We study phase ordering on networks and we establish a relation between the exponent a(chi) of the aging part of the integrated autoresponse function chi(ag) and the topology of the underlying structures. We show that a(chi)> 0 in full generality on networks which are above the lower critical dimension d(L), i.e., where the corresponding statistical model has a phase transition at finite temperature. For discrete symmetry models on finite ramified structures with T-c=0, which are at the lower critical dimension d(L), we show that a(chi) is expected to vanish. We provide numerical results for the physically interesting case of the 2-d percolation cluster at or above the percolation threshold, i.e., at or above d(L), and for other networks, showing that the value of a(chi) changes according to our hypothesis. For O(N) models we find that the same picture holds in the large-N limit and that a(chi) only depends on the spectral dimension of the network.

Aging dynamics and the topology of inhomogenous networks

Vezzani A
2006

Abstract

We study phase ordering on networks and we establish a relation between the exponent a(chi) of the aging part of the integrated autoresponse function chi(ag) and the topology of the underlying structures. We show that a(chi)> 0 in full generality on networks which are above the lower critical dimension d(L), i.e., where the corresponding statistical model has a phase transition at finite temperature. For discrete symmetry models on finite ramified structures with T-c=0, which are at the lower critical dimension d(L), we show that a(chi) is expected to vanish. We provide numerical results for the physically interesting case of the 2-d percolation cluster at or above the percolation threshold, i.e., at or above d(L), and for other networks, showing that the value of a(chi) changes according to our hypothesis. For O(N) models we find that the same picture holds in the large-N limit and that a(chi) only depends on the spectral dimension of the network.
2006
INFM
OFF-EQUILIBRIUM
PHASE-TRANSITIONS
SPIN MODELS
SYSTEMS
FRACTALS
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/122449
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