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Bayesian hierarchical models are frequently used in practical data analysis contexts. One interpretation of these models is that they provide an indirect way of assigning a prior for unknown parameters, through the introduction of…

Machine Learning · Statistics 2026-05-01 Brendon J. Brewer

If the probability distribution model aims to approximate the hidden mother distribution, it is imperative to establish a useful criterion for the resemblance between the mother and the model distributions. This study proposes a criterion…

Statistics Theory · Mathematics 2025-11-13 Yo Sheena

Thermodynamical properties of canonical and grand-canonical ensembles of the half-filled two-site Hubbard model have been discussed within the framework of the nonextensive statistics (NES). For relating the physical temperature $T$ to the…

Statistical Mechanics · Physics 2009-11-10 Hideo Hasegawa

In this paper we introduce the three main notions of probability used by physicists and discuss how these are to be used when invoking spacelike separated observers in a relativistic format. We discuss a standard EPRB experiment and…

Quantum Physics · Physics 2007-05-23 Thomas Marlow

In this chapter we shall discuss the recent progresses of information theoretic tools in the context of free and confined harmonic oscillator. Confined quantum systems have provided appreciable interest in areas of physics, chemistry,…

Quantum Physics · Physics 2021-05-06 Neetik Mukherjee , Amlan K. Roy

Laplace's "add-one" rule of succession modifies the observed frequencies in a sequence of heads and tails by adding one to the observed counts. This improves prediction by avoiding zero probabilities and corresponds to a uniform Bayesian…

Information Theory · Computer Science 2015-03-17 Yann Ollivier

In quantum mechanics (formulated, say, in Schr\"{o}dinger picture) only the knowledge of a complete set of observables $\Lambda_j$ enables us to declare the related physical inner product (i.e., the Hilbert-space metric $\Theta$ such that…

Quantum Physics · Physics 2024-03-15 Miloslav Znojil

We examine the estimation of the Kullback-Leibler (KL) divergence and the use of the goodness-of-fit test for multivariate continuous distributions. Our starting point is the maximum entropy principle for Shannon entropy: among all…

Statistics Theory · Mathematics 2026-03-10 Mehmet Siddik Cadirci , Martin Singull

We investigate the separability of the two-mode Gaussian states by using the variances of a pair of Einstein-Podolsky-Rosen (EPR)-like observables. Our starting point is inspired by the general necessary condition of separability introduced…

Quantum Physics · Physics 2019-05-02 Paulina Marian , Tudor A. Marian

In standard formulations of the uncertainty principle, two fundamental features are typically cast as impossibility statements: two noncommuting observables cannot in general both be sharply defined (for the same state), nor can they be…

Quantum Physics · Physics 2018-06-08 Tom Bullock , Paul Busch

We derive upper bounds for Hilbert-Schmidt's quantum coherence of general states of a $d$-level quantum system, a qudit, in terms of its incoherent uncertainty, with the latter quantified using the linear and von Neumann's entropies of the…

Quantum Physics · Physics 2020-07-22 Marcos L. W. Basso , Diego S. S. Chrysosthemos , Jonas Maziero

We report formulas for the joint moments of the determinantal products (det{rho})^k (det{rho^PT})^K (k=0, 1, 2,...,N; K = 0, 1, 2, 3, 4) of Hilbert-Schmidt (HS) probability distributions over the two-rebit and (K = 0, 1) two-qubit density…

Quantum Physics · Physics 2011-05-26 Paul B. Slater

The problem of source separation is by its very nature an inductive inference problem. There is not enough information to deduce the solution, so one must use any available information to infer the most probable solution. We demonstrate…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Kevin H. Knuth

This paper applies the recently axiomatized Optimum Information Principle (minimize the Kullback-Leibler information subject to all relevant information) to nonparametric density estimation, which provides a theoretical foundation as well…

Statistics Theory · Mathematics 2011-03-28 Alexis Akira Toda

Bayesian predictive inference provides a coherent description of entire predictive uncertainty through predictive distributions. We examine several widely used sparsity priors from the predictive (as opposed to estimation) inference…

Statistics Theory · Mathematics 2024-06-03 Veronika Rockova

Achieving the ultimate precisions for multiple parameters simultaneously is an outstanding challenge in quantum physics, because the optimal measurements for incompatible parameters cannot be performed jointly due to the Heisenberg…

Quantum Physics · Physics 2023-10-12 Binke Xia , Jingzheng Huang , Hongjing Li , Han Wang , Guihua Zeng

Shannon entropy, a cornerstone of information theory, statistical physics and inference methods, is uniquely identified by the Shannon-Khinchin or Shore-Johnson axioms. Generalizations of Shannon entropy, motivated by the study of…

Data Analysis, Statistics and Probability · Physics 2026-04-20 Andrea Somazzi , Diego Garlaschelli

The notions of predictability and visibility are essential in the mathematical formulation of wave particle duality. The work of Jakob and Bergou [Phys. Rev. A 76, 052107] generalises these notions for higher-dimensional quantum systems,…

Quantum Physics · Physics 2024-01-03 Shailja Kapoor , Sohail , Gautam Sharma , Arun K. Pati

In 1927, Heisenberg heuristically disclosed the tradeoff between the error in the measurement and the caused disturbance on another complementary observable. In the quantum theory, most of uncertainty relations are proposed to reveal the…

Quantum Physics · Physics 2014-10-29 Li-Yi Hsu

We make use of the Quantum Hamilton-Jacobi (QHJ) theory to investigate conditional quasi-solvability of the quantum symmetric top subject to combined electric fields (symmetric top pendulum). We derive the conditions of quasi-solvability of…

Mathematical Physics · Physics 2023-02-09 Konrad Schatz , Bretislav Friedrich , Simon Becker , Burkhard Schmidt