Direct evidence of nonstationary collisionless shocks in space plasmas.

Collisionless shocks are ubiquitous throughout the universe: around stars, supernova remnants, active galactic nuclei, binary systems, comets, and planets. Key information is carried by electromagnetic emissions from particles accelerated by high Mach number collisionless shocks. These shocks are intrinsically nonstationary, and the characteristic physical scales responsible for particle acceleration remain unknown. Quantifying these scales is crucial, as it affects the fundamental process of redistributing upstream plasma kinetic energy into other degrees of freedom-particularly electron thermalization. Direct in situ measurements of nonstationary shock dynamics have not been reported. Thus, the model that best describes this process has remained unknown. Here, we present direct evidence demonstrating that the transition to nonstationarity is associated with electron-scale field structures inside the shock ramp.

Observations of discrete harmonics emerging from equatorial noise.

A number of modes of oscillations of particles and fields can exist in space plasmas. Since the early 1970s, space missions have observed noise-like plasma waves near the geomagnetic equator known as 'equatorial noise'. Several theories were suggested, but clear observational evidence supported by realistic modelling has not been provided. Here we report on observations by the Cluster mission that clearly show the highly structured and periodic pattern of these waves. Very narrow-banded emissions at frequencies corresponding to exact multiples of the proton gyrofrequency (frequency of gyration around the field line) from the 17th up to the 30th harmonic are observed, indicating that these waves are generated by the proton distributions. Simultaneously with these coherent periodic structures in waves, the Cluster spacecraft observes 'ring' distributions of protons in velocity space that provide the free energy for the waves. Calculated wave growth based on ion distributions shows a very similar pattern to the observations.

Generalized multiscale radial basis function networks.

A novel modelling framework is proposed for constructing parsimonious and flexible multiscale radial basis function networks (RBF). Unlike a conventional standard single scale RBF network, where all the basis functions have a common kernel width, the new network structure adopts multiscale Gaussian functions as the bases, where each selected centre has multiple kernel widths, to provide more flexible representations with better generalization properties for general nonlinear dynamical systems. As a direct extension of the traditional single scale Gaussian networks, the new multiscale network is easy to implement and is quick to learn using standard learning algorithms. A k-means clustering algorithm and an improved orthogonal least squares (OLS) algorithm are used to determine the unknown parameters in the network model including the centres and widths of the basis functions, and the weights between the basis functions. It is demonstrated that the new network can lead to a parsimonious model with much better generalization property compared with the traditional single width RBF networks.