Nature of project: data analysis, software
Available to students on full-time physics degree schemes or joint students.
A huge dataset from the Atmospheric Imaging Assembly (AIA) and Helioseismic Magnetic Imager (HMI) instrument aboard the Solar Dynamic Observatory (SDO) has been processed to provide maps of the low coronal temperature, emission measure (EM ~=mass) and photospheric magnetic field (B). The result of this effort is a set of ~100,000 maps of coronal temperature, EM and B, approximately one per half-hour over 6 years.
The project involves analysis of this rich source of information. The student must:
- access the data (available locally at Aberystwyth University), and open the files in IDL or similar
- identify and isolate individual active regions in the data
- record and reduce the physical characteristics of the active regions (record mean, standard deviation, min, max etc in each physical value)
- analyse the changes in active region characteristics over time
The output of the project will be a detailed study of several dozen active regions, reporting on their time evolution and any other findings arising from the analysis.
A successful project will develop beyond the above in one/some of the following directions:
For best marks, the student can examine and seek relationships between active region characteristics with various parameters including active region size, age, latitude, mean magnetic field etc.
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: For a 4th year project, the analysis and discussion is expected to be considerably more detailed. Interpretation of the results in the context of theories of coronal heating is desirable for a 4th year project.
Please speak to Huw Morgan (hum2) if you consider doing this project.
Initial literature for students:
Access to data is easy (stored locally). Project is software-intensive. Student must be able to write code in IDL or similar. Supervisor can provide help with IDL (but not Python sorry).
|milestone||to be completed by|
|Ideas on how to reduce data||end of October|
|Able to open data in IDL, and identify/isolate active regions||Christmas|
|Full working version of software, application to test cases||end of February|
|Full analysis of many active regions, appropriate visualisation of reduced results||Easter|