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).

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-λ 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 µJy IRAC 3.6 µm flux density
err3p6 µJy Error on IRAC 3.6 µm flux density
flag3p6   IRAC 3.6 µm source extraction flag (see below)
f4p5 µJy IRAC 4.5 µm flux density
err4p5 µJy IRAC 4.5 µm flux density
flag4p5   IRAC 4.5 µm source extraction flag (see below)
f5p8 µJy IRAC 5.8 µm flux density
err5p8 µJy Error on IRAC 5.8 µm flux density
flag5p8   IRAC 5.8 µm source extraction flag (see below)
f8p0 µJy IRAC 8.0 µm flux density
err8p0 µJy Error on IRAC 8.0 µm flux density
flag8p0   IRAC 8.0 µm source extraction flag (see below)
f24 µJy MIPS 24 µm flux density
err24_ima µJy MIPS 24 µm flux error on residual map
err24_sim µJy MIPS 24 µm flux error on Monte-Carlo simulations
cov24   MIPS 24 µm coverage map value (equal to sec/pixel)
f70 µJy MIPS 70 µm flux density
err70_ima µJy MIPS 70 µm flux error on residual map
err70_sim µJy MIPS 70 µm flux error on Monte-Carlo simulations
cov70   MIPS 70 µm coverage map value (equal to sec/pixel)
f100 µJy PACS 100 µm flux density
err100_ima µJy PACS 100 µm flux error on residual map
err100_sim µJy PACS 100 µm flux error on Monte-Carlo simulations
cov100   PACS 100 µm coverage map value (proportional to sec/pixel)
f160 µJy PACS 160 µm flux density
err160_ima µJy PACS 160 µm flux error on residual map
err160_sim µJy PACS 160 µm flux error on Monte-Carlo simulations
cov160   PACS 160 µm coverage map value (proportional to sec/pixel)
f250 µJy SPIRE 250 µm flux density
err250_ima µJy SPIRE 250 µm flux error on residual map
err250_sim µJy SPIRE 250 µm flux error on Monte-Carlo simulations
cov250   SPIRE 250 µm coverage map value (proportional to sec/pixel)
f350 µJy SPIRE 350 µm flux density
err350_ima µJy SPIRE 350 µm flux error on residual map
err350_sim µJy SPIRE 350 µm flux error on Monte-Carlo simulations
cov350   SPIRE 350 µm coverage map value (proportional to sec/pixel)
f500 µJy SPIRE 500 µm flux density
err500_ima µJy SPIRE 500 µm flux error on residual map
err500_sim µJy SPIRE 500 µm flux error on Monte-Carlo simulations
cov500 µJy SPIRE 500 µm 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 µm (resp. 100 µm 160 µm…). 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