Effective Fractal Dimensions
Jack Lutz
Department of Computer Science
Iowa State University
The two most important notions of fractal dimension are Hausdorff dimension, developed by Hausdorff (1919), and packing dimension, developed by Tricot (1982). Both dimensions have the mathematical advantage of being defined from measures, and both have yielded extensive applications in fractal geometry and dynamical systems. In 2000, the speaker proved a simple characterization of Hausdorff dimension in terms of gales, which are betting strategies that generalize martingales. Imposing various computability and complexity constraints on these gales produces a spectrum of effective versions of Hausdorff dimension, including constructive, computable, polynomial-space, polynomial- time, and finite-state dimensions. Work by several investigators has already used these effective dimensions to shed light on a variety of topics in theoretical computer science, including algorithmic information theory, computational complexity, prediction, and data compression. Constructive dimension has also been discretized, assigning a dimension to each finite binary string in a way that arises naturally from Hausdorff and constructive dimensions and gives the unexpected characterization that the Kolmogorov (program-size) complexity of a string is just its length times its dimension. We survey these developments, along with a more recent result by Athreya, Hitchcock, Mayordomo and the speaker showing that packing dimension -- previously thought to be much more complex than Hausdorff dimension -- admits a gale characterization that is an exact dual of that of Hausdorff dimension. This talk is intended for nonspecialists. No prior knowledge of fractal dimension or martingales will be assumed.