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Comparison-based algorithms are algorithms for which the execution of each operation is solely based on the outcome of a series of comparisons between elements. Comparison-based computations can be naturally represented via the following…

Data Structures and Algorithms · Computer Science 2020-11-17 Michel Schellekens

In view of the relation between information and thermodynamics we investigate how much information about an external protocol can be stored in the memory of a stochastic measurement device given an energy budget. We consider a layered…

Quantitative Methods · Quantitative Biology 2015-07-28 Stefano Bo , Marco Del Giudice , Antonio Celani

In an equilibrium thermal environment, random elastic collisions between background particles and a tracer establish the picture of Brownian motion fulfilling the celebrated Einstein relation between diffusivity and mobility. In nature,…

We consider a dynamical system to have memory if it remembers the current state as well as the state before that. The dynamics is defined as follows: $x_{n+1}=T_{\alpha}(x_{n-1},x_{n})=\tau (\alpha \cdot x_{n}+(1-\alpha)\cdot x_{n-1}),$…

Dynamical Systems · Mathematics 2016-04-26 Paweł Góra , Abraham Boyarsky , Zhenyang Li , Harald Proppe

The definition of memory in operational approaches to quantum non-Markovianity depends on the statistical properties of different sets of outcomes related to successive measurement processes performed over the system of interest. Using…

Quantum Physics · Physics 2021-01-26 Mariano Bonifacio , Adrián A. Budini

Memory effects are a key feature in the description of the dynamical systems governed by the generalized Langevin equation, which presents an exact reformulation of the equation of motion. A simple measure for the estimation of memory…

Disordered Systems and Neural Networks · Physics 2007-05-23 Anatolii V. Mokshin , Renat M. Yulmetyev , Peter Hänggi

The degree of entanglement in an open quantum system varies according to how information in the environment is read. A measure of this contextual entanglement is introduced based on quantum trajectory unravelings of the open system…

Quantum Physics · Physics 2009-11-10 Hyunchul Nha , H. J. Carmichael

We combine momentum from machine learning with evolutionary dynamics, where momentum can be viewed as a simple mechanism of intergenerational memory. Using information divergences as Lyapunov functions, we show that momentum accelerates the…

Machine Learning · Computer Science 2025-11-05 Marc Harper , Joshua Safyan

In this paper, we wish to investigate the dynamics of information transfer in evolutionary dynamics. We use information theoretic tools to track how much information an evolving population has obtained and managed to retain about different…

Populations and Evolution · Quantitative Biology 2021-04-09 Nicholas Guttenberg

We extend the notion of estimation entropy of autonomous dynamical systems proposed by Liberzon and Mitra [1] to nonlinear dynamical systems with uncertain inputs with bounded variation. We call this new notion the {$\epsilon$}-estimation…

Systems and Control · Electrical Eng. & Systems 2023-11-14 Hussein Sibai , Sayan Mitra

In any ecosystem, the conditions of the environment and the characteristics of the species that inhabit it are entangled, co-evolving in space and time. We introduce a model that couples active agents with a dynamic environment, interpreted…

Populations and Evolution · Quantitative Biology 2025-12-10 G. Briozzo , G. J. Sibona , F. Peruani

Inspired by the swarming or flocking of animal systems we study groups of agents moving in unbounded 2D space. Individual trajectories derive from a ``bottom-up'' principle: individuals reorient to maximise their future path entropy over…

Statistical Mechanics · Physics 2023-04-21 Harvey L. Devereux , Matthew S. Turner

Economists model knowledge use and acquisition as a cause-and-effect calculus associating observations made by a decision-maker about their world with possible underlying causes. Knowledge models are well-established for static contexts,…

Neural and Evolutionary Computing · Computer Science 2024-12-03 Abigail Devereaux , Roger Koppl

The standard feedback model of reinforcement learning requires revealing the reward of every visited state-action pair. However, in practice, it is often the case that such frequent feedback is not available. In this work, we take a first…

Machine Learning · Computer Science 2021-03-08 Yonathan Efroni , Nadav Merlis , Shie Mannor

Transport equations with a nonlocal velocity field have been introduced as a continuum model for interacting particle systems arising in physics, chemistry and biology. Fractional time derivatives, given by convolution integrals of the…

Analysis of PDEs · Mathematics 2019-04-16 Fabio Camilli , Raul De Maio

Human communication is commonly represented as a temporal social network, and evaluated in terms of its uniqueness. We propose a set of new entropy-based measures for human communication dynamics represented within the temporal social…

Social and Information Networks · Computer Science 2018-10-29 Marcin Kulisiewicz , Przemysław Kazienko , Bolesław K. Szymański , Radosław Michalski

This work presents a novel means for understanding learning dynamics and scaling relations in neural networks. We show that certain measures on the spectrum of the empirical neural tangent kernel, specifically entropy and trace, yield…

Machine Learning · Computer Science 2024-10-11 Samuel Tovey , Sven Krippendorf , Michael Spannowsky , Konstantin Nikolaou , Christian Holm

Quantum open systems evolve according to completely positive, trace preserving maps acting on the density operator, which can equivalently be unraveled in term of so-called quantum trajectories. These stochastic sequences of pure states…

Quantum Physics · Physics 2019-05-01 Cyril Elouard , Hamed Mohammady

Dynamics, the study of change, is normally the subject of mechanics. Whether the chosen mechanics is ``fundamental'' and deterministic or ``phenomenological'' and stochastic, all changes are described relative to an external time. Here we…

Mathematical Physics · Physics 2009-10-31 Ariel Caticha

The paper describes an approach to measuring convergence of an algorithm to its result in terms of an entropy-like function of partitions of its inputs of a given length. The goal is to look at the algorithmic data processing from the…

Computational Complexity · Computer Science 2016-05-06 Anatol Slissenko