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Weak values and Kirkwood--Dirac (KD) quasiprobability distributions have been independently associated with both foundational issues in quantum theory and advantages in quantum metrology. We propose simple quantum circuits to measure weak…

A feature of certain ensembles of random matrices is that the corresponding measure is invariant under conjugation by unitary matrices. Study of such ensembles realised by matrices with Gaussian entries leads to statistical quantities…

Classical Analysis and ODEs · Mathematics 2009-11-11 P. J. Forrester , N. S. Witte

We extend some results on the convergence of one-dimensional diffusions killed at the boundary, conditioned on extended survival, to the case of general killing on the interior. We show, under fairly general conditions, that a diffusion…

Probability · Mathematics 2007-05-23 David Steinsaltz , Steven N. Evans

This paper is about statistical properties of quasistatic dynamical systems. These are a class of non-stationary systems that model situations where the dynamics change very slowly over time due to external influence. We focus on the case…

Dynamical Systems · Mathematics 2018-07-05 Juho Leppänen

Atar, Chowdhary and Dupuis have recently exhibited a variational formula for exponential integrals of bounded measurable functions in terms of R\'enyi divergences. We develop a variational characterization of the R\'enyi divergences between…

Information Theory · Computer Science 2017-01-27 Venkat Anantharam

We consider an infinitely divisible random field indexed by $\mathbb{R}^d$, $d\in\mathbb{N}$, given as an integral of a kernel function with respect to a L\'evy basis with a L\'evy measure having a regularly varying right tail. First we…

Probability · Mathematics 2022-01-04 Anders Rønn-Nielsen , Mads Stehr

An essential character for a distribution to play a central role in the limit theory is infinite divisibility. In this note, we prove that the Conway-Maxwell-Poisson (CMP) distribution is infinitely divisible iff it is the Poisson or…

Probability · Mathematics 2023-02-27 Xi Geng , Aihua Xia

This paper studies the sensitivity analysis of mass-action systems against their diffusion approximations, particularly the dependence on population sizes. As a continuous time Markov chain, a mass-action system can be described by a…

Numerical Analysis · Mathematics 2022-11-10 Yao Li , Yaping Yuan

We consider the classical Shiryaev--Roberts martingale diffusion, $(R_t)_{t\ge0}$, restricted to the interval $[0,A]$, where $A>0$ is a preset absorbing boundary. We take yet another look at the well-known phenomenon of quasi-stationarity…

Statistics Theory · Mathematics 2023-10-31 Soumik Banerjee , Aleksey S. Polunchenko

A definition for elliptical tempered stable distribution, based on the characteristic function, have been explained which involve a unique spectral measure. This definition provides a framework for creating a connection between infinite…

Probability · Mathematics 2014-08-18 Hassan A. Fallahgoul , Young S. Kim

Under the formalism of annealed averaging of the partition function, a type of random multifractal measures with their multipliers satisfying exponentially distributed is investigated in detail. Branching emerges in the curve of generalized…

Adaptation and Self-Organizing Systems · Physics 2009-10-31 Wei-Xing Zhou , Zun-Hong yu

In this paper, we propose a new distribution with unitary support which can be characterized as a ratio of the type $W=X_1/(X_1+X_2)$, where $(X_1, X_2)^\top$ follows a bivariate extreme distribution with Fr\'echet margins, that is, $X_1$…

Methodology · Statistics 2025-01-03 Roberto Vila , Felipe Quintino

We identify the linear space spanned by the real-valued excessive functions of a Markov process with the set of those functions which are quasimartingales when we compose them with the process. Applications to semi-Dirichlet forms are…

Probability · Mathematics 2017-09-07 Iulian Cîmpean , Lucian Beznea

`Distribution regression' refers to the situation where a response Y depends on a covariate P where P is a probability distribution. The model is Y=f(P) + mu where f is an unknown regression function and mu is a random error. Typically, we…

Machine Learning · Statistics 2013-02-04 Barnabas Poczos , Alessandro Rinaldo , Aarti Singh , Larry Wasserman

In this paper we present a flexible bivariate distribution specified by a quantile function. The distribution contains as special cases new bivariate exponential, Pareto I, Pareto II, beta, power, log logistic and uniform distributions and…

Other Statistics · Statistics 2025-03-17 Shifna P R , N. Unnikrishnan Nair , S. M. Sunoj

We derive some estimates for the integral modulus of continuity of probability densities of infinitely divisible distributions. The paper is splitted into two parts. The first part deals with general infinitely divisible distributions. The…

Probability · Mathematics 2018-05-07 David Berger

The Kantorovich-Rubinshtein metric is an $L^1$-like metric on spaces of probability distributions that enjoys several serendipitous properties. It is complete separable if the underlying metric space of points is complete separable, and in…

General Topology · Mathematics 2022-12-23 Jean Goubault-Larrecq

We consider a quasi-variational inequality governed by a moving set. We employ the assumption that the movement of the set has a small Lipschitz constant. Under this requirement, we show that the quasi-variational inequality has a unique…

Optimization and Control · Mathematics 2019-09-09 Gerd Wachsmuth

We give counterexamples to a problem of M. Kac in the Scottish Book, which asks whether a certain nonlinear operation on two characteristic functions characterizes Laplace distributions, in analogy with the Cram\'er--L\'evy theorem for…

Probability · Mathematics 2026-04-07 Robert Koirala

This paper aims to explore the inherent connection among Heisenberg groups, quantum Fourier transform and (quasiprobability) distribution functions. Distribution functions for continuous and finite quantum systems are examined first as a…

Mathematical Physics · Physics 2015-05-18 Manas K. Patra , Samuel L. Braunstein
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