The Evolution of Reaction-diffusion Controllers for Minimally Cognitive Agents

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A High Speed Particle Phase Discriminator (PPD-HS) for the classification of airborne particles, as tested in a continuous flow diffusion chamber

© Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License.A new instrument, the High-speed Particle Phase Discriminator (PPD-HS), developed at the University of Hertfordshire, for sizing individual cloud hydrometeors and determining their phase is described herein. PPD-HS performs an in situ analysis of the spatial intensity distribution of near-forward scattered light for individual hydrometeors yielding shape properties. Discrimination of spherical and aspherical particles is based on an analysis of the symmetry of the recorded scattering patterns. Scattering patterns are collected onto two linear detector arrays, reducing the complete 2-D scattering pattern to scattered light intensities captured onto two linear, one-dimensional strips of light sensitive pixels. Using this reduced scattering information, we calculate symmetry indicators that are used for particle shape and ultimately phase analysis. This reduction of information allows for detection rates of a few hundred particles per second. Here, we present a comprehensive analysis of instrument performance using both spherical and aspherical particles generated in a well-controlled laboratory setting using a vibrating orifice aerosol generator (VOAG) and covering a size range of approximately 3-32 μm. We use supervised machine learning to train a random forest model on the VOAG data sets that can be used to classify any particles detected by PPD-HS. Classification results show that the PPD-HS can successfully discriminate between spherical and aspherical particles, with misclassification below 5% for diameters >3μm. This phase discrimination method is subsequently applied to classify simulated cloud particles produced in a continuous flow diffusion chamber setup. We report observations of small, near-spherical ice crystals at early stages of the ice nucleation experiments, where shape analysis fails to correctly determine the particle phase. Nevertheless, in the case of simultaneous presence of cloud droplets and ice crystals, the introduced particle shape indicators allow for a clear distinction between these two classes, independent of optical particle size. From our laboratory experiments we conclude that PPD-HS constitutes a powerful new instrument to size and discriminate the phase of cloud hydrometeors. The working principle of PPD-HS forms a basis for future instruments to study microphysical properties of atmospheric mixed-phase clouds that represent a major source of uncertainty in aerosol-indirect effect for future climate projections..Peer reviewe

Probing the sign of on-site Hubbard interaction by two-particle quantum walks

We consider two identical bosons propagating on a one-dimensional lattice and address the prob- lem of discriminating whether their mutual on-site interaction is attractive or repulsive. We suggest a probing scheme based on the properties of the corresponding two-particle quantum walks, and show that the sign of the interaction introduces specific and detectable features in the dynamics of quantum correlations, thus permitting to discriminate between the two cases. We also discuss how these features are connected to the band-structure of the Hubbard Hamiltonian, and prove that discrimination may be obtained only when the two walkers are initially prepared in a superposition of localized states.Comment: 9 pages, 9 figure