Note
This technote is a work-in-progress.
1 Abstract¶
Summary of crowded field processing performance with the pipe_crowd prototype code.
2 Test cases¶
To test the performance of pipe_crowd, four datasets were chosen, with varying degree of crowding. Below is a brief description of these datasets from u/kherner/PREOPS-597_20220120.:
"instrument": "DECam", "visit":205419 High crowding
"instrument": "DECam", "visit":223501 Medium crowindg
"instrument": "DECam", "visit":428066 Low crowding
In addition to these three fields, we also select a high latitude field from the HiTS SN survey.:
"instrument": "DECam", "visit":288970 Control u/sullivan/DM-30831-HiTS2014-templates_test/20211011T191211Z
Below is the result of running pipe_crowd without any modifications to the code and using its default configuration.
3 Issues identified¶
Through successive runs of pipe_crowd using default parameters, the following issues were identified:
Poor performance in iterative source detection. Essentially, source detection in the residual images produce no additional sources.
PSF model has wings. Produces oversubtract residual images.
Centroid coordinates are NaN after first iteration
3.1 Testing PSF model performance¶
In the crowded fields the first potential issue identified was the presence of wings in the PSF model produced by ProcCCD/CharactrizeImage. Below we show two examples of PSF models for an medium crowded field and the control field.
Since the winged PSF can potentially oversubtract flux from neighbor sources, this could affect source detection in the residual images. This could be the culprit for the iterative source detection not yielding additional. This effect was confirmed by inspecting the residual images.
We attempt to replace the PSF model with the SimplePSF one, which is described by a 2D normal distribution. However, this had no effect in identifying more sources in iteration > 1.
3.2 Centroiding¶
Centroiding removes too many (all) new sources.
This was solved by brute force updating the spurious centroid positions with the less accurate coarse positions. See code block
TODO: investigate point of failure of centroid()
3.3 Deblending¶
TODO: make plots
4 Performance¶
TODO: Summary of the performance after XM with Gaia (external catalogue).
5 People¶
This project is part of in-kind contribution program NED-UTR-S3. The main people involved are:
Eduardo Balbinot (Leiden) - from Nov 2022 to present
Zuzanna Kostrzewa-Rutkowska (Leiden) - from ? to Sep 2022.
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