Nature of project: experimental, data analysis
Available to students on full-time physics degree schemes or joint students.
In Extreme UltraViolet (EUV) images of hot (>1.5MK) emission lines from the solar corona, cooler structures such as coronal holes and filaments appear dark. The Atmospheric Imaging Assembly (AIA) aboard the Solar Dynamic Observatory (SDO) views the chromosphere and low corona at several narrow bandwidths in the EUV. Each bandwidth is dominated by emission from a highly-ionised emission line, each formed at a range of temperatures. The solar disk viewed in EUV is a patchwork of different objects: active regions, filaments and filament channels, coronal holes and quiet Sun.
The task for this project is to develop software that will:
- load an AIA image, or a set of AIA images at different wavelengths
- apply image processing/segmentation to separate and identify different large-scale regions (coronal holes and filaments in particular)
- catalogue the various features, saving out a reduced set of data for each image (e.g. date, type of feature, geometry, area)
A successful project will develop beyond the above in one/some of the following directions:
The successful project will apply this procedure to a long time period (at least a solar rotation), and show preliminary findings related to the time-evolution of filaments/coronal holes. For example: What is their lifetime? Do they change in area?
When considering where to take your project, please bear in mind the time available. It is preferable to do fewer things well than to try many and not get conclusive results on any of them. However, sometimes it is useful to have a couple of strands of investigation in parallel to work on in case delays occur.
Additional scope or challenge if taken as a Year-4 project: A deeper problem is to distinguish filament channels from coronal holes: both are large, dark, cool regions. For a 4th year project, you can use solar magnetogram data to distinguish coronal holes (largely unipolar) from filaments (mixed polarity).
Please speak to Huw Morgan (hum2) if you consider doing this project.
Initial literature for students:
Work is quite novel - a successful cataloging software for filaments would be very useful to the solar community. Work is software-intensive, need to develop code. Student must be proficient with IDL and/or Python. Supervisor can help a lot with IDL, but can't help with Python.
|milestone||to be completed by|
|Ability to open AIA images in IDL||end of October|
|Ideas on image processing/segmentation, with basic code||Christmas|
|Basic working set of software||end of February|
|Analysis of long time period, working software package||Easter|