[English]

What's hot and what's not: a multi-wavelength study of the Sun

(supervisor: Huw Morgan)

Nature of project: data analysis, software

Available to full-time physicists or joint students.

Project description and methodology

The Atmospheric Imaging Assembly (AIA) aboard the Solar Dynamic Observatory (SDO) views the chromosphere and low corona at several narrow bandwidths in the Extreme UltraViolet (EUV). Each bandwidth is dominated by emission from a highly-ionised emission line, therefore comparing the intensity of signal in the different images can give a measure of temperature. The quiescent solar disk viewed in EUV is a patchwork of different objects: active regions, filaments and filament channels, coronal holes and quiet Sun. Also observed by AIA are smaller-scale dynamic events such as spicules, filament eruptions and flares. The project involves downloading an appropriate set of AIA data, using all suitable channels, and identifying several large-scale quiescent features. The students can then make qualitative and quantitative estimates of temperature of different features using the known temperature response of each wavelength channel.

A successful project will develop beyond the above in one/some of the following directions:
Although the project is aimed at measuring large-scale quiescent features, if the students do find interesting dynamic events I would encourage their study (for example, measuring the changing temperature during a flare would be interesting). The student is expected to use initiative and imagination in presenting the results in the best possible way using the plotting and imaging capabilities of IDL. This is an interesting study in itself, but I will also like the students to attempt to answer an advanced difficult question using the temperature diagnosis: Are dark regions in EUV solar images filaments or coronal holes? It is very difficult to distinguish between them by eye alone.

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 4th year student will be expected to go into far more detail regarding the question of distinguishing filaments from coronal holes. To do this successfully, data from a magnetometer (HMI/SDO for example) may be used with the EUV observations of AIA. This will require some analysis software to be written.

Initial literature for students:

  1. Global conditions of the solar corona 2010-1017, Morgan, Science Advances 3 (2017) e1602056
  2. Aschwanden et al, Solar Physics 283 (2013) 5, Automated Temperature and Emission Measure...
  3. Differential emission measures from the regularized inversion of Hinode and SDO data, Hannah & Kontar Astronomy&Astrophysics 539, A146 2012
  4. IDL help at: (i) IDL guide book, (ii) Help document written by Morgan, (iii) http://www.idlcoyote.com/

Novelty, degree of difficulty and amount of assistance required

The data is publicly available and it is easy to use the IDL software provided by the instrument team to read and calibrate the data. The challenge then lies in learning to manipulate the 2D arrays, and displaying using IDL. I will provide initial guidance (or a written list) on some straightforward ways of displaying the data, and on how to find help online. There are also IDL guide books in the library. Making qualitative interpretation of the data in terms of temperature is straightforward given some basic understanding of the temperature responses of the channels. Making a quantiative estimate is more advanced, and will require thought and a few dozen lines of IDL software. The last question re. distinguishing filaments and coronal holes is an advanced research topic which would be suitable for a 3 year PhD course, but the students can attempt to make sensible conclusions if they have succeeded in making quantatitive estimates of temperature.

Project milestones and deliverables (including timescale)

milestoneto be completed by
download data, load it in IDL, familiarisation with terminologyend of October
range of imaginative IDL plotsend of November
quantitative temperature estimatesmid-March
comparison of various features and their temperaturesEaster