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We extend algorithmic information theory to quantum mechanics, taking a universal semicomputable density matrix (``universal probability'') as a starting point, and define complexity (an operator) as its negative logarithm. A number of…

Quantum Physics · Physics 2009-11-06 Peter Gacs

In many simple integral domains, such as $\mathbb{Z}$ or $\mathbb{Z}[i]$, there is a straightforward procedure to determine if an element is prime by simply reducing to a direct check of finitely many potential divisors. Despite the fact…

Logic · Mathematics 2018-05-23 Damir D. Dzhafarov , Joseph R. Mileti

Kolmogorov complexity is the length of the ultimately compressed version of a file (that is, anything which can be put in a computer). Formally, it is the length of a shortest program from which the file can be reconstructed. We discuss the…

Information Theory · Computer Science 2020-04-22 Paul Vitanyi

A coarse description of a subset A of omega is a subset D of omega such that the symmetric difference of A and D has asymptotic density 0. We study the extent to which noncomputable information can be effectively recovered from all coarse…

Logic · Mathematics 2015-05-08 Denis R. Hirschfeldt , Carl G. Jockusch , Rutger Kuyper , Paul E. Schupp

The main goal of this article is to put some known results in a common perspective and to simplify their proofs. We start with a simple proof of a result of Vereshchagin saying that $\limsup_n C(x|n)$ equals $C^{0'}(x)$. Then we use the…

Logic · Mathematics 2012-04-03 Laurent Bienvenu , Andrej Muchnik , Alexander Shen , Nikolai Vereshchagin

We investigate the strength of a randomness notion $\mathcal R$ as a set-existence principle in second-order arithmetic: for each $Z$ there is an $X$ that is $\mathcal R$-random relative to $Z$. We show that the equivalence between…

Logic · Mathematics 2019-09-04 André Nies , Paul Shafer

We investigate the coboundary expansion property of tensor product codes, known as product expansion, which plays an important role in recent constructions of good quantum LDPC codes and classical locally testable codes. Prior research has…

Information Theory · Computer Science 2025-10-23 Gleb Kalachev , Pavel Panteleev

D. Krieger and J. Shallit have proved that every real number greater than 1 is a critical exponent of some sequence. We show how this result can be derived from some general statements about sequences whose subsequences have (almost)…

Combinatorics · Mathematics 2010-09-28 Andrey Rumyantsev

For any class of operators which transform unary total functions in the set of natural numbers into functions of the same kind, we define what it means for a real function to be uniformly computable or conditionally computable with respect…

Logic · Mathematics 2013-10-23 Ivan Georgiev , Dimiter Skordev

Randomness extraction is the process of constructing a source of randomness of high quality from one or several sources of randomness of lower quality. The problem can be modeled using probability distributions and min-entropy to measure…

Computational Complexity · Computer Science 2012-06-19 Marius Zimand

We introduce a machine free mathematical framework to get a natural formalization of some general notions of infinite computation in the context of Kolmogorov complexity. Namely, the classes Max^{X\to D}_{PR} and Max^{X\to D}_{Rec} of…

Logic · Mathematics 2008-01-07 Marie Ferbus-Zanda , Serge Grigorieff

To enable the study of open sets in computational approaches to mathematics, lots of extra data and structure on these sets is assumed. For both foundational and mathematical reasons, it is then a natural question, and the subject of this…

Logic · Mathematics 2020-10-02 Dag Normann , Sam Sanders

While it is not known whether each real that is Kolmogorov-Loveland random is Martin-L\"of random, i.e., whether $\mathrm{KLR}\subseteq\mathrm{MLR}$, Kjos-Hanssen and Webb (2021) showed that $\mathrm{MLR}$ is truth-table Medvedev reducible…

Logic · Mathematics 2022-04-29 Bjørn Kjos-Hanssen , David J. Webb

We introduce a notion of computable randomness for infinite sequences that generalises the classical version in two important ways. First, our definition of computable randomness is associated with imprecise probability models, in the sense…

Probability · Mathematics 2020-09-23 Floris Persiau , Jasper De Bock , Gert de Cooman

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…

Logic in Computer Science · Computer Science 2010-10-15 Marie Ferbus-Zanda

Choosing an encoding over binary strings for input/output to/by a Turing Machine is usually straightforward and/or inessential for discrete data (like graphs), but delicate -- heavily affecting computability and even more computational…

Logic in Computer Science · Computer Science 2018-12-11 Akitoshi Kawamura , Donghyun Lim , Svetlana Selivanova , Martin Ziegler

The Kolmogorov complexity of x, denoted C(x), is the length of the shortest program that generates x. For such a simple definition, Kolmogorov complexity has a rich and deep theory, as well as applications to a wide variety of topics…

Computational Complexity · Computer Science 2017-02-17 Stephen Fenner , Lance Fortnow

We investigate how non-zero rational multiplication and rational addition affect normality with respect to $Q$-Cantor series expansions. In particular, we show that there exists a $Q$ such that the set of real numbers which are $Q$-normal…

Number Theory · Mathematics 2014-07-16 Dylan Airey , Bill Mance , Joseph Vandehey

An infinite binary sequence has randomness rate at least $\sigma$ if, for almost every $n$, the Kolmogorov complexity of its prefix of length $n$ is at least $\sigma n$. It is known that for every rational $\sigma \in (0,1)$, on one hand,…

Computational Complexity · Computer Science 2009-02-13 Marius Zimand

Solomonoff unified Occam's razor and Epicurus' principle of multiple explanations to one elegant, formal, universal theory of inductive inference, which initiated the field of algorithmic information theory. His central result is that the…

Machine Learning · Computer Science 2008-06-26 Marcus Hutter