Equilibrium of disordered systems : constructing the appropriate valleys in each sample via strong disorder renormalization in configuration space

Details Equilibrium of disordered systems : constructing the appropriate valleys in each sample via strong disorder renormalization in configuration space Equilibrium of disordered systems : constructing the appropriate valleys in each sample via strong disorder renormalization in configuration space

2008-06-20

arxiv.org/abs/0806.3335v1

J. Phys. A: Math. Theor. 41 (2008) 375005

Physics

Condensed Matter

Disordered Systems and Neural Networks

17 pages, 10 figures

Scientific paper

10.1088/1751-8113/41/37/375005

To describe the equilibrium properties of disordered systems and the possible emergence of various 'phases' at low temperature, we adopt here the 'broken ergodicity' point of view advocated in particular by Palmer [Adv. Phys. 31, 669 (1982)] : the aim is then to construct the valleys of configurations that become separated by diverging barriers and to study their relative weights, as well as their internal properties. To characterize the slow non-equilibrium dynamics of disordered systems, we have recently introduced in [C. Monthus and T. Garel, J. Phys. A 41, 255002 (2008) and arxiv:0804.1847] a strong disorder renormalization procedure in configuration space, based on the iterative elimination of the smallest barrier remaining in the system. In the present paper, we show how this renormalization procedure allows to construct the longest-lived valleys in each disordered sample, and to obtain their free-energies, energies and entropies. This explicit RG formulation is very general since it can be defined for any master equation, and it gives new insights into the main ingredients of the droplet scaling picture. As an application, we have followed numerically the RG flow for the case of a directed polymer in a two-dimensional random medium to obtain histograms of the free-energy, entropy and energy differences between the two longest-lived valleys in each sample.

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