Scaling, Scale-invariance and Self-similarity

Author(s):  
Santo Banerjee ◽  
M K Hassan ◽  
Sayan Mukherjee ◽  
A Gowrisankar
Author(s):  
Claudio Xavier Mendes dos Santos ◽  
Carlos Molina Mendes ◽  
Marcelo Ventura Freire

Fractals play a central role in several areas of modern physics and mathematics. In the present work we explore resistive circuits where the individual resistors are arranged in fractal-like patterns. These circuits have some of the characteristics typically found in geometric fractals, namely self-similarity and scale invariance. Considering resistive circuits as graphs, we propose a definition of self-similar circuits which mimics a self-similar fractal. General properties of the resistive circuits generated by this approach are investigated, and interesting examples are commented in detail. Specifically, we consider self-similar resistive series, tree-like resistive networks and Sierpinski’s configurations with resistors.


Symmetry ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1927
Author(s):  
Nachiketa Chakraborty

Stochastic variability is ubiquitous among astrophysical sources. Quantifying stochastic properties of observed time-series or lightcurves, can provide insights into the underlying physical mechanisms driving variability, especially those of the particles that radiate the observed emission. Toy models mimicking cosmic ray transport are particularly useful in providing a means of linking the statistical analyses of observed lightcurves to the physical properties and parameters. Here, we explore a very commonly observed feature; finite sized self-similarity or scale invariance which is a fundamental property of complex, dynamical systems. This is important to the general theme of physics and symmetry. We investigate it through the probability density function of time-varying fluxes arising from a Ornstein–Uhlenbeck Model, as this model provides an excellent description of several time-domain observations of sources like active galactic nuclei. The probability density function approach stems directly from the mathematical definition of self-similarity and is nonparametric. We show that the OU model provides an intuitive description of scale-limited self-similarity and stationary Gaussian distribution while potentially showing a way to link to the underlying cosmic ray transport. This finite size of the scale invariance depends upon the decay time in the OU model.


Author(s):  
Paul Charbonneau

This chapter explores how naturally occurring inanimate structures grow by accretion of smaller-sized components, focusing on one specific accretion process: diffusion-limited aggregation (DLA). In DLA, particles move about in random fashion, but stick together when they come into contact. Clumps of particles then form and grow further by colliding with other individual particles, or clumps of particles. Over time, one or more aggregates of individual particles will grow. After providing an overview of how DLA works, the chapter describes its numerical implementation and shows a representative simulation of a two-dimensional DLA aggregate. It then considers two peculiar geometrical properties of aggregates resulting from the DLA process, namely self-similarity and scale invariance, and shows that rule based growth through DLA can lead to the buildup of complex structures, sometimes exhibiting fractal geometry. The chapter includes exercises and further computational explorations, along with a suggested list of materials for further reading.


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