Several functions can be found in this project to help us get a better understanding of the central engine of AGNs:
- timescale-dependent color variation (CV) calculation.
- structure-function (SF) calculation and fits.
- generate stochastic process light curves.
- fractional variability.
- ...
A JULIA
version for calculating SF and color variation can be found at run_demo.jl. Read the full documentation here.
A PYTHON
version for calculating SF and color variation can be found at run_demo.py, tested through Python 3.8.8
.
Run & plot it!
TODO:
- reprocessing model
- structure function calculation (see kozlowski+16)
- update the tutorial ...
- lag calculation, mainly convert PYCCF to julia version
julia> # Press the key "]"
(@v1.9) pkg> add https://github.com/wssuzb/Jirachi.jl.git
julia> using Jirachi
or alternatively, you can also download this Jirachi.jl-main.zip
file, and load it by
julia> push!(LOAD_PATH, "'~/where/you/download/the/package/Jirachi")
julia> using Jirachi
enjoy!
If this project makes your life easier, please cite this code below:
@misc{su2024new,
title={A new timescale-mass scaling for the optical variation of active galactic nuclei across the intermediate-mass to supermassive scales},
author={Zhen-Bo Su and Zhen-Yi Cai and Mouyuan Sun and Hengxiao Guo and Wei-Min Gu and Jun-Xian Wang},
year={2024},
eprint={2405.02584},
archivePrefix={arXiv},
primaryClass={astro-ph.GA}
}
or
@software{jirachi,
author = {Su, Zhen-Bo},
title = {{Julia project for analyzing variability in active
galaxies harboring massive black holes}},
month = dec,
year = 2023,
publisher = {Zenodo},
version = {v0.0.1},
doi = {10.5281/zenodo.10428783},
url = {https://doi.org/10.5281/zenodo.10428783}
}
also see CITATION.bib
for the relevant reference(s).