Duration
20h Th, 10h Pr
Number of credits
| Master in space sciences, research focus | 4 crédits | |||
| Master in space sciences, professional focus | 4 crédits |
Lecturer
Language(s) of instruction
English language
Organisation and examination
Teaching in the second semester
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
The course is a practical introduction to gravitational wave data analysis and covers the following signal processing techniques:
- Time series analysis in time- and frequency- domains
- Spectral filtering for instrumental noise reduction
- Matched filtering for searches of compact binary coalescences
- Excess power searches with minimal assumptions about signal properties
Learning outcomes of the learning unit
Ability to understand basic signal processing techniques currently used in the gravitational wave communit, explore dataset with a priori unknown characteristics, and other useful tools for data scientists.
Prerequisite knowledge and skills
Prerequisite: The student is expected to be familiar with the Python programming language and its most popular scientific libraries (Numpy / Scipy / Matplotlib / Astropy) as covered by "Programming techniques, numerical methods and machine learning" (SPAT0002-1).
Recommended: The student is also advised to enroll in the course "Gravitational waves" (SPAT0075-1) covering principles of detection & sources of gravitational waves.
Planned learning activities and teaching methods
This course is based on interactive Jupyter notebooks introduced in the beginning of the session.
Course website
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face course
Additional information:
Face-to-face lectures 2h/week, starting from the 2nd semester.
Course materials and recommended or required readings
Python for Signal Processing, José Unpingco
Written work / report
Work placement(s)
Organisational remarks and main changes to the course
Computer available in the classroom.
If you wish to use your own laptop, preinstallation of software mandatory. Please get in touch with the lecturer prior to the start of the course.
Contacts
Maxime Fays (maxime.fays@uliege.be) Room 4.43 Bât. B5A Inter. fondamentales en physique et astrophysique (IFPA) Quartier Agora allée du six Août 19 4000 Liège 1 Belgique Phone: +32 4 3663643