60 research outputs found
Computability and Representations of the Zero Set
In this note we give a new representation for closed sets under which the robust zero set of a function is computable. We call this representation the component cover representation. The computation of the zero set is based on topological index theory, the most powerful tool for finding robust solutions of equations
Effective Choice and Boundedness Principles in Computable Analysis
In this paper we study a new approach to classify mathematical theorems according to their computational content. Basically, we are asking the question which theorems can be continuously or computably transferred into each other? For this purpose theorems are considered via their realizers which are operations with certain input and output data. The technical tool to express continuous or computable relations between such operations is Weihrauch reducibility and the partially ordered degree structure induced by it. We have identified certain choice principles on closed sets which are cornerstones among Weihrauch degrees and it turns out that certain core theorems in analysis can be classified naturally in this structure. In particular, we study theorems such as the Intermediate Value Theorem, the Baire Category Theorem, the Banach Inverse Mapping Theorem, the Closed Graph Theorem and the Uniform Boundedness Theorem. Well-known omniscience principles from constructive mathematics such as and can naturally be considered as Weihrauch degrees and they play an important role in our classification. Our classification scheme does not require any particular logical framework or axiomatic setting, but it can be carried out in the framework of classical mathematics using tools of topology, computability theory and computable analysis. Finally, we present a number of metatheorems that allow to derive upper bounds for the classification of the Weihrauch degree of many theorems and we discuss the Brouwer Fixed Point Theorem as an example
Real Computation with Least Discrete Advice: A Complexity Theory of Nonuniform Computability
It is folklore particularly in numerical and computer sciences that, instead of solving some general problem , additional structural information about the input (that is any kind of promise that belongs to a certain subset ) should be taken advantage of. Some examples from real number computation show that such discrete advice can even make the difference between computability and uncomputability. We turn this into a both topological and combinatorial complexity theory of information, investigating for several practical problem show much advice is necessary and sufficient to render them computable.
Specifically, finding a nontrivial solution to a homogeneous linear equation for a given singular real -matrix is possible when knowing ; and we show this to be best possible. Similarly, diagonalizing (i.e. finding a basis of eigenvectors of) a given real symmetric -matrix is possible when knowing the number of distinct eigenvalues: an integer between and (the latter corresponding to the nondegenerate case). And again we show that --fold (i.e. roughly bits of) additional information is indeed necessary in order to render this problem (continuous and) computable; whereas finding emph{some single} eigenvector of requires and suffices with --fold advice
Revising Type-2 Computation and Degrees of Discontinuity
By the sometimes so-called MAIN THEOREM of Recursive Analysis, every
computable real function is necessarily continuous. Weihrauch and Zheng
(TCS'2000), Brattka (MLQ'2005), and Ziegler (ToCS'2006) have considered
different relaxed notions of computability to cover also discontinuous
functions. The present work compares and unifies these approaches. This is
based on the concept of the JUMP of a representation: both a TTE-counterpart to
the well known recursion-theoretic jump on Kleene's Arithmetical Hierarchy of
hypercomputation: and a formalization of revising computation in the sense of
Shoenfield.
We also consider Markov and Banach/Mazur oracle-computation of discontinuous
fu nctions and characterize the computational power of Type-2 nondeterminism to
coincide with the first level of the Analytical Hierarchy.Comment: to appear in Proc. CCA'0
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