NFYK12009U Astronomical Data Processing

Volume 2022/2023

MSc Programme in Physics


Standard processing techniques of generic astronomical imaging and spectroscopic data, and basic astrophysical measurements.

Fundamental instructions in processing of astronomical imaging and spectroscopic data, the nature and properties of generic UV-optical imaging and spectroscopic detectors (IR is addressed as time permits) relevant for data processing, and in signal-to-noise computations, noise‐contributions, error-propagations, and photon statistics.

For the spectroscopic data there will be a focus on long-slit spectroscopy, thereby providing a background for Echelle and Integral Field Spectroscopic processing. Introduction to the fundamental issues related to the planning of data acquisition at the telescope.

The purpose is to enable the student to single‐handedly process standard imaging and long-slit spectral data in future research projects. These competences lay the background for potential future expansion of the competences to more advanced and complex data processing techniques by the student.

Learning Outcome

To pass this course the student must:

  • Be able to process both imaging and long‐slit spectral data well enough to allow the student to extract reasonable basic measurements from the data
  • Demonstrate the ability to critically assess the data quality, error sources, the necessary processing and calibration tasks needed at each processing steps, and the goodness/quality of the data processing performed.
  • Perform the necessary basic data processing of raw astronomical UV-optical imaging and spectral data, as presented as part of the course exercises/projects.
  • Perform the necessary calibration of the scientific imaging and spectral data
  • Perform basic analysis of the data such as 2‐dimensional photometry, and 1-dimensional spectroscopic measurements of line equivalent widths, velocities, line flux, and continuum shifting. 
  • Calculate signal‐to‐noise ratios, generate error-propagated imaging data and spectra, estimate exposure times and plan the basic data taking details for new observations.


Upon satisfactory completion of this course the student will be able to:

  • account for the necessary steps needed to process and calibrate raw astronomical UV-optical imaging and spectral data, as obtained from the telescopes.
  • Explain, justify, and assess each step in the data reduction process and how the data and their quality are evaluated.
  • account for and critically assess the methods used to perform basic analyses and measurements, including accounting for errors, on the data.
  • explain and justify how to calculate the signal-to-noise ratios, estimate exposure times, and account for the important considerations related to obtaining new data at the telescope


This course will provide the students with a basic background on (a) the important aspects of the processing of UV-optical astronomical imaging and (long-slit) spectroscopic data, (b) how to critically assess and evaluate the data quality and sources of error, and on (c) planning and preparing new observations. In addition, the course will provide the students with software tools and techniques on data processing and basic analysis. In concert, these competences and tools can be applied during further studies within astrophysics, for example in a M.Sc. and/or Ph. D project.

These competences also lay the background for further expansion of the competences to more advanced and complex data processing techniques.

See Absalon for final course material. The following is an example of expected course literature.

Lecture notes, exercise sheets and the latest edition of

Steve B. Howell: Handbook of CCD Astronomy (Cambridge Observing Handbooks for Research Astronomers). See the Absalon pages for the ISBN no.


Students who have not had other astronomy courses prior to this course should let the instructors know before course start.
It is strongly recommended that the student has a background equivalent to that covered by the courses ‘Statistical Physics’ and ‘Electromagnetism’ (EM1, EM2). Students who have good reasons for taking this course, but do not fulfill this requirement should contact the course instructors prior to registering for this course. Although not a mandatory requirement, it will be useful for the student to have a background equivalent to that covered by the course ‘Optical Physics and Laser’.

It is strongly recommended to have a basic knowledge of Python programming, e.g. acquired through the Dat-F course or similar basic course in Python programming.

A brief introduction to command-line communication with Unix is given, but students will benefit from having prior experience with command-line input, programming in simple scripts, and with interacting with program software, since an introduction to use of computers is not given.

Academic qualifications equivalent to a BSc degree is recommended.
Lectures, in-class discussions, hands‐on computer projects
Students are required to bring their own laptops. Installation of Python and further installation of various Python modules will be needed.

The following terminal software is necessary:
Windows: the latest version of Xming (Windows 7 or earlier) or MobaXterm (for Windows 10) software.
Linux: the X11 environment is standard and runs automatically.
MacIntosh/MACs: Starting with operating system OS 10.5 the X11 environment is needed. This can be downloaded for free from http:/​/​​
For operating systems Leopard and Lion the X11 environment is a part of OS X.

This course is highly recommended for Master students in Astronomy and Astrophysics. Students are advised to take this course as one of the very first courses during the Master’s studies.
  • Category
  • Hours
  • Lectures
  • 24
  • Preparation
  • 60
  • Project work
  • 122
  • Total
  • 206
Continuous feedback during the course
Peer feedback (Students give each other feedback)
7,5 ECTS
Type of assessment
Written assignment, during course
Type of assessment details
To pass the course the student must:

- submit a report (minimum of 15 pages) on the data processing of both imaging and spectral data performed in the course. More specifically it should address:

All the necessary steps needed and the reasons for them and how the quality of each processing step is evaluated. The report needs to be approved by the instructors. To be approved, the report itself should be of a sufficient quality that the student or others could use it as a compendium. The report should include a sufficient amount of the material covered in the course for the reader(at the level of a starting Master’s student) to understand with ease the procedures and techniques and why they are performed.
Exam registration requirements

The student must be present for the majority of the classes, equivalent to 80% or more of the 88 class-hours of the 8 weeks duration of the course. The class hours include lectures, discussions, and project work. Attendance will be taken.
Also, the student should actively participate in all activities in class, including the hands-on exercises, the discussions in class, participate in the peer-review activity both outside of and in class. The student should work with her/his group, do 1/3 of the work for both the midterm and the final report, and should - joint with the group - submit the course report for review.

All aids allowed
Marking scale
passed/not passed
Censorship form
No external censorship
More internal examiners

Same as ordinary exam. The report must be re-submitted and approved by the instructors.
The requirements for participation cannot be ignored. If the level of attendance and participation does not meet the requirements, the student must follow the course again the following year.

Criteria for exam assesment

See learning outcome.