Diffusion Estimation via Particle Tracking with Vernier-like Time Sampling

Over the last two decades, particle tracking has become an essential technique for the analysis of diffusion processes and soft material properties. Much of this work has relied on time series data captured at fixed frequencies with speeds that are limited by the camera used. Here we present a flexible imaging scheme that generates time series with a Vernier-like structure. This scheme is analogous to the method used in Vernier calipers to achieve high precision length measurements. Two cameras acquire data at frequencies f₁ and f₂ with a frequency difference a = f₁ - f₂. These acquisitions are partially synchronized so that simultaneous exposures occur every 1/a seconds. The inter-camera exposures then exhibit a controlled desynchronization and produce a uniquely structured set of statistically independent lag times. In applications that investigate time independent processes, such as diffusion estimation and microrheology, these time series offer efficient access to data with a large field of view, wide dynamic range, with peak frequencies well in excess of f₁ and f₂. Our poster will describe the properties of the Vernier time series, its impact of data acquisition and analysis, and experimental results for particle diffusion in glycerol-water solutions.