PEP PACS and MIPS Cross-IDs Catalog Definitions
Overview
The PACS Evolutionary Probe (PEP, Lutz et al. 2011) is a Herschel guaranteed time deep extragalactic survey (KPGT_dlutz_1) targeting six among the most popular "blank fields", ten lensing clusters of galaxies, and two z ~1 clusters at wavelengths of 100, and 160 microns. PEP includes SPIRE observations of the two z ~1 clusters at wavelengths of 250, 350, and 500 microns. SPIRE coverage of all other fields is available from the HerMES survey (Oliver et al. 2010). In addition, deep SPIRE GOODS-N data are provided by the GOODS-Herschel program (Elbaz et al. 2011).
The PACS blind catalogs extracted using Starfinder have been matched to the available 24 micron source lists by means of a maximum likelihood analysis (Ciliegi et al. 2001; Sutherland & Saunders 1992), taking advantage of the available 24 micron fluxes. See the documentation for details.
| Name | Intype | Units | Description |
|---|---|---|---|
| ra | double | deg | Right Ascension (J2000) |
| dec | double | deg | Declination (J2000) |
| idp160 | int | PACS 160 micron ID number | |
| flux_160 | double | jy | PACS 160 micron flux density |
| err_160 | double | jy | Uncertainty in flux_160 |
| ra_160 | double | deg | RA of PACS 160 micron detection |
| dec_160 | double | deg | Dec of PACS 160 micron detection |
| idp100 | int | PACS 100 micron ID number | |
| flux_100 | double | jy | PACS 100 micron flux density |
| err_100 | double | jy | Uncertainty in flux_100 |
| ra_100 | double | deg | RA of PACS 100 micron detection |
| dec_100 | double | deg | Dec of PACS 100 micron detection |
| idm24 | int | MIPS 24 micron ID number | |
| flux_24 | double | mjy | MIPS 24 micron flux density |
| err_24 | double | mjy | Uncertainty in flux_24 |
| ra_24 | double | deg | RA of MIPS 24 micron detection |
| dec_24 | double | deg | Dec of MIPS 24 micron detection |
| acf | c | Area Coverage Flag: N = PACS source lies outside the MIPS 24 micron map A = PACS source lies inside the MIPS 24 micron map |
|
| cln | int | Clean Index: 24 micron neighbors + 10*(100 micron neighbors) + 100*(160 micron neighbors); see documentation. |