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The set of badly approximable $m \times n $ matrices is known to have Hausdorff dimension $mn $. Each such matrix comes with its own approximation constant $c$, and one can ask for the dimension of the set of badly approximable matrices…

Number Theory · Mathematics 2015-10-12 Ryan Broderick , Dmitry Kleinbock

We present a new technique in order to quantify the dynamics of spatially extended systems. Using a test on the existence of unstable periodic orbits, we identify intermediate spatial scales, wherein the dynamics is characterized by maximum…

chao-dyn · Physics 2008-02-03 G. Zoeller , R. Engbert , S. Hainzl , J. Kurths

In this paper we investigate the Erd\"os/Falconer distance conjecture for a natural class of sets statistically, though not necessarily arithmetically, similar to a lattice. We prove a good upper bound for spherical means that have been…

Classical Analysis and ODEs · Mathematics 2007-05-23 Alex Iosevich , Misha Rudnev

A measure of primal importance for capturing the serial dependence of a stationary time series at extreme levels is provided by the limiting cluster size distribution. New estimators based on a blocks declustering scheme are proposed and…

Statistics Theory · Mathematics 2020-11-11 Axel Bücher , Tobias Jennessen

In this paper we develop the theory of essential dimension of group schemes over an integral base. Shortly we concentrate over a local base. As a consequence of our theory we give a result of invariance of the essential dimension over a…

Algebraic Geometry · Mathematics 2017-09-08 Dajano Tossici

The uniform infinite planar quadrangulation is an infinite random graph embedded in the plane, which is the local limit of uniformly distributed finite quadrangulations with a fixed number of faces. We study asymptotic properties of this…

Probability · Mathematics 2017-01-05 Jean-François Le Gall , Laurent Ménard

Nonlocal metric dimension ${\rm dim}_{\rm n\ell}(G)$ of a graph $G$ is introduced as the cardinality of a smallest nonlocal resolving set, that is, a set of vertices which resolves each pair of non-adjacent vertices of $G$. Graphs $G$ with…

Combinatorics · Mathematics 2022-11-22 Sandi Klavžar , Dorota Kuziak

Signal scaling is a fundamental operation of practical importance in which a signal is enlarged or shrunk in the coordinate direction(s). Scaling or magnification is not trivial for signals of a discrete variable since the signal values may…

Signal Processing · Electrical Eng. & Systems 2021-01-19 Aykut Koç , Burak Bartan , Haldun M. Ozaktas

In a recent publication we have investigated the spectrum of anomalous dimensions for arbitrary composite operators in the critical N-vector model in 4-epsilon dimensions. We could establish properties like upper and lower bounds for the…

High Energy Physics - Theory · Physics 2009-10-28 Stefan K. Kehrein , Franz Wegner

The (delta-) normal cone to an arbitrary intersection of sublevel sets of proper, lower semicontinuous, and convex functions is characterized, using either epsilon-subdifferentials at the nominal point or exact subdifferentials at nearby…

Optimization and Control · Mathematics 2017-10-30 Abderrahim Hantoute , Anton Svensson

The domain-independent universal Normalized Information Distance based on Kolmogorov complexity has been (in approximate form) successfully applied to a variety of difficult clustering problems. In this paper we investigate theoretical…

Information Theory · Computer Science 2025-07-30 Marcus Hutter

To learn about a physical system of interest, experimental results must be able to discriminate among models. We introduce a geometrical measure to quantify the distance between models for pseudoscalar-meson photoproduction in amplitude…

High Energy Physics - Phenomenology · Physics 2016-06-22 J. Nys , J. Ryckebusch , D. G. Ireland , D. I. Glazier

The magnitude of a metric space is a novel invariant that provides a measure of the 'effective size' of a space across multiple scales, while also capturing numerous geometrical properties, such as curvature, density, or entropy. We develop…

Machine Learning · Computer Science 2025-01-16 Katharina Limbeck , Rayna Andreeva , Rik Sarkar , Bastian Rieck

We study discrete random fields $\{X_t: t\in \mathbb{Z}^d\}$ parameterized on the $d$-dimensional integer lattice $\mathbb{Z}^d$. For a fixed threshold $u$, the excursion set $\{t \in \mathbb{Z}^d : X_t > u\}$ decomposes into connected…

Statistics Theory · Mathematics 2026-01-22 Dan Cheng , John Ginos

In this paper we consider adaptive sampling's local-feature size, used in surface reconstruction and geometric inference, with respect to an arbitrary landmark set rather than the medial axis and relate it to a path-based adaptive metric on…

Computational Geometry · Computer Science 2018-07-24 Nicholas J. Cavanna , Donald R. Sheehy

Lifted maximum rank distance (MRD) codes, which are constant dimension codes, are considered. It is shown that a lifted MRD code can be represented in such a way that it forms a block design known as a transversal design. A slightly…

Information Theory · Computer Science 2016-11-17 Tuvi Etzion , Natalia Silberstein

We establish geometric relationships between the average scale-invariant Cassinian metric and other hyperbolic type metrics. In addition, we study the local convexity properties of the scale-invariant metric balls in Euclidean once…

Metric Geometry · Mathematics 2025-07-29 Manas Mohapatra , Antti Rasila , Matti Vuorinen

In this paper we perform an analytical and numerical study of Extreme Value distributions in discrete dynamical systems that have a singular measure. Using the block maxima approach described in Faranda et al. [2011] we show that,…

Dynamical Systems · Mathematics 2011-06-14 Davide Faranda , Valerio Lucarini , Giorgio Turchetti , Sandro Vaienti

While multiple time scales generally arise in the dynamics of disordered systems, we find multiple time scales in absence of disorder, in a simple model with hard local constraints. The dynamics of the model, which consists of local…

Statistical Mechanics · Physics 2015-06-22 O. Cepas

The pseudo-marginal algorithm is a variant of the Metropolis--Hastings algorithm which samples asymptotically from a probability distribution when it is only possible to estimate unbiasedly an unnormalized version of its density.…

Computation · Statistics 2019-12-04 Sebastian M. Schmon , George Deligiannidis , Arnaud Doucet , Michael K. Pitt
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