784 research outputs found
Algorithmic complexity of quantum capacity
Recently the theory of communication developed by Shannon has been extended
to the quantum realm by exploiting the rules of quantum theory. This latter
stems on complex vector spaces. However complex (as well as real) numbers are
just idealizations and they are not available in practice where we can only
deal with rational numbers. This fact naturally leads to the question of
whether the developed notions of capacities for quantum channels truly catch
their ability to transmit information. Here we answer this question for the
quantum capacity. To this end we resort to the notion of semi-computability in
order to approximately (by rational numbers) describe quantum states and
quantum channel maps. Then we introduce algorithmic entropies (like algorithmic
quantum coherent information) and derive relevant properties for them. Finally
we define algorithmic quantum capacity and prove that it equals the standard
one
On Empirical Entropy
We propose a compression-based version of the empirical entropy of a finite
string over a finite alphabet. Whereas previously one considers the naked
entropy of (possibly higher order) Markov processes, we consider the sum of the
description of the random variable involved plus the entropy it induces. We
assume only that the distribution involved is computable. To test the new
notion we compare the Normalized Information Distance (the similarity metric)
with a related measure based on Mutual Information in Shannon's framework. This
way the similarities and differences of the last two concepts are exposed.Comment: 14 pages, LaTe
Kolmogorov Complexity in perspective. Part I: Information Theory and Randomnes
We survey diverse approaches to the notion of information: from Shannon
entropy to Kolmogorov complexity. Two of the main applications of Kolmogorov
complexity are presented: randomness and classification. The survey is divided
in two parts in the same volume. Part I is dedicated to information theory and
the mathematical formalization of randomness based on Kolmogorov complexity.
This last application goes back to the 60's and 70's with the work of
Martin-L\"of, Schnorr, Chaitin, Levin, and has gained new impetus in the last
years.Comment: 40 page
Complexity vs Energy: Theory of Computation and Theoretical Physics
This paper is a survey dedicated to the analogy between the notions of {\it
complexity} in theoretical computer science and {\it energy} in physics. This
analogy is not metaphorical: I describe three precise mathematical contexts,
suggested recently, in which mathematics related to (un)computability is
inspired by and to a degree reproduces formalisms of statistical physics and
quantum field theory.Comment: 23 pages. Talk at the satellite conference to ECM 2012, "QQQ Algebra,
Geometry, Information", Tallinn, July 9-12, 201
A Computable Economist’s Perspective on Computational Complexity
A computable economist's view of the world of computational complexity theory is described. This means the model of computation underpinning theories of computational complexity plays a central role. The emergence of computational complexity theories from diverse traditions is emphasised. The unifications that emerged in the modern era was codified by means of the notions of efficiency of computations, non-deterministic computations, completeness, reducibility and verifiability - all three of the latter concepts had their origins on what may be called 'Post's Program of Research for Higher Recursion Theory'. Approximations, computations and constructions are also emphasised. The recent real model of computation as a basis for studying computational complexity in the domain of the reals is also presented and discussed, albeit critically. A brief sceptical section on algorithmic complexity theory is included in an appendix
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