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Understanding natural phenomenon through the interactions of different complex systems has become an increasing focus in scientific inquiry. Defining complexity and actually measuring it is an ongoing debate and no standard framework has…

Information Theory · Computer Science 2026-01-21 Gabriel Potestades

Probabilistic graphical models allow us to encode a large probability distribution as a composition of smaller ones. It is oftentimes the case that we are interested in incorporating in the model the idea that some of these smaller…

Artificial Intelligence · Computer Science 2021-11-17 Jesus Cerquides

Recently, shearlet systems were introduced as a means to derive efficient encoding methodologies for anisotropic features in 2-dimensional data with a unified treatment of the continuum and digital setting. However, only very few…

Functional Analysis · Mathematics 2010-02-16 P. Kittipoom , G. Kutyniok , W. Lim

We examine the fundamental question whether a random discrete structure with the minimal number of restrictions can converge to continuous metric space. We study the geometrical properties such as the dimensionality and the curvature…

Disordered Systems and Neural Networks · Physics 2024-05-14 Ioannis Kleftogiannis , Ilias Amanatidis

Motivated by the presence of deep connections among dynamical equations, experimental data, physical systems, and statistical modeling, we report on a series of findings uncovered by the Authors and collaborators during the last decade…

Data Analysis, Statistics and Probability · Physics 2018-08-22 Sean Alan Ali , Carlo Cafaro , Steven Gassner , Adom Giffin

We present an information geometric characterization of Grover's quantum search algorithm. First, we quantify the notion of quantum distinguishability between parametric density operators by means of the Wigner-Yanase quantum information…

Mathematical Physics · Physics 2015-06-03 Carlo Cafaro , Stefano Mancini

The natural gradient is central in neural quantum states optimizations but it is limited by the cost of computing and inverting the quantum geometric tensor, the quantum analogue of the Fisher information matrix. We introduce a…

Quantum Physics · Physics 2025-11-05 Ahmedeo Shokry , Alessandro Santini , Filippo Vicentini

Causal inference is perhaps one of the most fundamental concepts in science, beginning originally from the works of some of the ancient philosophers, through today, but also weaved strongly in current work from statisticians, machine…

Information Theory · Computer Science 2020-03-31 Sudam Surasinghe , Erik M. Bollt

Graph states are versatile resources for various quantum information processing tasks, including measurement-based quantum computing and quantum repeaters. Although the type-II fusion gate enables all-optical generation of graph states by…

Quantum Physics · Physics 2023-12-25 Seok-Hyung Lee , Hyunseok Jeong

Simple time-reversible systems can generate {\it irreversible} flows satisfying the Second Law of Thermodynamics. Maps, and equivalent random walks, can also do this. We study a pair of time-reversible Baker Maps, $N2$ and $N3$, which…

Chaotic Dynamics · Physics 2023-03-30 William Graham Hoover , Carol Griswold Hoover

This paper elaborates on an intrinsically quantum approach to gravity, which begins with a general framework for quantum mechanics and then seeks to identify additional mathematical structure on Hilbert space that is responsible for gravity…

High Energy Physics - Theory · Physics 2019-03-27 Steven B. Giddings

This paper concerns models and convergence principles for dealing with stochasticity in a wide range of algorithms arising in nonlinear analysis and optimization in Hilbert spaces. It proposes a flexible geometric framework within which…

Optimization and Control · Mathematics 2026-02-17 Patrick L. Combettes , Javier I. Madariaga

Data-driven reduced-order models of the dynamics of complex flows are important for tasks related to design, understanding, prediction, and control. Many flows obey symmetries, and the present work illustrates how these can be exploited to…

Machine Learning · Computer Science 2025-04-23 Carlos E. Pérez De Jesús , Alec J. Linot , Michael D. Graham

A unit cube in $k$ dimensional space (or \emph{$k$-cube} in short) is defined as the Cartesian product $R_1\times R_2\times...\times R_k$ where $R_i$(for $1\leq i\leq k$) is a closed interval of the form $[a_i,a_i+1]$ on the real line. A…

Discrete Mathematics · Computer Science 2008-03-26 L. Sunil Chandran , Mathew C. Francis , Naveen Sivadasan

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

We establish that many fundamental concepts and techniques in quantum field theory and collider physics can be naturally understood and unified through a simple new geometric language. The idea is to equip the space of collider events with…

High Energy Physics - Phenomenology · Physics 2020-07-15 Patrick T. Komiske , Eric M. Metodiev , Jesse Thaler

Quantum metrology exploits quantum mechanical effects to increase the precision of measurements of physical quantities. A wide variety of applications are currently being developed for scientific and technological purposes, however, most…

Quantum Physics · Physics 2026-02-16 B. J. Alexander , Ş. K. Özdemir , M. S. Tame

We formulate a geometric framework in which physical laws emerge from restricted access to microscopic information. Measurement constraints are modeled as a gauge symmetry acting on density operators, inducing a gauge-reduced space of…

Quantum Physics · Physics 2026-05-19 Tiago Pernambuco , Lucas Chibebe Céleri

Random geometric graphs (RGG) can be formalized as hidden-variables models where the hidden variables are the coordinates of the nodes. Here we develop a general approach to extract the typical configurations of a generic hidden-variables…

Disordered Systems and Neural Networks · Physics 2015-04-28 Massimo Ostilli , Ginestra Bianconi

Quantum Graphity is an approach to quantum gravity based on a background independent formulation of condensed matter systems on graphs. We summarize recent results obtained on the notion of emergent geometry from the point of view of a…

General Relativity and Quantum Cosmology · Physics 2012-05-23 Francesco Caravelli
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