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Finding the most powerful node in a dynamic random network, the largest set in a partition-valued stochastic process, or the largest family in an evolving population at a given time, can be a very difficult problem. This is particularly the…

Probability · Mathematics 2020-09-09 Cécile Mailler , Peter Mörters , Anna Senkevich

Random Boolean networks, originally invented as models of genetic regulatory networks, are simple models for a broad class of complex systems that show rich dynamical structures. From a biological perspective, the most interesting networks…

Disordered Systems and Neural Networks · Physics 2009-11-07 Joshua E. S. Socolar , Stuart A. Kauffman

Boolean networks model finite discrete dynamical systems with complex behaviours. The state of each component is determined by a Boolean function of the state of (a subset of) the components of the network. This paper addresses the…

Artificial Intelligence · Computer Science 2020-02-28 Stéphanie Chevalier , Christine Froidevaux , Loïc Paulevé , Andrei Zinovyev

We consider a population spreading across a finite number of sites. Individuals can move from one site to the other according to a network (oriented links between the sites) that vary periodically over time. On each site, the population…

Dynamical Systems · Mathematics 2026-03-02 Michel Benaïm , Claude Lobry , Tewfik Sari , Edouard Strickler

We describe systems using Kauffman and similar networks. They are directed funct ioning networks consisting of finite number of nodes with finite number of discr ete states evaluated in synchronous mode of discrete time. In this paper we…

Disordered Systems and Neural Networks · Physics 2009-11-13 Andrzej Gecow

The level-$k$ $\ell_1$-Fourier weight of a Boolean function refers to the sum of absolute values of its level-$k$ Fourier coefficients. Fourier growth refers to the growth of these weights as $k$ grows. It has been extensively studied for…

Computational Complexity · Computer Science 2023-07-27 Uma Girish , Makrand Sinha , Avishay Tal , Kewen Wu

Mathematical method based on a direct or indirect analysis of growth rates is described. It is shown how simple assumptions and a relatively easy analysis can be used to describe mathematically complicated trends and to predict growth. Only…

General Finance · Quantitative Finance 2017-06-27 Ron W. Nielsen

We develope a computationally efficient extension of the Dyson Brownian Motion (DBM) algorithm to generate random function in C2 locally. We further explain that random functions generated via DBM show an unstable growth as the traversed…

High Energy Physics - Theory · Physics 2016-09-09 Gaoyuan Wang , Thorsten Battefeld

We consider a probability distribution on the set of Boolean functions in n variables which is induced by random Boolean expressions. Such an expression is a random rooted plane tree where the internal vertices are labelled with connectives…

Combinatorics · Mathematics 2015-09-28 Antoine Genitrini , Bernhard Gittenberger , Veronika Kraus , Cécile Mailler

This is the second in a series of articles aimed at exploring the relationship between the complexity classes of P and NP. The research in this article aims to find conditions of an algorithmic nature that are necessary and sufficient to…

Computational Complexity · Computer Science 2023-11-07 Stepan G. Margaryan

In this paper, we investigate the growth error bound condition. By using the proximal point algorithm, we first provide a more accessible and elementary proof of the fact that Kurdyka-{\L}ojasiewicz conditions imply growth error bound…

Optimization and Control · Mathematics 2024-06-12 Qinian Jin

The link between a particular class of growth processes and random matrices was established in the now famous 1999 article of Baik, Deift, and Johansson on the length of the longest increasing subsequence of a random permutation. During the…

Probability · Mathematics 2010-03-16 Patrik L. Ferrari , Herbert Spohn

The relationship between the properties of a dynamical system and the structure of its defining equations has long been studied in many contexts. Here we study this problem for the class of conjunctive (resp. disjunctive) Boolean networks,…

Combinatorics · Mathematics 2008-05-13 Abdul Salam Jarrah , Reinhard Laubenbacher , Alan Veliz-Cuba

Networks are a powerful abstraction with applicability to a variety of scientific fields. Models explaining their morphology and growth processes permit a wide range of phenomena to be more systematically analysed and understood. At the…

Neural and Evolutionary Computing · Computer Science 2020-04-27 Telmo Menezes , Camille Roth

It has been shown \citep{broeck90:physicalreview,patarnello87:europhys} that feedforward Boolean networks can learn to perform specific simple tasks and generalize well if only a subset of the learning examples is provided for learning.…

Neural and Evolutionary Computing · Computer Science 2019-11-12 Alireza Goudarzi , Christof Teuscher , Natali Gulbahce , Thimo Rohlf

We provide sufficient density condition for a set of nonuniform samples to give rise to a set of sampling for multivariate bandlimited functions when the measurements consist of pointwise evaluations of a function and its first $k$…

Numerical Analysis · Mathematics 2016-09-12 Ben Adcock , Milana Gataric , Anders C. Hansen

The dynamical processes taking place on a network depend on its topology. Influencing the growth process of a network therefore has important implications on such dynamical processes. We formulate the problem of influencing the growth of a…

Social and Information Networks · Computer Science 2016-12-28 Dominik Thalmeier , Vicenç Gómez , Hilbert J. Kappen

We consider the problem of searching for proofs in sequential presentations of logics with multiplicative (or intensional) connectives. Specifically, we start with the multiplicative fragment of linear logic and extend, on the one hand, to…

Logic in Computer Science · Computer Science 2007-05-23 James Harland , David Pym

We propose conditions for the emergence of Turing patterns in a domain that changes in size by homogeneous growth/shrinkage. These conditions to determine the bifurcation are based on considering the geometric change of a potential function…

Pattern Formation and Solitons · Physics 2023-08-25 Aldo Ledesma-Durán

Using linearized elasticity as a convenient mechanical framework, we show that volumetric growth can be formulated as an optimization-driven process in which the growth tensor is determined implicitly by constrained optimization rather than…

Mathematical Physics · Physics 2026-05-14 Rohan Abeyaratne , Roberto Paroni , Marco Picchi Scardaoni