7,429 research outputs found
Effective Topological Degree Computation Based on Interval Arithmetic
We describe a new algorithm for calculating the topological degree deg (f, B,
0) where B \subseteq Rn is a product of closed real intervals and f : B
\rightarrow Rn is a real-valued continuous function given in the form of
arithmetical expressions. The algorithm cleanly separates numerical from
combinatorial computation. Based on this, the numerical part provably computes
only the information that is strictly necessary for the following combinatorial
part, and the combinatorial part may optimize its computation based on the
numerical information computed before. We also present computational
experiments based on an implementation of the algorithm. Also, in contrast to
previous work, the algorithm does not assume knowledge of a Lipschitz constant
of the function f, and works for arbitrary continuous functions for which some
notion of interval arithmetic can be defined
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 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 and others. We also explore how existing
classifications of the Hahn-Banach Theorem and Weak K"onig's Lemma fit into
this picture. We compare the results of our classification with existing
classifications in constructive and reverse mathematics and we claim that in a
certain sense our classification is finer and sheds some new light on the
computational content of the respective theorems. We develop a number of
separation techniques based on a new parallelization principle, on certain
invariance properties of Weihrauch reducibility, on the Low Basis Theorem of
Jockusch and Soare and based on the Baire Category Theorem. 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
Mass problems and intuitionistic higher-order logic
In this paper we study a model of intuitionistic higher-order logic which we
call \emph{the Muchnik topos}. The Muchnik topos may be defined briefly as the
category of sheaves of sets over the topological space consisting of the Turing
degrees, where the Turing cones form a base for the topology. We note that our
Muchnik topos interpretation of intuitionistic mathematics is an extension of
the well known Kolmogorov/Muchnik interpretation of intuitionistic
propositional calculus via Muchnik degrees, i.e., mass problems under weak
reducibility. We introduce a new sheaf representation of the intuitionistic
real numbers, \emph{the Muchnik reals}, which are different from the Cauchy
reals and the Dedekind reals. Within the Muchnik topos we obtain a \emph{choice
principle} and a \emph{bounding principle} where range over Muchnik
reals, ranges over functions from Muchnik reals to Muchnik reals, and
is a formula not containing or . For the convenience of the
reader, we explain all of the essential background material on intuitionism,
sheaf theory, intuitionistic higher-order logic, Turing degrees, mass problems,
Muchnik degrees, and Kolmogorov's calculus of problems. We also provide an
English translation of Muchnik's 1963 paper on Muchnik degrees.Comment: 44 page
Satisfiability of Non-Linear Transcendental Arithmetic as a Certificate Search Problem
For typical first-order logical theories, satisfying assignments have a
straightforward finite representation that can directly serve as a certificate
that a given assignment satisfies the given formula. For non-linear real
arithmetic with transcendental functions, however, no general finite
representation of satisfying assignments is available. Hence, in this paper, we
introduce a different form of satisfiability certificate for this theory,
formulate the satisfiability verification problem as the problem of searching
for such a certificate, and show how to perform this search in a systematic
fashion. This does not only ease the independent verification of results, but
also allows the systematic design of new, efficient search techniques.
Computational experiments document that the resulting method is able to prove
satisfiability of a substantially higher number of benchmark problems than
existing methods
ESOLID—a system for exact boundary evaluation
We present a system, ESOLID, that performs exact boundary evaluation of low-degree curved solids in reasonable amounts of time. ESOLID performs accurate Boolean operations using exact representations and exact computations throughout. The demands of exact computation require a different set of algorithms and efficiency improvements than those found in a traditional inexact floating point based modeler. We describe the system architecture, representations, and issues in implementing the algorithms. We also describe a number of techniques that increase the efficiency of the system based on lazy evaluation, use of floating point filters, arbitrary floating point arithmetic with error bounds, and lower dimensional formulation of subproblems. ESOLID has been used for boundary evaluation of many complex solids. These include both synthetic datasets and parts of a Bradley Fighting Vehicle designed using the BRL-CAD solid modeling system. It is shown that ESOLID can correctly evaluate the boundary of solids that are very hard to compute using a fixed-precision floating point modeler. In terms of performance, it is about an order of magnitude slower as compared to a floating point boundary evaluation system on most cases
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