabilities. Certain eigenvectors of this matrix provide observables, and when these are plotted in the appropriate multi-dimensional space the phases (in the sense of phase…

Statistical Mechanics · Physics 2007-11-08 B. Gaveau , L. S. Schulman

Just as point objects are parallel transported along curves, giving holonomies, string-like objects are parallel transported along surfaces, giving surface holonomies. Composition of these surfaces correspond to products in a category…

High Energy Physics - Theory · Physics 2015-06-26 Amitabha Lahiri

The collection of $d \times N$ complex matrices with prescribed column norms and prescribed (nonzero) singular values forms a compact algebraic variety, which we refer to as a frame space. Elements of frame spaces -- i.e., frames -- are…

Functional Analysis · Mathematics 2022-08-25 Tom Needham , Clayton Shonkwiler

An investigation of the effect of surface diffusion in random deposition model is made by analytical methods and reasoning. For any given site, the extent to which a particle can diffuse is decided by the morphology in the immediate…

Soft Condensed Matter · Physics 2011-12-14 Baisakhi Mal , Subhankar Ray , J. Shamanna

We introduce a new framework to analyze shape descriptors that capture the geometric features of an ensemble of point clouds. At the core of our approach is the point of view that the data arises as sampled recordings from a metric…

Statistics Theory · Mathematics 2024-09-11 Anne van Delft , Andrew J. Blumberg

In this paper we develop an abstract theory for the Codazzi equation on surfaces, and use it as an analytic tool to derive new global results for surfaces in the space forms ${\bb R}^3$, ${\bb S}^3$ and ${\bb H}^3$. We give essentially…

Differential Geometry · Mathematics 2009-02-16 Juan A. Aledo , José M. Espinar , José A. Gálvez

We consider the two problems of predicting links in a dynamic graph sequence and predicting functions defined at each node of the graph. In many applications, the solution of one problem is useful for solving the other. Indeed, if these…

Machine Learning · Computer Science 2012-03-27 Emile Richard , Andreas Argyriou , Theodoros Evgeniou , Nicolas Vayatis

In this paper, we perform a detailed investigation on the various geometrical properties of trapped surfaces and the boundaries of trapped region in general relativity. This treatment extends earlier work on LRS II spacetimes to a general 4…

General Relativity and Quantum Cosmology · Physics 2018-05-16 Abbas Sherif , Rituparno Goswami , Sunil D Maharaj

We introduce a stochastic model of diffeomorphisms, whose action on a variety of data types descends to stochastic evolution of shapes, images and landmarks. The stochasticity is introduced in the vector field which transports the data in…

Computer Vision and Pattern Recognition · Computer Science 2018-10-23 Alexis Arnaudon , Darryl D. Holm , Stefan Sommer

Inspired by the prospect of having discretized spaces emerge from random graphs, we construct a collection of simple and explicit exponential random graph models that enjoy, in an appropriate parameter regime, a roughly constant vertex…

Disordered Systems and Neural Networks · Physics 2021-10-01 Pawat Akara-pipattana , Thiparat Chotibut , Oleg Evnin

We propose a simple mechanism by which scaling laws emerge from feature learning in multi-layer networks. We study a high-dimensional hierarchical target that is a globally high-degree function, but that can be represented by a combination…

Machine Learning · Statistics 2026-05-15 Arie Wortsman-Zurich , Hugo Tabanelli , Yatin Dandi , Florent Krzakala , Bruno Loureiro

While the phenomenon of grokking, i.e., delayed generalization, has been studied extensively, it remains an open problem whether there is a mathematical framework that characterizes what kind of features will emerge, how and in which…

Machine Learning · Computer Science 2025-12-03 Yuandong Tian

Regularization is used in many different areas of optimization when solutions are sought which not only minimize a given function, but also possess a certain degree of regularity. Popular applications are image denoising, sparse regression…

Optimization and Control · Mathematics 2021-11-15 Bennet Gebken , Katharina Bieker , Sebastian Peitz

In this paper, we study Bertrand surface offsets by considering the dual geodesic trihedron(dual Darboux frame) of the ruled surfaces. We obtain the relationships between the invariants of Bertrand trajectory ruled surfaces. Furthermore, we…

Differential Geometry · Mathematics 2015-07-13 Mehmet Önder

Accretion of mineralized thin wall-like structures via localized growth along their edges is observed in a range of physical and biological systems ranging from molluscan and brachiopod shells to carbonate-silica composite precipitates. To…

Soft Condensed Matter · Physics 2022-02-23 C. Nadir Kaplan , L. Mahadevan

This work investigates slant timelike-ruled surfaces and their evolute offsets in Minkowski 3-space $\mathbb{E}_{1}^{3}$. Using the symmetry of evolute curves, we derive a parametric formulation for skew timelike-ruled surfaces and…

Differential Geometry · Mathematics 2025-03-28 Areej A. Almoneef , Rashad A. Abdel-baky

We propose a novel approach to continuum modelling of dynamics of crystal surfaces. Our model follows the evolution of an ensemble of step configurations, which are consistent with the macroscopic surface profile. Contrary to the usual…

Statistical Mechanics · Physics 2007-05-23 Navot Israeli , Daniel Kandel

We present a framework to define a large class of neural networks for which, by construction, training by gradient flow provably reaches arbitrarily low loss when the number of parameters grows. Distinct from the fixed-space global…

Optimization and Control · Mathematics 2025-01-13 David A. R. Robin , Kevin Scaman , Marc Lelarge