Plasma transport and magnetic flux circulation in Saturn's magnetosphere

Thesis (Ph.D.) University of Alaska Fairbanks, 2021The magnetospheres of outer planets are very different than the terrestrial magnetosphere. The magnetosphere of Saturn is rapidly rotating, and has its own plasma source. Enceladus located around 4Rs is the main source of plasma. The strong magnetic field of Saturn's magnetosphere picks up the plasma which experiences a strong centrifugal force in the non-inertial reference frame. The plasma produced in the inner magnetosphere has to be transported radially outward and lost to the solar wind. The transport of plasma in Saturn's magnetosphere is not fully understood. It is believed that transport is centrifugally-driven, occurring via flux tube interchange motions in the inner magnetosphere and via plasmoid expulsion in the magnetotail due to reconnection. It has been found that these mechanisms are not sufficient to explain the transport. We tried to determine different possible transport mechanisms that could exist in the outer planetary magnetosphere. Ma et al. (2019a) showed the low-specific entropy plasma with a narrow distribution in Saturn's inner magnetosphere and suggests a significant nonadiabatic cooling process during the inward motion while high specific entropy suggests the nonadiabatic heating during the outward transport. We have estimated the outward plasma transport rate about 55 kg s⁻¹. The calculation of magnetic flux transport and analysis of magnetic field data indicates that plasma transport in the Saturn magnetosphere could be dominated by small scale magnetic reconnection.1. Introduction -- 2. Quantifying mass and magnetic flux transport in Saturn's magnetosphere -- 3. On the nature of turbulent heating and radial transport in Saturn's magnetosphere -- 4. The study of electron fluctuation in Saturn's magnetosphere: implication for radial transport -- 5. Summary and future work -- Appendix -- Bibliography

Comparison Between Fluid Simulation with Test Particles and 1 Hybrid Simulation for the Kelvin-Helmholtz Instability

A quantitative investigation of plasma transport rate via the Kelvin‐Helmholtz (KH) instability can improve our understanding of solar‐wind‐magnetosphere coupling processes. Simulation studies provide a broad range of transport rates by using different measurements based on different initial conditions and under different plasma descriptions, which makes cross literature comparison difficult. In this study, the KH instability under similar initial and boundary conditions (i.e., applicable to the Earth\u27s magnetopause environment) is simulated by Hall magnetohydrodynamics with test particles and hybrid simulations. Both simulations give similar particle mixing rates. However, plasma is mainly transported through a few big magnetic islands caused by KH‐driven reconnection in the fluid simulation, while magnetic islands in the hybrid simulation are small and patchy. Anisotropic temperature can be generated in the nonlinear stage of the KH instability, in which specific entropy and magnetic moment are not conserved. This can have an important consequence on the development of secondary processes within the KH instability as temperature asymmetry can provide free energy for wave growth. Thus, the double‐adiabatic theory is not applicable and a more sophisticated equation of state is desired to resolve mesoscale process (e.g., KH instability) for a better understanding of the multi‐scale coupling process

Single lesion multibacillary leprosy, a treatment enigma: a case report

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Information Horizon of Solar Active Regions

Information theory is used to characterize the solar active region periodicities and memories from the Carrington map images 1974–2021. The active regions typically evolve and move from one map to the next. In order to track these active region structures in sequences of images, an innovative method based on information theory is developed. Image entropy provides a measure of the organization of structures in the images. The entropy can also be used as a filter to identify structures and partition the active regions, which are then registered for each image. The partitions are used to compute the mutual information and measure the information flow from the active regions from one image to the next. Finally, conditional mutual information is used to give a measure of the information flow from one image to another given the third image. The results suggest the following: (1) there is a long-term memory of two cycles or more; (2) the coherence time of the active regions is ∼2 yr; and (3) the average active region structure scale size carrying the most information is approximately 118 × 10 ^3 –236 × 10 ^3 Mm ^2 . The study has implications to the short- and long-term predictability of active regions and sunspots as well as the nature of flux transport at the Sun. Finally, our innovative method can be similarly applied to stellar data to determine the dynamics of the active regions of stars