A machine-learning-based electron density (MLED) model in the inner magnetosphere

Plasma density is an important factor in determining wave-particle interactions in the magnetosphere.We develop a machine-learning-based electron density(MLED)model in the inner magnetosphere using electron density data from Van Allen Probes between September 25,2012 and August 30,2019.This MLED model is a physics-based nonlinear network that employs fundamental physical principles to describe variations of electron density.It predicts the plasmapause location under different geomagnetic conditions,and models separately the electron densities of the plasmasphere and of the trough.We train the model using gradient descent and backpropagation algorithms,which are widely used to deal effectively with nonlinear relationships among physical quantities in space plasma environments.The model gives explicit expressions with few parameters and describes the associations of electron density with geomagnetic activity,solar cycle,and seasonal effects.Under various geomagnetic conditions,the electron densities calculated by this model agree well with empirical observations and provide a good description of plasmapause movement.This MLED model,which can be easily incorporated into previously developed radiation belt models,promises to be very helpful in modeling and improving forecasting of radiation belt electron dynamics.

Array gain of fourth-order cumulants beamforming under typical probability density background

The fourth-order cumulant of zero mean Gaussian distribution noise always equals to zero theoretically. In practice the probability density of noise and reverberation is the key problem to performance of the fourth-order cumulant beamforming technique. In this paper, the array gain functions of the fourth-order cumulant beamforming are deducted considering the instantaneous amplitude distribution of the ambient sea noise and bottom reverberation respectively. And the relationships are determined between array gain and the factors including the number of the array elements, the fourth-order and second-order statistical properties of the noise and reverberation, and the input signal-to-noise ratio. It is also verified that there is a critical signal-to-interference ratio and the fourth-order cumulant beamforming can obtain higher gain and resolution than the conventional beamforming method when the ratio is larger than it. The results of experiment data processing demonstrate that the gain and the resolution of the fourth-order cumulant beamforming coincide with the theoretic.