This course introduces principles and techniques for visualizing complex scientific models and 3D numerical simulations, particularly in computational astrophysics. It focuses on extracting and clearly communicating information from large, multi-variable datasets using methods such as feature extraction, color and opacity design, slicing, isosurfaces, and volumetric rendering. The course also briefly explores immersive visualization, including virtual reality, as an extension of core visualization principles for enhanced spatial understanding and analysis.
The course is intended for doctoral students with a strong background in Astrophysics, but can be attended by PhD students in nearly any discipline of Physics which are interested in visualization of large scientific datasets (most likely three-dimensional datasets).
- Teacher: Aloy Toras, Miguel Angel
- Teacher: ORLANDO, SALVATORE