Modelling the Multiwavelength Variability of Mrk-335 using Gaussian Processes
This repo contains all source code for the paper "Modelling the Multiwavelength Variability of Mrk 335 using Gaussian Processes " available here (https://iopscience.iop.org/article/10.3847/1538-4357/abfa9f/meta). We interpolate the gaps in the observational lightcurves of Mrk 335 using a Gaussian process and use these "GP Lightcurves" to perform a cross-correlation analysis. The (purely decorative) gif below illustrates the resampling procedure for obtaining bootstrap uncertainty estimates on the parameters of power law fits (black) to a Gaussian process structure function (red).
Installation
We recommend using a conda environment.
conda create -n mrk python==3.7
conda install astropy scikit-learn matplotlib
conda install -c conda-forge statsmodels
pip install git+https://github.com/GPflow/GPflow.git@develop#egg=gpflow
pip install scipy
Gaussian Process Fitting to Observational Data
The gp_fit_real_data folder contains the code for fitting Gaussian processes to the observational data
| X-ray | UVW2 |
|---|---|
 |
 |
Lightcurve Simulations
The simulations folder contains code for performing lightcurve simulations according to the Timmer and Konig algorithm.
Structure Function Computation
The structure_function folder contains the code for computing structure functions of both the observational lightcurves and the Gaussian process-interpolated lightcurves of Mrk 335.
Log-Normality Tests
The folder log_normal_tests contains code for distribution testing of the observational data from Mrk 335, including both graphical distribution tests such as PP-plots, ECDFs and histograms as well as statistical hypothesis testing using the Kolmogorov-Smirnov test.
Citing
If you find this code useful please consider citing the following paper
@article{griffiths2021modeling,
title={Modeling the Multiwavelength Variability of Mrk 335 Using Gaussian Processes},
author={Griffiths, Ryan-Rhys and Jiang, Jiachen and Buisson, Douglas JK and Wilkins, Dan and Gallo, Luigi C and Ingram, Adam and Grupe, Dirk and Kara, Erin and Parker, Michael L and Alston, William and others},
journal={The Astrophysical Journal},
volume={914},
number={2},
pages={144},
year={2021},
publisher={IOP Publishing}
}