The photometric classification server for Pan-STARRS1

2012 
The Pan-STARRS1 survey is obtaining multi-epoch imaging in five bands (g{sub P1} r{sub P1} i{sub P1} z{sub P1} y{sub P1}) over the entire sky north of declination -30 deg. We describe here the implementation of the Photometric Classification Server (PCS) for Pan-STARRS1. PCS will allow the automatic classification of objects into star/galaxy/quasar classes based on colors and the measurement of photometric redshifts for extragalactic objects, and will constrain stellar parameters for stellar objects, working at the catalog level. We present tests of the system based on high signal-to-noise photometry derived from the Medium-Deep Fields of Pan-STARRS1, using available spectroscopic surveys as training and/or verification sets. We show that the Pan-STARRS1 photometry delivers classifications and photometric redshifts as good as the Sloan Digital Sky Survey (SDSS) photometry to the same magnitude limits. In particular, our preliminary results, based on this relatively limited data set down to the SDSS spectroscopic limits, and therefore potentially improvable, show that stars are correctly classified as such in 85% of cases, galaxies in 97%, and QSOs in 84%. False positives are less than 1% for galaxies, Almost-Equal-To 19% for stars, and Almost-Equal-To 28% for QSOs. Moreover, photometric redshifts for 1000 luminous red galaxies up to redshiftmore » 0.5 are determined to 2.4% precision (defined as 1.48 Multiplication-Sign Median|z{sub phot} - z{sub spec}|/(1 + z)) with just 0.4% catastrophic outliers and small (-0.5%) residual bias. For bluer galaxies up to the same redshift, the residual bias (on average -0.5%) trend, percentage of catastrophic failures (1.2%), and precision (4.2%) are higher, but still interestingly small for many science applications. Good photometric redshifts (to 5%) can be obtained for at most 60% of the QSOs of the sample. PCS will create a value-added catalog with classifications and photometric redshifts for eventually many millions of sources.« less
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    13
    References
    49
    Citations
    NaN
    KQI
    []