LSSTDESC / SprintWeek2023

Meeting repository for the LSST DESC 2023 Sprint Week @ CMU

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Implementing a pipeline in RAIL for the generation of mock photometry from diffsky #35

Closed torluca closed 1 year ago

torluca commented 1 year ago

Implementing a pipeline in RAIL for the generation of mock photometry from diffsky

The sprint aims at creating a pipeline using classes implemented in RAIL to generate mock LSST photometry for photo-z testing and other science cases.

Contacts: Luca Tortorelli Day/Time: Monday-Friday 15:00-18:00 CET, only remote Main communication channel: Slack GitHub repo: https://github.com/LSSTDESC/rail_lib_gp_comp Zoom room (if applicable): https://stanford.zoom.us/j/93249165933?pwd=UEpjeXMxNGoxZDFrSkkyYlpwR2FUUT09

Goals and deliverable

Goals:

[x] Implement interface to skysim/diffsky in rail_lib_gp_comp.
[x] Use the output star-formation histories to generate SEDs and model photometry using rail_dsps.
[x] Map the model photometry to the observed one using the LSSTErrorModel in RAIL.

Deliverable:

[x] Catalog of galaxy SEDs and LSST-like photometry based on skysim/diffsky galaxy population model.
[x] Demo notebook illustrating the pipeline.

Resources and skills needed

Knowledge of RAIL, dsps and skysim/diffsky

torluca commented 1 year ago

The sprint was completed on Thursday. I implemented the relevant classes and created a demo notebook in rail_lib_gp_comp that illustrates how to produce mock catalogs of LSST-like photometry with additionally knowing the input physical properties of galaxies and their SEDs.