The hydrodynamic limit of a one-dimensional nearest neighbor gradient system

1987 ◽  
Vol 48 (3-4) ◽  
pp. 769-788 ◽  
Author(s):  
Michael G. M�rmann
Keyword(s):  
Hydrodynamic Limit ◽  
Nearest Neighbor ◽  
Gradient System ◽  
One Dimensional ◽  
Nearest Neighbor Gradient System

Study of the one-dimensional Holstein model with next-nearest-neighbor hopping

2010 ◽  
Vol 23 (2) ◽  
pp. 025601 ◽  
Author(s):  
Monodeep Chakraborty ◽  
A N Das ◽  
Atisdipankar Chakrabarti
Keyword(s):  
Nearest Neighbor ◽  
One Dimensional ◽  
Holstein Model ◽  
The One

scholarly journals Effective Hamiltonian for a half-filled asymmetric ionic Hubbard chain with alternating on-site interaction

2016 ◽  
Vol 30 (03) ◽  
pp. 1550260 ◽  
Author(s):  
I. Grusha ◽  
M. Menteshashvili ◽  
G. I. Japaridze
Keyword(s):  
Magnetic Field ◽  
Nearest Neighbor ◽  
Effective Hamiltonian ◽  
Heisenberg Chain ◽  
Spin Hamiltonian ◽  
Effective Spin ◽  
One Dimensional ◽  
The One ◽  
Strong Repulsion ◽  
Ionic Hubbard Model

We derive an effective spin Hamiltonian for the one-dimensional half-filled asymmetric ionic Hubbard model (IHM) with alternating on-site interaction in the limit of strong repulsion. It is shown that the effective Hamiltonian is that of a spin S = 1/2 anisotropic XXZ Heisenberg chain with alternating next-nearest-neighbor (NNN) and three-spin couplings in the presence of a uniform and a staggered magnetic field.

scholarly journals EXACT SOLUTION OF AN IRREVERSIBLE ONE-DIMENSIONAL MODEL WITH FULLY BIASED SPIN EXCHANGES

1996 ◽  
Vol 10 (25) ◽  
pp. 3451-3459 ◽  
Author(s):  
ANTÓNIO M.R. CADILHE ◽  
VLADIMIR PRIVMAN
Keyword(s):  
Exact Solution ◽  
Domain Wall ◽  
Nearest Neighbor ◽  
Spin Exchange ◽  
Initial Conditions ◽  
Strong Dependence ◽  
Zero Temperature ◽  
Dimensional Model ◽  
One Dimensional ◽  
Temperature Dynamics

We introduce a model with conserved dynamics, where nearest neighbor pairs of spins ↑↓ (↓↑) can exchange to assume the configuration ↓↑ (↑↓), with rate β(α), through energy decreasing moves only. We report exact solution for the case when one of the rates, α or β, is zero. The irreversibility of such zero-temperature dynamics results in strong dependence on the initial conditions. Domain wall arguments suggest that for more general, finite-temperature models with steady states the dynamical critical exponent for the anisotropic spin exchange is different from the isotropic value.

ROBUSTNESS OF COMPLETE STABILITY FOR 1-D CIRCULAR CNNs

2006 ◽  
Vol 16 (08) ◽  
pp. 2177-2190
Author(s):  
MAURO DI MARCO ◽  
CHIARA GHILARDI
Keyword(s):  
Neural Networks ◽  
Equilibrium Point ◽  
Nearest Neighbor ◽  
Perturbation Parameter ◽  
Relative Magnitude ◽  
Loss Of Stability ◽  
Unique Equilibrium ◽  
Small Perturbations ◽  
Structure Preserving ◽  
One Dimensional

This paper investigates the issue of robustness of complete stability of standard Cellular Neural Networks (CNNs) with respect to small perturbations of the nominally symmetric interconnections. More specifically, a class of circular one-dimensional (1-D) CNNs with nearest-neighbor interconnections only, is considered. The class has sparse interconnections and is subject to perturbations which preserve the interconnecting structure. Conditions assuring that the perturbed CNN has a unique equilibrium point at the origin, which is unstable, are provided in terms of relative magnitude of the perturbations with respect to the nominal interconnection weights. These conditions allow one to characterize regions in the perturbation parameter space where there is loss of stability for the perturbed CNN. In turn, this shows that even for sparse interconnections and structure preserving perturbations, robustness of complete stability is not guaranteed in the general case.

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