We consider the trajectories of points on under sequences of certain folding maps associated with reflections. The main result characterizes collections of folding maps that produce dense trajectories. The minimal number of maps in such a collection is d+1.
A standard technique for establishing geometric inequalities is to approximate full radial symmetrization by a sequence of simpler symmetrizations. Two-point symmetrization has been used in this way to prove the isoperimetric inequality on spheres @cite_12 , and sharp inequalities for path integrals @cite_8 @cite_3 @cite_2 . The convergence of random sequences of symmetrizations has received some attention in the literature, most notably in the work of Klartag @cite_4 on Steiner symmetrizations of convex sets. Convergence of two-point symmetrizations is less well studied. Very recently, De Keyser and Van Schaftingen have considered random symmetrization processes with time correlations @cite_14 . Open questions in the area include precise conditions for convergence, and bounds on the rate of convergence.
@cite_14 @cite_4 @cite_8 @cite_3 @cite_2 @cite_12
2074528182 2101606546 2963879560 2094096036
It is a classical fact, that given an arbitrary convex body (K R ^n , ) there exists an appropriate sequence of Minkowski symmetrizations (or Steiner symmetrizations), that converges in Hausdorff metric to a Euclidean ball. Here we provide quantitative estimates regarding this convergence, for both Minkowski and Steiner symmetrizations. Our estimates are polynomial in the dimension and in the logarithm of the desired distance to a Euclidean ball, improving previously known exponential estimates. Inspired by a method of Diaconis [D], our technique involves spherical harmonics. We also make use of an earlier result by the author regarding “isomorphic Minkowski symmetrization”. Under continuity and recurrence assumptions, we prove that the iteration of successive partial symmetrizations that form a time-homogeneous Markov process, converges to a symmetrization. We cover several settings, including the approximation of the spherical nonincreasing rearrangement by Steiner symmetrizations, polarizations and cap symmetrizations. A key tool in our analysis is a quantitative measure of the asymmetry. We consider an analogue of the Kac random walk on the special orthogonal group SO(N)SO(N), in which at each step a random rotation is performed in a randomly chosen 2-plane of RNRN. We obtain sharp asymptotics for the rate of convergence in total variance distance, establishing a cut-off phenomenon in the large NN limit. In the special case where the angle of rotation is deterministic, this confirms a conjecture of Rosenthal [Ann. Probab. 22 (1994) 398–423]. Under mild conditions, we also establish a cut-off for convergence of the walk to stationarity under the L2L2 norm. Depending on the distribution of the randomly chosen angle of rotation, several surprising features emerge. For instance, it is sometimes the case that the mixing times differ in the total variation and L2L2 norms. Our estimates use an integral representation of the characters of the special orthogonal group together with saddle point analysis. We show that if X is a complete separable metric space and C is a countable family of Borel subsets of X with finite VC dimension, then, for every stationary ergodic process with values in X, the relative frequencies of sets C ∈ C converge uniformly to their limiting probabilities. Beyond ergodicity, no assumptions are imposed on the sampling process, and no regularity conditions are imposed on the elements of C. The result extends existing work of Vapnik and Chervonenkis, among others, who have studied uniform convergence for i.i.d. and strongly mixing processes. Our method of proof is new and direct: it does not rely on symmetrization techniques, probability inequalities or mixing conditions. The uniform convergence of relative frequencies for VC-major and VC-graph classes of functions under ergodic sampling is established as a corollary of the basic result for sets.