The ROSAT Deep Surveys in the direction of the Lockman Hole are the most sensitive X-ray surveys performed with the ROSAT satellite. About 70-80% of the X-ray background has been resolved into discrete sources at a flux limit of ∼10-15 erg cm-2 s-1 in the 0.5-2.0 keV energy band. A nearly complete optical identification of the ROSAT Deep Survey (RDS) has shown that the great majority of sources are AGNs. We describe in this paper the ROSAT Ultra Deep Survey (UDS), an extension of the RDS in the Lockman Hole. The Ultra Deep Survey reaches a flux level of 1.2 10-15 erg cm-2 s-1 in 0.5-2.0 keV energy band, a level ∼4.6 times fainter than the RDS. We present nearly complete spectroscopic identifications (90%) of the sample of 94 X-ray sources based on low-resolution Keck spectra. The majority of the sources (57) are broad emission line AGNs (type I), whereas a further 13 AGNs show only narrow emission lines or broad Balmer emission lines with a large Balmer decrement (type II AGNs) indicating significant optical absorption. The second most abundant class of objects (10) are groups and clusters of galaxies (∼11%). Further we found five galactic stars and one "normal" emission line galaxy. Eight X-ray sources remain spectroscopically unidentified. We see no evidence for any change in population from the RDS survey to the UDS survey. The photometric redshift determination indicates in three out of the eight sources the presence of an obscured AGN. Their photometric redshifts, assuming that the spectral energy distribution (SED) in the optical/near-infrared is due to stellar processes, are in the range of 1.2 ≤ z ≤ 2.7. These objects could belong to the long-sought population of type 2 QSOs, which are predicted by the AGN synthesis models of the X-ray background. Finally, we discuss the optical and soft X-ray properties of the type I AGN, type II AGN, and groups and clusters of galaxies, and the implication to the X-ray background.
All Science Journal Classification (ASJC) codes
- Astronomy and Astrophysics
- Space and Planetary Science