Computational benefit of smoothness: Parameterized bit-complexity of numerical operators on analytic functions and Gevrey's hierarchy
Computational benefit of smoothness: Parameterized bit-complexity of numerical operators on analytic functions and Gevrey's hierarchy
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平滑度的计算优势:解析函数和 Gevrey 层次结构上数值运算符的参数化位复杂度
DOI:
10.1016/j.jco.2015.05.001
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发表时间:
2015
期刊:
影响因子:
--
通讯作者:
M. Ziegler
中科院分区:
文献类型:
--
作者:
A. Kawamura;N. Müller;C. Rösnick;M. Ziegler
The synthesis of (discrete) Complexity Theory with Recursive Analysis provides a quantitative algorithmic foundation to calculations over real numbers, sequences, and functions by approximation up to prescribable absolute error 1/2 n (roughly corresponding to n binary digits after the radix point). In this sense Friedman and Ko have shown the seemingly simple operators of maximization and integration ‘complete’for the standard complexity classes NP and# P—even when restricted to smooth (= C∞) arguments. Analytic polynomial-time computable functions on the other hand are known to get mapped to polynomial-time computable functions: non-uniformly, that is, disregarding dependences other than on the output precision n. The present work investigates the uniform parameterized complexity of natural operators Λ on subclasses of smooth functions: evaluation, pointwise addition and multiplication,(iterated) differentiation, integration, and maximization. We identify natural integer parameters k= k (f) which, when given as enrichment to approximations to the function argument f, permit to computably produce approximations to Λ (f); and we explore the asymptotic worst-case running time sufficient and necessary for such computations in terms of the output precision n and said k. It turns out that Maurice Gevrey’s 1918 classical hierarchy climbing from analytic to (just below) smooth functions provides for a quantitative gauge of the uniform computational complexity of maximization and integration that, non-uniformly, exhibits the phase transition from tractable (ie polynomial-time) to intractable (in the sense of NP-‘hardness’). Our proof methods involve Hard Analysis, Approximation Theory, and an adaptation of Information-Based Complexity to the bit model.
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DOI:
10.1007/978-3-642-38896-5
发表时间:
2013-08
期刊:
--
影响因子:
--
作者:
Peter Bürgisser;F. Cucker
通讯作者:
Peter Bürgisser;F. Cucker
DOI:
10.1016/s0304-3975(98)00300-4
发表时间:
1999
期刊:
Theor. Comput. Sci.
影响因子:
--
作者:
H. Wozniakowski
通讯作者:
H. Wozniakowski
DOI:
--
发表时间:
2011
期刊:
International Symposium on Mathematical Foundations of Computer Science
影响因子:
--
作者:
Olivier Bournez;D. Graça;Amaury Pouly
通讯作者:
Amaury Pouly
影响因子:
0.5
作者:
Tobias Gärtner;G. Hotz
通讯作者:
G. Hotz
DOI:
--
发表时间:
2009
期刊:
影响因子:
--
作者:
G. Hotz
通讯作者:
G. Hotz