Look at real DES images. Discover flaws we would otherwise have missed.
Make our data better!
We all want to do science with the DES data. However, no data set is perfect, so we need to identify and account for imaging artifacts in our data. This application helps in two ways:
Check out our Tutorial and you'll know what to do in no time.
The basic statistics are computed in real time. More detailed analyses will become available once we have gathered enough submissions, but you can go to our API page and download the anonymized submissions right now.
The code is on github. Please open a new Issue to let us know what we could add, improve, ...
If you find particular failure cases and you think they may constitute a new class of artifacts, please go to the DESDM users wiki [link removed for DEMO], where we list and discuss such cases.