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In this paper, we present a detailed framework to analyze the evolution of the random topology of a time-varying wireless network via the information theoretic notion of entropy rate. We consider a propagation channel varying over time with…

Information Theory · Computer Science 2018-11-08 Arta Cika , Mihai-Alin Badiu , Justin P. Coon , Shahriar Etemadi Tajbakhsh

In this paper we establish fundamental limits on the performance of knowledge sharing in opportunistic social net- works. In particular, we introduce a novel information-theoretic model to characterize the performance limits of knowledge…

Networking and Internet Architecture · Computer Science 2015-05-14 Mai ElSherief , Tamer ElBatt , Ahmed Zahran , Ahmed Helmy

Discoveries of fundamental limits for the rates of physical processes, from the speed of light to the Lieb-Robinson bound for information propagation, often lead to breakthroughs in the our understanding of the underlying physics. Here we…

Diffusion of information in networks is at the core of many problems in AI. Common examples include the spread of ideas and rumors as well as marketing campaigns. Typically, information diffuses at a non-linear rate, for example, if markets…

Probability · Mathematics 2024-12-04 Tobias Friedrich , Andreas Göbel , Nicolas Klodt , Martin S. Krejca , Marcus Pappik

One of the fundamental physical limits on the speed of time evolution of a quantum state is known in the form of the celebrated Mandelstam-Tamm inequality. This inequality gives an answer to the question on how fast an isolated quantum…

Quantum Physics · Physics 2022-04-14 Sergio Albeverio , Alexander K. Motovilov

We present an achievable rate for general deterministic relay networks, with broadcasting at the transmitters and interference at the receivers. In particular we show that if the optimizing distribution for the information-theoretic cut-set…

Information Theory · Computer Science 2007-10-24 A. S. Avestimehr , S. N. Diggavi , D. N. C. Tse

There is accumulating evidence in the literature that stability of learning algorithms is a key characteristic that permits a learning algorithm to generalize. Despite various insightful results in this direction, there seems to be an…

Machine Learning · Statistics 2019-05-10 Karim Abou-Moustafa , Csaba Szepesvari

We prove upper bounds on outside probabilities for generic non-autonomous Schr\"odinger operators on lattices of arbitrary dimension. Our approach is based on a combination of commutator method originated in scattering theory and novel…

Mathematical Physics · Physics 2024-10-01 Jingxuan Zhang

A widely studied model of influence diffusion in social networks represents the network as a graph $G=(V,E)$ with an influence threshold $t(v)$ for each node. Initially the members of an initial set $S\subseteq V$ are influenced. During…

Data Structures and Algorithms · Computer Science 2018-07-19 Gennaro Cordasco , Luisa Gargano , Joseph Peters , Adele Anna Rescigno , Ugo Vaccaro

The Margolus-Levitin (ML) bound says that for any time-independent Hamiltonian, the time needed to evolve from one quantum state to another is at least $\pi \alpha(\epsilon) / (2 \langle E-E_0 \rangle)$, where $\langle E-E_0 \rangle$ is the…

Quantum Physics · Physics 2023-10-06 H. F. Chau

We generalize to multi-commutators the usual Lieb-Robinson bounds for commutators. In the spirit of constructive QFT, this is done so as to allow the use of combinatorics of minimally connected graphs (tree expansions) in order to estimate…

Mathematical Physics · Physics 2017-03-08 J. -B. Bru , W. de Siqueira Pedra

Statistical divergences are important tools in data analysis, information theory, and statistical physics, and there exist well known inequalities on their bounds. However, in many circumstances involving temporal evolution, one needs…

Data Analysis, Statistics and Probability · Physics 2025-03-25 Jan Karbowski

Random linear network coding (RLNC) unicast protocol is analyzed over a rapidly-changing network topology. We model the probability mass function (pmf) of the dissemination time as a sequence of independent geometric random variables whose…

Information Theory · Computer Science 2014-04-01 Shwan Ashrafi , Sumit Roy , Hamed Firooz

We present a Krylov space based theoretical framework for modeling inhomogeneous spin ensembles with arbitrary distributions of spin frequencies and couplings. The framework is then used to asymptotically large spin ensemble. In the…

Quantum Physics · Physics 2026-04-16 Rahul Gupta , Florian Mintert , Himadri Shekhar Dhar

For Schroedinger equations with both time-independent and time-dependent Kato potentials, we give a simple proof of the maximal speed bound. The latter states that the probability to find the quantum system outside the ball of radius…

Mathematical Physics · Physics 2021-05-11 Jack Arbunich , Fabio Pusateri , Israel Michael Sigal , Avraham Soffer

We study epidemic spreading processes in large networks, when the spread is assisted by a small number of external agents: infection sources with bounded spreading power, but whose movement is unrestricted vis-\`a-vis the underlying network…

Social and Information Networks · Computer Science 2014-04-15 Siddhartha Banerjee , Aditya Gopalan , Abhik Kumar Das , Sanjay Shakkottai

We derive a sharp bound as the quantum speed limit (QSL) for the minimal evolution time of quantum open systems in the non-Markovian strong-coupling regime with initial mixed states by considering the effects of both renormalized…

Quantum Physics · Physics 2022-02-07 Xiangyi Meng , Chengjun Wu , Hong Guo

We study semi-classical communication in positivity-violating k-essence scalar field theories, with superluminal modes propagating on a rolling background. The self-interactions due to the non-linear nature of these theories pose a…

High Energy Physics - Theory · Physics 2021-10-27 Xi Tong , Yi Wang , Yuhang Zhu

This paper is concerned with the speeds of propagation for the monostable Lotka-Volterra competition-diffusion system in general unbounded domains of $\mathbb{R}^N$. We first establish various definitions of spreading speeds at large time…

Analysis of PDEs · Mathematics 2026-03-26 Yang-Yang Yan , Wei-Jie Sheng

Dependency networks (Heckerman et al., 2000) provide a flexible framework for modeling complex systems with many variables by combining independently learned local conditional distributions through pseudo-Gibbs sampling. Despite their…

Machine Learning · Computer Science 2026-04-02 Kazuya Takabatake , Shotaro Akaho
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