The invariances of power law size distributions
Steven A. Frank

TL;DR
This paper explores the invariant properties underlying power law size distributions in nature, explaining their simplicity through concepts like shift, stretch, and rotational invariance, with tree size as an illustrative example.
Contribution
It introduces a framework linking invariance principles to power law patterns, providing a unifying explanation for diverse natural size distributions.
Findings
Power law patterns are invariant under specific transformations.
Invariance principles explain the emergence of simple size distribution patterns.
Tree size exemplifies how invariance shapes observed distributions.
Abstract
Size varies. Small things are typically more frequent than large things. The logarithm of frequency often declines linearly with the logarithm of size. That power law relation forms one of the common patterns of nature. Why does the complexity of nature reduce to such a simple pattern? Why do things as different as tree size and enzyme rate follow similarly simple patterns? Here I analyze such patterns by their invariant properties. For example, a common pattern should not change when adding a constant value to all observations. That shift is essentially the renumbering of the points on a ruler without changing the metric information provided by the ruler. A ruler is shift invariant only when its scale is properly calibrated to the pattern being measured. Stretch invariance corresponds to the conservation of the total amount of something, such as the total biomass and consequently the…
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