On the metastable states of the zero-temperature SK mode

Nonlinear response of the trap model in the aging regime: exact results in the strong-disorder limit

We study the dynamics in the one-dimensional disordered trap model with a broad distribution of trapping times p(tau) approximately 1/tau(1+mu), when an external force is applied from the very beginning at t=0, or only after a waiting time t(w), in the linear as well as in the nonlinear response regime. Using a real-space renormalization procedure that becomes exact in the limit of strong disorder mu-->0, we obtain explicit results for many observables, such as the diffusion front, the mean position, the thermal width, the localization parameters and the two-particle correlation function. In particular, the scaling functions for these observables give access to the complete interpolation between the unbiased case and the directed case. Finally, we discuss in detail the various regimes that exist for the average position in terms of the two times and the external field.

Exact occupation time distribution in a non-Markovian sequence and its relation to spin glass models

We compute exactly the distribution of the occupation time in a discrete non-Markovian toy sequence that appears in various physical contexts such as the diffusion processes and Ising spin glass chains. The non-Markovian property makes the results nontrivial even for this toy sequence. The distribution is shown to have non-Gaussian tails characterized by a nontrivial large deviation function that is computed explicitly. An exact mapping of this sequence to an Ising spin glass chain via a gauge transformation raises an interesting question for a generic finite sized spin glass model; at a given temperature, what is the distribution (over disorder) of the thermally averaged number of spins that are aligned to their local fields? We show that this distribution remains nontrivial even at infinite temperature and can be computed explicitly in few cases such as in the Sherrington-Kirkpatrick model with Gaussian disorder.