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tests:astropars:challenge3

Challenge 3: Fit BP/RP and RVS simultaneously

Objectives

  • Compare performance of GSP-Phot to Andy's SICK code when fitting only BP/RP.
  • Investigate fitting BP/RP alone, RVS alone, and BP/RP+RVS simultaneously with Andy's SICK code.
  • Is this a route to beat APSIS?
  • Where can BP/RP help to estimate abundances from RVS?
  • Where can RVS help to improve on BP/RP?
  • This project employs synthetic MARCS spectra.

GSP-Phot vs. SICK

Conclusions
  • GSP-Phot and SICK overall agree very nicely. No algorithm clearly outperforms the other.
  • logg: GSP-Phot is slightly better than SICK. SICK may suffer from some convergence problems (red dots below dwarfs).
  • [Fe/H]: SICK is slightly better than GSP-Phot. GSP-Phot appears to systematically underestimate [Fe/H] by ~1dex for some stars. These problematic stars are fainter than G~15, i.e., SICK estimates [Fe/H] more robustly at lower S/N than GSP-Phot.
Test data
  • 2000 synthetic MARCS spectra in Gaia BP/RP.
  • Mostly Main-Sequence dwarfs but also some giants.
  • Teff from 4000K to 8000K.
  • Test spectra created by GOG. (Not by our own forward models!)
Examples of posterior samples
  • Posterior distributions mostly well behaved for BP/RP, i.e., fast convergence, unimodal.
  • Even in simple case the posteriors cannot be well approximated by a Gaussian.
  • Rare examples with multimodal posterior.

Results for fitting BP/RP alone
GSP-Phot bias SICK bias GSP-Phot sigma SICK sigma
Teff [K] 14 18 100 100
AV [mag] 0.02 0.03 0.07 0.08
logg [dex] 0.02 0.07 0.19 0.29
[Fe/H] [dex] 0.12 0.00 0.37 0.28

Future tests
  • Compare initial guesses of GSP-Phot and SICK. (Possibly SVM fails for noisy data, which may explain why SICK estimates [Fe/H] better at faint magnitudes.)

SICK: BP/RP alone vs. RVS alone

SICK: Fitting BP/RP and RVS simultaneously

tests/astropars/challenge3.txt · Last modified: 2014/10/31 13:55 by randrae