No abstract

The nonlinear dynamical equation for the propagation of kinetic Alfvén waves has been derived in two dimensions using the two-fluid model of the plasma and by taking the adiabatic response for the background density in the presence of nonlinear electron heating and the ponderomotive force. Dynamically evolving filamentary structures are predicted. The effect of these filaments on solar wind turbulence and coronal heating has also been pointed out.

[1] This paper presents the model equations governing the mutual nonlinear interaction between two small but finite amplitude kinetic Alfven waves using two fluid models when the b of the plasma is less than unity (for high-b cases one has to use the Boltzmann equation). The source of nonlinearity is the nonlinear electron heating and ponderomotive force-driven nonlinear modification in the background density. The solutions of these model equations have been obtained by using analytical and numerical methods to study the effect of their mutual interaction on filament (hot spot) formation. It is concluded that the threshold field required for filament formation and their critical size is significantly affected by the mutual nonlinear interaction. Its effect on solar wind turbulence and coronal heating is also pointed out. Citation: Shukla, A., and R. P. Sharma, Mutual nonlinear interaction between two kinetic Alfven waves and its effect on filamentation: Application to solar wind and coronal heating,

This paper presents an investigation of the growth of a Gaussian perturbation on a uniform plane wave front of an Alfvén wave (AW). The effect of the nonlinear coupling between the main AW and the perturbation has been studied. The dynamical equation for the field of the perturbation has been established and its semianalytical solution has been obtained in low (β≪me/mi) and high (β≫me/mi) β cases (β≪1). The critical field of the perturbation has been evaluated for the given size of the perturbation for its filamentation process (hot spot formation). Nonlinear evolution of the perturbation into filamentary structures and its dependence on various parameters of the solar wind and corona has been investigated in detail.

In Wireless Body Area Networks (WBAN) the energy consumption is dominated by sensing and communication. Previous Compressed Sensing (CS) based solutions to EEG tele-monitoring over WBAN's could only reduce the communication cost. In this work, we propose a matrix completion based formulation that can also reduce the energy consumption for sensing. We test our method with state-of-the-art CS based techniques and find that the reconstruction accuracy from our method is significantly better and that too at considerably less energy consumption. Our method is also tested for post-reconstruction signal classification where it outperforms previous CS based techniques. At the heart of the system is an Analog to Information Converter (AIC) implemented in 65nm CMOS technology. The pseudorandom clock generator enables random under-sampling and subsequent conversion by the 12-bit Successive Approximation Register Analog to Digital Converter (SAR ADC). AIC achieves a sample rate of 0.5 KS/s, an ENOB 9.54 bits, and consumes 108 nW from 1 V power supply.