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Effective Representations of the Space of Linear Bounded Operators
by
Vasco Brattka
Theoretische Informatik 1, FernUniversität Hagen
Representations of topological spaces by infinite sequences of symbols
are used in computable analysis to describe computations
in topological spaces with the help of Turing machines.
From the computer science point of view such representations can
be considered as data structures of topological spaces.
Formally, a representation of a topological space is a surjective
mapping from Cantor space onto the corresponding space.
Typically, one is interested in admissible, i.e. topologically well-behaved
representations which are continuous and characterized by a certain
maximality condition.
In this talk a number of representations of the space of linear bounded
operators in Banach spaces are discussed. Unfortunately, the operator
norm topology of the operator space is non-separable in typical cases and hence
the operator space cannot be represented admissibly with respect to this
topology. However, other topologies, like the compact open
topology and the Fell topology (on the operator graph) give rise to a
number of promising representations of operator spaces which can partially
replace the operator norm topology.
These representations reflect the information which is included
in certain data structures for operators, such as programs or
enumerations of graphs.
We investigate the sublattice of these representations with respect
to continuous and computable reducibility. Certain additional conditions,
as finite dimensionality, let some classes of representations collapse,
and thus, change the corresponding graph. Altogether, a precise picture
of possible data structures for operator spaces and their mutual relation
can be drawn.
The talk is based on results included in the following report.
Date received: July 20, 2001
Copyright © 2001 by the author(s). The author(s) of this document and the organizers of the conference have granted their consent to include this abstract in Atlas Conferences Inc. Document # cagx-51.