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Recently, J. D. Lawson encouraged the domain theory community to consider the scientific program of developing domain theory in the wider context of $T_0$ spaces instead of restricting to posets. In this paper, we respond to this calling…

Logic in Computer Science · Computer Science 2023-06-22 Hadrian Andradi , Weng Kin Ho

Information diagram and the I-measure are useful mnemonics where random variables are treated as sets, and entropy and mutual information are treated as a signed measure. Although the I-measure has been successful in machine proofs of…

Information Theory · Computer Science 2023-07-17 Cheuk Ting Li

We give an upper bound for the topological entropy of maps on inverse limit spaces in terms of their set-valued components. In a special case of a diagonal map on the inverse limit space $\underleftarrow{\lim}(I,f)$, where every diagonal…

Dynamical Systems · Mathematics 2020-10-30 Ana Anusic , Christopher Mouron

Given a closed orientable surface (\Sigma) of genus at least two, we establish an affine isomorphism between the convex compact set of isotopy-invariant topological measures on (\Sigma) and the convex compact set of additive functions on…

General Topology · Mathematics 2009-03-17 Frol Zapolsky

Models of bounded rationality include quantum--like (QL) models, which use Hilbert--space amplitudes to represent context and order effects, and entropy--regularised (ER) models, including rational inattention, which smooth expected utility…

Econometrics · Economics 2026-03-03 Anders Karlström , Christer Persson

Quantum information quantities, such as mutual information and entropies, are essential for characterizing quantum systems and protocols in quantum information science. In this contribution, we identify types of information measures based…

Quantum Physics · Physics 2025-10-21 Christopher Popp , Tobias C. Sutter , Beatrix C. Hiesmayr

Over the past few years, insights from computer science, statistical physics, and information theory have revealed phase transitions in a wide array of high-dimensional statistical problems at two distinct thresholds: One is the…

Statistics Theory · Mathematics 2018-08-14 Yihong Wu , Jiaming Xu

In this work, we explore the state-space formulation of a network process to recover, from partial observations, the underlying network topology that drives its dynamics. To do so, we employ subspace techniques borrowed from system…

Signal Processing · Electrical Eng. & Systems 2019-06-26 Mario Coutino , Elvin Isufi , Takanori Maehara , Geert Leus

In this article we provide, from a novel perspective, arguments that support the idea that, in the wake of Cox' approach to probability theory, von Neumann's entropy should be the natural one in Quantum Mechanics. We also generalize the…

Quantum Physics · Physics 2015-10-02 F. Holik , A. Plastino , M. Sáenz

A central issue of the science of complex systems is the quantitative characterization of complexity. In the present work we address this issue by resorting to information geometry. Actually we propose a constructive way to associate to a -…

Mathematical Physics · Physics 2017-12-19 Roberto Franzosi , Domenico Felice , Stefano Mancini , Marco Pettini

Topological matter provides natural platforms for robust, non-local information storage, central to quantum error correction. Yet, while the relation between entanglement and topology is well established, little is known about the role of…

In this paper we describe a triple correspondence between graph limits, information theory and group theory. We put forward a new graph limit concept called log-convergence that is closely connected to dense graph limits but its main…

Combinatorics · Mathematics 2015-04-06 Balazs Szegedy

The order topology $\tau_o(P)$ (resp. the sequential order topology $\tau_{os}(P)$) on a poset $P$ is the topology that has as its closed sets those that contain the order limits of all their order convergent nets (resp. sequences). For a…

Operator Algebras · Mathematics 2014-11-10 Emmanuel Chetcuti , Jan Hamhalter , Hans Weber

In computational PDE-based inverse problems, a finite amount of data is collected to infer unknown parameters in the PDE. In order to obtain accurate inferences, the collected data must be informative about the unknown parameters. How to…

Numerical Analysis · Mathematics 2021-05-04 Tan Bui-Thanh , Qin Li , Leonardo Zepeda-Núñez

Matrix completion is a fundamental problem that comes up in a variety of applications like the Netflix problem, collaborative filtering, computer vision, and crowdsourcing. The goal of the problem is to recover a k-by-n unknown matrix from…

Information Theory · Computer Science 2014-02-19 Changho Suh

Informational dependence between statistical or quantum subsystems can be described with Fisher matrix or Fubini-Study metric obtained from variations of the sample/configuration space coordinates. Using these non-covariant objects as…

High Energy Physics - Theory · Physics 2019-01-30 Vitaly Vanchurin

We formulate a universal characterization of the many-particle quantum entanglement in the ground state of a topologically ordered two-dimensional medium with a mass gap. We consider a disk in the plane, with a smooth boundary of length L,…

High Energy Physics - Theory · Physics 2009-11-11 Alexei Kitaev , John Preskill

The max-relative entropy and the conditional min-entropy it induces have become central to one-shot information theory. Both may be expressed in terms of a conic program over the positive semidefinite cone. Recently, it was shown that the…

Quantum Physics · Physics 2024-10-15 Ian George , Eric Chitambar

We advocate the use of a notion of entropy that reflects the relative abundances of the symbols in an alphabet, as well as the similarities between them. This concept was originally introduced in theoretical ecology to study the diversity…

Machine Learning · Computer Science 2022-07-12 Jose Gallego-Posada , Ankit Vani , Max Schwarzer , Simon Lacoste-Julien

This paper establishes an information theoretic framework for deep metric based image registration techniques. We show an exact equivalence between maximum profile likelihood and minimization of joint entropy, an important early information…

Computer Vision and Pattern Recognition · Computer Science 2019-01-03 Alireza Sedghi , Jie Luo , Alireza Mehrtash , Steve Pieper , Clare M. Tempany , Tina Kapur , Parvin Mousavi , William M. Wells
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