arXiv subjects

Marius Zimand

Publications and source records attributed to Marius Zimand.

34 records · Page 2Linked to original sources

arXiv2013

On optimal language compression for sets in PSPACE/poly

We show that if DTIME[2^O(n)] is not included in DSPACE[2^o(n)], then, for every set B in PSPACE/poly, all strings x in B of length n can be represented by a string compressed(x) of length at most log(|B^{=n}|)+O(log n), such that a polynomial-time algorithm, given compressed(x), can distinguish x from all the other strings in B^{=n}. Modulo the O(log n) additive term, this achieves the information-theoretic optimum for string compression. We also observe that optimal compression is not possible for sets more complex than PSPACE/poly because for any time-constructible superpolynomial function t, there is a set A computable in space t(n) such that at least one string x of length n requires compressed(x) to be of length 2 log(|A^=n|).

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arXiv2013

Short lists with short programs in short time - a short proof

Bauwens, Mahklin, Vereshchagin and Zimand [ECCC TR13-007] and Teutsch [arxiv:1212.6104] have shown that given a string x it is possible to construct in polynomial time a list containing a short description of it. We simplify their technique and present a shorter proof of this result.

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arXiv2012

On efficient constructions of short lists containing mostly Ramsey graphs

One of the earliest and best-known application of the probabilistic method is the proof of existence of a 2 log n$-Ramsey graph, i.e., a graph with n nodes that contains no clique or independent set of size 2 log n. The explicit construction of such a graph is a major open problem. We show that a reasonable hardness assumption implies that in polynomial time one can construct a list containing polylog(n) graphs such that most of them are 2 log n-Ramsey.

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arXiv2012

Symmetry of Information: A Closer Look

Symmetry of information establishes a relation between the information that x has about y (denoted I(x : y)) and the information that y has about x (denoted I(y : x)). In classical information theory, the two are exactly equal, but in algorithmical information theory, there is a small excess quantity of information that differentiates the two terms, caused by the necessity of packaging information in a way that makes it accessible to algorithms. It was shown in [Zim11] that in the case of strings with simple complexity (that is the Kolmogorov complexity of their Kolmogorov complexity is small), the relevant information can be packed in a very economical way, which leads to a tighter relation between I(x : y) and I(y : x) than the one provided in the classical symmetry-of-information theorem of Kolmogorov and Levin. We give here a simpler proof of this result, using a suggestion of Alexander Shen. This result implies a van Lambalgen- type theorem for finite strings and plain complexity: If x is c-random and y is c-random relative to x, then xy is O(c)-random. We show that a similar result holds for prefix-free complexity and weak-K-randomness.

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arXiv2012

Possibilities and impossibilities in Kolmogorov complexity extraction

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 their quality and also by using individual strings and Kolmogorov complexity to measure their quality. Complexity theorists are more familiar with the first approach. In this paper we survey the second approach. We present the connection between extractors and Kolmogorov extractors and the basic positive and negative results concerning Kolmogorov complexity extraction.

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arXiv2012

Nonuniform Kolmogorov extractors

We establish tight bounds on the amount on nonuniformity that is necessary for extracting a string with randomness rate 1 from a single source of randomness with lower randomness rate. More precisely, as instantiations of more general results, we show that while O(1) amount of advice regarding the source is not enough for extracting a string with randomness rate 1 from a source string with constant subunitary random rate, ω(1) amount of advice is.

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arXiv2011

On the optimal compression of sets in PSPACE

We show that if DTIME[2^{O(n)}] is not included in DSPACE[2^{o(n)}], then, for every set B in PSPACE, all strings x in B of length n can be represented by a string compressed(x) of length at most log (|B^{=n}|) + O(log n), such that a polynomial-time algorithm, given compressed(x), can distinguish x from all the other strings in B^{=n}. Modulo the O(log n) additive trem, this achieves the information-theoretical optimum for string compression.

cs.CC↗

arXiv2011

Symmetry of information and bounds on nonuniform randomness extraction via Kolmogorov extractors

We prove a strong Symmetry of Information relation for random strings (in the sense of Kolmogorov complexity) and establish tight bounds on the amount on nonuniformity that is necessary for extracting a string with randomness rate 1 from a single source of randomness. More precisely, as instantiations of more general results, we show: (1) For all n-bit random strings x and y, x is random conditioned by y if and only if y is random conditioned by x, and (2) while O(1) amount of advice regarding the source is not enough for extracting a string with randomness rate 1 from a source string with constant random rate, ω(1) amount of advice is. The proofs use Kolmogorov extractors as the main technical device.

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arXiv2010

Counting dependent and independent strings

The paper gives estimations for the sizes of the the following sets: (1) the set of strings that have a given dependency with a fixed string, (2) the set of strings that are pairwise αindependent, (3) the set of strings that are mutually αindependent. The relevant definitions are as follows: C(x) is the Kolmogorov complexity of the string x. A string y has α-dependency with a string x if C(y) - C(y|x) \geq α. A set of strings {x_1, \ldots, x_t} is pairwise α-independent if for all i different from j, C(x_i) - C(x_i | x_j) \leq α. A tuple of strings (x_1, \ldots, x_t) is mutually α-independent if C(x_{π(1)} \ldots x_{π(t)}) \geq C(x_1) + \ldots + C(x_t) - α, for every permutation πof [t].

