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As shown by early studies on mean-field models of the glass transition, the geometrical features of the energy landscape provide fundamental information on the dynamical transition at the Mode-Coupling temperature $T_d$. We show that active…

Statistical Mechanics · Physics 2021-11-10 Giacomo Gradenigo , Matteo Paoluzzi

Synchronization is an important behavior that characterizes many natural and human made systems composed by several interacting units. It can be found in a broad spectrum of applications, ranging from neuroscience to power-grids, to mention…

Adaptation and Self-Organizing Systems · Physics 2025-10-22 Riccardo Muolo , Timoteo Carletti , James P. Gleeson , Malbor Asllani

This paper is concerned with the dynamics evolution of opinions in the presence of both cooperations and antagonisms. The class of Laplacian flows is addressed through signed digraphs subject to switching topologies. Further, a state…

Systems and Control · Computer Science 2017-05-15 Deyuan Meng , Ziyang Meng , Yiguang Hong

We present a coherent approach to the competition between thermodynamic states in spatially inhomogeneous systems, such as the Edwards-Anderson spin glass with a fixed coupling realization. This approach explains and relates chaotic size…

adap-org · Physics 2009-10-28 C. M. Newman , D. L. Stein

To observe synchronization in a large network of classical or quantum systems demands both excellent control of the interactions between the nodes and very accurate preparation of the initial conditions due to the involved nonlinearities…

Quantum Physics · Physics 2023-04-14 Christopher W. Wächtler , Gloria Platero

Complex dynamical systems are often modeled as networks, with nodes representing dynamical units which interact through the network's links. Gene regulatory networks, responsible for the production of proteins inside a cell, are an example…

Statistical Mechanics · Physics 2009-09-30 Zoran Levnajić

It is well-known that the fundamental diagram in a realistic traffic system is featured by capacity drop. From a mesoscopic approach, we demonstrate that such a phenomenon is linked to the unique properties of stochastic noise, which, when…

Applications · Statistics 2025-03-21 Mariana Pereira de Melo , Leon Alexander Valencia , Wei-Liang Qian

We propose a general framework to extract microscopic interactions from raw configurations with deep neural networks. The approach replaces the modeling Hamiltonian by the neural networks, in which the interaction is encoded. It can be…

Computational Physics · Physics 2020-08-19 Lingxiao Wang , Yin Jiang , Kai Zhou

Cortical activity in-vivo displays relaxational time scales much longer than the membrane time constant of the neurons or the deactivation time of ionotropic synaptic conductances. The mechanisms responsible for such slow dynamics are not…

Disordered Systems and Neural Networks · Physics 2025-08-07 Ferdinand Tixidre , Gianluigi Mongillo , Alessandro Torcini

We analyse the stability of linear dynamical systems defined on sparse, random graphs with predator-prey, competitive, and mutualistic interactions. These systems are aimed at modelling the stability of fixed points in large systems defined…

Statistical Mechanics · Physics 2025-01-30 Andrea Marcello Mambuca , Chiara Cammarota , Izaak Neri

Real-world networks in technology, engineering and biology often exhibit dynamics that cannot be adequately reproduced using network models given by smooth dynamical systems and a fixed network topology. Asynchronous networks give a…

Dynamical Systems · Mathematics 2017-02-07 Christian Bick , Michael Field

Recent studies of networks representing complex systems from the brain to social graphs have revealed their higher-order architecture, which can be described by aggregates of simplexes (triangles, tetrahedrons, and higher cliques). Current…

Soft Condensed Matter · Physics 2026-03-11 Bosiljka Tadic , Neelima Gupte

Glassy systems are disordered systems characterized by extremely slow dynamics. Examples are supercooled liquids, whose dynamics slow down under cooling. The specific pattern of slowing-down depends on the material considered. This…

Disordered Systems and Neural Networks · Physics 2016-04-12 Le Yan

The physical properties of magnetic nanoparticles have been investigated with focus on the influence of dipolar interparticle interaction. For weakly coupled nanoparticles, thermodynamic perturbation theory is employed to derive analytical…

Materials Science · Physics 2016-08-31 Petra E. Jönsson

In many strongly correlated electron systems, non-Fermi liquid behavior and unconventional superconductivity can be viewed as emerging from an effective 4-fermion interaction with a singular frequency dependence. A pairing instability in…

Strongly Correlated Electrons · Physics 2026-04-17 Yue Yu , Andrey V. Chubukov

In this paper we report that notions of topological protection can be applied to stationary configurations that are driven far from equilibrium by active, dissipative processes. We show this for physically two disparate cases : stochastic…

Statistical Mechanics · Physics 2022-06-08 Kinjal Dasbiswas , Kranthi K. Mandadapu , Suriyanarayanan Vaikuntanathan

Many mechanical systems exhibit changes in their kinematic topology altering the mobility. Ideal contact is the best known cause, but also stiction and controlled locking of parts of a mechanism lead to topology changes. The latter is…

Robotics · Computer Science 2026-04-22 Andreas Mueller

Biological and social networks have recently attracted enormous attention between physicists. Among several, two main aspects may be stressed: A non trivial topology of the graph describing the mutual interactions between agents exists…

Statistical Mechanics · Physics 2015-05-19 Adriano Barra , Elena Agliari

We study the off-equilibrium dynamics of the Edwards-Anderson spin glass in four dimensions under the influence of a non-hamiltonian perturbation. We find that for small asymmetry the model behaves as the hamiltonian one, while for large…

Disordered Systems and Neural Networks · Physics 2009-10-30 Enzo Marinari , Daniel A Stariolo

We study systems of interacting reinforced stochastic processes, where agents' decisions evolve under reinforcement, network-mediated interactions, and environmental influences. In competitive environments with irreducible networks, we…

Probability · Mathematics 2025-09-18 Michele Aleandri , Paolo Dai Pra , Ida Germana Minelli
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