We introduce a property of measures on Euclidean space, termed 'uniform scaling scenery'. For these measures, the empirical distribution of the measure-valued time series, obtained by rescaling around a point, is (almost everywhere) independent of the point. This property is related to existing notions of self-similarity: it is satisfied by the occupation measure of a typical Brownian motion (which is 'statistically' self-similar), as well as by the measures associated to attractors of affine iterated function systems (which are 'exactly' self-similar). It is possible that different notions of self-similarity are unified under this property. The proofs trace a connection between uniform scaling scenery and Furstenberg's 'CP processes', a class of natural, discrete-time, measure-valued Markov processes, useful in fractal geometry.
All Science Journal Classification (ASJC) codes
- Applied Mathematics