Abstract

We consider the binary fragmentation problem in which, at any breakup event, one of the daughter segments either survives with probability p or disappears with probability 1-p. It describes a stochastic dyadic Cantor set that evolves in time, and eventually becomes a fractal. We investigate this phenomenon, through analytical methods and Monte Carlo simulation, for a generic class of models, where segment breakup points follow a symmetric beta distribution with shape parameter α, which also determines the fragmentation rate. For a fractal dimension d_{f}, we find that the d_{f} th moment M_{d_{f}} is a conserved quantity, independent of p and α. While the scaling exponents do not depend on p, the self-similar distribution shows a weak p dependence. We use the idea of data collapse-a consequence of dynamical scaling symmetry-to demonstrate that the system exhibits self-similarity. In an attempt to connect the symmetry with the conserved quantity, we reinterpret the fragmentation equation as the continuity equation of a Euclidean quantum-mechanical system. Surprisingly, the Noether charge corresponding to dynamical scaling is trivial, while M_{d_{f}} relates to a purely mathematical symmetry: Quantum-mechanical phase rotation in Euclidean time.

Highlights

  • Natural objects rarely have regular shapes and smooth edges: they most often come with sparsely-distributed constituents, badly-twisted tips, or wildly-folded surfaces

  • For a fractal dimension df, we find that the df -th moment Mdf is a conserved quantity, independent of p and α

  • We use the idea of data collapse−a consequence of dynamical scaling symmetry−to demonstrate that the system exhibits self-similarity

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Summary

INTRODUCTION

Natural objects rarely have regular shapes and smooth edges: they most often come with sparsely-distributed constituents, badly-twisted tips, or wildly-folded surfaces. Similar features appear in a variety of seemingly disparate systems across many branches of science Objects with such irregularities have traditionally been considered as geometrical monsters, since Euclidean geometry confines us only to integer dimensions. In order to incorporate randomness/stochasticity and the notion of time, one may instead apply probabilistic rules in a sequential manner. We explore of the stochastic DCS problem for a generic class of models, where a shape parameter α encodes in a symmetric beta distribution the degree of randomness in choosing the fragment breakup points, and tunes the fragmentation rate as well. Extensive Monte Carlo simulations corroborate all our analytical results: a fractal dimension, a conserved moment and dynamical scaling symmetry.

FORMULATION OF THE PROBLEM
ANALYTICAL STUDIES
Power-Law Exponents
Scaling Functions
NUMERICAL SIMULATION
Quantum-Mechanical Description
Global Symmetries and Noether Charges
Phase Rotation
Dynamical Scaling
REMARKS
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