T-6
Goal: Trap model. Captures aging in a simplified single particle description.
Key concepts: gradient descent, rugged landscapes, metastable states, Hessian matrices, random matrix theory, landscape’s complexity.
Langevin, Activation
- Monte Carlo dynamics.Langevin dynamics.
-Arrhenius law, trapping and activation.
-aging
The energy landscape of the REM. Consider the REM discussed in Problems 1. Assume that the Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle 2^N } configurations are organised in an hypercube of connectivity Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle N } : each configuration has Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle N } neighbours, that are obtained flipping one spin of the first configuration.
Problem 6.1: the trap model, and its foundations
The trap model is an abstract, effective model for the dynamics in complex landscapes. The configuration space is described as a collection of traps labeled by Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \alpha } having random depths/energies, see sketch. The dynamics is a sequence of jumps between the traps: the system spends in a trap Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \alpha } an exponentially large time with average (the probability to jump out of the trap in time Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle [t, t+dt]} is Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle dt/\tau_\alpha } .). The average times are distributed as
where Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle m }
is a parameter. When the system exits the trap, it jumps into another one randomly chosen among the Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle M=2^N }
. In this exercise, we aim at understanding the main features of this dynamics and at connecting it to models discussed before, like the REM and the spin.
- Aging. Compute the average trapping time and show that there is a critical value of Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle m } below which it diverges, signalling a non-ergodic phase (the system needs infinite time to explore the whole configuration space). Consider a dynamics running from time Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle t_w} to some later time : compute the typical value of the maximal trapping time Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \tau_{\text{max}}(t) } encountered in this time interval, an show that in the non-ergodic phase Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \tau_{\text{max}}(t) \sim t } . Why is this interpretable as a condensation phenomenon, as the ones discussed in Problems 1? Why is this an indication of aging?
- Correlation functions. Assume now that the trap represent a collection of microscopic configurations having self overlap . Assume that the overlap between configurations of different traps is Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle q_0 }
. Justify why the correlation function can be written as
Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle C(t_w + t, t_w)= q_{EA} \Pi(t, t_w)+ q_0 \left(1-\Pi(t, t_w)\right), \quad \quad \Pi(t, t_w)= \text{probability systems has not jumped in }[t_w, t_w+t]. } For one finds this. Consider the - REM: golf course energy landscape. The smallest energies values Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle E_\alpha }
among the Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle M=2^N }
, those with energy density , can be assumed to be distributed as
Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle P_N(E) \approx C_N \text{exp}\left[2 \sqrt{\log 2}(E+ N \sqrt{\log 2}) \right], \quad \quad E<0 } where Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle C_N } is a normalisation factor. Justify the form of this distribution (Hint: recall the discussion on extreme value statistics in Lecture 1!). Consider now one of these deep configurations of very small energy, which we will call traps : what is the minimal energy density among the neighbouring configurations of the trap? Does it depend on the entry of the trap itself? Why is this consistent with the results on the entropy of the REM that we computed in Problem 1.1? - REM: trapping times. The results above show that the energy landscape of the REM has a "golf course" structure: configuration with deep energy are isolated, surrounded by configurations of much higher energy (zero energy density). The Arrhenius law states that the time needed for the system to escape from a trap of energy and reach a configuration of zero energy is Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \tau \sim e^{\beta |E| } } . We call this a trapping time . Given the energy distribution Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle P_N(E) } , determine the distribution of trapping times . Do you recognise this temperature?
- p-spin: the “trap” picture of long time dynamics.
the system has spent almost all the time up to Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle t} in only one trap, the deepest one.
the age of the system is also the typical timescale for its evolution