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Related papers: Differential Entropy on Statistical Spaces

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Entropy and information can be considered dual: entropy is a measure of the subspace defined by the information constraining the given ambient space. Negative entropies, arising in na\"ive extensions of the definition of entropy from…

Probability · Mathematics 2023-03-06 Daniel Lazarev

Differential privacy is a mathematical framework for developing statistical computations with provable guarantees of privacy and accuracy. In contrast to the privacy component of differential privacy, which has a clear mathematical and…

Cryptography and Security · Computer Science 2020-11-13 Gilles Barthe , Rohit Chadha , Paul Krogmeier , A. Prasad Sistla , Mahesh Viswanathan

The additional information carried by an enlarged filtration and its measurement was studied by several authors. Already Meyer (Sur un theoreme de J. Jacod, 1978) and Yor (Entropie d'une partition, et grossissement initial d'une filtration,…

Probability · Mathematics 2026-03-26 Anna Aksamit

Differential privacy (DP) considers a scenario, where an adversary has almost complete information about the entries of a database This worst-case assumption is likely to overestimate the privacy thread for an individual in real life.…

Cryptography and Security · Computer Science 2025-04-16 Dennis Breutigam , Rüdiger Reischuk

Exploiting the geometric nature of statistical divergences, we devise a way to define associated induced uncertainty measures for discrete and finite probability distributions. We also report new uncertainty measures and discuss their…

Quantum Physics · Physics 2021-06-29 Gautam Sharma , Sk Sazim

In this paper, we investigate and compare two well-developed definitions of entropy relevant for describing the dynamics of isolated quantum systems: bipartite entanglement entropy and observational entropy. In a model system of interacting…

Quantum Physics · Physics 2020-06-01 Dana Faiez , Dominik Šafránek , J. M. Deutsch , Anthony Aguirre

The estimation of covariance operators of spatio-temporal data is in many applications only computationally feasible under simplifying assumptions, such as separability of the covariance into strictly temporal and spatial factors.Powerful…

Statistics Theory · Mathematics 2020-03-30 Holger Dette , Gauthier Dierickx , Tim Kutta

We first show how a new definition of entropy, which is intuitively very simple, as a divergence in cluster-size space, leads to a generalized form that is nonextensive for correlated units, but coincides exactly with the conventional one…

Disordered Systems and Neural Networks · Physics 2007-11-20 Fariel Shafee

In ref [math.ST/0411462] the notion of statistically dual distributions is introduced. The reconstruction of confidence density [AIP Conference Proceedings 803 (2005) 398] for the location parameter for several pairs of statistically dual…

Data Analysis, Statistics and Probability · Physics 2013-11-26 S. Bityukov , N. Krasnikov , V. Smirnova , V. Taperechkina

We investigate a quantum dynamical entropy of one-dimesional quantum spin systems. We show that the dynamical entropy is bounded from above by a quantity which is related with group velocity determined by the interaction and mean entropy of…

Quantum Physics · Physics 2015-06-26 Takayuki Miyadera , Masanori Ohya

The need to analyze sensitive data, such as medical records or financial data, has created a critical research challenge in recent years. In this paper, we adopt the framework of differential privacy, and explore mechanisms for generating…

Cryptography and Security · Computer Science 2024-05-09 Nikolija Bojkovic , Po-Ling Loh

The theories known as doubly special relativity are introduced in order to take into account an observer-independent length scale and the speed of light in the framework of special relativity. These theories can be generally formulated on…

General Relativity and Quantum Cosmology · Physics 2016-03-23 M. A. Gorji , V. Hosseinzadeh , K. Nozari , B. Vakili

The physical foundations of a variety of emerging technologies --- ranging from the applications of quantum entanglement in quantum information to the applications of nonequilibrium bulk and interface phenomena in microfluidics, biology,…

Quantum Physics · Physics 2014-03-25 Gian Paolo Beretta , Enzo Zanchini

This paper uses differential spaces to obtain some new results in integrable Hamiltonian systems

Symplectic Geometry · Mathematics 2017-09-01 Richard Cushman , Jedrzej Sniatycki

The fermionic von Neumann entropy, the fermionic entanglement entropy and the fermionic relative entropy are defined for causal fermion systems. Our definition makes use of entropy formulas for quasi-free fermionic states in terms of the…

Mathematical Physics · Physics 2025-04-16 Felix Finster , Robert H. Jonsson , Magdalena Lottner , Albert Much , Simone Murro

Upon a consistent topological statistical theory the application of structural statistics requires a quantification of the proximity structure of model spaces. An important tool to study these structures are Pseudo-Riemannian metrices,…

Statistics Theory · Mathematics 2020-06-23 Patrick Michl

Entropy is one of the key thermodynamic variables reflecting changes in the state of matter. Unlike other thermodynamic variables, it is well-defined also for nonequilibrium steady states through its relation to information. Applying this…

Statistical Mechanics · Physics 2026-04-15 Haim Diamant , Gil Ariel

Using the definition of entropy of a family of increasing distances on a compact metric set given in [10] we introduce a notion of Finsler entropy for smooth distributions and Stefan-Sussmann foliations. This concept generalizes most of…

Differential Geometry · Mathematics 2015-06-11 F. Pelletier

We generalize, improve and unify theorems of Rumin, and Maassen--Uffink about classical entropies associated to quantum density matrices. These theorems refer to the classical entropies of the diagonals of a density matrix in two different…

Mathematical Physics · Physics 2015-05-30 Rupert L. Frank , Elliott H. Lieb

We introduce a new measure of interdependence among the components of a random vector along the main diagonal of the vector copula, i.e. along the line $u_{1}=\ldots=u_{J}$, for $\left(u_{1},\ldots,u_{J}\right)\in\left[0,1\right]^{J}$. Our…

Methodology · Statistics 2014-08-29 Jhan Rodríguez , András Bárdossy
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