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Quantum Fisher information is a central quantity in quantum metrology. We discuss an alternative representation of quantum Fisher information for unitary parametrization processes. The highlight of this representation is that all…

Quantum Physics · Physics 2015-02-25 Jing Liu , Xiaoxing Jing , Xiaoguang Wang

We present a survey of some of our recent results on Bayesian nonparametric inference for a multitude of stochastic processes. The common feature is that the prior distribution in the cases considered is on suitable sets of piecewise…

Statistics Theory · Mathematics 2024-06-04 Denis Belomestny , Frank van der Meulen , Peter Spreij

Variance and Fisher information are ingredients of the Cramer-Rao inequality. We regard Fisher information as a Riemannian metric on a quantum statistical manifold and choose monotonicity under coarse graining as the fundamental property of…

Quantum Physics · Physics 2009-11-07 Denes Petz

Although the hyperbolic metric possesses many remarkable properties, it is not defined on arbitrary subdomains of $\mathbb{R}^n$ with $n \geq 2$. This article introduces a new hyperbolic-type metric that provides an alternative approach to…

Metric Geometry · Mathematics 2025-08-01 Bibekananda Maji , Pritam Naskar , Swadesh Kumar Sahoo

In this paper, we study the geometry induced by the Fisher-Rao metric on the parameter space of Dirichlet distributions. We show that this space is geodesically complete and has everywhere negative sectional curvature. An important…

Differential Geometry · Mathematics 2020-11-20 Alice Le Brigant , Stephen Preston , Stéphane Puechmorel

We introduce a nonparametric way to estimate the global probability density function for a random persistence diagram. Precisely, a kernel density function centered at a given persistence diagram and a given bandwidth is constructed. Our…

Statistics Theory · Mathematics 2018-03-14 Joshua Lee Mike , Vasileios Maroulas

Parametric geometry of numbers is a new theory, recently created by Schmidt and Summerer, which unifies and simplifies many aspects of classical Diophantine approximations, providing a handle on problems which previously seemed out of…

Number Theory · Mathematics 2019-05-07 Damien Roy , Michel Waldschmidt

Although continuous density estimation has received abundant attention in the Bayesian nonparametrics literature, there is limited theory on multivariate mixed scale density estimation. In this note, we consider a general framework to…

Statistics Theory · Mathematics 2014-05-26 Antonio Canale , David B. Dunson

We revisit the problem of thermalization process for an Unruh-DeWitt (UDW) detector in de Sitter space. We derive the full dynamics of the detector in the context of open quantum system, neither using Markovian or RWA approximations. We…

High Energy Physics - Theory · Physics 2025-06-09 Langxuan Chen , Jun Feng

Many problems arising in applications result in the need to probe a probability distribution for functions. Examples include Bayesian nonparametric statistics and conditioned diffusion processes. Standard MCMC algorithms typically become…

Computation · Statistics 2015-03-20 S. L. Cotter , G. O. Roberts , A. M. Stuart , D. White

A non-Hermitian generalisation of the Marsden--Weinstein reduction method is introduced to construct families of quantum $\mathcal{PT}$-symmetric superintegrable models over an $n$-dimensional sphere $S^n$. The mechanism is illustrated with…

Mathematical Physics · Physics 2023-08-15 Francisco Correa , Luis Inzunza , Ian Marquette

In this paper we investigate the geometry of the likelihood of the unknown parameters in a simple class of Bayesian directed graphs with hidden variables. This enables us, before any numerical algorithms are employed, to obtain certain…

Machine Learning · Computer Science 2013-02-01 Raffaella Settimi , Jim Q. Smith

The nonlocal Fisher equation is a diffusion-reaction equation with a nonlocal quadratic competition, which describes the reaction between distant individuals. This equation arises in evolutionary biological systems, where the arena for the…

Pattern Formation and Solitons · Physics 2018-04-25 Yehuda A. Ganan , David A. Kessler

Bayesian inference typically requires the computation of an approximation to the posterior distribution. An important requirement for an approximate Bayesian inference algorithm is to output high-accuracy posterior mean and uncertainty…

Statistics Theory · Mathematics 2018-10-03 Jonathan H. Huggins , Trevor Campbell , Mikołaj Kasprzak , Tamara Broderick

We propose a principled way to define Gaussian process priors on various sets of unweighted graphs: directed or undirected, with or without loops. We endow each of these sets with a geometric structure, inducing the notions of closeness and…

Machine Learning · Statistics 2023-02-28 Viacheslav Borovitskiy , Mohammad Reza Karimi , Vignesh Ram Somnath , Andreas Krause

In the present paper, we would like to draw attention to a possible generalized Fisher information that fits well in the formalism of nonextensive thermostatistics. This generalized Fisher information is defined for densities on…

Mathematical Physics · Physics 2013-01-18 J. -F. Bercher

Our focus is on constructing a multiscale nonparametric prior for densities. The Bayes density estimation literature is dominated by single scale methods, with the exception of Polya trees, which favor overly-spiky densities even when the…

Methodology · Statistics 2014-10-06 Antonio Canale , David B. Dunson

An implicit Euler finite-volume scheme for a nonlocal cross-diffusion system on the multidimensional torus is analyzed. The equations describe the dynamics of population species with repulsive or attractive interactions. The numerical…

Numerical Analysis · Mathematics 2026-01-06 Ansgar Jüngel , Panchi Li , Zhiwei Sun

The problem of estimating a parametric or nonparametric regression function in a model with normal errors is considered. For this purpose, a novel objective prior for the regression function is proposed, defined as the distribution…

Statistics Theory · Mathematics 2019-12-13 Wicher Bergsma

We generalize the classical Fisher information metric on statistical models to $L^p$-metrics on various spaces of differential forms or group of diffeomorphisms. Using this new interpretation from information geometry, we derive several new…

Algebraic Topology · Mathematics 2025-12-16 Yuxiu Lu