Dr. J. R. Johnson is a Principal Research Physicist and Head of Space
Physics at Princeton Plasma Physics Laboratory. He received his
Ph.D. degree from Massachusetts
Institute of Technology in 1992. He has published more than 30
papers on theoretical plasma physics.
Dr. Johnson's area of expertise is in theoretical plasma physics with
emphasis on applications to space plasmas. His past work includes
areas of mode conversion associated with the development of a
kinetic-fluid model, kinetic Alfven waves and associated plasma
transport, linear mode conversion of Alfven ion cyclotron waves in a
multi-ion species plasma, global mirror modes, plasma stability
analysis, nonlinear plasma waves, and nonlinear dynamics. In
particular, he has shown that kinetic Alfven waves could be a
significant source for the observed plasma transport across the
interface between the solar wind and magnetosphere. He has also shown
that Alfven ion cyclotron waves generated in the equatorial region of
the magnetosphere could propagate earthward along magnetic field lines
and tunnel through the ``stop gaps'' associated with the minority ion
species. He has demonstrated a detailed mode conversion analysis that
substantial coupling between the propagating modes occurs near the
minority ion resonances and that substantial wave power is both
transmitted and absorbed. Both the transmitted and absorbed wave
power can contribute substantially to energization and outflow of
oxygen ions from the ionosphere. He has demonstrated that kinetic
Alfven waves at the magnetopause could be a significant source
for the observed plasma transport across the interface between the
solar wind and magnetosphere. He worked closely with Simon Wing of
Johns Hopkins University/Applied Physics Laboratory to
interpret remote observations of the plasma sheet to better
understand the transport mechanisms. In particular, he has helped to
establish constraints on dawn-dusk asymmetries and entropy
for quiescent and active-time magnetosphere transport under different
solar
wind conditions. Recently, he also developed
cumulant-based methods for analysis of nonlinear magnetospheric
dynamics and detecting high-order statistical dependencies.
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