Selection function for metal-poor giants in the heart of the Galaxy

Selection function for metal-poor giants in the heart of the Galaxy#

This is a part of the GaiaUnlimited project.

Summary#

We utilize red giant branch (RGB) stars from Gaia, with metallicities estimated by Andrae et al. (2023) using spectro-photometry from Gaia Data Release 3 (XP). By accounting for Gaia’s selection functions and testing several parametric density models, we examine the spatial distribution of metal-poor ([M/H]<-1.3) RGB stars, from the Galactic center (r ~ 1 kpc) out to beyond the Solar radius (r ~ 20 kpc).

This is a worked example of a specialized selection function for the Gaia survey, based on the forthcoming paper by Evgeney Kurbatov et al.

Installation#

Install the requirements with:

pip install -r requirements.txt

Code#

The whole pipeline is:

  • 1. Download and prepare RGB star catalogue.ipynb

    • Download the Andrae R. et al. (2023) catalogue of RGB stars

    • Make the transformation from Galactic to Galactocentric frame

  • 1a. Plot kinematics.ipynb (optional)

    • Clean the RGB star catalogue of globular clusters (Vasiliev & Baumgardt 2021), SMC and LMC

    • Use AGAMA for potential estimate

    • Make cool plots

  • 2. Extinctions.ipynb

    • Estimate extinctions in G, RP and, BP bands

    • Estimate monochromatic exctinction A_0

    • Fit A_G(A_0) A_BP(A_0) and A_RP(A_0) neglecting the T_eff dependency

  • 3. Luminosity function.ipynb

    • Take NGC 6397 globular cluster from Vasiliev & Baumgardt (2021) catalogue

    • Correct the magnitudes for extinctions

    • Extract luminosity function of the RGB stars

  • 4. Parallax errors.ipynb

    • Query and count Gaia source (GS) stars on the HEALPix vs G grid

    • Count XP stars on the HEALPix vs G grid

    • Count number of visits and bin parallax errors

    • Fit the parallax error vs G magnitude

  • 5. Domain.ipynb

    • Define the computational domain

    • Calculate map from (l, b, D) to (x, y, z)

  • 6. XP selection function.ipynb

    • Query XP statistics over the sky and the G band

    • Estimate subsample selection function

  • 7. Probability transformation function.ipynb

    • Join together the extinction A_G, the XP selection function, the parallax error model and the luminosity function

    • Estimate the transformation function for PDF, from model to observable

  • 8. Aurora model.ipynb One example of the Aurora + GS/E model

Contents