2023-2024 / SPAT0085-1

Analysis mehtods in gravitational-wave astronomy


20h Th, 10h Pr

Number of credits

 Master in space sciences (120 ECTS)4 crédits 


Maxime Fays

Language(s) of instruction

English language

Organisation and examination

Teaching in the second semester


Schedule online

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.

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. 


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

Association of one or more MOOCs