Fast Magnetosonic Waves Observed by Van Allen Probes: Testing Local Wave Excitation Mechanism

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Abstract

Linear Vlasov theory and particle-in-cell (PIC) simulations for electromagnetic fluctuations in a homogeneous, magnetized, and collisionless plasma are used to investigate a fast magnetosonic wave event observed by the Van Allen Probes. The fluctuating magnetic field observed exhibits a series of spectral peaks at harmonics of the proton cyclotron frequency Ω_p and has a dominant compressional component, which can be classified as fast magnetosonic waves. Furthermore, the simultaneously observed proton phase space density exhibits positive slopes in the perpendicular velocity space, ∂f_p/∂v_⊥ > 0, which can be a source for these waves. Linear theory analyses and PIC simulations use plasma and field parameters measured in situ except that the modeled proton distribution is modified to have larger ∂f_p/∂v_⊥ under the assumption that the observed distribution corresponds to a marginally stable state when the distribution has already been scattered by the excited waves. The results show that the positive slope is the source of the proton cyclotron harmonic waves at propagation quasi-perpendicular to the background magnetic field, and as a result of interactions with the excited waves the evolving proton distribution progresses approximately toward the observed distribution.

Description

Includes supplementary material

Keywords

Radiation belts, Magnetosphere, Electromagnetic measurements, Magnetic fields

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The RBSPICE instrument was supported by the Johns Hopkins University Applied Physics Laboratory (JHU/APL) subcontract 937836 to the New Jersey Institute of Technology (NJIT) under NASA prime contract NAS5-01072. The EMFISIS instrument was supported on JHU/APL contract 921647 under NASA prime contract NAS5-01072. The ECT suite was supported by RBSP-ECT funding provided by JHU/APL contract 967399 under NASA’s prime contract NAS5-01072. Computational resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center. This work was supported by NASA prime contract NAS5-01072 through a subcontract from NJIT, NASA grant NNX16AM98G, and NSF grant AGS-1602388. Work at the University of Texas at Dallas was supported by NASA grant NNX17AI52G and NSF grant AGS-1705079.

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CC BY-NC-ND 4.0 (Attribution-NonCommercial-NoDerivatives), ©2018 The Authors

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