Data

S-PLUS will have regular public data releases. The latest data release is DR1 and can be accessed through NOAO Data Lab. Below we will describe how to access these data and what's included in the release. Full details on reduction and calibration can be found in Mendes de Oliveira et al. (2019).

How to download

> Using Data Lab Table Access Protocol (TAP) service

TAP provides a convenient access layer to the S-PLUS catalog database. TAP-aware clients (such as TOPCAT) can point to http://datalab.noao.edu/tap, select the splus_dr1 database, and see the database tables and descriptions. splus_dr1 contains eight tables: stripe82, allwise, des_dr1, gaia_dr2, ls_dr5, ls_dr6, nsc_dr1, sdss_dr14_specobj. The last seven are cross-match tables between S-PLUS and the relevant datasets.

> Using Data Lab Query Manager

The Query Manager is available as part of the Data Lab software distribution. The Query Manager client provides a Python API to Data Lab database services. This includes authenticated access, synchronous and asynchronous queries, TAP queries, personal database storage, and storage through the Data Lab VOSpace.

> Image cutouts

The Data Lab Simple Image Access (SIA) service provides a fast way to retrieve cutouts from S-PLUS images. For an example of how to use the SIA service see this Jupyter notebook that describes it for the SMASH data set (about 2/3 the way down the page). For S-PLUS the SIA URL is http://datalab.noao.edu/sia/splus_dr1

What is in DR1?

As explained in Mendes de Oliveira+2019, the procedure adopted in S-PLUS for the catalog production is similar to that thoroughly explained in Molino+14 for the ALHAMBRA survey (Moles et al, 2008). The S-PLUS photometric pipeline is based on the SExtractor software. Photometric catalogs are constructed in double-image mode to perform multi-band aperture-matched photometry. Detection images are created as a weighted-combination of the reddest (griz) broad-band filters to maximize the detectability of faint (or low-surface brightness) sources and to enhance the definition of the photometric apertures. An empirical noise characterization is done beforehand on an image-by-image basis, to account for correlations among adjacent pixels during image reduction process (Molino+14). Magnitudes for non-detected sources on individual images are set to m = 99. and corresponding uncertainties replaced by upper-limits. Photometric zero-point calibrations have been performed for every pointing using a novel technique optimized for wide-field multi-band photometric surveys (Sampedro et al, in prep.). The technique uses a combination of libraries of stellar models and the stellar locus of main-sequence stars, applied to typically ~1500 stars per field, bringing all zero-points to a typical error of 1-2%.

As explained in Sampedro et al., (in prep.), the catalog includes both astrometric, morphologic, photometric and photo-z information for all detected sources in the S-PLUS detection images. Astrometric as well as morphological information is extracted from detection images: celestial coordinates (RA, Dec) in the J2000 system, physical position on the CCD (X,Y), photometric aperture size (ISOarea), the signal-to-noise (s2nDet; defined as SExt_FLUX_PETRO/SExt_FLUXERR_PETRO on the detection image), compactness (FWHM and MUMAX) , basic shape parameters (A, B & THETA), the fraction-of-light radii (FlRadDet) and Kron apertures (KrRadDet). We have also included the standard SeXtractor photometric Flags (PhotoFlag). The meaning of the flag's number is the following:

1: The object has neighbors, bright and close enough to significantly bias the MAG_AUTO photometry, or bad pixels,
2: The object was originally blended with another one,
4: At least one pixel of the object is saturated,
8: The object is truncated (too close to an image boundary),
16: Object's aperture data are incomplete or corrupted,
32: Object's isophotal data are incomplete or corrupted,
64: A memory overflow occurred during the deblending,
128: A memory overflow occurred during the extraction.

Objects with a different flag's number may suffer from a combination of the already mentioned flags, being the number the sum of the different flags.

The catalog contains a triple photometry where magnitudes (& uncertainties) are named according to the filter's name and the adopted photometric aperture. Here we provide an example for clarifications: F660_auto, F660_petro & F660_aper correspond to the AB magnitudes for the F660 narrow-band filter, where “auto” refers to the total (restricted) apertures used to derive photo-z estimations, “petro” to the total (moderate) apertures used to derive absolute magnitudes and stellar masses and “aper” to the standard circular 3”-diameter apertures (see Molino+16, Molino+18, for more information). Photometric uncertainties take the same name (as magnitudes) but adding the prefix “d”): “dF660_autodF660_petro” & “dF660_aper”.

An estimate of the signal-to-noise for every detection, within each one of the three apertures, is also provided as “s2n_F660_auto”, “s2n_F660_petro” & “s2n_F660_aper”, defined as explained before for the detection image. For each sets of magnitudes, photometric uncertainties are empirically corrected in all the 12 bands. Whenever a source was not detected, its magnitude was set to 99. and its photometric uncertainty replaced by a 2-σ upper limit. Magnitudes are corrected from galactic extinction using Schlegel+98.

The catalog also includes a photometric redshift estimate for every source using a new version of the BPZ code (Benítez 2000) optimized for galaxies in the local Universe (Molino et al, in prep.). “zb” correspond to the most likely value (i.e., peak) and “zb_Min” and “zb_Max” represent the lower and upper limits for the first peak within a 1σ interval, i.e., ∆z = 0.02 x (1 + z). Based on the most likely redshift, a spectral-type classification is also provided by “Tb”, where its number refers to the selected template. “Odds” gives the amount of redshift probability enclosed around the main peak and “χ2” the reduced chi-squared from the comparison between observed and predicted fluxes according to the selected template and redshift. An estimation of the stellar-mass content (in units of log10(M⊙)) is given by “Stell_Mass”. Absolute magnitudes in the Johnson B-band (“M_B”) are estimated for each detection according to its most likely redshift and spectral-type.