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Prediction and control of network dynamics are grand-challenge problems in network science. The lack of understanding of fundamental laws driving the dynamics of networks is among the reasons why many practical problems of great…

Physics and Society · Physics 2016-02-02 Konstantin Zuev , Fragkiskos Papadopoulos , Dmitri Krioukov

The effects of the symmetry energy softening of the relativistic mean field (RMF) models on the properties of matter with neutrino trapping are investigated. It is found that the effects are less significant than those in the case without…

Nuclear Theory · Physics 2009-11-11 A. Sulaksono , T. Mart

We study localization in a quasiperiodic spinful antiferromagnetic Hubbard ring within a self-consistent Hartree-Fock framework, emphasizing the interplay of quasiperiodicity, staggered Zeeman-field-induced antiferromagnetic order, and…

Mesoscale and Nanoscale Physics · Physics 2026-04-01 Souvik Roy , Ranjini Bhattacharya

We study the synchronous dynamics of the Hopfield model when a random antisymmetric part is added to the otherwise symmetric synaptic matrix. We use a generating functional technique to derive analytical expressions for the order parameters…

Disordered Systems and Neural Networks · Physics 2007-05-23 Manoranjan P. Singh

We derive a general mean-field theory of inhomogeneous polymer dynamics; a theory whose form has been speculated and widely applied, but not heretofore derived. Our approach involves a functional integral representation of a…

Soft Condensed Matter · Physics 2015-06-18 Glenn H. Fredrickson , Henri Orland

The non-equilibrium process where the system does not evolve to the featureless state is one of the new central objects in the non-equilibrium phenomena. In this paper, starting from the short-range entangled state in the two-dimensional…

High Energy Physics - Theory · Physics 2024-07-30 Masahiro Nozaki , Kotaro Tamaoka , Mao Tian Tan

We present a general theory for the onset of coherence in collections of heterogeneous maps interacting via a complex connection network. Our method allows the dynamics of the individual uncoupled systems to be either chaotic or periodic,…

Disordered Systems and Neural Networks · Physics 2009-11-11 Juan G. Restrepo , Edward Ott , Brian R. Hunt

We consider the covariant Lyapunov vectors (CLV) of a high-dimensional Hamiltonian flow in the case of long range potential, namely the Hamiltonian Mean Field (HMF) problem, by studying the behavior of the Lyapunov spectra and the…

Chaotic Dynamics · Physics 2014-01-10 Matteo Sala , Alessio Turchi , Roberto Artuso

Recently, Hamiltonian neural networks (HNN) have been introduced to incorporate prior physical knowledge when learning the dynamical equations of Hamiltonian systems. Hereby, the symplectic system structure is preserved despite the…

Machine Learning · Computer Science 2023-06-07 Eva Dierkes , Christian Offen , Sina Ober-Blöbaum , Kathrin Flaßkamp

Model Hamiltonians with long-range interaction yield energies that are corrected taking into account the universal behavior of the electron-electron interaction at short range. Although the intention of the paper is to explore the…

Chemical Physics · Physics 2020-10-28 Andreas Savin

The process of renormalisation in nonperturbative Hamiltonian Effective Field Theory (HEFT) is examined in the $\Delta$-resonance scattering channel. As an extension of effective field theory incorporating the L\"uscher formalism, HEFT…

High Energy Physics - Lattice · Physics 2022-08-31 Curtis D. Abell , Derek B. Leinweber , Anthony W. Thomas , Jia-Jun Wu

We study a generic model of globally coupled rotors that includes the effects of noise, phase shift in the coupling, and distributions of moments of inertia and natural frequencies of oscillation. As particular cases, the setup includes…

Chaotic Dynamics · Physics 2014-07-11 Maxim Komarov , Shamik Gupta , Arkady Pikovsky

Entanglement or modular Hamiltonians play a crucial role in the investigation of correlations in quantum field theories. In particular, in 1+1 space-time dimensions, the spectra of entanglement Hamiltonians of conformal field theories…

Statistical Mechanics · Physics 2020-08-06 Ananda Roy , Frank Pollmann , Hubert Saleur

We consider finite horizon stochastic mean field games in which the state space is a network. They are described by a system coupling a backward in time Hamilton-Jacobi-Bellman equation and a forward in time Fokker-Planck equation. The…

Analysis of PDEs · Mathematics 2019-03-08 Yves Achdou , Manh-Khang Dao , Olivier Ley , Nicoletta Tchou

We study the synchronization properties of a generic networked dynamical system, and show that, under a suitable approximation, the transition to synchronization can be predicted with the only help of eigenvalues and eigenvectors of the…

We review the basic ideas of the dynamical mean field theory (DMFT) and some of the insights into the electronic structure of strongly correlated electrons obtained by this method in the context of model Hamiltonians. We then discuss the…

Strongly Correlated Electrons · Physics 2007-05-23 G. Kotliar , S. Y. Savrasov

Heider balance theory provides a fundamental framework for understanding the formation of friendly and hostile relations in social networks. Existing stochastic formulations typically assume a uniform social temperature, implying that all…

Physics and Society · Physics 2026-05-19 Zhen Li , Yuki Izumida

Lattice Hamiltonian systems underpin models across condensed matter, nonlinear optics, and biophysics, yet learning their dynamics from data is obstructed by two unknowns: the interaction topology and whether node dynamics are homogeneous.…

Machine Learning · Computer Science 2026-04-28 Ru Geng , Panayotis Kevrekidis , Yixian Gao , Hong-Kun Zhang , Jian Zu

We analyze a class of mean-field (MF) lattice-fermion Hamiltonians and construct the corresponding grand-canonical density operator for such system. New terms are introduced, which may be interpreted as local fugacities, molecular fields,…

Strongly Correlated Electrons · Physics 2009-09-01 Jakub Jȩdrak , Jozef Spałek

The convergence to the self-consistency in the dynamical-mean-field-theory (DMFT) calculations for models of correlated electron systems can be significantly accelerated by using an appropriate mixing of hybridization functions which are…

Strongly Correlated Electrons · Physics 2009-11-11 Rok Zitko