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More and more countries show a significant slowdown in the number of new COVID-19 infections due to effective governmentally instituted lockdown and social distancing measures. We have analyzed the growth behavior of the top 25 most affected countries by means of a local slope analysis and found three distinct patterns that individual countries follow depending on the strictness of the lockdown protocols: exponential rise and fall, power law, or logistic. For countries showing power law growth we have determined the scaling exponents. For countries that showed a strong slowdown in the rate of infections we have extrapolated the expected saturation of the number of infections and the expected final date. Two different extrapolation methods (logistic and parabolic) were used. Both methods agree on the order of magnitude of saturation and end dates. Global infections rates are analyzed with the same methods. The relevance and accuracy of these extrapolations is discussed., Comment: 10 pages, 13 figures, 3 tables

The number of corona virus (COVID-19) infections grows worldwide. In order to create short term predictions to prepare for the extent of the global pandemic we analyze infection data from the top 25 affected countries. It is shown that all country-specific infection rates follow a power law growth behavior and the scaling exponents per country are calculated. We find two different growth patterns: either steady power law growth from the very beginning with moderate scaling exponents of 3-5 or explosive power law growth with dramatic scaling exponents of 8-11. In the case of the USA we even find an exponent of 16.59. By means of data analysis we confirm that instituting strict measures of lock-downs combined with a strong adherence by the population are effective means to bring the growth rates down. While many countries have instituted measures there are only three countries (Denmark, Norway, and South Korea) so far where such lock-downs led to a significant reduction of the growth rate. In the case of Denmark we calculate the reduction of the scaling exponents to move from 6.82 to 1.47., Comment: 6 pages, 8 figures

We present a novel algorithm that predicts the probability that the time derivative of the horizontal component of the ground magnetic field $dB/dt$ exceeds a specified threshold at a given location. This quantity provides important information that is physically relevant to Geomagnetically Induced Currents (GIC), which are electric currents { associated to} sudden changes in the Earth's magnetic field due to Space Weather events. The model follows a 'gray-box' approach by combining the output of a physics-based model with machine learning. Specifically, we combine the University of Michigan's Geospace model that is operational at the NOAA Space Weather Prediction Center, with a boosted ensemble of classification trees. We discuss the problem of re-calibrating the output of the decision tree to obtain reliable probabilities. The performance of the model is assessed by typical metrics for probabilistic forecasts: Probability of Detection and False Detection, True Skill Statistic, Heidke Skill Score, and Receiver Operating Characteristic curve. We show that the ML enhanced algorithm consistently improves all the metrics considered., Comment: under review

We present a numerical and experimental study of feedback control of unstable cellular patterns in directional solidification (DS). The sample, a dilute binary alloy, solidifies in a 2D geometry under a control scheme which applies local heating close to the cell tips which protrude ahead of the other. For the experiments, we use a real-time image processing algorithm to track cell tips, coupled with a movable laser spot array device, to heat locally. We show, numerically and experimentally, that spacings well below the threshold for a period-doubling instability can be stabilized. As predicted by the numerical calculations, cellular arrays become stable, and the spacing becomes uniform through feedback control which is maintained with minimal heating., Comment: 4 pages, 4 figures, 1 table

We report an experimental investigation of momentum diffusion in the delta-function kicked rotor where time symmetry is broken by a two-period kicking cycle and spatial symmetry by an alternating linear potential. The momentum diffusion constant is thus modified by kick-to-kick correlations which show a momentum dependence. We exploit this, and a technique involving a moving optical potential, to create an asymmetry in the momentum diffusion that is due entirely to the chaotic dynamics., Comment: 4 pages, 4 figures

We present the results of experiments performed on cold caesium in a pulsed sinusoidal optical potential created by counter-propagating laser beams having a small frequency difference in the laboratory frame. Since the atoms, which have average velocity close to zero in the laboratory frame, have non-zero average velocity in the co-moving frame of the optical potential, we are able to centre the initial velocity distribution of the cloud at an arbitrary point in phase-space. In particular, we demonstrate the use of this technique to place the initial velocity distribution in a region of phase-space not accessible to previous experiments, namely beyond the momentum boundaries arising from the finite pulse duration of the potential. We further use the technique to explore the kicked rotor dynamics starting from a region of phase-space where there is a strong velocity dependence of the diffusion constant and quantum break time and demonstrate that this results in a marked asymmetry in the chaotic evolution of the atomic momentum distribution., Comment: 4 pages, 3 figures

We present Van Allen Probe observations of electromagnetic ion cyclotron (EMIC) waves triggered solely due to individual substorm-injected ions in the absence of storms or compressions of the magnetosphere during 9 August 2015. The time at which the injected ions are observed directly corresponds to the onset of EMIC waves at the location of Van Allen Probe A (L = 5.5 and 18:06 magnetic local time). The injection was also seen at geosynchronous orbit by the Geostationary Operational Environmental Satellite and Los Alamos National Laboratory spacecraft, and the westward(eastward) drift of ions(electrons) was monitored by Los Alamos National Laboratory spacecraft at different local times. The azimuthal location of the injection was determined by tracing the injection signatures backward intime to their origin assuming a dipolar magnetic field of Earth. The center of this injection location wasdetermined to be close to 20:00 magnetic local time. Geostationary Operational Environmental Satelliteand ground magnetometer responses confirm substorm onset at approximately the same local time.The observed EMIC wave onsets at Van Allen Probe were also associated with a magnetic field decrease.The arrival of anisotropic ions along with the decrease in the magnetic field favors the growth of the EMICwave instability based on linear theory analysis.