Regarding your first question: the procedure is described here T1500618, but I don’t think code is available.
Regarding your second question, please reach out to the authors of that paper directly.
Max gave you a pointer for the method to create Fig. 5, but Fig. 4 is created using a different analysis (the IMR consistency test). I’m not sure if the code to create that specific figure is available publicly, but the code to run the IMR consistency test is available publicly. The current version of the analysis (that is, e.g., used in the analysis of O3b data, https://arxiv.org/abs/2112.06861) is slightly different than the one presented in the GW150914 testing GR paper that you are considering, since the current analysis normalizes using the average of the inspiral and postinspiral instead of the IMR results. The current version also reweights to a flat prior in the deviation parameters. This analysis (without the reweighting) is implemented in the PESummary summarytgr executable, which is applied to the inspiral and postinspiral analyses computed using a standard parameter estimation code, e.g., Bilby.
Thank you for your answers.
- I am still trying to figure out what is the code in order to reconstruct fig. 5 in this article: [1602.03841] Tests of general relativity with GW150914 .
- And still trying to figure what are the codes in order to reconstruct fig. 1, fig. 2, fig. 5, fig. 6, fig. 7, fig. 8 in this article:
[1902.07527] Observational Black Hole Spectroscopy: A time-domain multimode analysis of GW150914
For point 1, as Max mentioned, it doesn’t appear that the code to replicate Fig. 5 is publicly available. There is a link to the code repository in the document that Max shared, but that repository is only accessible to LVK collaboration members. You should thus contact the code’s author, Reinhard Prix (see Dr. Reinhard Prix | Max Planck Institute for Gravitational Physics (Albert Einstein Institute) for contact information; the @ligo.org address given in the notes will not work, as Reinhard is no longer a collaboration member), to see if he would be willing to share it with you.
For point 2, as Max also mentioned, you should contact the authors of the paper in question directly by e-mail–I don’t think that any of them participate in this discussion forum.
In comment 33 there is a link to this github GitHub - johnveitch/cpnest: Parallel nested sampling
I am trying to reconstruct graphs useing this github, and it doesn’t work. what is wrong with what I do: I copy-paste from github to google colab. what other comment should I write?