Probability distribution anomalous diffusion

Do we expect this model to be accurate for a dynamics dictated by Tsallis statistics A jump diffusion process that randomly samples the equilibrium canonical Tsallis distribution has been shown to lead to anomalous diffusion and Levy flights in the 5/3 < q < 3 regime. [3] Due to the delocalized nature of the equilibrium distributions, we might find that the microstates of our master equation are not well defined. Even at low temperatures, it may be difficult to identify distinct microstates of the system. The same delocalization can lead to large transition probabilities for states that are not adjacent ill configuration space. This would be a violation of the assumptions of the transition state theory - that once the system crosses the transition state from the reactant microstate it will be deactivated and equilibrated in the product state. Concerted transitions between spatially far-separated states may be common. This would lead to a highly connected master equation where each state is connected to a significant fraction of all other microstates of the system. [9, 10]... 

In this chapter, we use a type of initial condition that is different from the waterbag used in Refs. 15 and 18, and we show that (i) probability distribution functions do not have power-law tails in quasi-stationary states and (ii) the diffusion becomes anomalous if and only if the state is neither stationary nor quasi-stationary. In other words, the diffusion is shown to be normal in quasi-stationary states, although a stretched exponential correlation function is present instead of usual exponential correlation. Some scaling laws concerned with degrees of freedom are also exhibited, and the simple scaling laws imply that the results mentioned above holds irrespective of degrees of freedom. 

The two linear regions are associated to two different mechanisms in the diffusion process. For small q s—that is, for the core of the probability distribution function P( Ax, t)—only one exponent (vi = v(q) 0.65 for q < 2) fully characterizes the diffusion process. This means that the typical (i.e., nonrare) events obey a (weak) anomalous diffusion process. Roughly speaking, one can say that at scale l the characteristic time r(/) behaves as x ( ) = On the other hand, for q > 2 the behavior q v(q) q const... 

The fact that the temporal occurrence of the motion events performed by the random walker is so broadly distributed that no characteristic waiting time exists has been exploited by a number of investigators [7,19,31] in order to generalize the various diffusion equations of Brownian dynamics to explain anomalous relaxation phenomena. The resulting diffusion equations are called fractional diffusion equations because in general they will involve fractional derivatives of the probability density with respect to the time. For example, in fractional noninertial diffusion in a potential, the diffusion Eq. (5) becomes [7,31]... 

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