Repository for developing and testing code to calculate differential chromatic refraction effects on survey data.

This repository is based on a project started by Matthew Lugatiman (contact details below) who was exploring the impact of DCR in OpSims during the summer of 2024. It has been uploaded to GitHub and further developed by Maya Redden (msredden@stanford.edu).

Notebooks

• SEDAnalysis.ipynb
  • Propagates stellar and galactic SEDs through filter bands and then to distributions of refraction angle due to DCR (dN/dR).
  • Shows the distribution of DCR measurables (mean refraction angle E[R] and distribution dN/dR widths) for the set of SEDs.
  • Attempts to show relationship between in-band SED slope and mean refraction angle within that band.
• DCRSecondStacker.ipynb
  • Used for developing and testing a new MAF stacker class that will add a column(s) to OpSim .db files with estimated DCR second moment additive biases for an "average" galaxy.
  • Calculates the DCR second moment "magnitudes", $I_{DCR_{45}}$, that will be used in the new stacker.
  • Defines and tests the new stacker class with a real .db file.
• airmass.ipynb
  • Plots airmass distributions for a given .db file.

Data

• The "baseline_v3.3_10yrs.db" file used in airmass.ipynb (and other .db files) can be found at https://s3df.slac.stanford.edu/data/rubin/sim-data/ --> sims_featureScheduler_runs3.3/baseline/baseline_v3.3_10yrs.db

Simulated galaxy and stellar SEDs are used to evaluate DCR

• 1000 simulated Galaxy SEDs w/ r magnitudes less than 26: 1000SEDs.txt
  • first row is wavelengths in nanometers
  • next 1000 rows are the SED values in photons/nm/cm^2/s
• 4000 simulated Star SEDs w/ magnitudes between 17 and 22 from SkyCatalogs (paths preserved from their original location in NERSC)
  • Two different sets of SEDs, kurucz and phoSimMLT, stored in starSEDs/global/cfs/cdirs/descssim/lsst/data/sim_sed_library/starSED/
  • list of stellar SED paths in starSED_files_list.txt

Original README by Matthew:

dcr_utils.py is all the code that I used to make each plot.

filter_files is a directory with all the filters that I manually call in my code (might be Different when you use MAF)

airmass.ipnyb is a neat python notebook that Sid gave me to use the cursor to select visits from a specific database.

maf-egfootprint-example.html is a python tutorial to applying the cosmology cuts provided by Humna

quick_example contains an example of when I used the MAF to apply cosmology cuts and looked at the ellipticity quantiles at each filter. This uses a lot of functions in dcr_utils and I thought it would be helpful to incorporate.

Feel free to message me on slack @Matthew Lugatiman or email mluga002@ucr.edu in case you have any questions!