astrometry-inference-tutorials

This is the repository for the tutorials that accompany the Gaia DR2 paper Luri et al. 2018, A&A Special Issue for Gaia DR2 (also available on arxiv.org) describing recommended practices for the use of astrometric data (in particular parallaxes) in astronomical data analysis problems.

You can launch the tutorials through binder. This was installed on 2018.12.12 and is not yet working properly.

Getting things to work

Installation instructions to make sure you have everything needed to run the tutorials are here.

Tutorials

• Infer distance to a single source (R)

  • Bayesian inference of distance from parallax only for a single source
  • Comparison of distance estimators

• Infer distance to and size of a cluster (R)

  • Notebook

• Infer distance and tangential velocity of a source (R)

  • Notebook

• Luminosity calibration (Python)

  • Explanation of negative parallaxes
  • Distribution of quantities derived from parallaxes for naive estimators and posteriors based on minimal prior information
  • Basics of handling data truncation
  • Simulation of parallax surveys
  • Inference of the luminosity of a class of stars

• The period luminosity relation (R and Python)

  • R notebook interfaced to python
  • R notebook