On a problem posed by Steve Smale
成果类型:
Article
署名作者:
Buergisser, Peter; Cucker, Felipe
刊物名称:
ANNALS OF MATHEMATICS
ISSN/ISSBN:
0003-486X
DOI:
10.4007/annals.2011.174.3.8
发表日期:
2011
页码:
1785-1836
关键词:
smoothed analysis
condition numbers
polynomial-time
bezout-theorem
17th problem
complexity
probability
primality
algorithm
摘要:
The 17th of the problems proposed by Steve Smale for the 21st century asks for the existence of a deterministic algorithm computing an approximate solution of a system of n complex polynomials in n unknowns in time polynomial, on the average, in the size N of the input system. A partial solution to this problem was given by Carlos Beltran and Luis Miguel Pardo who exhibited a randomized algorithm doing so. In this paper we further extend this result in several directions. Firstly, we exhibit a linear homotopy algorithm that efficiently implements a nonconstructive idea of Mike Shub. This algorithm is then used in a randomized algorithm, call it LV, a la Beltran-Pardo. Secondly, we perform a smoothed analysis (in the sense of Spielman and Teng) of algorithm LV and prove that its smoothed complexity is polynomial in the input size and sigma(-1), where sigma controls the size of of the random perturbation of the input systems. Thirdly, we perform a condition-based analysis of LV. That is, we give a bound, for each system f, of the expected running time of LV with input f. In addition to its dependence on N this bound also depends on the condition of f. Fourthly, and to conclude, we return to Smale's 17th problem as originally formulated for deterministic algorithms. We exhibit such an algorithm and show that its average complexity is N-O(log log N). This is nearly a solution to Smale's 17th problem.