Quasi-random (also called low discrepancy) sequences are a deterministic alternative to random sequences for use in Monte Carlo methods, such as integration and particle simulations of transport processes. The error in uniformity for such a sequence of N points in the s-dimensional unit cube is measured by its discrepancy, which is of size (log N) N-Ifor large N, as opposed to discrepancy of si...

We demonstrate a one-to-one correspondence between idempotent closure operators and the so-called saturated quasi-uniform structures on category C. Not only this result allows to obtain categorical counterpart P of Császár-Pervin quasi-uniformity P, that we characterize as transitive compatible with an interior operator, but also permits describe those topogenous orders are induced by The P⁎ P−...

Lenses and quasi-lenses on a space X form models of erratic non-determinism. When is equipped with quasi-metric d, there are natural quasi-metrics dP dPa the X, which resemble Pompeiu-Hausdorff metric (and contain it as subcase when d metric), tightly connected to Kantorovich-Rubinstein dKR dKRa Parts I, II III, through an isomorphism between so-called discrete normalized forks. We show that co...

A model of coherent upper conditional prevision for bounded random variables is proposed in a metric space. It is defined by the Choquet integral with respect to Hausdorff outer measure if the conditioning event has positive and finite Hausdorff outer measure in its Hausdorff dimension. Otherwise, when the conditioning event has Hausdorff outer measure equal to zero or infinity in its Hausdorff...

Two moving mesh partial differential equations (MMPDEs) with spatial smoothing are derived based upon the equidistribution principle. This smoothing technique is motivated by the robust moving mesh method of Dorfi and Drury [J. Comput. Phys., 69 (1987), pp. 175–195]. It is shown that under weak conditions the basic property of no node-crossing is preserved by the spatial smoothing, and a local ...

We present deterministic sequences for use in sampling-based approaches to motion planning. They simultaneously combine the qualities found in many other sequences: i) the incremental and self-avoiding tendencies of pseudo-random sequences, ii) the lattice structure provided by multiresolution grids, and iii) lowdiscrepancy and low-dispersion measures of uniformity provided by quasi-random sequ...

We consider planar systems driven by a central force which depends periodically on time. If the force is sublinear and attractive, then there is a connected set of subharmonic and quasi-periodic solutions rotating around the origin at different speeds; moreover, this connected set stretches from zero to infinity. The result still holds allowing the force to be attractive only in average provide...

We construct an invariant measure $\mu$ for the Surface Quasi-Geostrophic (SQG) equation and show that almost all functions in support of are initial conditions global, unique solutions SQG, depend continuously on data. In addition, we is infinite dimensional, meaning it not locally a subset any compact set with finite Hausdorff dimension. Also, there global have arbitrarily large condition. Th...

Appendix A: Properties of EDS grids In this appendix, we characterize the dispersion of points, the number of points, and the degree of uniformity of the constructed EDS. Also, we discuss the relation of our results to recent mathematical literature. A.1 Dispersion of points in EDS grids We borrow the notion of dispersion from the literature on quasi-Monte Carlo optimization methods; see, for e...

Monte Carlo is one of the most versatile and widely used numerical methods. Its convergence rate, O(N~^), is independent of dimension, which shows Monte Carlo to be very robust but also slow. This article presents an introduction to Monte Carlo methods for integration problems, including convergence theory, sampling methods and variance reduction techniques. Accelerated convergence for Monte Ca...