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Related papers: Large deviations and Chernoff bound for certain co…

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This paper develops an optimal Chernoff type bound for the probabilities of large deviations of sums $\sum_{k=1}^n f (X_k)$ where $f$ is a real-valued function and $(X_k)_{k \in \mathbb{Z}_{\ge 0}}$ is a finite state Markov chain with an…

Probability · Mathematics 2019-12-24 Vrettos Moulos , Venkat Anantharam

Large deviation inequalities for ergodic sums is an important subject since the seminal contribution of Bernstein for independent random variables with finite variances, followed by the Chernoff method and the Hoefding result for…

Probability · Mathematics 2025-12-12 Miguel Abadi

The purpose of this paper is to ensure the conditions of G\"artner-Ellis Theorem for evaluations of the empirical measure. We show that up-to-date conditions for ensuring the convergence to a quasi-stationary distribution can be applied…

Probability · Mathematics 2020-04-21 Aurélien Velleret

We show sharp bounds for probabilities of large deviations for sums of independent random variables satisfying Bernstein's condition. One such bound is very close to the tail of the standard Gaussian law in certain case; other bounds…

Probability · Mathematics 2015-07-13 Xiequan Fan , Ion Grama , Quansheng Liu

Exploiting quantum measurements is a promising route for preparation of correlated quantum states. We use methods from large deviation theory to solve this problem exactly for a specific system: the deterministic quantum East circuit with…

Statistical Mechanics · Physics 2026-04-21 Jimin Li , Bruno Bertini , Juan P. Garrahan , Robert L. Jack

We establish the large deviation principle for a topological Markov shift over infinite alphabet which satisfies strong combinatorial assumptions called ``finite irreducibility'' or ``finite primitiveness''. More precisely, we assume the…

Dynamical Systems · Mathematics 2019-03-19 Hiroki Takahasi

In this article we consider an extension of the classical Curie-Weiss model in which the global and deterministic external magnetic field is replaced by local and random external fields which interact with each spin of the system. We prove…

Probability · Mathematics 2013-04-18 Matthias Löwe , Raphael Meiners , Felipe Torres

The Chernoff bound is a well-known tool for obtaining a high probability bound on the expectation of a Bernoulli random variable in terms of its sample average. This bound is commonly used in statistical learning theory to upper bound the…

Machine Learning · Statistics 2022-05-18 Andrew Y. K. Foong , Wessel P. Bruinsma , David R. Burt

An identity between two versions of the Chernoff bound on the probability a certain large deviations event, is established. This identity has an interpretation in statistical physics, namely, an isothermal equilibrium of a composite system…

Information Theory · Computer Science 2007-07-13 Neri Merhav

Under the assumption that the distribution of a nonnegative random variable $X$ admits a bounded coupling with its size biased version, we prove simple and strong concentration bounds. In particular the upper tail probability is shown to…

Probability · Mathematics 2014-07-15 Richard Arratia , Peter Baxendale

We consider decision problems on finite sets of hypotheses represented by pairwise different shift-invariant states on a quantum spin chain. The decision in favor of one of the hypotheses is based on outputs of generalized measurements…

Quantum Physics · Physics 2015-05-18 Michael Nussbaum , Arleta Szkola

We obtain large deviations for a class of dependent random variables in the domain of attraction of an $\alpha$-stable law, $\alpha\in (0, 1)\cup (1, 2]$. This class includes ergodic sums of observables in the domain of attraction of an…

Probability · Mathematics 2024-06-18 Jonny Imbierski , Dalia Terhesiu

By combining the Minkowski inequality and the quantum Chernoff bound, we derive easy-to-compute upper bounds for the error probability affecting the optimal discrimination of Gaussian states. In particular, these bounds are useful when the…

Quantum Physics · Physics 2008-07-27 Stefano Pirandola , Seth Lloyd

Let $\Sigma_{A}(\mathbb{N})$ be a topologically mixing countable Markov shift with the BIP property over the alphabet $\mathbb{N}$ and $f: \Sigma_{A}(\mathbb{N}) \rightarrow \mathbb{R}$ a potential satisfying the Walters condition with…

Dynamical Systems · Mathematics 2016-12-23 Rodrigo Bissacot , Jairo K. Mengue , Edgardo Pérez

In probability theory, the Chernoff bound gives exponentially decreasing bounds on tail distributions for sums of independent random variables and such bound is applied at different fields in science and engineering. In this work, we…

Probability · Mathematics 2021-09-29 Shih Yu Chang

We study generalisations of a simple, combinatorial proof of a Chernoff bound similar to the one by Impagliazzo and Kabanets (RANDOM, 2010). In particular, we prove a randomized version of the hitting property of expander random walks and…

Discrete Mathematics · Computer Science 2015-01-16 Jan Hązła , Thomas Holenstein

Using local density correlation functions for a one-dimensional spin system, we introduce a correlation function difference (CFD) which compares correlations on a given site between a full system of size $L$ and its restriction to $\ell<L$…

Disordered Systems and Neural Networks · Physics 2023-03-30 Tomasz Szołdra , Piotr Sierant , Maciej Lewenstein , Jakub Zakrzewski

We consider level-2 large deviations for the one-sided countable full shift without assuming the existence of Bowen's Gibbs state. To deal with non-compact closed sets, we provide a sufficient condition in terms of inducing which ensures…

Dynamical Systems · Mathematics 2023-07-26 Hiroki Takahasi

Chernoff's bound binds a tail probability (ie. $Pr(X \ge a)$, where $a \ge EX$). Assuming that the distribution of $X$ is $Q$, the logarithm of the bound is known to be equal to the value of relative entropy (or minus Kullback-Leibler…

Probability · Mathematics 2012-08-27 M. Grendar, , M. Grendar

The paper that is commented by Touchette contains a computational study which opens the door to a desirable generalization of the standard large deviation theory (applicable to a set of $N$ nearly independent random variables) to systems…

Statistical Mechanics · Physics 2015-06-12 Guiomar Ruiz , Constantino Tsallis
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