arXiv subjects

Akhil S

Publications and source records attributed to Akhil S.

6 recordsLinked to original sources

arXiv2026

Resource bounded Ku\v{c}era-G\'{a}cs Theorems

The Ku\v{c}era--G\'{a}cs theorem is a fundamental result in algorithmic randomness. It states that every infinite sequence $X$ is Turing reducible to a Martin-L\"of random $R$. This paper studies resource-bounded analogues of the Ku\v{c}era-G\'acs Theorem, at the resource bounds of polynomial-time and finite-state computation. We prove a {quasi-polynomial-time}{ Ku\v{c}era-G\'acs Theorem}, showing that every infinite sequence $X$ is quasi-polynomial-time reducible to a \emph{polynomial-time random} sequence $R$. We also show that for any $X$, the oracle use of $R$ is $n+o(n)$ bits for obtaining the first $n$ bits of $X$. We then study the relationship between compressibility and Turing reductions, in the polynomial-time setting. We establish that $\rho^-_{\mathsf{poly}}(X) = K_{poly}(X)$, demonstrating that the lower polynomial-time Turing decompression ratio is precisely characterized by the polynomial-time Kolmogorov complexity rate. We note that this characterization fails for the polynomial-time dimension if one-way functions exist, resolving an open problem from Doty's work. We use these results to strengthen the {quasi-polynomial-time}{ Ku\v{c}era-G\'acs Theorem}. We show that every infinite sequence $X$ is quasi-polynomial-time reducible to a {polynomial-time random} sequence $R$, where the lower oracle use rate of the reduction is less than ${K}_{poly}(X)$. We also show that any sequence extracted from the (even larger) set of \emph{normal sequences} by a finite-state reduction must have a convergent asymptotic frequency for its symbols. Since sequences lacking this invariant property exist, they cannot be finite-state reduced from any normal sequence. Hence we show that the Ku\v{c}era-G\'acs theorem \emph{fails} for finite-state reductions.

cs.CC↗

arXiv2025

Product gales and Finite state dimension

In this work, we introduce the notion of product gales, which is the modification of an $s$-gale such that $k$ separate bets can be placed at each symbol. The product of the bets placed are taken into the capital function of the product-gale. We show that Hausdorff dimension can be characterised using product gales. A $k$-bet finite-state gambler is one that can place $k$ separate bets at each symbol. We call the notion of finite-state dimension, characterized by product gales induced by $k$-bet finite-state gamblers, as multi-bet finite-state dimension. Bourke, Hitchcock and Vinodchandran gave an equivalent characterisation of finite state dimension by disjoint block entropy rates. We show that multi-bet finite state dimension can be characterised using sliding block entropy rates. Further, we show that multi-bet finite state dimension can also be charatcterised by disjoint block entropy rates. Hence we show that finite state dimension and multi-bet finite state dimension are the same notions, thereby giving a new characterisation of finite state dimension using $k$-bet finite state $s$-gales. We also provide a proof of equivalence between sliding and disjoint block entropy rates, providing an alternate, automata based proof of the result by Kozachinskiy, and Shen.

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arXiv2024

One-Way Functions and Polynomial Time Dimension

This paper demonstrates a duality between the non-robustness of polynomial time dimension and the existence of one-way functions. Polynomial-time dimension (denoted $\mathrm{cdim}_\mathrm{P}$) quantifies the density of information of infinite sequences using polynomial time betting algorithms called $s$-gales. An alternate quantification of the notion of polynomial time density of information is using polynomial-time Kolmogorov complexity rate (denoted $\mathcal{K}_\text{poly}$). Hitchcock and Vinodchandran (CCC 2004) showed that $\mathrm{cdim}_\mathrm{P}$ is always greater than or equal to $\mathcal{K}_\text{poly}$. We first show that if one-way functions exist then there exists a polynomial-time samplable distribution with respect to which $\mathrm{cdim}_\mathrm{P}$ and $\mathcal{K}_\text{poly}$ are separated by a uniform gap with probability $1$. Conversely, we show that if there exists such a polynomial-time samplable distribution, then (infinitely-often) one-way functions exist. Using our main results, we solve a long standing open problem posed by Hitchcock and Vinodchandran (CCC 2004) and Stull under the assumption that one-way functions exist. We demonstrate that if one-way functions exist, then there are individual sequences $X$ whose poly-time dimension strictly exceeds $\mathcal{K}_\text{poly}(X)$, that is $\mathrm{cdim}_\mathrm{P}(X) > \mathcal{K}_\text{poly}(X)$. Further, we show that the gap between these quantities can be made as large as possible (i.e. close to 1). We also establish similar bounds for strong poly-time dimension versus asymptotic upper Kolmogorov complexity rates.

