Eldad Kepten, Yuval Garini
The Mean Square Displacement is a central tool in the analysis of Single Particle Tracking experiments. However, as we show, it suffers from two systematic errors when analyzing tracks of anomalous diffusing particles. The first is significant at short time differences and is induced by measurement errors. The second arises from the natural heterogeneity in biophysical systems. We show how to correct these two errors and improve the estimation of the mean square displacement. In addition we present a new method to characterize ensembles of particles even at very short and noisy measurements where regular time averaged mean square displacement analysis fails. All results are proven both mathematically and with simulations.
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http://arxiv.org/abs/1212.0793
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