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We explore the relationship between a machine-learned structural quantity (softness) and excess entropy in simulations of supercooled liquids. Excess entropy is known to scale well the dynamical properties of liquids, but this…

Soft Condensed Matter · Physics 2023-06-07 Ian R. Graham , Paulo E. Arratia , Robert A. Riggleman

Randomized network ensembles are the null models of real networks and are extensivelly used to compare a real system to a null hypothesis. In this paper we study network ensembles with the same degree distribution, the same…

Disordered Systems and Neural Networks · Physics 2009-11-13 Ginestra Bianconi

The principle of maximum entropy (Maxent) is often used to obtain prior probability distributions as a method to obtain a Gibbs measure under some restriction giving the probability that a system will be in a certain state compared to the…

Information Theory · Computer Science 2019-06-26 Hector Zenil , Narsis A. Kiani , Jesper Tegnér

This paper considers the problem of stabilizing a discrete-time non-linear stochastic system over a finite capacity noiseless channel. Our focus is on systems which decompose into a stable and unstable component, and the stability notion…

Optimization and Control · Mathematics 2021-09-07 Nicolás Garcia , Christoph Kawan , Serdar Yüksel

Consider a stochastic nonlinear system controlled over a possibly noisy communication channel. An important problem is to characterize the largest class of channels for which there exist coding and control policies so that the closed-loop…

Optimization and Control · Mathematics 2021-02-11 Nicolas Garcia , Christoph Kawan , Serdar Yuksel

Natural and artificial networks, from the cerebral cortex to large-scale power grids, face the challenge of converting noisy inputs into robust signals. The input fluctuations often exhibit complex yet statistically reproducible…

Adaptation and Self-Organizing Systems · Physics 2018-11-19 Henrik Ronellenfitsch , Jörn Dunkel , Michael Wilczek

The structure of interactions in most of animals and human societies can be best represented by complex hierarchical networks. In order to maintain close to optimal functioning both stability and adaptability are necessary. Here we…

Physics and Society · Physics 2018-02-20 Maryam Zamani , Leonardo Camargo-Forero , Tamas Vicsek

We review an scenario for the non-equilibrium dynamics of glassy systems that has been motivated by the exact solution of simple models. This approach allows one to set on firmer grounds well-known phenomenological theories. The old ideas…

Statistical Mechanics · Physics 2009-11-07 Leticia F. Cugliandolo

Understanding the effects of noise on quantum computations is fundamental to the development of quantum hardware and quantum algorithms. Simulation tools are essential for quantitatively modelling these effects, yet unless artificial…

Quantum Physics · Physics 2025-10-07 Anthony P. Thompson , Arie Soeteman , Chris Cade , Ido Niesen

A pattern of a sequence is a sequence of integer indices with each index describing the order of first occurrence of the respective symbol in the original sequence. In a recent paper, tight general bounds on the block entropy of patterns of…

Information Theory · Computer Science 2007-11-15 Gil I. Shamir

Whether noisy quantum devices without error correction can provide quantum advantage over classical computers is a critical issue of current quantum computation. In this work, the random quantum circuits, which are used as the paradigm…

Quantum Physics · Physics 2022-12-07 Meng Zhang , Chao Wang , Shaojun Dong , Hao Zhang , Yongjian Han , Lixin He

Whether a system is to be considered complex or not depends on how one searches for correlations. We propose a general scheme for calculation of entropies in lattice systems that has high flexibility in how correlations are successively…

Statistical Mechanics · Physics 2015-06-18 Torbjørn Helvik , Kristian Lindgren

This paper presents a new generator of chaotic bit sequences with mixed-mode (continuous and discrete) inputs. The generator has an improved level of chaotic properties in comparison with the existing single source (input) digital chaotic…

Chaotic Dynamics · Physics 2017-12-27 Michal Melosik , Wieslaw Marszalek

Analyzing and controlling system entropy is a powerful tool for regulating predictability of control systems. Applications benefiting from such approaches range from reinforcement learning and data security to human-robot collaboration. In…

Systems and Control · Electrical Eng. & Systems 2026-03-06 Menno van Zutphen , Giannis Delimpaltadakis , Duarte J. Antunes

Using a maximum entropy principle to assign a statistical weight to any graph, we introduce a model of random graphs with arbitrary degree distribution in the framework of standard statistical mechanics. We compute the free energy and the…

Disordered Systems and Neural Networks · Physics 2007-05-23 M. Bauer , D. Bernard

Network glasses are the physical prototype for many self-organized systems, ranging from proteins to computer science. Conventional theories of gases, liquids, and crystals do not account for the strongly material-selective character of the…

Disordered Systems and Neural Networks · Physics 2007-05-23 P. Boolchand , G. Lucovsky , J. C. Phillips , M. F. Thorpe

The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world…

A large class of technically non-chaotic systems, involving scatterings of light particles by flat surfaces with sharp boundaries, is nonetheless characterized by complex random looking motion in phase space. For these systems one may…

Chaotic Dynamics · Physics 2009-11-10 Henk van Beijeren

Thermal jitter (phase noise) from a free-running ring oscillator is a common, easily implementable physical randomness source in True Random Number Generators (TRNGs). We show how to evaluate entropy, autocorrelation, and bit pattern…

Cryptography and Security · Computer Science 2021-10-13 Markku-Juhani O. Saarinen

The entropy of network ensembles characterizes the amount of information encoded in the network structure, and can be used to quantify network complexity, and the relevance of given structural properties observed in real network datasets…

Disordered Systems and Neural Networks · Physics 2014-06-18 Kartik Anand , Dimitri Krioukov , Ginestra Bianconi