Aging Correlation Functions for Blinking Nano-Crystals, and Other On - Off Stochastic Processes

TL;DR

This paper analyzes the aging behavior of blinking nano-crystals using a two-state stochastic model, deriving correlation functions and classifying different asymptotic behaviors relevant to experimental observations.

Contribution

It introduces a detailed classification of intensity correlation behaviors for blinking nano-crystals based on different on/off time distributions, including aging effects.

Findings

Aging behavior occurs for specific on/off time distributions.

Four classes of asymptotic correlation behaviors are identified.

Analytical scaling laws for correlation functions are derived.

Abstract

Following recent experiments on power law blinking behavior of single nano-crystals, we calculate two-time intensity correlation functions <I(t)I(t+t')> for these systems. We use a simple two state (on and off) stochastic model to describe the dynamics. We classify possible behaviors of the correlation function and show that aging, e.g., dependence of the correlation function on age of process t, is obtained for classes of the on time and off time distributions relevant to experimental situation. Analytical asymptotic scaling behaviors of the intensity correlation in the double time t and t' domain are obtained. In the scaling limit <I(t)I(t+t')> --> h(x), where four classes of behaviors are found: (i) finite averaged on and off times x=t' (standard behavior) (ii) on and off times with identical power law behaviors x=t/t' (case relevant for capped nano-crystals). (iii) exponential on times and power law off times x=tt' (case relevant for uncapped nano-crystals). (iv) For defected off time distribution we also find x=t+t' . Origin of aging behavior is explained based on simple diffusion model. We argue that the diffusion controlled reaction A+B <--> AB, when followed on a single particle level exhibits aging behavior.