CMG--Particle Filtering for Time-Dependent Tomographic Analysis of the Solar Atmosphere

点击翻译按钮获取中文摘要

Knowledge of the solar corona's 3D distribution of density and temperature is needed to model the propagation of solar disturbances from the Sun's surface out to the near-Earth environment, where effects on space-weather may be observed, experienced and, ultimately, mitigated. Current and next generation Sun observing spacecraft are providing us with unprecedented access to, and challenging amounts of, data regarding the three dimensional and time varying structure of the corona. Dynamic solar rotational tomography (SRT) is the approach that this collaboration of geoscientists and statisticians from the University of Illinois (Urbana-Champaign) will develop under a NSF interdisciplinary program, Collaborations in Mathematical Geosciences. Their approach seeks the development of Monte Carlo filtering algorithms optimized for non-linear and non-Gaussian probability distribution functions. To be capable of handling the large data sets associated with these tomographic problems requires progress in statistical estimation theory as well as the design of efficient computational algorithms. As well as benefiting the broader geophysical and statistical communities, graduate and undergraduate research and training to take between the two disciplinary areas provides an important educational incentive for the work. Tomographic particle filtering techniques, such as those proposed here, may have additional applications of interest to other fields in the geosciences, as well as in engineering and biomedical imaging.