Jammy2211 / autogalaxy_likelihood_function

PyAutoGalaxy: URL links to notebooks describing the likelihood function

PyAutoGalaxy Likelihood Function

The autogalaxy_workspace contains Jupyter notebooks describing the (log) likelihood functions used by PyAutoGalaxy.

The notebooks provide a step-by-step guide of how PyAutoGalaxy fits galaxy data, with the aim to make the analysis clear to readers without background experience in galaxy modeling and make the modeling less of a "black box".

We recommend that when writing a paper using PyAutoGalaxy the author links to this GitHub repository when describing their likelihood function.

The notebooks are not stored here (they are on the autogalaxy_workspace), however URLs to every notebook are provided here. We recommend authors link to this GitHub repository (as opposed to direct links to each) because the URLs to notebooks on the autogalaxy_workspace may change after papers are published.

By linking to this repository a permanent URL is provided.

Notebook Links

There are different ways a galaxy can be modeled in PyAutoGalaxy, we provide links describing the likelihood function of all approaches below:

Imaging Dataset + Parametric Light Profiles:

https://github.com/Jammy2211/autogalaxy_workspace/blob/main/notebooks/imaging/advanced/log_likelihood_function/parametric.ipynb

Imaging Dataset + Pixelized Reconstruction:

https://github.com/Jammy2211/autogalaxy_workspace/blob/main/notebooks/imaging/advanced/log_likelihood_function/pixelized.ipynb