GaiaUnlimited

Who is In, and Who is Not? Determining the Gaia Survey Selection Function

This project is funded by the European Union’s Horizon 2020 research and innovation program under grant agreement No 101004110.

GaiaUnlimited aims at determining the Gaia survey selection function and providing corresponding data and tools. The GaiaUnlimited project was started at the 2019 Santa Barbara Gaia Sprint, hosted by the Kavli Institute for Theoretical Physics at the University of California, Santa Barbara.

The code for the GaiaUnlimited tools is hosted at https://github.com/gaia-unlimited

See Tools and Data pages for more details

This project kicked off on 2021-01-01 and you can expect the first results, data, and tools to appear in 2022. Selection functions developed independently for Gaia DR2 and EDR3 can be found on the Related Projects page.

  • Emperical Gaia DR3 selection funtion paper on arXiv
    This paper present an emprically determined selection function for Gaia DR3. It is a simple analytical completeness model of Gaia as a function of the observed G magnitude and position over the sky, which accounts for both the effects of crowding and the complex Gaia scanning law. The model only depends on a single quantity:…
  • GaiaUnlimited community workshop Sep 13-15 2022
    The first GaiaUnlimited community workshop will take place on September 13 to 15 2022 at the MPIA in Heidelberg, Germany. This event will be a three-day workshop and unconference, where we will discuss and learn from each other about the finer details of the Gaia selection function and how to build and use it in…
  • Vacancy for a postdoc in the GaiaUnlimited Project (CLOSED)
    The University of Torino in Italy is hiring a post-doc for the GaiaUnlimited Project. More information on this position can be found from the Torino website. Deadline for the application is 1 November 2021.
  • Selection functions paper on arXiv
    The first paper from the GaiaUnlmiited project appeared on arXiv on 2021-06-16. It discusses the use of selection functions in astronomical data modeling, with the space density of white dwarfs as worked example.