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Jack H. Lutz

Publications and source records attributed to Jack H. Lutz.

43 records · Page 3Linked to original sources

Points on Computable Curves

The ``analyst's traveling salesman theorem'' of geometric measure theory characterizes those subsets of Euclidean space that are contained in curves of finite length. This result, proven for the plane by Jones (1990) and extended to higher-dimensional Euclidean spaces by Okikiolu (1991), says that a bounded set $K$ is contained in some curve of finite length if and only if a certain ``square beta sum'', involving the ``width of $K$'' in each element of an infinite system of overlapping ``tiles'' of descending size, is finite. In this paper we characterize those {\it points} of Euclidean space that lie on {\it computable} curves of finite length by formulating and proving a computable extension of the analyst's traveling salesman theorem. Our extension says that a point in Euclidean space lies on some computable curve of finite length if and only if it is ``permitted'' by some computable ``Jones constriction''. A Jones constriction here is an explicit assignment of a rational cylinder to each of the above-mentioned tiles in such a way that, when the radius of the cylinder corresponding to a tile is used in place of the ``width of $K$'' in each tile, the square beta sum is finite. A point is permitted by a Jones constriction if it is contained in the cylinder assigned to each tile containing the point. The main part of our proof is the construction of a computable curve of finite length traversing all the points permitted by a given Jones constriction. Our construction uses the main ideas of Jones's ``farthest insertion'' construction, but our algorithm for computing the curve must work exclusively with the Jones constriction itself, because it has no direct access to the (typically uncomputable) points permitted by the Jones constriction.

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Dimensions of Copeland-Erdos Sequences

The base-$k$ {\em Copeland-Erdös sequence} given by an infinite set $A$ of positive integers is the infinite sequence $\CE_k(A)$ formed by concatenating the base-$k$ representations of the elements of $A$ in numerical order. This paper concerns the following four quantities. The {\em finite-state dimension} $\dimfs (\CE_k(A))$, a finite-state version of classical Hausdorff dimension introduced in 2001. The {\em finite-state strong dimension} $\Dimfs(\CE_k(A))$, a finite-state version of classical packing dimension introduced in 2004. This is a dual of $\dimfs(\CE_k(A))$ satisfying $\Dimfs(\CE_k(A))$ $\geq \dimfs(\CE_k(A))$. The {\em zeta-dimension} $\Dimzeta(A)$, a kind of discrete fractal dimension discovered many times over the past few decades. The {\em lower zeta-dimension} $\dimzeta(A)$, a dual of $\Dimzeta(A)$ satisfying $\dimzeta(A)\leq \Dimzeta(A)$. We prove the following. $\dimfs(\CE_k(A))\geq \dimzeta(A)$. This extends the 1946 proof by Copeland and Erdös that the sequence $\CE_k(\mathrm{PRIMES})$ is Borel normal. $\Dimfs(\CE_k(A))\geq \Dimzeta(A)$. These bounds are tight in the strong sense that these four quantities can have (simultaneously) any four values in $[0,1]$ satisfying the four above-mentioned inequalities.

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Zeta-Dimension

The zeta-dimension of a set A of positive integers is the infimum s such that the sum of the reciprocals of the s-th powers of the elements of A is finite. Zeta-dimension serves as a fractal dimension on the positive integers that extends naturally usefully to discrete lattices such as the set of all integer lattice points in d-dimensional space. This paper reviews the origins of zeta-dimension (which date to the eighteenth and nineteenth centuries) and develops its basic theory, with particular attention to its relationship with algorithmic information theory. New results presented include extended connections between zeta-dimension and classical fractal dimensions, a gale characterization of zeta-dimension, and a theorem on the zeta-dimensions of pointwise sums and products of sets of positive integers.

