agn

Modelling jetted Active Galactic Nuclei radiative processes with python

JetSeT a framework for self-consistent modeling and fitting of astrophysical relativistic jets

Galaxy Line Emission & Absorption Modeling

A Python Toolkit for AGN Time Series Analysis using CARMA models

Efficient AGN light curve modeling and parameter estimation using celerite

Python module for estimation of cross-correlation function of astronomical time-series based on the ZDCF method.

Python module to compute the SED of an AGN following Kubota & Done (2018).

A pipeline for estimating AGN time lags

Amoeba: an AGN Model of Optical Emissions Beyond steady-state Accretion disks

Nirdust is a python package that uses K-band (2.2 micrometers) spectra to measure the temperature of the dust heated by a type 2 Active Galactic Nuclei (AGN) accretion disk.

Python code for modelling spectral timing properties in AGN. Performs calculations of fully time-dependent SEDs following an input variable X-ray light-curve (See Hagen & Done (2023a)

This code accomponies the paper: Active galactic nuclei identification using diffusion-based inpainting of Euclid VIS images - Euclid Collaboration: Stevens et al. (2025)

A package following Stone & Shen (2023) for AGN accretion disk temperature fluctuation maps

Uncertainty quantification of black hole mass estimation

Code for "Joint Modeling of Quasar Variability and Accretion Disk Reprocessing using Latent Stochastic Differential Equation"

Code supporting paper: A forward modeling approach to AGN variability – method description and early applications (2019ApJ...883..139S)

A Python package for automated detection and analysis of EVPA rotations in AGN polarimetric data using Bayesian Blocks and statistical testing

Code for "Predicting High Magnification Events in Microlensed Quasars in the Era of LSST using Recurrent Neural Networks"

Comparative study of AGN host galaxies in SDSS DR7 and IllustrisTNG, focused on green valley demographics and sSFR offsets.

Code for "Latent Stochastic Differential Equations for Modeling Quasar Variability and Inferring Black Hole Properties"