PKS1510_modelling

Code using agnpy for the modelling the FSRQ PKS 1510-1019

Refer to Jupyter Notebooks for the MCMC implementation to datasets using gammapy. Use the method below when implementing with sherpa.

Basic usage

Basic functionalities are wrapped via click. Two commands are available

Environment

Added an environment installing all the dependencies needed to run the analysis.

conda env create -f environment.yml

a pks1510-modelling conda environment will be created. To activate it:

source activate pks1510-modelling

fitting

You can fit a particulare state via the command

$ python make.py fit

Pass the options --help when in doubt

$ python make.py fit --help
Usage: make.py fit [OPTIONS]

  Perform the fit of PKS 1510-089 SED for a given state

Options:
  --state [low|2012|2015a|2015b|hess_2016|magic_2016]
  --k_e FLOAT                     electron normalisation
  --gamma_min FLOAT               minimum Lorentz factor
  --gamma_max FLOAT               maximum Lorentz factor
  --t_var FLOAT                   variability time scale
  --r FLOAT                       distance of blob from BH
  --help                          Show this message and exit.

So, to perform the fit of the 2012 state adjusting some of the initial parameters (the ones specified in the help command)

python make.py fit --state 2012 --k_e 0.01 --gamma_min 3 --gamma_max 7e4

in the directory results a directory per each state will be created, containing the plot of the fitted SED and a dicitonary, a .yaml file, containing all the model parameters.

Plotting

After performing the fit, SED and best-fit model can be plotted via the command

$ python make.py plot --state 2015a

you should obtain a plot like this

To plot all the SED together, use

$ python make.py plot --state all

you should obtain a plot like this