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Dawid Tarłowski

Publications and source records attributed to Dawid Tarłowski.

5 recordsLinked to original sources

The equality cases $P_t(\mathbb{N})=\tfrac12$ for the deconvolved sum-of-digits measures

Let $s(n)$ denote the number of ones in the binary expansion of an integer $n\in\mathbb{N}$, and let $μ_t$ be the probability measure on $\mathbb{Z}$ defined by the asymptotic densities of the level sets of the function $\mathbb{N}\ni n\mapsto s(n+t)-s(n)\in\mathbb{Z}$. Let $P_t$ be the family of finitely supported measures defined by the convolution $μ_t=μ_1*P_t$. Recently, Tarlowski (2026) has shown that the family $P_t$ may be represented as a recursively grown binary tree $T_t$, and that the Cusick's conjecture - $μ_t(\mathbb{N})>\frac12$, $t\in\mathbb{N}$, - follows from the asymmetry property of the family $T_t$, which was posed there as an open problem. Next, Cheng (2026) has provided the combinatorial description of the family $T_t$ in the language of principal subsequence ideals, and proved both conjectures. Both of these problems are directly related to the problem of determining the zeros of the function $\mathbb{N}\ni t \mapsto P_t(\mathbb{N})-\frac12\in[0,\tfrac12]$, a problem left open by Cheng (2026) as a saturation problem, and previously analyzed only numerically. In this paper we solve this problem completely. Writing an odd integer $t\ge3$ as $t=(1\,w\,1)_2$ with $w\in\{0,1\}^{\star}$, we show that $P_t(\mathbb{N})=\frac12$ if and only if $w$ is \emph{saturated} in the following sense: in the block decomposition $w=1^{a_0}\,0\,1^{a_1}\,0\cdots0\,1^{a_k}$ with exactly $k$ zeros, every block of "1" satisfies $a_i\ge k$. Additionally, we show that the lower bound for $P_t(\mathbb{N})$ established by Cheng for $0$-initial words holds true for all non-saturated words.

math.NT↗

On the sum-of-digits measures and Cusick's conjecture via stopped random walks

Let $s(n)$ denote the number of ones in the binary expansion of a natural number $n\in\mathbb{N}$. For any $t\in\mathbb{N}$ and $d\in\mathbb{Z}$, let $μ_t(d)$ denote the asymptotic density of the set of those natural numbers $n$ for which $s(n+t)-s(n)=d$. The $μ_t$ are properly defined probability measures on $\Z$, and the Cusick conjecture states that $μ_t(\mathbb{N})>\frac{1}{2}$ for any $t\in\mathbb{N}$. We investigate the properties of the family $\{μ_t\}_{t\in\N}$ by reindexing the odd integers via a suitable partial order. This construction leads to a nonautonomous dynamics on pairs of probability measures on $\Z$, which represents the process of growing a tree. The associated stopped random walk allows a transparent structural description of those measures, including their support, symmetries, variance, and an asymptotic dichotomy between the central limit theorem and the almost sure convergence. Next, we focus on the median-preserving property of this process, and show that the Cusick conjecture is a special case of a more general claim about the asymmetric evolution of the associated binary trees, which we support numerically.

math.PR↗

Conditional uncorrelation equals independence

We show that the stochastic independence of real-valued random variables is equivalent to the conditional uncorrelation, where the conditioning takes place over the Cartesian products of intervals. Next, we express the mutual independence in terms of the conditional correlation matrix. Our results extend the results of Jaworski et al. (Electron. J. Stat., 18(1), 653-673, 2024), which are based on the copula functions and assume the existence of the joint density of the variables. We relax this assumption and show that the independence characterization via conditional uncorrelation is valid in full generality - that is, for all kinds of random variables and any dependencies between them. Additionally, we analyse the assumptions under which the independence is determined by the local uncorrelation. The measure-theoretic methodology we present uses the Radon-Nikodym derivative to reduce the multidimensional characterization problem to the simple one-dimensional conditioning. To demonstrate the potential usefulness of the presented results, various numerical examples are presented.

math.ST↗

Sleeping Beauty and Markov chains

Sleeping Beauty Problem (SBP) is a probability puzzle which has created much confusion in the literature. In this paper we present the analysis of SBP with use of ergodic Markov chains. The presented model formally connects two different answers to the problem and clarifies some errors related to the frequentist analysis of the paradox.

math.PR↗

On Exponential Convergence of Random Variables

Given the discrete-time sequence of nonnegative random variables, general dependencies between the exponential convergence of the expectations, exponential convergence of the trajectories and the logarithmic growth of the corresponding expected hitting times are analysed. The applications are presented: the general results are applied to the areas of optimization, stochastic control and estimation.

math.PR↗