Computer Simulations in Solar System Physics Mats Holmström Swedish Institute of Space Physics (IRF) Forskarskolan i rymdteknik Göteborg 12 September 2005.

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Presentation transcript:

Computer Simulations in Solar System Physics Mats Holmström Swedish Institute of Space Physics (IRF) Forskarskolan i rymdteknik Göteborg 12 September 2005

Solar System Physics and Space Technology SSPT Scientific Goals ● How does the interplanetary medium affect and shape the bodies in the inner solar system? ● What plasma physical processes determine the structure of the interaction regions? ● How do the solar system dust population evolve and interact with planetary bodies? Study the environment and the solar wind interaction as well as the evolution and dynamics of solar system objects with focus on the inner planets, moons, asteroids, comets and dust. Development of scientific instrumentation for satellite-based measurements in support of space exploration.

Overview ● The science we do ● The simulations we do. Some examples: 1. Ion precipitation at Mercury 2. Instrument design 3. Energetic neutral atom (ENA) production at Mars 4. ENA production at the Moon 5. Solar wind charge exchange X-rays at Mars 6. Magnetohydrodynamics and particle simulations

Solar Wind-Solar System Objects Interaction [Kivelson and Russel]

Detectors of... ●... Ions, and ●... Energetic Neutral Atoms (ENAs) Direction, flux, mass, energy/velocity

Current and Future Missions

Simulation Needs 1) Proposals and Mission planning What is the sensor environment? What can we detect? What science can be done? Example: Sputtered neutral atoms at Mercury 2) Instrument design Optimization (performance-weight-power) Example: Neutral atom detector for Mercury and the moon 3) Data analysis Extract as much information as possible Example: ENA production at Mars

Ion Trajectories Example 1: Sputtered neutral atoms at Mercury

Ion Precipitation Map Example 1: Sputtered neutral atoms at Mercury

The three columns correspond to, from left to right, sputtering fromsolar wind protons, from magnetotail accelerated protons, and fromsodium photoions. The top row show maps of the ion precipitation on Mercury's surface[1/(cm^2 s)]. The subsolar point has zero longitude and latitude. The bottom row shows the fluxes of sputtered sodium atoms in theenergy range eV as seen from a height of 400 km over areas of large precipitation with a 160 degree field of view. The unit is [1/(cm^2 sr s) Example 1: Sputtered neutral atoms at Mercury

Simulation Details ● C++ ● RKSUITE for the trajectory computation Adaptive Runge-Kutta ODE solver ● Parallelize the trajectory computations ● MPI for communication Example 1: Sputtered neutral atoms at Mercury

Designing a Neutral Atom Imager ● For missions to the moon and to Mercury ● Particle trajectories in the sensor by an MPI application (A. Fedorov, CESR, France) ● Optimize weight (dimensions) and mass resolution Example 2: Neutral atom detector for Mercury and moon

Electric Potential Example 2: Neutral atom detector for Mercury and moon

Particle Trajectories Example 2: Neutral atom detector for Mercury and moon

Mass Resolution Example 2: Neutral atom detector for Mercury and moon

ENA Production at Mars ● Generated by – Solar wind-exosphere charge exchange – Atmospheric sputtering and backscatter (of precipitating ions and ENAs) – Planetary ions-exosphere charge exchange – Solar wind-Phobos gas torus charge exchange ● Three-dimensional emissions Example 3: ENA Production at Mars

[Futaana, 2004] ENA imager Field of View at Mars Example 3: ENA Production at Mars

Different ENA production models Empirical Hybrid MHD Sensitive to  Flow model  Exosphere model Example 3: ENA Production at Mars Effects of parameter changes

Interpreting ENA images at Mars  ENA flux = Line of sight integration (ion flux and neutral density)  Inverse problem (forward modeling) Example 3: ENA Production at Mars

ENA Production at the moon  Generated by sputtering from  Micro meteoroid impact vaporization  Photon desorption  Precipitating  Magnetospheric ions  Solar wind ions  Significant contribution only from precipitating solar wind ions  Two-dimensional emissions Example 4: ENA Production at the Moon

[Futaana, 2004] Example 4: ENA Production at the Moon

What can we learn from moon ENA images? ● Regolith composition ● Size and location of magnetic anomalies ● Space weathering effects on the regolith Solar wind flow around an anomaly [Harnett and Winglee] [Futaana, 2004] Example 4: ENA Production at the Moon

ENA imaging of shaded areas ● Kinetic effects => solar wind ion precipitation in shaded areas [Clementine] Example 4: ENA Production at the Moon

Solar Wind Charge Exchange X-rays ObservationSimulations Example 5: SWCX X-rays at Mars

The FLASH Code ● Magnetohydrodynamic (MHD) solver that can include particles ● From University of Chicago ● General compressible flow solver ● Adaptive (Paramesh) and parallel (MPI) ● Open source, Fortran 90 ● Add boundary conditions and sources for solar system objects - solar wind simulations (Mercury, Venus, earth, moon, Mars,...) ● First investigations: – A comet (MHD with a photoion source) – Mars' exosphere (particles) Example 6: Magnetohydrodynamics and particle simulations

Simulations is an integral part of our science