scholarly journals Assouad Spectrum Thresholds for Some Random Constructions

2019 ◽  
Vol 63 (2) ◽  
pp. 434-453 ◽  
Author(s):  
Sascha Troscheit
Keyword(s):  
Scaling Function ◽  
Threshold Function ◽  
Similar Model ◽  
Scaling Properties ◽  
Fractal Sets ◽  
Box Counting ◽  
Random Fractal ◽  
Assouad Dimension ◽  
Self Similar ◽  
Gromov Boundary

AbstractThe Assouad dimension of a metric space determines its extremal scaling properties. The derived notion of the Assouad spectrum fixes relative scales by a scaling function to obtain interpolation behaviour between the quasi-Assouad and the box-counting dimensions. While the quasi-Assouad and Assouad dimensions often coincide, they generally differ in random constructions. In this paper we consider a generalised Assouad spectrum that interpolates between the quasi-Assouad and the Assouad dimension. For common models of random fractal sets, we obtain a dichotomy of its behaviour by finding a threshold function where the quasi-Assouad behaviour transitions to the Assouad dimension. This threshold can be considered a phase transition, and we compute the threshold for the Gromov boundary of Galton–Watson trees and one-variable random self-similar and self-affine constructions. We describe how the stochastically self-similar model can be derived from the Galton–Watson tree result.

scholarly journals Hausdorff measure and Assouad dimension of generic self-conformal IFS on the line

2020 ◽  
pp. 1-31
Author(s):  
Balázs Bárány ◽  
Károly Simon ◽  
István Kolossváry ◽  
Michał Rams
Keyword(s):  
Hausdorff Measure ◽  
Similar Case ◽  
Iterated Function Systems ◽  
The Self ◽  
Dimensional Hausdorff Measure ◽  
Assouad Dimension ◽  
Iterated Function ◽  
Self Similar ◽  
Weak Separation ◽  
Topological Sense

This paper considers self-conformal iterated function systems (IFSs) on the real line whose first level cylinders overlap. In the space of self-conformal IFSs, we show that generically (in topological sense) if the attractor of such a system has Hausdorff dimension less than 1 then it has zero appropriate dimensional Hausdorff measure and its Assouad dimension is equal to 1. Our main contribution is in showing that if the cylinders intersect then the IFS generically does not satisfy the weak separation property and hence, we may apply a recent result of Angelevska, Käenmäki and Troscheit. This phenomenon holds for transversal families (in particular for the translation family) typically, in the self-similar case, in both topological and in measure theoretical sense, and in the more general self-conformal case in the topological sense.

Fractal and Convolutional Analysis for Deep Atmospheric Turbulence Using Machine Learning

2021 ◽  
Author(s):  
Nicholas Dudu ◽  
Arturo Rodriguez ◽  
Gael Moran ◽  
Jose Terrazas ◽  
Richard Adansi ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Atmospheric Turbulence ◽  
Isotropic Turbulence ◽  
Passive Scalar ◽  
Counting Method ◽  
Data Set ◽  
Box Counting ◽  
Box Counting Dimension ◽  
Self Similar ◽  
Box Counting Method

Abstract Atmospheric turbulence studies indicate the presence of self-similar scaling structures over a range of scales from the inertial outer scale to the dissipative inner scale. A measure of this self-similar structure has been obtained by computing the fractal dimension of images visualizing the turbulence using the widely used box-counting method. If applied blindly, the box-counting method can lead to misleading results in which the edges of the scaling range, corresponding to the upper and lower length scales referred to above are incorporated in an incorrect way. Furthermore, certain structures arising in turbulent flows that are not self-similar can deliver spurious contributions to the box-counting dimension. An appropriately trained Convolutional Neural Network can take account of both the above features in an appropriate way, using as inputs more detailed information than just the number of boxes covering the putative fractal set. To give a particular example, how the shape of clusters of covering boxes covering the object changes with box size could be analyzed. We will create a data set of decaying isotropic turbulence scenarios for atmospheric turbulence using Large-Eddy Simulations (LES) and analyze characteristic structures arising from these. These could include contours of velocity magnitude, as well as of levels of a passive scalar introduced into the simulated flows. We will then identify features of the structures that can be used to train the networks to obtain the most appropriate fractal dimension describing the scaling range, even when this range is of limited extent, down to a minimum of one order of magnitude.

