Application of the probabilistic flux variation gradient (PFVG) method, as presented in "Disentangling the optical AGN and host-galaxy luminosity with a probabilistic flux variation gradient". An implementation of the method can be found here ProbabilisticFluxVariationGradient.jl.
In the following examples we apply the PFVG method on observations from the source 3C120. The light curves for 3C120 have been taken from the published work of Ramolla et al. (2018).
This package is implemented in the Julia language.
A current release of Julia may be downloaded here.
Apart from cloning, an easy way of using the package is the following:
1 - Add the registry AINJuliaRegistry.
2 - Switch into "package mode" with ] and add the package with
add PFVG_AA2021
3 - Go back to the REPL (press backspace) and execute:
using PFVG_AA2021
The light curves for 3C120 can be inspected using the following command:
Check3C120()
This will output the following plot:
The filled circles mark simultaneous observations obtained for each filter. These observations are used in the PFVG analysis.
To run the PFVG method on the light curves above, run the code:
runPFVG()
The code will use the light curves stored in the data folder and output the distribution of host-galaxy fluxes as ascii files with names PFVG.dist.object.filter.txt, in the same data folder. The input galaxy color vector taken from Sakata et al. (2010) is stored as Galaxy_vec.txt
To plot the distributions use the following command:
PlotPFVGdist()
This will output the following plot:
which is the same as Fig. A.5 presented in Gianniotis, N., Pozo Nunez, F., and Polsterer, K.L. (2021).
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