Note

Writing and experiments in progress

1 Introduction¶

Running self-calibration (aka ubercal) on an LSST-sized dataset is difficult (though not impossible). It would be convenient if there was an external source of calibration stars we could use to set LSST observation zeropoints.

2 GAIA and ULYSSES¶

The GAIA mission will observe around a billion stars. The BP/RP spectrograph will take low resolution spectra of the GAIA targets. ULYSSES.

Python wrappers to the ULYSSES code can be found in the sims_gaia_calib repo.

3 Generating a GAIA-like Catalog¶

By default, ULYSSES output is in terms of electrons. To calibrate the output spectra to physical units, we run a flat spectrum source through ULYSSES and use the noiseless output to define the instrument response function. We are essentially assuming GAIA will be able to calibrate it’s spectra to a level where the calibration does not significantly contribute to the final spectra noise.

Figure 1 Example stellar spectrum input to ULSYSSES with the LSST filters shown.

Figure 2 Example of the resulting BP/RP spectra when the input spectrum is passed through ULYSSES.

The BP and RP channels have a region of overlap. For simplicity, we use the BP output blueward of 675 nm and the RP output redward. In theory, one could slightly increase the SNR in the overlap region by properly weighting and combining the spectra. This would only impact the LSST r filter.

We use a subset of the Gaia GUMS catalog to generate Gaia end-of-mission (i.e., 75 transits) quality spectra for all the stars down to G~20 in a single LSST pointing. We then compute synthetic LSST magnitudes for each star.

Figure 3 Residuals of recovered g magnitudes.

Figure 4 Residuals of recovered r magnitudes.

Figure 5 Residuals of recovered i magnitudes.

Figure 6 Residuals of recovered z magnitudes.

Figure 7 Residuals of recovered y magnitudes.

The GAIA wavelength coverage does not extend to cover all the u filter. We thus define new u_short filter that is identical to the LSST filter, but has sharp cutoffs so it remains in the Gaia wavelength coverage.

Figure 8 Residuals of recovered u-truncated magnitudes.

4 Results¶

Note the GUMS field which we used is located at (RA, dec) = (340.104, 27.547) with 33,000 stars (13,000 in the range 17 < g < 19). Scaling to the galactic pole, we would expect the density of stars to drop to ~25% that level. So we would still have ~30 Gaia stars per LSST CCD at the galactic pole that could be used for calibration.

5 Recovering the u-band¶

The synthetic y-band magnitudes are still usable because the LSST y throughput is very low in the region where Gaia cuts off. That is not true for the u-band, thus, if we are going to use Gaia to calibrate the u filter, there needs to be an extra step in extrapolating Gaia observations to LSST u-magnitudes.

Two possible methods: 1) Because there is some overlap between Gaia BP spectra and LSST u, one could use model spectra to construct a synthetic u-u_gaia v u_gaia-g diagram from model spectra, then recover u from the Gaia data. 2) Gaia claims to return full stellar parameters for every star (Teff, Fe/H, log g). If those parameters are accurate and precise enough, they could be converted to a model stellar spectrum and the LSST u could be computed. There is a risk of making things slightly circular, using GAIA derived stellar parameters to infer LSST u-magnitudes, which are then used to compute LSST colors that are used to fit stellar parameters.

Lui et al look at how well Gaia will be able to recover stellar parameters.

Figure 9 Kurucz model grid.

Figure 10 Same as Figure 9, but color-coded by stellar log g.

Figure 11 If we assume Gaia returns perfect stellar parameters, the Gaia synthetic LSST g and r magnitudes can be used with the Kurucz models to generate LSST u magnitudes with the plotted residual distribution. Results in 0.005 mag RMS at u=18.

Figure 12 Same as Figure 11, but inserting 0.1 dex RMS errors on both the metallicity and log g Gaia values. Results in 0.002 mag RMS at u=18.

Figure 13 Same as Figure 11, but inserting 0.35 dex RMS errors on the metallicity and 0.2 dex errors on log g. Results in 0.06 mag RMS at u=18.

It would appear that if

we believe that stars can be described by Kurucz models
we believe Gaia will return stellar parameters with their expected precision

it should be possible to construct a u-band stellar catalog from the Gaia data that would be adequate for calibrating LSST observations.

6 Other Issues¶

Besides the difficulty in extrapolating the u-band, Gaia will not observe as deep in the galactic plane. This leaves the possibility that there will not be any overlap in the Gaia observations and LSST stars that are not saturated.

The Gaia data release scenarios do not include releasing the reduced BP/RP spectra, but only the derived stellar parameters. Thus we may need to request the Gaia collaboration compute synthetic LSST magnitudes or expand the scope of their data releases to include BP/RP (non-integrated) spectra.

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