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The quantum central limit theorem for bosonic quantum systems states that the sequence of states $\rho^{\boxplus n}$ obtained from the $n$-fold convolution of a centered quantum state $\rho$ converges to a quantum Gaussian state $\rho_G$…

Quantum Physics · Physics 2025-08-01 Salman Beigi , Hami Mehrabi

A quantum analogue of the Central Limit Theorem (CLT) for bosonic system, first introduced by Cushen and Hudson (1971), states that the $n$-fold convolution $\rho^{\boxplus n}$ of an $m$-mode quantum state $\rho$, with zero first moments…

Quantum Physics · Physics 2026-05-11 Salman Beigi , Milad M. Goodarzi , Hami Mehrabi

Let $Q$ be a transition probability on a measurable space $E$, let $(X\_n)\_n$ be a Markov chain associated to $Q$, and let $\xi$ be a real-valued measurable function on $E$, and $S\_n = \sum\_{k=1}^{n} \xi(X\_k)$. Under functional…

Probability · Mathematics 2007-05-23 Loïc Hervé

Let $Q$ be a transition probability on a measurable space $E$ which admits an invariant probability measure, let $(X_n)_n$ be a Markov chain associated to $Q$, and let $\xi$ be a real-valued measurable function on $E$, and $S_n=\sum…

Probability · Mathematics 2008-12-18 Loïc Hervé

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

We establish effective convergence rates in the Doeblin-Lenstra law, describing the limiting distribution of approximation coefficients arising from continued fraction convergents of a typical real number. More generally, we prove…

Number Theory · Mathematics 2025-07-28 Gaurav Aggarwal , Anish Ghosh

This paper is concerned with normal approximation under relaxed moment conditions using Stein's method. We obtain the explicit rates of convergence in the central limit theorem for (i) nonlinear statistics with finite absolute moment of…

Probability · Mathematics 2021-06-16 Nguyen Tien Dung

We establish central limit theorems for a large class of supercritical branching Markov processes in infinite dimension with spatially dependent and non-necessarily local branching mechanisms. This result relies on a fourth moment…

Probability · Mathematics 2025-01-31 Bertrand Cloez , Nicolás Zalduendo

We provide rates of convergence in the central limit theorem in terms of projective criteria for adapted stationary sequences of centered random variables taking values in Banach spaces, with finite moment of order $p \in ]2,3]$ as soon as…

Probability · Mathematics 2025-02-21 Aurélie Bigot

We derive rates of convergence for limit theorems that reveal the intricate structure of the phase transitions in a mean-field version of the Blume-Emery-Griffith model. The theorems consist of scaling limits for the total spin. The model…

Probability · Mathematics 2015-06-15 Peter Eichelsbacher , Bastian Martschink

In classical estimation theory, the central limit theorem implies that the statistical error in a measurement outcome can be reduced by an amount proportional to n^(-1/2) by repeating the measures n times and then averaging. Using quantum…

Quantum Physics · Physics 2015-05-27 Vittorio Giovannetti , Seth Lloyd , Lorenzo Maccone

We define the quantile set of order $\alpha \in \left[ 1/2,1\right) $ associated to a law $P$ on $\mathbb{R}^{d}$ to be the collection of its directional quantiles seen from an observer $O\in \mathbb{R}^{d}$. Under minimal assumptions these…

Statistics Theory · Mathematics 2016-12-06 Adil Ahidar-Coutrix , Philippe Berthet

The quantum central limit theorem derived by Cushen and Hudson provides the foundations for understanding how subsystems of large bosonic systems evolving unitarily do reach equilibrium. It finds important applications in the context of…

Quantum Physics · Physics 2024-04-18 Marco Robbio , Michael G. Jabbour , Leonardo Novo , Nicolas J. Cerf

We are interested in a fragmentation process. We observe fragments frozen when their sizes are less than {\epsilon} ({\epsilon} > 0). It is known ([BM05]) that the empirical measure of these fragments converges in law, under some…

Probability · Mathematics 2022-10-17 Camille Noûs , Sylvain Rubenthaler

We provide new bounds for the rate of convergence of the multivariate Central Limit Theorem in Wasserstein distances of order $p \geq 2$. In particular, we obtain what we conjecture to be the asymptotically optimal rate whenever the density…

Probability · Mathematics 2024-04-30 Thomas Bonis

A famous result in renewal theory is the Central Limit Theorem for renewal processes. As in applications usually only observations from a finite time interval are available, a bound on the Kolmogorov distance to the normal distribution is…

Probability · Mathematics 2018-07-24 Gesine Reinert , Ce Yang

We present a way to use Stein's method in order to bound the Wasserstein distance of order $2$ between two measures $\nu$ and $\mu$ supported on $\mathbb{R}^d$ such that $\mu$ is the reversible measure of a diffusion process. In order to…

Probability · Mathematics 2018-06-25 Thomas Bonis

Let $G$ be a group with a non-elementary action on a proper CAT(0) space $X$, and let $\mu$ be a measure on $G$ such that the random walk $(Z_n)_n$ generated by $\mu$ has finite second moment on $X$. Let $o$ be a basepoint in $X$, and…

Group Theory · Mathematics 2024-07-31 Corentin Le Bars

In the literature of high-dimensional central limit theorems, there is a gap between results for general limiting correlation matrix $\Sigma$ and the strongly non-degenerate case. For the general case where $\Sigma$ may be degenerate, under…

Probability · Mathematics 2023-05-30 Xiao Fang , Yuta Koike , Song-Hao Liu , Yi-Kun Zhao

We introduce a framework to derive quantitative central limit theorems in the context of non-linear approximation of Gaussian random variables taking values in a separable Hilbert space. In particular, our method provides an alternative to…

Probability · Mathematics 2020-11-25 Solesne Bourguin , Simon Campese
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