scholarly journals MULTIRESOLUTION CONTROL OF CURVES AND SURFACES WITH A SELF-SIMILAR MODEL

Fractals ◽  
2010 ◽  
Vol 18 (03) ◽  
pp. 271-286 ◽  
Author(s):  
HOUSSAM HNAIDI ◽  
ERIC GUÉRIN ◽  
SAMIR AKKOUCHE
Keyword(s):  
Wavelet Transform ◽  
Control Point ◽  
Iterated Function Systems ◽  
Control Points ◽  
Similar Model ◽  
Surface Theory ◽  
Curves And Surfaces ◽  
Iterated Function ◽  
Resolution Level ◽  
Self Similar

This paper presents two self-similar models that allow the control of curves and surfaces. The first model is based on IFS (Iterated Function Systems) theory and the second on subdivision curve and surface theory. Both of these methods employ the detail concept as in the wavelet transform, and allow the multiresolution control of objects with control points at any resolution level.In the first model, the detail is inserted independently of control points, requiring it to be rotated when applying deformations. In contrast, the second method describes details relative to control points, allowing free control point deformations.Modeling examples of curves and surfaces are presented, showing manipulation facilities of the models.

scholarly journals Multifractal spectra for random self-similar measures via branching processes

2011 ◽  
Vol 43 (01) ◽  
pp. 1-39
Author(s):  
J. D. Biggins ◽  
B. M. Hambly ◽  
O. D. Jones
Keyword(s):  
Random Number ◽  
Branching Processes ◽  
Multifractal Spectrum ◽  
Compact Set ◽  
Similar Measure ◽  
Random Mass ◽  
Random Fractal ◽  
Multifractal Spectra ◽  
Self Similar ◽  
Random Division

Start with a compact setK⊂Rd. This has a random number of daughter sets, each of which is a (rotated and scaled) copy ofKand all of which are insideK. The random mechanism for producing daughter sets is used independently on each of the daughter sets to produce the second generation of sets, and so on, repeatedly. The random fractal setFis the limit, asngoes to ∞, of the union of thenth generation sets. In addition,Khas a (suitable, random) mass which is divided randomly between the daughter sets, and this random division of mass is also repeated independently, indefinitely. This division of mass will correspond to a random self-similar measure onF. The multifractal spectrum of this measure is studied here. Our main contributions are dealing with the geometry of realisations inRdand drawing systematically on known results for general branching processes. In this way we generalise considerably the results of Arbeiter and Patzschke (1996) and Patzschke (1997).

Canonical number systems, counting automata and fractals

2002 ◽  
Vol 133 (1) ◽  
pp. 163-182 ◽  
Author(s):  
KLAUS SCHEICHER ◽  
JÖRG M. THUSWALDNER
Keyword(s):  
Direct Methods ◽  
Number Fields ◽  
Dimensional Vector ◽  
Dimensional Vector Space ◽  
Box Counting ◽  
Number Systems ◽  
Rings Of Integers ◽  
Box Counting Dimension ◽  
Self Similar ◽  
Affine Set

In this paper we study properties of the fundamental domain [Fscr ]β of number systems, which are defined in rings of integers of number fields. First we construct addition automata for these number systems. Since [Fscr ]β defines a tiling of the n-dimensional vector space, we ask, which tiles of this tiling ‘touch’ [Fscr ]β. It turns out that the set of these tiles can be described with help of an automaton, which can be constructed via an easy algorithm which starts with the above-mentioned addition automaton. The addition automaton is also useful in order to determine the box counting dimension of the boundary of [Fscr ]β. Since this boundary is a so-called graph-directed self-affine set, it is not possible to apply the general theory for the calculation of the box counting dimension of self similar sets. Thus we have to use direct methods.

scholarly journals A New Analytical Jet Model

1996 ◽  
Vol 175 ◽  
pp. 459-460
Author(s):  
C.R. Kaiser ◽  
P. Alexander
Keyword(s):  
Similar Model ◽  
Self Consistent ◽  
Self Similar

We present a self-consistent, self-similar model for classical radio double sources (FRIIs). This model depends only on quantities which can in principle be measured.

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