GOODS-Herschel data release 1 - readme ====================================== This is the readme for the first data release of the GOODS-Herschel project. A more complete document, a PDF file named GOODS-Herschel_release.pdf, is accompanying this readme. It is very important you read this document as it gives instructions on how to use these data. The PDF file should be found where you got the GOODS-Herschel data, or can be downloaded from the Herschel Database in Marseille (HeDaM - http://hedam.oamp.fr/GOODS-Hersche). GOODS-Herschel (Elbaz et al, 2011, A&A, 533, 119) is in ESA open time key project consisting of the deepest Herschel observations of the two *Great Observatories Origins Deep Survey* (GOODS) fields in the Northern and Southern hemispheres. A - Catalogues -------------- The release contains two multi-lambda catalogues, one for each field: GOODS-North and GOODS-South. ### 1. Column description Column Unit Description -------------- ------ ----------------------------------------------- iau_name GOODS IAU coded object identifier id Sequential id (specific to the catalogue) ra deg Right Ascension dec deg Declination f3p6 uJy IRAC 3.6 um flux density err3p6 uJy Error on IRAC 3.6 um flux density flag3p6 IRAC 3.6 um source extraction flag (see below) f4p5 uJy IRAC 4.5 um flux density err4p5 uJy IRAC 4.5 um flux density flag4p5 IRAC 4.5 um source extraction flag (see below) f5p8 uJy IRAC 5.8 um flux density err5p8 uJy Error on IRAC 5.8 um flux density flag5p8 IRAC 5.8 um source extraction flag (see below) f8p0 uJy IRAC 8.0 um flux density err8p0 uJy Error on IRAC 8.0 um flux density flag8p0 IRAC 8.0 um source extraction flag (see below) f24 uJy MIPS 24 um flux density err24_ima uJy MIPS 24 um flux error on residual map err24_sim uJy MIPS 24 um flux error on Monte-Carlo simulations cov24 MIPS 24 um coverage map value (equal to sec/pixel) f70 uJy MIPS 70 um flux density err70_ima uJy MIPS 70 um flux error on residual map err70_sim uJy MIPS 70 um flux error on Monte-Carlo simulations cov70 MIPS 70 um coverage map value (equal to sec/pixel) f100 uJy PACS 100 um flux density err100_ima uJy PACS 100 um flux error on residual map err100_sim uJy PACS 100 um flux error on Monte-Carlo simulations cov100 PACS 100 um coverage map value (proportional to sec/pixel) f160 uJy PACS 160 um flux density err160_ima uJy PACS 160 um flux error on residual map err160_sim uJy PACS 160 um flux error on Monte-Carlo simulations cov160 PACS 160 um coverage map value (proportional to sec/pixel) f250 uJy SPIRE 250 um flux density err250_ima uJy SPIRE 250 um flux error on residual map err250_sim uJy SPIRE 250 um flux error on Monte-Carlo simulations cov250 SPIRE 250 um coverage map value (proportional to sec/pixel) f350 uJy SPIRE 350 um flux density err350_ima uJy SPIRE 350 um flux error on residual map err350_sim uJy SPIRE 350 um flux error on Monte-Carlo simulations cov350 SPIRE 350 um coverage map value (proportional to sec/pixel) f500 uJy SPIRE 500 um flux density err500_ima uJy SPIRE 500 um flux error on residual map err500_sim uJy SPIRE 500 um flux error on Monte-Carlo simulations cov500 uJy SPIRE 500 um coverage map value (proportional to sec/pixel) clean_index Index measuring flux contamination from nearby sources (see below) On GOODS-South, the catalogue has no SPIRE measurements (columns f250 to cov500). ### 2. Notes on some column contents #### a. error columns Please, read the GOODS-Herschel release document for a complete description of the two noise estimations: errNNN_ima based on the residual map and errNNN_sim based on Monte-Carlo simulations. In particular, to be conservative, users should always use the highest uncertainty but not the quadratic combination of both since they are not independent. Also, the Monte-Carlo simulations were made on regions with relatively homogeneous exposure time; therefore, uncertainties derived from these simulations are not suitable and hence not provided for sources situated outside these homogeneous exposure time regions. #### b. IRAC source extraction flag The IRAC source extraction flag come from the IRAC flag maps as described in the GOODS project DR1 documentation. It's a composite flag based on the values from the table below. Flag value Condition ------------ ------------------------------------------- 0 > 50% of the modal exposure time 1 < 50% of the modal exposure time 2 < 20% of the modal exposure time 16 Region with significant residual muxbleed 64 No data (zero retained exposure time) These values will often appear in combination. For example, regions with < 20% of the modal exposure time (flag value 2) also have < 50% of the modal exposure time (flag value 1). Therefore, those sources will have flag values of 2 + 1 = 3. Regions with no data will have flag values 64 + 2 + 1 = 67. Regions with residual muxbleed (flag 16) and also < 50% modal exposure time (flag 1) will have flag 16 + 1 = 17. #### c. clean_index The clean_index measures the flux contamination by nearby sources. It is computed as follows: clean_index = Neib24 + Neib100 × 10 + Neib160 × 100 + Neib250 × 1.000 + Neib350 × 10.000 + Neib500 × 100.000 Where Neib24 (resp. Neib100, Neib160…) is the number of bright neighbours (see the GOODS-Herschel release document) at 24 um (resp. 100 um 160 um…). On GOODS-South, it is assumed that Neib250 = Neib350 = Neib500 = 0. B - Maps -------- For each Herschel filter (PACS100, PACS160, SPIRE250, SPIRE350 and SPIRE500 on GOODS-North; only PACS bands on GOODS-South) we provide three four fits files: - GH_(field)_(version)_(lambda)_sci.fits: the flux map - GH_(field)_(version)_(lambda)_err.fits: the error map - GH_(field)_(version)_(lambda)_cov.fits: the coverage map - GH_(field)_(version)_(lambda)_psf.fits: the PSF of the map