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Related papers: Quantitative Strong Laws of Large Numbers

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Strong converse theorems refer to the study of impossibility results in information theory. In particular, Mosonyi and Ogawa established a one-shot strong converse bound for quantum hypothesis testing [Comm. Math. Phys, 334(3), 2014], which…

Quantum Physics · Physics 2024-03-21 Hao-Chung Cheng , Li Gao

Quantum-enhanced measurements exploit quantum mechanical effects to provide ultra-precise estimates of physical variables for use in advanced technologies, such as frequency calibration of atomic clocks, gravitational waves detection, and…

Quantum Physics · Physics 2014-07-28 J. Calsamiglia , B. Gendra , R. Munoz-Tapia , E. Bagan

Let $A_q(n,d)$ be the maximum order (maximum number of codewords) of a $q$-ary code of length $n$ and Hamming distance at least $d$. And let $A(n,d,w)$ that of a binary code of constant weight $w$. Building on results from algebraic graph…

Information Theory · Computer Science 2008-07-01 Salim Y. El Rouayheb , C. N. Georghiades , E. Soljanin , A. Sprintson

Quantum mechanics for many-body systems may be reduced to the evaluation of integrals in 3N dimensions using Monte-Carlo, providing the Quantum Monte Carlo ab initio methods. Here we limit ourselves to expectation values for trial…

Computational Physics · Physics 2010-11-22 John Robert Trail , Ryo Maezono

Let $X_1,X_2,...,X_n$ be a sequence of independent or locally dependent random variables taking values in $\mathbb{Z}_+$. In this paper, we derive sharp bounds, via a new probabilistic method, for the total variation distance between the…

Statistics Theory · Mathematics 2010-10-11 Michael V. Boutsikas , Eutichia Vaggelatou

We study random compositions of transformations having certain uniform fiberwise properties and prove bounds which in combination with other results yield a quenched central limit theorem equipped with a convergence rate, also in the…

Dynamical Systems · Mathematics 2020-01-08 Olli Hella , Mikko Stenlund

Peng (2006) initiated a new kind of central limit theorem under sub-linear expectations. Song (2017) gave an estimate of the rate of convergence of Peng's central limit theorem. Based on these results, we establish a new kind of almost sure…

Probability · Mathematics 2018-10-19 Weihuan Huang , Panyu Wu

In this paper, we develop a general approach to proving global and local uniform limit theorems for the Horvitz-Thompson empirical process arising from complex sampling designs. Global theorems such as Glivenko-Cantelli and Donsker…

Statistics Theory · Mathematics 2019-05-31 Qiyang Han , Jon A. Wellner

Codes in the sum-rank metric have received many attentions in recent years, since they have wide applications in the multishot network coding, the space-time coding and the distributed storage. In this paper, by constructing covering codes…

Information Theory · Computer Science 2026-02-19 Chao Liu , Hao Chen , Qinqin Ji , Ziyan Xie , Dabin Zheng , Yongbo Xia

We survey some results that provide different versions of classical results through different summability methods. Specifically, in order to adapt such classical results, we analyze which properties should satisfy the summability methods.…

The dominated convergence theorem implies that if (f_n) is a sequence of functions on a probability space taking values in the interval [0,1], and (f_n) converges pointwise a.e., then the sequence of integrals converges to the integral of…

Functional Analysis · Mathematics 2014-01-03 Jeremy Avigad , Edward Dean , Jason Rute

We show that external randomization may enforce the convergence of test statistics to their limiting distributions in particular cases. This results in a sharper inference. Our approach is based on a central limit theorem for weighted sums.…

Statistics Theory · Mathematics 2022-11-17 Nikita Puchkin , Vladimir Ulyanov

The Law of Large Numbers tells us that as the sample size (N) is increased, the sample mean converges on the population mean, provided that the latter exists. In this paper, we investigate the opposite effect: keeping the sample size fixed…

Probability · Mathematics 2008-03-28 Kieran Kelly , Przemyslaw Repetowicz , Seosamh macReamoinn

Quantitative limit theorems for non-linear functionals on the Wiener space are considered. Given the possibly infinite sequence of kernels of the chaos decomposition of such a functional, an estimate for different probability distances…

Probability · Mathematics 2016-10-06 Tobias Fissler , Christoph Thaele

We consider a random tree and introduce a metric in the space of trees to define the ``mean tree'' as the tree minimizing the average distance to the random tree. When the resulting metric space is compact we have laws of large numbers and…

Probability · Mathematics 2007-05-23 David Balding , Pablo A. Ferrari , Ricardo Fraiman , Mariela Sued

We define a metric on $\mathbb{F}_q^n$ using the linear complexity of finite sequences. We will then develop a coding theory for this metric. We will give a Singleton-like bound and we will give constructions of subspaces of…

Information Theory · Computer Science 2018-03-19 Tovohery Randrianarisoa

The quantum adversary method is a versatile method for proving lower bounds on quantum algorithms. It yields tight bounds for many computational problems, is robust in having many equivalent formulations, and has natural connections to…

Quantum Physics · Physics 2007-05-23 Peter Hoyer , Troy Lee , Robert Spalek

A family of random matrices is said to converge strongly to a limiting family of operators if the operator norm of every noncommutative polynomial of the matrices converges to that of the limiting operators. Recent developments surrounding…

Probability · Mathematics 2025-10-15 Ramon van Handel

Let $X$, $X_1$, $X_2$, $...$ be i.i.d. random variables, and let $S_n=X_1+... + X_n$ be the partial sums and $M_n=\max_{k\le n}|S_k|$ be the maximum partial sums. We give the sufficient and necessary conditions for a kind of limit theorems…

Probability · Mathematics 2007-05-23 Li-Xin Zhang

In this paper, under some weaker conditions, we give three laws of large numbers under sublinear expectations (capacities), which extend Peng's law of large numbers under sublinear expectations in [8] and Chen's strong law of large numbers…

Probability · Mathematics 2012-02-10 Feng Hu