SIMBAD references

2009AJ....138..110H - Astron. J., 138, 110-129 (2009/July-0)

Stellar locus regression: accurate color calibration and the real-time determination of galaxy cluster photometric redshifts.

HIGH F.W., STUBBS C.W., REST A., STALDER B. and CHALLIS P.

Abstract (from CDS):

We present stellar locus regression (SLR), a method of directly adjusting the instrumental broadband optical colors of stars to bring them into accord with a universal stellar color-color locus, producing accurately calibrated colors for both stars and galaxies. This is achieved without first establishing individual zero points for each passband, and can be performed in real-time at the telescope. We demonstrate how SLR naturally makes one wholesale correction for differences in instrumental response, for atmospheric transparency, for atmospheric extinction, and for Galactic extinction. We perform an example SLR treatment of Sloan Digital Sky Survey data over a wide range of Galactic dust values and independently recover the direction and magnitude of the canonical Galactic reddening vector with 14-18 mmag rms uncertainties. We then isolate the effect of atmospheric extinction, showing that SLR accounts for this and returns precise colors over a wide range of air mass, with 5-14 mmag rms residuals. We demonstrate that SLR-corrected colors are sufficiently accurate to allow photometric redshift estimates for galaxy clusters (using red sequence galaxies) with an uncertainty σ(z)/(1 + z) = 0.6% per cluster for redshifts 0.09 < z < 0.25. Finally, we identify our objects in the 2MASS all-sky catalog, and produce i-band zero points typically accurate to 18 mmag using only SLR. We offer open-source access to our IDL routines, validated and verified for the implementation of this technique, at http://stellar-locus-regression.googlecode.com.

Abstract Copyright:

Journal keyword(s): galaxies: fundamental parameters - methods: data analysis - stars: fundamental parameters - stars: statistics - techniques: photometric

Status at CDS:  

Simbad objects: 10

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2020.04.09-23:17:46

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