Gravitational-wave data contains excess noise that affects the estimation of astrophysical source parameters.
In some cases, the excess noise looks nearly identical to the noise seen previously, enabling us to categorize this noise into different classes (so-called glitch classes).
In my previous work (see antiglitch ), I showed that it is possible to model short-duration glitches using a quasi-physical model. Using JAX, the glitches can be fitted to the quasi-physical model which then allows us to remove these glitches.
In this project, I show that short-duration glitches like blips and tomtes can also be modeled using autoencoders. With an autoencoder, I am able to fit a glitch model to the data orders of magnitude faster than the previous JAX-based fitting method, while keeping the same precision.