NFYK12009U Astronomical Data Processing
MSc Programme in Physics
Standard processing techniques of generic astronomical imaging and spectroscopic data, and basic astrophysical measurements in photometry and spectroscopy.
Fundamental instructions in processing of astronomical imaging and spectroscopic data, the nature and properties of generic UV-optical imaging and spectroscopic detectors (Infrared imaging 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.
Skills
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.
Knowledge
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
Competences
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.
http://www.cambridge.org/gb/knowledge/isbn/item1157662/?site_locale=en_GB
It is a requirement to have a basic knowledge of Python programming, e.g. acquired through the Dat-F course or similar basic course in Python programming, since no introduction to Python programming will be given.
Students will benefit from having prior experience with command-line input, programming in simple scripts, and with interacting with program software.
Academic qualifications equivalent to a BSc degree is recommended.
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
- Credit
- 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 their 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.- Aid
- All aids allowed
- Marking scale
- passed/not passed
- Censorship form
- No external censorship
Several internal examiners
- Re-exam
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.
Course information
- Language
- English
- Course code
- NFYK12009U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 1
- Schedule
- A
- Course capacity
- No limitation – unless you register in the late-registration period (BSc and MSc) or as a credit or single subject student.
Study board
- Study Board of Physics, Chemistry and Nanoscience
Contracting department
- The Niels Bohr Institute
Contracting faculty
- Faculty of Science
Course Coordinators
- Lise Bech Christensen (8-706d676c766d77784472666d326f7932686f)
Lecturers
Lise Christensen
Christa Gall