On computational complexity of Siegel Julia sets

被引：10
|
作者：
Binder, I [1 ]
Braverman, M
Yampolsky, M
机构：
[1] Univ Toronto, Dept Math, Toronto, ON M5S 2E4, Canada
[2] Univ Toronto, Dept Comp Sci, Toronto, ON M5S 2E4, Canada
来源：
COMMUNICATIONS IN MATHEMATICAL PHYSICS | 2006年 / 264卷 / 02期
关键词：
Neural Network; Statistical Physic; Complex System; Computational Complexity; Nonlinear Dynamics;
D O I：
10.1007/s00220-006-1546-3
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
It has been previously shown by two of the authors that some polynomial Julia sets are algorithmically impossible to draw with arbitrary magnification. On the other hand, for a large class of examples the problem of drawing a picture has polynomial complexity. In this paper we demonstrate the existence of computable quadratic Julia sets whose computational complexity is arbitrarily high.
引用
收藏
页码：317 / 334
页数：18
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