Computer Science/Discrete Mathematics Seminar I

Dispersion of Mass and the Complexity of Randomized Algorithms

Perhaps the most appealing conjectures in asymptotic convex geometry are (i) slicing (or isotropic constant) and (ii) variance. Together, they imply that for a random point X from an isotropic convex body in \R^n, the variance of |X|^2 is O(n). We prove a reverse inequality: for any isotropic convex polytope with at most poly(n) facets, the variance of |X|^2 is AT LEAST n/ln n (up to a constant). In fact, the lower bound holds for any polytope of unit volume with poly(n) facets contained in the ball of radius poly(n). It implies that in order for most of such a convex polytope to be contained between two concentric spheres, their radii have to differ by about 1/\sqrt{ln n}; in contrast, most of a unit-volume ball lies in between two spheres whose radii differ by only about 1/\sqrt{n}. This geometric dispersion leads to linear and quadratic lower bounds on the randomized complexity of some basic algorithmic problems. This is joint work with Luis Rademacher.

Date & Time

January 23, 2006 | 11:15am – 12:15pm

Location

S-101

Speakers

Santosh Vempala

Affiliation

MIT