About StreamObs

About StreamObs#

Overview#

StreamObs is a Python package designed for stellar stream data generation and observation simulation. It provides a complete pipeline to transform theoretical or dynamical stream models into realistic mock observations as they would appear in astronomical surveys.

Note

StreamObs is not intended for generating dynamical models or N-body simulations. Instead, it provides tools to study statistical realizations of parametrized stream geometries and convert simulation outputs into mock observations.

What StreamObs Does#

StreamObs enables to:

  1. Generate mock stellar stream data from parametric models

    • Create positions of stars along streams using various parametric descriptions

    • Model stream morphologies including linear, sinusoidal, and spline-based geometries

  2. Assign photometric properties to stream stars

    • Attribute magnitudes in multiple photometric bands based on stellar isochrones

  3. Simulate survey observations of streams

    • Convert idealized mock data into observable quantities for specific surveys (e.g., LSST)

    • Apply survey selection functions and detection limits

    • Generate realistic photometric errors and observational uncertainties

Use Cases#

StreamObs is particularly useful for people who:

  • Run dynamical simulations of stellar streams and need to convert results into observable quantities

  • Develop stream detection algorithms and require realistic test data with known properties

  • Need to generate mock catalogs for testing analysis pipelines

  • …

Development Team#

StreamObs is developed and maintained by members of the LSST Dark Energy Science Collaboration (DESC).

Core Contributors:

  • Matthieu Pélissier (Université Grenoble Alpes, CNRS/IN2P3, LPSC, 53 avenue des Martyrs, F-38026 Grenoble, France)

  • Peter Ferguson (DiRAC Institute and the Department of Astronomy, University of Washington, Seattle, WA, USA)

  • Alex Drlica-Wagner (Department of Astronomy and Astrophysics, University of Chicago, Chicago, IL 60637, USA)

Contact:

License#

MIT Licence

Acknowledgments#

If you use StreamObs in your research, please see the Citation page for how to properly cite this software.

Funding and Support:

  • This project is supported by the LSST Dark Energy Science Collaboration

Related Projects: