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Analyzing the dynamics of open quantum systems has a long history in mathematics and physics. Depending on the system at hand, basic physical phenomena that one would like to explain are, for example, convergence to equilibrium, the…

Mathematical Physics · Physics 2015-06-15 Laurent Bruneau , Alain Joye , Marco Merkli

We explore the interplay of network structure, topology, and dynamic interactions between nodes using the paradigm of distributed synchronization in a network of coupled oscillators. As the network evolves to a global steady state,…

Disordered Systems and Neural Networks · Physics 2015-06-04 Kristina Lerman , Rumi Ghosh

Complex system arises as a result of the nonlinear interactions between components. In particular, the evolutionary dynamics of a multivariate system encodes the ways in which different variables interact with each other individually or in…

Information Theory · Computer Science 2020-04-22 Peishi Jiang , Praveen Kumar

We present an approach which enables to identify phase synchronization in coupled chaotic oscillators without having to explicitly measure the phase. We show that if one defines a typical event in one oscillator and then observes another…

Statistical Mechanics · Physics 2009-11-13 T. Pereira , M. S. Baptista , J. Kurths

Detecting coherence transfer in complex quantum networks can be challenging due to uncharacterized experimental conditions and limited system access. Here, we use static and dynamic coherence features to introduce a nonlinear criterion for…

The ubiquity of multiscale interactions in complex systems is well-recognized, with development and heredity serving as a prime example of how processes at different temporal scales influence one another. This work introduces a novel…

Signal Processing · Electrical Eng. & Systems 2024-09-04 Nayely Vélez-Cruz , Manfred D. Laubichler

I employ random-matrix methods to set up and solve statistical models of noisy nonunitary dynamics that appear in the context of monitored quantum systems. The models cover a range of scenarios combining random dynamics and measurements of…

Quantum Physics · Physics 2023-12-15 Henning Schomerus

We consider a complex-valued linear mixture model, under discrete weakly stationary processes. We recover latent components of interest, which have undergone a linear mixing. We study asymptotic properties of a classical unmixing estimator,…

Statistics Theory · Mathematics 2020-03-12 Niko Lietzén , Lauri Viitasaari , Pauliina Ilmonen

We propose a unified theoretical framework for quantifying spatio-temporal interactions in a stochastic dynamical system based on information geometry. In the proposed framework, the degree of interactions is quantified by the divergence…

Neurons and Cognition · Quantitative Biology 2016-12-08 Masafumi Oizumi , Naotsugu Tsuchiya , Shun-ichi Amari

An extension to computational mechanics complexity measure is proposed in order to tackle quantum states complexity quantification. The method is applicable to any $n-$partite state of qudits through some simple modifications. A Werner…

Computational Physics · Physics 2011-10-28 Yuri Campbell , José Roberto Castilho Piqueira

Data-based inference of directed interactions in complex dynamical systems is a problem common to many disciplines of science. In this work, we study networks of spatially separate dynamical entities, which could represent physical systems…

Statistical Mechanics · Physics 2024-03-15 Tim Hempel , Sarah A. M. Loos

Complex network dynamics have been analyzed with models of systems of coupled switches or systems of coupled oscillators. However, many complex systems are composed of components with diverse dynamics whose interactions drive the system's…

Quantitative Methods · Quantitative Biology 2012-01-09 Matthew R. Francis , Elana J. Fertig

Discovering the underlying dynamics of complex systems from data is an important practical topic. Constrained optimization algorithms are widely utilized and lead to many successes. Yet, such purely data-driven methods may bring about…

Dynamical Systems · Mathematics 2023-05-17 Nan Chen , Yinling Zhang

We generalize our recent approach to reconstruction of phase dynamics of coupled oscillators from data [B. Kralemann et al., Phys. Rev. E, 77, 066205 (2008)] to cover the case of small networks of coupled periodic units. Starting from the…

Chaotic Dynamics · Physics 2015-05-27 Björn Kralemann , Arkady Pikovsky , Michael Rosenblum

Complex network states are characterized by the interplay between system's structure and dynamics. One way to represent such states is by means of network density matrices, whose von Neumann entropy characterizes the number of distinct…

Physics and Society · Physics 2022-12-06 Arsham Ghavasieh , Manlio De Domenico

In the realm of big data, discerning patterns in nonlinear systems affected by external control inputs is increasingly challenging. Our approach blends the coarse-graining strengths of centroid-based unsupervised clustering with the clarity…

Fluid Dynamics · Physics 2023-12-25 Nitish Arya , Aditya G. Nair

We introduce a simple dynamical model of two interacting communities whose elements are subject to stochastic discrete-time updates governed by only bilinear interactions. When the intra- and inter-couplings are cooperative, the two…

Disordered Systems and Neural Networks · Physics 2014-10-29 M. Ostilli , W. Figueiredo

We investigate the role of a statistical complexity measure to assign equilibration in isolated quantum systems. While unitary dynamics preserve global purity, expectation values of observables often exhibit equilibration-like behavior,…

Quantum Physics · Physics 2025-08-14 Marcos G. Alpino , Tiago Debarba , Reinaldo O. Vianna , André T. Cesário

Topological measurements are increasingly being accepted as an important tool for quantifying complex structures. In many applications, these structures can be expressed as nodal domains of real-valued functions and are obtained only…

Probability · Mathematics 2020-05-29 Konstantin Mischaikow , Thomas Wanner

We propose a methodology to explore and measure the pairwise correlations that exist between variables in a dataset. The methodology leverages copulas for encoding dependence between two variables, state-of-the-art optimal transport for…

Machine Learning · Statistics 2016-11-01 Gautier Marti , Sebastien Andler , Frank Nielsen , Philippe Donnat