Unrecognized blends are blended objects that are mistakenly identified as a single object, usually due to a high degree of overlap caused by ground based seeing. Using a space based catalog we can attempt to match objects between the two and identify any unrecognized blends. In this technote we use the truth catalogs as a proxy and create a simple matching algorithm between truth and observation to label recognized and unrecognized blends. We then see how the rate varies with object properties such as i-mag and local density.
Links:
- Publication URL: https://sitcomtn-128.lsst.io
- Alternative editions: https://sitcomtn-128.lsst.io/v
- GitHub repository: https://github.com/lsst-sitcom/sitcomtn-128
- Build system: https://github.com/lsst-sitcom/sitcomtn-128/actions/
You can clone this repository and build the technote locally if your system has Python 3.11 or later:
git clone https://github.com/lsst-sitcom/sitcomtn-128
cd sitcomtn-128
make init
make htmlRepeat the make html command to rebuild the technote after making changes.
If you need to delete any intermediate files for a clean build, run make clean.
The built technote is located at _build/html/index.html.
This technote is published to https://sitcomtn-128.lsst.io whenever you push changes to the main branch on GitHub.
When you push changes to a another branch, a preview of the technote is published to https://sitcomtn-128.lsst.io/v.
The main content of this technote is in index.rst (a reStructuredText file).
Metadata and configuration is in the technote.toml file.
For guidance on creating content and information about specifying metadata and configuration, see the Documenteer documentation: https://documenteer.lsst.io/technotes.