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With the recent development of quantum information theory, some attempts exist to construct information theory beyond quantum theory. Here we consider hypothesis testing relative entropy and one-shot classical capacity, that is, the optimal…

Quantum Physics · Physics 2024-06-14 Shintaro Minagawa , Hayato Arai

In this paper, we build upon the asymptotic theory for GARCH processes, considering the general class of augmented GARCH($p$, $q$) processes. Our contribution is to complement the well-known univariate asymptotics by providing a joint…

Statistics Theory · Mathematics 2019-12-24 Marcel Bräutigam , Marie Kratz

The Shannon based conditional entropy that underlies five-dimensional Einstein-Hilbert gravity coupled to a dilaton field is investigated in the context of dynamical holographic AdS/QCD models. Considering the UV and IR dominance limits of…

High Energy Physics - Theory · Physics 2016-09-22 Alex E. Bernardini , Roldao da Rocha

General Central limit theorem deals with weak limits (in type) of sums of row-elements of array random variables. In some situations as in the invariance principle problem, the sums may include only parts of the row-elements. For strictly…

We introduce the entropic measure transform (EMT) problem for a general process and prove the existence of a unique optimal measure characterizing the solution. The density process of the optimal measure is characterized using a…

Mathematical Finance · Quantitative Finance 2019-02-22 Renjie Wang , Cody Hyndman , Anastasis Kratsios

This work deals with the asymptotic distribution of both potentials and couplings of entropic regularized optimal transport for compactly supported probabilities in $\R^d$. We first provide the central limit theorem of the Sinkhorn…

Probability · Mathematics 2024-06-06 Alberto Gonzalez-Sanz , Jean-Michel Loubes , Jonathan Niles-Weed

Estimation of quantum relative entropy and its R\'{e}nyi generalizations is a fundamental statistical task in quantum information theory, physics, and beyond. While several estimators of these divergences have been proposed in the…

Quantum Physics · Physics 2024-10-16 Sreejith Sreekumar , Mario Berta

The classical condition on the existence of uniformly exponentially consistent tests for testing the true density against the complement of its arbitrary neighborhood has been widely adopted in study of asymptotics of Bayesian nonparametric…

Statistics Theory · Mathematics 2008-12-01 Yang Xing

Asymptotic bootstrap validity is usually understood as consistency of the distribution of a bootstrap statistic, conditional on the data, for the unconditional limit distribution of a statistic of interest. From this perspective, randomness…

Econometrics · Economics 2025-10-09 Giuseppe Cavaliere , Iliyan Georgiev

The more information a measurement provides about a quantum system's position statistics, the less information a subsequent measurement can provide about the system's momentum statistics. This information trade-off is embodied in the…

Quantum Physics · Physics 2016-05-16 Gregory A. Howland , James Schneeloch , Daniel J. Lum , John C. Howell

We study the convergence in distribution norms in the Central Limit Theorem for non identical distributed random variables that is $$ \varepsilon_{n}(f):={\mathbb{E}}\Big(f\Big(\frac 1{\sqrt…

Probability · Mathematics 2019-05-16 Vlad Bally , Lucia Caramellino , Guillaume Poly

When the study variable is functional and storage capacities are limited or transmission costs are high, selecting with survey sampling techniques a small fraction of the observations is an interesting alternative to signal compression…

Statistics Theory · Mathematics 2013-02-15 Hervé Cardot , Camelia Goga , Pauline Lardin

Entanglement is a physical phenomenon that each state cannot be described individually. Entanglement entropy gives quantitative understanding to the entanglement. We use decomposition of the Hilbert space to discuss properties of the…

High Energy Physics - Theory · Physics 2016-02-17 Chen-Te Ma

Quantum many-body states that frequently appear in physics often obey an entropy scaling law, meaning that an entanglement entropy of a subsystem can be expressed as a sum of terms that scale linearly with its volume and area, plus a…

Quantum Physics · Physics 2021-05-26 Isaac H. Kim

We show central limit theorems (CLT) for the Stieltjes transforms or more general analytic functions of symmetric matrices with independent heavy tailed entries, including entries in the domain of attraction of $\alpha$-stable laws and…

Probability · Mathematics 2015-06-12 Florent Benaych-Georges , Alice Guionnet , Camille Male

The main purpose of this article is to study estimates for the Tsallis relative operator entropy, by the use of Hermite-Hadamard inequality. Thus, we obtain alternative bounds for the Tsallis relative operator entropy. In the process to…

Functional Analysis · Mathematics 2018-01-11 Shigeru Furuichi , Nicuşor Minculete

Violation of the assumptions underlying classical (Gaussian) limit theory often yields unreliable statistical inference. This paper shows that the bootstrap can detect such violations by delivering simple and powerful diagnostic tests that…

Econometrics · Economics 2025-10-09 Giuseppe Cavaliere , Luca Fanelli , Iliyan Georgiev

The main topic of this thesis is the proof of two fundamental entropic inequalities for quantum Gaussian channels. Quantum Gaussian channels model the propagation of electromagnetic waves through optical fibers and free space in the quantum…

Quantum Physics · Physics 2017-10-27 Giacomo De Palma

We establish a central limit theorem for the fluctuations of the linear statistics in the $\beta$-ensemble of dimension $N$ at a temperature proportional to $N$ and with confining smooth potential. In this regime, the particles do not…

Probability · Mathematics 2024-11-12 Charlie Dworaczek Guera , Ronan Memin

Concentration of measure has been argued to be the fundamental cause of adversarial vulnerability. Mahloujifar et al. presented an empirical way to measure the concentration of a data distribution using samples, and employed it to find…

Machine Learning · Computer Science 2021-03-25 Jack Prescott , Xiao Zhang , David Evans