Automated supermassive Blackhole Explorer(ABE) studies the co-evolution of the supermassive black holes with its host galaxies, particularly looking at the effect of AGN feedback
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Updated
Nov 6, 2018 - Python
Automated supermassive Blackhole Explorer(ABE) studies the co-evolution of the supermassive black holes with its host galaxies, particularly looking at the effect of AGN feedback
Codes to calculate Temperature and Density from the lines ratio of certain ions in the narrow line region of a given AGN
Testing the unification model of active galactic nucleus (AGN) by convolution neural network
Code supporting paper: A forward modeling approach to AGN variability – method description and early applications (2019ApJ...883..139S)
Code and data supporting paper: Observational Nonstationarity of AGN variability: The only way is down! ( 2020ApJ...889L..29C)
Efficient AGN light curve modeling and parameter estimation using celerite
Simulate post-starburst galaxy spectral energy distributions to see if active galactic nuclei play a role in quenching post-starburst galaxies using prospector-alpha and FSPS.
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)
The JAVELIN module for pyPetal.
Data supporting paper: Optical Variability of AGNs in the PTF/iPTF Survey (2017ApJ...834..111C)
Galaxy Line Emission & Absorption Modeling
Uncertainty quantification of black hole mass estimation
22 GHz Radio Data. Files should contain 1", 3", and 6" fits files.
A package following Stone & Shen (2023) for AGN accretion disk temperature fluctuation maps
Example code to run prediction pipeline from Carvajal et al. 2023
A Python Toolkit for AGN Time Series Analysis using CARMA models
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