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We present a formalism to derive the stochastic differential equations (SDEs) for several solid-on-solid growth models. Our formalism begins with a mapping of the microscopic dynamics of growth models onto the particle systems with…

Statistical Mechanics · Physics 2009-11-07 Su-Chan Park , Doochul Kim , Jeong-Man Park

Complex spatiotemporal dynamics of physicochemical processes are often modeled at a microscopic level (through e.g. atomistic, agent-based or lattice models) based on first principles. Some of these processes can also be successfully…

We consider the design of structure-preserving discretization methods for the solution of systems of boundary controlled Partial Differential Equations (PDEs) thanks to the port-Hamiltonian formalism. We first provide a novel general…

Numerical Analysis · Mathematics 2020-09-30 Andrea Brugnoli , Ghislain Haine , Anass Serhani , Xavier Vasseur

In this work we propose a new, arbitrary order space-time finite element discretisation for Hamiltonian PDEs in multisymplectic formulation. We show that the new method which is obtained by using both continuous and discontinuous…

Numerical Analysis · Mathematics 2021-08-18 Elena Celledoni , James Jackaman

Transportation processes, which play a prominent role in the life and social sciences, are typically described by discrete models on lattices. For studying their dynamics a continuous formulation of the problem via partial differential…

Symbolic Computation · Computer Science 2016-03-22 Christoph Koutschan , Helene Ranetbauer , Georg Regensburger , Marie-Therese Wolfram

A model of superconductivity is proposed taking into account repulsive particle interaction, mesoscopic phase separation and softening of crystalline lattice. These features are typical of many high-temperature superconductors. The main…

Superconductivity · Physics 2007-05-23 A. J. Coleman , E. P. Yukalova , V. I. Yukalov

This work discusses the model reduction problem for large-scale multi-symplectic PDEs with cubic invariants. For this, we present a linearly implicit global energy-preserving method to construct reduced-order models. This allows to…

Numerical Analysis · Mathematics 2023-08-08 Süleyman Yildiz , Pawan Goyal , Peter Benner

We consider the time evolution of a one dimensional $n$-gradient continuum. Our aim is to construct and analyze discrete approximations in terms of physically realizable mechanical systems, called microscopic because they are living on a…

Mathematical Physics · Physics 2015-05-06 Antonio Carcaterra , Francesco dell'Isola , Raffaele Esposito , Mario Pulvirenti

A linear irreversible thermodynamic framework of heat conduction in rigid conductors is introduced. The deviation from local equilibrium is characterized by a single internal variable and a current intensity factor. A general constitutive…

Statistical Mechanics · Physics 2014-04-08 P. Ván , T. Fülöp

We consider Markov models of large-scale networks where nodes are characterized by their local behavior and by a mobility model over a two-dimensional lattice. By assuming random walk, we prove convergence to a system of partial…

Networking and Internet Architecture · Computer Science 2016-04-27 Max Tschaikowski , Mirco Tribastone

We informally review a few PDEs for which the Monge-Kantorovich distance between pairs of solutions, possibly with some judicious cost function, decays: heat equation, Fokker-Planck equation, heat equation with varying coefficients,…

Analysis of PDEs · Mathematics 2025-08-27 Nicolas Fournier , Benoît Perthame

By combining different ideas, a general and efficient protocol to deal with discontinuous phase transitions at low temperatures is proposed. For small $T$'s, it is possible to derive a generic analytic expression for appropriate order…

Statistical Mechanics · Physics 2015-06-03 C. E. Fiore , M. G. E. da Luz

A multiscale theory of interacting continuum mechanics and thermodynamics of mixtures of fluids, electrodynamics, polarization and magnetization is proposed. The mechanical (reversible) part of the theory is constructed in a purely…

Classical Physics · Physics 2020-08-26 Petr Vagner , Michal Pavelka , Ogul Esen

Solving partial differential equations (PDEs) on fine spatio-temporal scales for high-fidelity solutions is critical for numerous scientific breakthroughs. Yet, this process can be prohibitively expensive, owing to the inherent complexities…

Numerical Analysis · Mathematics 2024-04-09 Yulong Lu , Wuzhe Xu

Extended Thermodynamics is a very important theory: for example, it predicts hyperbolicity, finite speeds of propagation waves as well as continuous dependence on initial data. Therefore, it constitutes a significative improvement of…

Mathematical Physics · Physics 2007-05-23 Sebastiano Pennisi , Maria Cristina Carrisi , Antonio Scanu

We derive the porous medium equation from an interacting particle system which belongs to the family of exclusion processes, with nearest neighbor exchanges. The particles follow a degenerate dynamics, in the sense that the jump rates can…

Probability · Mathematics 2020-12-08 Oriane Blondel , Clément Cancès , Makiko Sasada , Marielle Simon

We introduce and solve in closed form a simple model of a macroscopic body propagating in a one-dimensional resistive medium at temperature T. The assumption of completely inelastic collisions between the body and the particles composing…

Physics Education · Physics 2009-09-25 M. I. Molina

We show how the macroscopic state variables pressure, entropy and temperature of equilibrium thermodynamics can be consistently derived from the (quantum) chaotic spectral structure of one or two particles in two-dimensional domains. This…

A simple, general and practically exact method is developed for the equilibrium properties of the macroscopic physical systems with translational symmetry. Applied to the Ising model in two and three dimension, a modest calculation gives…

Strongly Correlated Electrons · Physics 2015-05-19 S. G. Chung

Modeling complex spatiotemporal dynamical systems, such as the reaction-diffusion processes, have largely relied on partial differential equations (PDEs). However, due to insufficient prior knowledge on some under-explored dynamical…

Machine Learning · Computer Science 2023-05-23 Chengping Rao , Pu Ren , Qi Wang , Oral Buyukozturk , Hao Sun , Yang Liu