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In this paper we present a switching control strategy to incrementally stabilize a class of nonlinear dynamical systems. Exploiting recent results on contraction analysis of switched Filippov systems derived using regularization, sufficient…

Systems and Control · Computer Science 2020-03-18 Mario di Bernardo , Davide Fiore

Dynamic processes of interacting units on a network are out of equilibrium in general. In the case of a directed tree, the dynamic cavity method provides an efficient tool that characterises the dynamic trajectory of the process for the…

Disordered Systems and Neural Networks · Physics 2022-05-25 Giuseppe Torrisi , Reimer Kühn , Alessia Annibale

In this paper we study the inference of the kinetic Ising model on sparse graphs by the decimation method. The decimation method, which was first proposed in [Phys. Rev. Lett. 112, 070603] for the static inverse Ising problem, tries to…

Disordered Systems and Neural Networks · Physics 2016-06-30 Aurélien Decelle , Pan Zhang

Direct simulation of biomolecular dynamics in thermal equilibrium is challenging due to the metastable nature of conformation dynamics and the computational cost of molecular dynamics. Biased or enhanced sampling methods may improve the…

Chemical Physics · Physics 2015-06-12 Benjamin Trendelkamp-Schroer , Frank Noe

We propose a semiclassical framework for solving open quantum dynamics in driven-dissipative spin systems. Our method consists of generalized spin-wave approximations tailored to describing quantum trajectories unravelled from the master…

Quantum Physics · Physics 2026-04-24 Zejian Li , Anna Delmonte , Rosario Fazio

We study the dynamics of an asymmetric simple exclusion process with open boundaries and local interactions using a pair approximation which generalizes the 2-node cluster mean field theory and the Markov chain approach to kinetics and…

Statistical Mechanics · Physics 2020-01-22 D. Botto , A. Pelizzola , M. Pretti

To identify emerging microscopic structures in low temperature spin glasses, we study self-sustained clusters (SSC) in spin models defined on sparse random graphs. A message-passing algorithm is developed to determine the probability of…

Disordered Systems and Neural Networks · Physics 2018-07-04 Jacopo Rocchi , David Saad , Chi Ho Yeung

We analyze the properties of degree-preserving Markov chains based on elementary edge switchings in undirected and directed graphs. We give exact yet simple formulas for the mobility of a graph (the number of possible moves) in terms of its…

Disordered Systems and Neural Networks · Physics 2012-03-12 E. S. Roberts , A. Annibale , A. C. C. Coolen

We investigate a stochastic approach to non-equilibrium quantum spin systems based on recent insights linking quantum and classical dynamics. Exploiting a sequence of exact transformations, quantum expectation values can be recast as…

Statistical Mechanics · Physics 2019-01-31 S. De Nicola , B. Doyon , M. J. Bhaseen

Experiments and computer simulation studies have revealed existence of rich dynamics in the orientational relaxation of molecules in confined systems such as water in reverse micelles, cyclodextrin cavities and nano-tubes. Here we introduce…

Statistical Mechanics · Physics 2015-05-18 Rajib Biswas , Biman Bagchi

The dynamical cavity method and its backtracking version provide a powerful approach to studying the properties of dynamical processes on large random graphs. This paper extends these methods to hypergraphs, enabling the analysis of…

Disordered Systems and Neural Networks · Physics 2025-11-13 Aude Maier , Freya Behrens , Lenka Zdeborová

We study the stochastic parallel dynamics of Ising spin systems defined on finitely connected directed random graphs with arbitrary degree distributions, using generating functional analysis. For fully asymmetric graphs the dynamics of the…

Disordered Systems and Neural Networks · Physics 2009-09-24 Kazushi Mimura , A. C. C. Coolen

We present the first exact asymptotic characterization of sequential dynamics for a broad class of local update algorithms on the Sherrington-Kirkpatrick (SK) model with Ising spins. Focusing on dynamics implemented via systematic scan --…

Disordered Systems and Neural Networks · Physics 2025-06-13 Yatin Dandi , David Gamarnik , Francisco Pernice , Lenka Zdeborová

We analyze the random sequential dynamics of a message passing algorithm for Ising models with random interactions in the large system limit. We derive exact results for the two-time correlation functions and the speed of convergence. The…

Disordered Systems and Neural Networks · Physics 2021-03-10 Burak Çakmak , Manfred Opper

We introduce a theoretical approach for designing generalizations of the approximate message passing (AMP) algorithm for compressed sensing which are valid for large observation matrices that are drawn from an invariant random matrix…

Information Theory · Computer Science 2017-05-12 Burak Çakmak , Manfred Opper , Ole Winther , Bernard H. Fleury

The usual setting for learning the structure and parameters of a graphical model assumes the availability of independent samples produced from the corresponding multivariate probability distribution. However, for many models the mixing time…

Machine Learning · Computer Science 2022-10-13 Arkopal Dutt , Andrey Y. Lokhov , Marc Vuffray , Sidhant Misra

In this communication we report the existence of a dynamic ``spin-reversal'' transition in an Ising system perturbed by a pulsed external magnetic field. The transition is achieved by tuning the strength ($h_p$) and/or the duration ($\Delta…

Condensed Matter · Physics 2015-06-25 A. Misra , B. K. Chakrabarti

We study Ising spin models on finitely connected random interaction graphs which are drawn from an ensemble in which not only the degree distribution $p(k)$ can be chosen arbitrarily, but which allows for further fine-tuning of the topology…

Disordered Systems and Neural Networks · Physics 2009-11-13 C. J. Perez-Vicente , A. C. C. Coolen

The cavity method is one of the cornerstones of the statistical physics of disordered systems such as spin glasses and other complex systems. It is able to analytically and asymptotically exactly describe the equilibrium properties of a…

Disordered Systems and Neural Networks · Physics 2023-09-11 Freya Behrens , Barbora Hudcová , Lenka Zdeborová

We give computable bounds on the rate of convergence of the transition probabilities to the stationary distribution for a certain class of geometrically ergodic Markov chains. Our results are different from earlier estimates of Meyn and…

Probability · Mathematics 2007-05-23 Peter H. Baxendale