2006
DOI: 10.1137/050643982
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Gradient Flows as a Selection Procedure for Equilibria of Nonconvex Energies

Abstract: Abstract. For atomistic material models, global minimization gives the wrong qualitative behavior; a theory of equilibrium solutions needs to be defined in different terms. In this paper, a concept based on gradient flow evolutions, to describe local minimization for simple atomistic models based on the Lennard-Jones potential, is presented. As an application of this technique, it is shown that an atomistic gradient flow evolution converges to a gradient flow of a continuum energy as the spacing between the at… Show more

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Cited by 7 publications
(6 citation statements)
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“…While the static questions of -convergence or relaxation are well studied, the related questions for evolutionary systems are treated less systematically, see e.g., [7,8,37]. Only recently, a systematic study for gradient flows was initialized in [36,[38][39][40][41].…”
Section: Introductionmentioning
confidence: 99%
“…While the static questions of -convergence or relaxation are well studied, the related questions for evolutionary systems are treated less systematically, see e.g., [7,8,37]. Only recently, a systematic study for gradient flows was initialized in [36,[38][39][40][41].…”
Section: Introductionmentioning
confidence: 99%
“…The limit systems obtained in this paper are gradient flows, but the functionals generating it have a different form. On the other hand, Hamiltonian systems generated by pair interaction potentials have been considered in . Some of the questions required to understand such problems have analogies with the ones considered in this last paper, including questions related with the stability of the dynamics for perturbations with length scales comparable with the distance between particles.…”
Section: Introductionmentioning
confidence: 88%
“…for example [19,23]). This can be best seen by considering an atomistic body which is clamped at the left-hand end with a small deformation applied to the right-hand end.…”
Section: Model Problem and Qc Approximationmentioning
confidence: 99%
“…In a quite similar spirit, we used an adaptive proximal point algorithm (PPA) (see [13] for an overview), which is essentially a time-discretized version of a gradient flow for E to compute critical points. The novelty of our algorithm is that, motivated by the analysis in [19], we chose the | · | w 1,2 ε -semi-norm as the gradient flow norm. Given an initial condition Y (0) , for the th step of the optimization method, we find a critical point (local minimizer) of…”
Section: Adaptive Algorithmmentioning
confidence: 99%
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