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The Arithmetical Complexity of Dimension and Randomness

Constructive dimension and constructive strong dimension are effectivizations of the Hausdorff and packing dimensions, respectively. Each infinite binary sequence A is assigned a dimension dim(A) in [0,1] and a strong dimension Dim(A) in [0,1]. Let DIM^alpha and DIMstr^alpha be the classes of all sequences of dimension alpha and of strong dimension alpha, respectively. We show that DIM^0 is properly Pi^0_2, and that for all Delta^0_2-computable alpha in (0,1], DIM^alpha is properly Pi^0_3. To classify the strong dimension classes, we use a more powerful effective Borel hierarchy where a co-enumerable predicate is used rather than a enumerable predicate in the definition of the Sigma^0_1 level. For all Delta^0_2-computable alpha in [0,1), we show that DIMstr^alpha is properly in the Pi^0_3 level of this hierarchy. We show that DIMstr^1 is properly in the Pi^0_2 level of this hierarchy. We also prove that the class of Schnorr random sequences and the class of computably random sequences are properly Pi^0_3.

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Effective Strong Dimension, Algorithmic Information, and Computational Complexity

The two most important notions of fractal dimension are {\it Hausdorff dimension}, developed by Hausdorff (1919), and {\it packing dimension}, developed by Tricot (1982). Lutz (2000) has recently proven a simple characterization of Hausdorff dimension in terms of {\it gales}, which are betting strategies that generalize martingales. Imposing various computability and complexity constraints on these gales produces a spectrum of effective versions of Hausdorff dimension. In this paper we show that packing dimension can also be characterized in terms of gales. Moreover, even though the usual definition of packing dimension is considerably more complex than that of Hausdorff dimension, our gale characterization of packing dimension is an exact dual of -- and every bit as simple as -- the gale characterization of Hausdorff dimension. Effectivizing our gale characterization of packing dimension produces a variety of {\it effective strong dimensions}, which are exact duals of the effective dimensions mentioned above. We develop the basic properties of effective strong dimensions and prove a number of results relating them to fundamental aspects of randomness, Kolmogorov complexity, prediction, Boolean circuit-size complexity, polynomial-time degrees, and data compression.

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Dimension in Complexity Classes

A theory of resource-bounded dimension is developed using gales, which are natural generalizations of martingales. When the resource bound Δ(a parameter of the theory) is unrestricted, the resulting dimension is precisely the classical Hausdorff dimension (sometimes called fractal dimension). Other choices of the parameter Δyield internal dimension theories in E, E2, ESPACE, and other complexity classes, and in the class of all decidable problems. In general, if C is such a class, then every set X of languages has a dimension in C, which is a real number dim(X|C) in [0,1]. Along with the elements of this theory, two preliminary applications are presented: 1. For every real number αin (0,1/2), the set FREQ(<=α), consisting of all languages that asymptotically contain at most αof all strings, has dimension H(α) -- the binary entropy of α-- in E and in E2. 2. For every real number αin (0,1), the set SIZE(α* (2^n)/n), consisting of all languages decidable by Boolean circuits of at most α*(2^n)/n gates, has dimension αin ESPACE.

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The Dimensions of Individual Strings and Sequences

A constructive version of Hausdorff dimension is developed using constructive supergales, which are betting strategies that generalize the constructive supermartingales used in the theory of individual random sequences. This constructive dimension is used to assign every individual (infinite, binary) sequence S a dimension, which is a real number dim(S) in the interval [0,1]. Sequences that are random (in the sense of Martin-Lof) have dimension 1, while sequences that are decidable, Σ^0_1, or Π^0_1 have dimension 0. It is shown that for every Δ^0_2-computable real number αin [0,1] there is a Δ^0_2 sequence S such that \dim(S) = α. A discrete version of constructive dimension is also developed using termgales, which are supergale-like functions that bet on the terminations of (finite, binary) strings as well as on their successive bits. This discrete dimension is used to assign each individual string w a dimension, which is a nonnegative real number dim(w). The dimension of a sequence is shown to be the limit infimum of the dimensions of its prefixes. The Kolmogorov complexity of a string is proven to be the product of its length and its dimension. This gives a new characterization of algorithmic information and a new proof of Mayordomo's recent theorem stating that the dimension of a sequence is the limit infimum of the average Kolmogorov complexity of its first n bits. Every sequence that is random relative to any computable sequence of coin-toss biases that converge to a real number βin (0,1) is shown to have dimension \H(β), the binary entropy of β.

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