cs.CC↗

arXiv2024

Point-to-set Principle and Constructive Dimension Faithfulness

Hausdorff $\Phi$-dimension is a notion of Hausdorff dimension developed using a restricted class of coverings of a set. We introduce an effective version of Hausdorff $\Phi$-dimension, which we call constructive $\Phi$-dimension. We prove a point-to-set principle for $\Phi$-dimension. We also provide a characterization of constructive $\Phi$-dimension using Kolmogorov complexity and $s$-gales. Finally, we apply these tools to study faithfulness of coverings $\Phi$. A family of coverings $\Phi$ is said to be faithful to Hausdorff dimension if the $\Phi$-dimension and Hausdorff dimension coincide for every set. Similarly, $\Phi$ is said to be faithful to constructive dimension if the constructive $\Phi$-dimension and constructive dimension coincide for every set. We derive the necessary and sufficient conditions for the constructive dimension faithfulness of the coverings generated by the Cantor series expansion, based on the terms of the expansion. Using the point-to-set principle for Cantor coverings, we show that the same condition characterises Hausdorff dimension faithfulness of Cantor coverings, thereby giving an information theoretic proof of the result by Albeverio, Ivanenko, Lebid, and Torbin. We investigate the question of weather the notions of faithfulness at Hausdorff and constructive levels are equivalent. Using a new technique for the construction of sequences satisfying a certain Kolmogorov complexity condition, we show that the notions of ``faithfulness'' of Cantor coverings at the Hausdorff and constructive levels are equivalent, independent of the log-limit condition.

cs.IT↗

arXiv2023

Effective Continued Fraction Dimension versus Effective Hausdorff Dimension of Reals

We establish that constructive continued fraction dimension originally defined using $s$-gales is robust, but surprisingly, that the effective continued fraction dimension and effective (base-$b$) Hausdorff dimension of the same real can be unequal in general. We initially provide an equivalent characterization of continued fraction dimension using Kolmogorov complexity. In the process, we construct an optimal lower semi-computable $s$-gale for continued fractions. We also prove new bounds on the Lebesgue measure of continued fraction cylinders, which may be of independent interest. We apply these bounds to reveal an unexpected behavior of continued fraction dimension. It is known that feasible dimension is invariant with respect to base conversion. We also know that Martin-L\"of randomness and computable randomness are invariant not only with respect to base conversion, but also with respect to the continued fraction representation. In contrast, for any $0 < \varepsilon < 0.5$, we prove the existence of a real whose effective Hausdorff dimension is less than $\varepsilon$, but whose effective continued fraction dimension is greater than or equal to $0.5$. This phenomenon is related to the ``non-faithfulness'' of certain families of covers, investigated by Peres and Torbin and by Albeverio, Ivanenko, Lebid and Torbin. We also establish that for any real, the constructive Hausdorff dimension is at most its effective continued fraction dimension.

cs.IT↗

arXiv2023

Finite-State Relative Dimension, dimensions of A. P. subsequences and a Finite-State van Lambalgen's theorem

Finite-state dimension (Dai, Lathrop, Lutz, and Mayordomo (2004)) quantifies the information rate in an infinite sequence as measured by finite-state automata. In this paper, we define a relative version of finite-state dimension. The finite-state relative dimension $dim_{FS}^Y(X)$ of a sequence $X$ relative to $Y$ is the finite-state dimension of $X$ measured using the class of finite-state gamblers with an oracle access to $Y$. We show its mathematical robustness by equivalently characterizing this notion using the relative block entropy rate of $X$ conditioned on $Y$. We derive inequalities relating the dimension of a sequence to the relative dimension of its subsequences along any arithmetic progression (A.P.). These enable us to obtain a strengthening of Wall's Theorem on the normality of A.P. subsequences of a normal number, in terms of relative dimension. In contrast to the original theorem, this stronger version has an exact converse yielding a new characterization of normality. We also obtain finite-state analogues of van Lambalgen's theorem on the symmetry of relative normality.

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