/sdss-v-mwm-scireq

SDSS V Milky Way Mapper: Science Requirements

Primary LanguagePython

SDSS V Milky Way Mapper: Science Requirements

What signal-to-noise ratios are required to deliver the requisite precision in stellar effective temperature, surface gravity, and chemical abundances from SDSS-V Milky Way Mapper?

Environment

conda create -n sdss python=3.6 anaconda
source activate sdss
conda install -n sdss -y numpy scipy matplotlib astropy ipython
git submodule init
git submodule update
cd AnniesLasso
python setup.py install

To-do

  • Download Holtz training set
  • Train model with existing Holtz training set
  • Train model with strict(er) optimization requirements and compare to existing trained model
  • Easily identify and extract individual visits
  • Map out original label recovery as a function of S/N -- save results

Experiments

  • Is DR14 optimized to the correct solution? Yes
  • Is there weirdness going on because labels are so similar? Yes: REMOVE THEM&
  • Map performance on individual visits with a trained model where we are confident that there is no weirdness going on
  • Limit correlated information by prohibiting negative :math:\theta coefficients for absorption lines (which would add emission to the spectrum)
  • Test with and without windows
  • Test with windows and RestrictedCannon
  • Test with windows and regularization
  • Test with RestrictedCannon and regularization
  • Train using the ASPCAP best-fitting spectra for each star instead of data
  • Script to make all comparison plots

Code

  • tc.plot.theta to take label names
  • tc.plot.theta to show censored regions (if they exist)
  • tc.plot.theta to show bounded regions (if they exist)
  • tc.plot.one_to_one to show in square format, if requested
  • new progressbar
  • Move SDSS-V MWM sci-req to SDSS github repository.