10,900 research outputs found
Three Puzzles on Mathematics, Computation, and Games
In this lecture I will talk about three mathematical puzzles involving
mathematics and computation that have preoccupied me over the years. The first
puzzle is to understand the amazing success of the simplex algorithm for linear
programming. The second puzzle is about errors made when votes are counted
during elections. The third puzzle is: are quantum computers possible?Comment: ICM 2018 plenary lecture, Rio de Janeiro, 36 pages, 7 Figure
Noise Sensitivity of Boolean Functions and Applications to Percolation
It is shown that a large class of events in a product probability space are
highly sensitive to noise, in the sense that with high probability, the
configuration with an arbitrary small percent of random errors gives almost no
prediction whether the event occurs. On the other hand, weighted majority
functions are shown to be noise-stable. Several necessary and sufficient
conditions for noise sensitivity and stability are given.
Consider, for example, bond percolation on an by grid. A
configuration is a function that assigns to every edge the value 0 or 1. Let
be a random configuration, selected according to the uniform measure.
A crossing is a path that joins the left and right sides of the rectangle, and
consists entirely of edges with . By duality, the probability
for having a crossing is 1/2. Fix an . For each edge , let
with probability , and
with probability , independently of the
other edges. Let be the probability for having a crossing in
, conditioned on . Then for all sufficiently large,
.Comment: To appear in Inst. Hautes Etudes Sci. Publ. Mat
On (not) computing the Mobius function using bounded depth circuits
Any function F : {0,...,N-1} -> {-1,1} such that F(x) can be computed from
the binary digits of x using a bounded depth circuit is orthogonal to the
Mobius function mu in the sense that E_{0 <= x <= N-1} mu(x)F(x) = o(1). The
proof combines a result of Linial, Mansour and Nisan with techniques of Katai
and Harman-Katai, used in their work on finding primes with specified digits.Comment: 10 pages, to appear in Combinatorics, Probability and Computing. A
few further small correction
DNF Sparsification and a Faster Deterministic Counting Algorithm
Given a DNF formula on n variables, the two natural size measures are the
number of terms or size s(f), and the maximum width of a term w(f). It is
folklore that short DNF formulas can be made narrow. We prove a converse,
showing that narrow formulas can be sparsified. More precisely, any width w DNF
irrespective of its size can be -approximated by a width DNF with
at most terms.
We combine our sparsification result with the work of Luby and Velikovic to
give a faster deterministic algorithm for approximately counting the number of
satisfying solutions to a DNF. Given a formula on n variables with poly(n)
terms, we give a deterministic time algorithm
that computes an additive approximation to the fraction of
satisfying assignments of f for \epsilon = 1/\poly(\log n). The previous best
result due to Luby and Velickovic from nearly two decades ago had a run-time of
.Comment: To appear in the IEEE Conference on Computational Complexity, 201
- …