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Related papers: V-variable fractals and superfractals

200 papers

We consider the breakdown of conformal and scale invariance in random systems with strongly random critical points. Extending previous results on one-dimensional systems, we provide an example of a three-dimensional system which has a…

Disordered Systems and Neural Networks · Physics 2009-10-31 M. B. Hastings , S. L. Sondhi

In this manuscript, we generalize F-calculus to apply it on fractal Tartan spaces. The generalized standard F-calculus is used to obtain the integral and derivative of the functions on the fractal Tartan with different dimensions. The…

Classical Analysis and ODEs · Mathematics 2018-01-31 Alireza Khalili Golmankhaneh

Many fluctuating systems consist of macroscopic structures in addition to noisy signals. Thus, for this class of fluctuating systems, the scaling behaviors are very complicated. Such phenomena are quite commonly observed in Nature, ranging…

Statistical Mechanics · Physics 2007-05-23 Ning-Ning Pang , Hisen-Ching Kao , Wen-Jer Tzeng

In this paper, we introduce the concept of the $\alpha$-fractal function and fractal approximation for a set-valued continuous map defined on a closed and bounded interval of real numbers. Also, we study some properties of such fractal…

Functional Analysis · Mathematics 2022-07-07 Megha Pandey , Tanmoy Som , Saurabh Verma

We study multifractal properties in time evolution of a single particle subject to repeated measurements. For quantum systems, we consider circuit models consisting of local unitary gates and local projective measurements. For classical…

Quantum Physics · Physics 2024-10-28 Kohei Yajima , Hisanori Oshima , Ken Mochizuki , Yohei Fuji

We study the convergence of random function iterations for finding an invariant measure of the corresponding Markov operator. We call the problem of finding such an invariant measure the stochastic fixed point problem. This generalizes…

Optimization and Control · Mathematics 2024-04-16 Neal Hermer , D. Russell Luke , Anja Sturm

It is shown that preferential concentrations of inertial (finite-size) particle suspensions in turbulent flows follow from the dissipative nature of their dynamics. In phase space, particle trajectories converge toward a dynamical fractal…

Chaotic Dynamics · Physics 2009-11-10 Jeremie Bec

Experiments on fracture surface morphologies offer increasing amounts of data that can be analyzed using methods of statistical physics. One finds scaling exponents associated with correlation and structure functions, indicating a rich…

Materials Science · Physics 2009-11-11 Eran Bouchbinder , Itamar Procaccia , Shani Sela

The paper concerns fractal homeomorphism between the attractors of two bi-affine iterated function systems. After a general discussion of bi-affine functions, conditions are provided under which a bi-affine iterated function system is…

Dynamical Systems · Mathematics 2011-10-24 Michael Barnsley , Andrew Vince

We apply the Principle of Maximum Entropy to the study of a general class of deterministic fractal sets. The scaling laws peculiar to these objects are accounted for by means of a constraint concerning the average content of information in…

Statistical Mechanics · Physics 2015-06-25 R. Pastor-Satorras , J. Wagensberg

We consider a stochastic version of the point vortex system, in which the fluid velocity advects single vortices intermittently for small random times. Such system converges to the deterministic point vortex dynamics as the rate at which…

Probability · Mathematics 2023-11-28 Andrea Agazzi , Francesco Grotto , Jonathan C. Mattingly

A $d$-dimensional random array on a nonempty set $I$ is a stochastic process $\boldsymbol{X}=\langle X_s:s\in \binom{I}{d}\rangle$ indexed by the set $\binom{I}{d}$ of all $d$-element subsets of $I$. We obtain structural decompositions of…

Probability · Mathematics 2025-02-18 Pandelis Dodos , Konstantinos Tyros , Petros Valettas

Many modern unsupervised or semi-supervised machine learning algorithms rely on Bayesian probabilistic models. These models are usually intractable and thus require approximate inference. Variational inference (VI) lets us approximate a…

Machine Learning · Computer Science 2018-10-24 Cheng Zhang , Judith Butepage , Hedvig Kjellstrom , Stephan Mandt

The work relates to a new way for analysis of one-dimensional stochastic systems, based on consideration of its higher order difference structure. From this point of view, the deterministic and random processes are analyzed. A new numerical…

Chaotic Dynamics · Physics 2016-09-08 A. Yu. Shahverdian , A. V. Apkarian

We use machine learning methods on local structure to identify flow defects - or regions susceptible to rearrangement - in jammed and glassy systems. We apply this method successfully to two disparate systems: a two dimensional experimental…

This paper discusses and summarizes some results on complex variables that are very useful in fractional-order systems analysis and design, specifically when the system is analyzed in the frequency domain. The author hopes that this…

Signal Processing · Electrical Eng. & Systems 2026-03-26 Emmanuel A. Gonzalez

The problem of quantum harmonic oscillator with "regular+random" square frequency, subjected to "regular+random external force, is considered in framework of representation of the wave function by complex-valued random process. Average…

Quantum Physics · Physics 2007-05-23 A. S. Gevorkyan , A. A. Udalov

There are three important types of structural properties that remain unchanged under the structural transformation of condensed matter physics and chemistry. They are the properties that remain unchanged under the structural periodic…

Statistical Mechanics · Physics 2020-06-09 John Hongguang Zhang

We study multifractality in a broad class of disordered systems which includes, e.g., the diluted x-y model. Using renormalized field theory we analyze the scaling behavior of cumulant averaged dynamical variables (in case of the x-y model…

Statistical Mechanics · Physics 2009-11-10 Olaf Stenull

We discuss properties of random fractals by means of a set of numbers that characterize their universal properties. This set is the generalized singularity specturm that consists of the usual spectrum of mulitfractal dimensions and the…

Condensed Matter · Physics 2009-10-30 Francisco J. Solis , Louis Tao