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We study the problem of graph structure identification, i.e., of recovering the graph of dependencies among time series. We model these time series data as components of the state of linear stochastic networked dynamical systems. We assume…

Machine Learning · Computer Science 2023-06-29 Sérgio Machado , Anirudh Sridhar , Paulo Gil , Jorge Henriques , José M. F. Moura , Augusto Santos

Subgraphs and cycles are often used to characterize the local properties of complex networks. Here we show that the subgraph structure of real networks is highly time dependent: as the network grows, the density of some subgraphs remains…

Disordered Systems and Neural Networks · Physics 2009-11-11 Alexei Vazquez , Joao G. Oliveira , Albert-Laszlo Barabasi

An analytical approach to network dynamics is used to show that when agents copy their state randomly the network arrives to a stationary status in which the distribution of states is independent of the agents degree. The effects of network…

Disordered Systems and Neural Networks · Physics 2009-11-10 Cesar A. Hidalgo , Francisco Claro , Pablo A. Marquet

We investigate in detail a recent model of colliding mobile agents [Phys. Rev. Lett.~96, 088702], used as an alternative approach to construct evolving networks of interactions formed by the collisions governed by suitable dynamical rules.…

Physics and Society · Physics 2013-01-01 Marta C. González , Pedro G. Lind , Hans J. Herrmann

Boolean networks is a well-established formalism for modelling biological systems. A vital challenge for analysing a Boolean network is to identify all the attractors. This becomes more challenging for large asynchronous Boolean networks,…

Molecular Networks · Quantitative Biology 2017-06-14 Andrzej Mizera , Jun Pang , Hongyang Qu , Qixia Yuan

We consider atoms interacting each other through the topological structure of a complex network and investigate lattice vibrations of the system, the quanta of which we call {\em netons} for convenience. The density of neton levels,…

Disordered Systems and Neural Networks · Physics 2007-05-23 Beom Jun Kim , H. Hong , M. Y. Choi

Large real-life complex networks are often modeled by various random graph constructions and hundreds of further references therein. In many cases it is not at all clear how the modeling strength of differently generated random graph model…

Data Structures and Algorithms · Computer Science 2020-09-01 András Faragó , Rupei Xu

We analyze a model of interacting agents (e.g. prebiotic chemical species) which are represended by nodes of a network, whereas their interactions are mapped onto directed links between these nodes. On a fast time scale, each agent follows…

Populations and Evolution · Quantitative Biology 2009-11-13 Adrian M. Seufert , Frank Schweitzer

Neural network quantum states are a promising tool to analyze complex quantum systems given their representative power. It can however be difficult to optimize efficiently and effectively the parameters of this type of ansatz. Here we…

Quantum Physics · Physics 2023-05-10 Wenxuan Zhang , Xiansong Xu , Zheyu Wu , Vinitha Balachandran , Dario Poletti

We propose a model to show the self-assembling of network-like structures between a set of nodes without using preexisting positional information or long-range attraction of the nodes. The model is based on Brownian agents that are capable…

Statistical Mechanics · Physics 2009-11-07 Frank Schweitzer , Benno Tilch

We analyse a model of fixed in-degree Random Boolean Networks in which the fraction of input-receiving nodes is controlled by a parameter gamma. We investigate analytically and numerically the dynamics of graphs under a parallel XOR…

Statistical Mechanics · Physics 2009-09-03 L. Ciandrini , C. Maffi , A. Motta , B. Bassetti , M. Cosentino Lagomarsino

Analytical description of propagation phenomena on random networks has flourished in recent years, yet more complex systems have mainly been studied through numerical means. In this paper, a mean-field description is used to coherently…

Statistical Mechanics · Physics 2010-10-08 Laurent Hébert-Dufresne , Pierre-André Noël , Vincent Marceau , Antoine Allard , Louis J. Dubé

A useful approach to the mathematical analysis of large-scale biological networks is based upon their decompositions into monotone dynamical systems. This paper deals with two computational problems associated to finding decompositions…

Molecular Networks · Quantitative Biology 2007-05-23 Bhaskar DasGupta , German Andres Enciso , Eduardo Sontag , Yi Zhang

A faithful description of the state of a complex dynamical network would require, in principle, the measurement of all its $d$ variables, an infeasible task for systems with practical limited access and composed of many nodes with high…

Chaotic Dynamics · Physics 2019-05-06 Christophe Letellier , Irene Sendiña-Nadal , Luis A. Aguirre

Quantum walks provide a natural framework to approach graph problems with quantum computers, exhibiting speedups over their classical counterparts for tasks such as the search for marked nodes or the prediction of missing links.…

Quantum Physics · Physics 2023-06-27 Duarte Magano , João Moutinho , Bruno Coutinho

The presence of disorder and inhomogeneities in quantum networks has often been unexpectedly beneficial for both quantum and classical resources. Here, we experimentally realize a controllable inhomogenous Quantum Walk dynamics, which can…

We introduce coherent-state propagation, a computational framework for simulating bosonic systems. We focus on bosonic circuits composed of displaced linear optics augmented by Kerr nonlinearities, a universal model of bosonic quantum…

Quantum Physics · Physics 2026-04-22 Nikita Guseynov , Zoë Holmes , Armando Angrisani

Topologically ordered states are among the most interesting quantum phases of matter that host emergent quasi-particles having fractional charge and obeying fractional quantum statistics. Theoretical study of such states is however…

Mesoscale and Nanoscale Physics · Physics 2026-05-29 Ahmed Abouelkomsan , Max Geier , Liang Fu

Real-world networks process structured connections since they have non-trivial vertex degree correlation and clustering. Here we propose a toy model of structure formation in real-world weighted network. In our model, a network evolves by…

Physics and Society · Physics 2015-06-26 C. C. Leung , H. F. Chau

Topologically ordered states are fundamentally important in theoretical physics, which are also suggested as promising candidates to build fault-tolerant quantum devices. However, it is still elusive how topological orders can be affected…

Statistical Mechanics · Physics 2019-05-08 Xi Chen , Shi-ju Ran , Shuo Yang , Maciej Lewenstein , Gang Su