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arXiv2010

Impossibility of independence amplification in Kolmogorov complexity theory

The paper studies randomness extraction from sources with bounded independence and the issue of independence amplification of sources, using the framework of Kolmogorov complexity. The dependency of strings $x$ and $y$ is ${\rm dep}(x,y) = \max\{C(x) - C(x \mid y), C(y) - C(y\mid x)\}$, where $C(\cdot)$ denotes the Kolmogorov complexity. It is shown that there exists a computable Kolmogorov extractor $f$ such that, for any two $n$-bit strings with complexity $s(n)$ and dependency $α(n)$, it outputs a string of length $s(n)$ with complexity $s(n)- α(n)$ conditioned by any one of the input strings. It is proven that the above are the optimal parameters a Kolmogorov extractor can achieve. It is shown that independence amplification cannot be effectively realized. Specifically, if (after excluding a trivial case) there exist computable functions $f_1$ and $f_2$ such that ${\rm dep}(f_1(x,y), f_2(x,y)) \leq β(n)$ for all $n$-bit strings $x$ and $y$ with ${\rm dep}(x,y) \leq α(n)$, then $β(n) \geq α(n) - O(\log n)$.

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arXiv2009

On generating independent random strings

It is shown that from two strings that are partially random and independent (in the sense of Kolmogorov complexity) it is possible to effectively construct polynomially many strings that are random and pairwise independent. If the two initial strings are random, then the above task can be performed in polynomial time. It is also possible to construct in polynomial time a random string, from two strings that have constant randomness rate.

cs.IT↗

arXiv2009

Extracting the Kolmogorov Complexity of Strings and Sequences from Sources with Limited Independence

An infinite binary sequence has randomness rate at least $σ$ if, for almost every $n$, the Kolmogorov complexity of its prefix of length $n$ is at least $σn$. It is known that for every rational $σ\in (0,1)$, on one hand, there exists sequences with randomness rate $σ$ that can not be effectively transformed into a sequence with randomness rate higher than $σ$ and, on the other hand, any two independent sequences with randomness rate $σ$ can be transformed into a sequence with randomness rate higher than $σ$. We show that the latter result holds even if the two input sequences have linear dependency (which, informally speaking, means that all prefixes of length $n$ of the two sequences have in common a constant fraction of their information). The similar problem is studied for finite strings. It is shown that from any two strings with sufficiently large Kolmogorov complexity and sufficiently small dependence, one can effectively construct a string that is random even conditioned by any one of the input strings.

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arXiv2008

Algorithmically independent sequences

Two objects are independent if they do not affect each other. Independence is well-understood in classical information theory, but less in algorithmic information theory. Working in the framework of algorithmic information theory, the paper proposes two types of independence for arbitrary infinite binary sequences and studies their properties. Our two proposed notions of independence have some of the intuitive properties that one naturally expects. For example, for every sequence $x$, the set of sequences that are independent (in the weaker of the two senses) with $x$ has measure one. For both notions of independence we investigate to what extent pairs of independent sequences, can be effectively constructed via Turing reductions (from one or more input sequences). In this respect, we prove several impossibility results. For example, it is shown that there is no effective way of producing from an arbitrary sequence with positive constructive Hausdorff dimension two sequences that are independent (even in the weaker type of independence) and have super-logarithmic complexity. Finally, a few conjectures and open questions are discussed.

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arXiv2007

Two sources are better than one for increasing the Kolmogorov complexity of infinite sequences

The randomness rate of an infinite binary sequence is characterized by the sequence of ratios between the Kolmogorov complexity and the length of the initial segments of the sequence. It is known that there is no uniform effective procedure that transforms one input sequence into another sequence with higher randomness rate. By contrast, we display such a uniform effective procedure having as input two independent sequences with positive but arbitrarily small constant randomness rate. Moreover the transformation is a truth-table reduction and the output has randomness rate arbitrarily close to 1.

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arXiv2005

Simple extractors via constructions of cryptographic pseudo-random generators

Trevisan has shown that constructions of pseudo-random generators from hard functions (the Nisan-Wigderson approach) also produce extractors. We show that constructions of pseudo-random generators from one-way permutations (the Blum-Micali-Yao approach) can be used for building extractors as well. Using this new technique we build extractors that do not use designs and polynomial-based error-correcting codes and that are very simple and efficient. For example, one extractor produces each output bit separately in $O(\log^2 n)$ time. These extractors work for weak sources with min entropy $λn$, for arbitrary constant $λ> 0$, have seed length $O(\log^2 n)$, and their output length is $\approx n^{λ/3}$.

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arXiv2000

Almost-Everywhere Superiority for Quantum Computing

Simon as extended by Brassard and Høyer shows that there are tasks on which polynomial-time quantum machines are exponentially faster than each classical machine infinitely often. The present paper shows that there are tasks on which polynomial-time quantum machines are exponentially faster than each classical machine almost everywhere.

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