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Abstract Wind-blown dust plays a critical role in numerous geophysical and biological systems, yet current models fail to explain the transport of coarse-mode particles (>5 μm) to great distances from their sources. For particles larger than a few microns, electrostatic effects have been invoked to account for longer-than-predicted atmospheric residence times. Although much effort has focused on elucidating the charging processes, comparatively little effort has been expended understanding the stability of charge on particles once electrified. Overall, electrostatic-driven transport requires that charge remain present on particles for days to weeks. Here, we present a set of experiments designed to explore the longevity of electrostatic charge on levitated airborne particles after a single charging event. Using an acoustic levitator, we measured the charge on particles of different material compositions suspended in atmospheric conditions for long periods of time. In dry environments, the total charge on particles decayed in over 1 week. The decay timescale decreased to days in humid environments. These results were independent of particle material and charge polarity. However, exposure to UV radiation could both increase and decrease the decay time depending on polarity. Our work suggests that the rate of charge decay on airborne particles is solely determined by ion capture from the air. Furthermore, using a one-dimensional sedimentation model, we predict that atmospheric dust of order 10 μm will experience the largest change in residence time due to electrostatic forces. 

The symmetric information bottleneck (SIB), an extension of the more familiar information bottleneck, is a dimensionality-reduction technique that simultaneously compresses two random variables to preserve information between their compressed versions. We introduce the generalized symmetric information bottleneck (GSIB), which explores different functional forms of the cost of such simultaneous reduction. We then explore the data set size requirements of such simultaneous compression. We do this by deriving bounds and root-mean-squared estimates of statistical fluctuations of the involved loss functions. We show that in typical situations, the simultaneous GSIB compression requires qualitatively less data to achieve the same errors compared to compressing variables one at a time. We suggest that this is an example of a more general principle that simultaneous compression is more data efficient than independent compression of each of the input variables. 

The collective behavior of levitated particles in a weakly ionized plasma (dusty plasma) has raised significant scientific interest. This is due to the complex array of forces acting on the particles and their potential to act as in situ diagnostics of the plasma environment. Ideally, the three-dimensional (3D) motion of many particles should be tracked for long periods of time. Typically, stereoscopic imaging using multiple cameras combined with particle image velocimetry is used to obtain a velocity field of many particles, yet this method is limited by its sample volume and short time scales. Here, we demonstrate a different, high-speed tomographic imaging method capable of tracking individual particles. We use a scanning laser sheet coupled to a single high-speed camera. We are able to identify and track tens of individual particles over centimeter length scales for several minutes, corresponding to more than 10 000 frames.