Venue: Emmy Noether Seminar Room

Class timings: 2:30 PM to 4:30 PM, Wednesdays and 9:30 AM to 11:30 AM, Fridays

First meeting: 18th January 2023

Course Description: 

This course aims to expose students to different aspects of gravitational-wave (GW) physics and astronomy. We will start from the pedagogical level and end with an exploration of current research. Tutorials will play an integral part in the course. Apart from textbooks, we will draw material from reviews and research papers. 

  • Theory of GWs: Expansion of the metric around flat space, transverse-traceless gauge, energy of GWs, GW propagation in curved spacetime, generation of GWs in linearised theory. 
  • Astrophysical sources of GWs: Binary star evolution, supernovae, spinning neutron stars, formation and merger of compact binaries, stochastic GW background, electromagnetic counterparts of mergers, gravitational lensing of GWs, modelling of GW sources.
  • Detection of GWs: Interaction of GWs with an elastic body, resonant bar detectors, Interaction of GWs with test masses, equation of geodesic deviation, interferometric detectors.
  • GW data analysis: Random processes, power spectrum, Gaussian noise, Bayes theorem, matched filter, template banks, parameter estimation, model selection, stochastic sampling methods, time-frequency detection methods.
  • GW astronomy: Estimating merger rates and population properties of compact binaries using GW observations, tests of GR, inferring neutron star equation of state, estimation of cosmological parameters.


  • Bernard F. Schutz, A First Course in General Relativity, Cambridge (2009). 
  • Misner, Thorne, Wheeler: Gravitation, Wheeler (2017). 
  • Michele Maggiore, Gravitational Waves: Vol 1 (Theory and Experiments), Oxford (2008). 
  • Peter R Saulson, Fundamentals of Interferometric Gravitational Wave Detectors, World Scientific (2017). 
  • Jolien Creighton and Warren G. Anderson, Gravitational-Wave Physics & Astronomy, Wiley-VCH (2011). 
  • Nils Andersson, Gravitational-Wave Astronomy: Exploring the Dark Side of the Universe, Oxford (2019). 


  • General Relativity. 
  • Familiarity with a programming language such as python or Mathematica.

Evaluation: 70% based on weekly assignments, 30% based on a final term paper.