The Chandra X-ray point source catalog in the DEEP2 Galaxy Redshift Survey fields
A. D. Goulding (1), W. R. Forman (1), R. C. Hickox (2), C. Jones (1),, R. Kraft (1), S. S. Murray (1,3), A. Vikhlinin (1), A. L. Coil (4), M. C., Cooper (5), M. Davis (6), J. A. Newman (7) ((1) CfA, (2) Dartmouth, (3) JHU,, (4) UCSD, (5) UCI, (6) UCB, (7) Pittsburgh)

TL;DR
This paper presents a comprehensive catalog of X-ray point sources detected in the DEEP2 Galaxy Redshift Survey fields using Chandra, including source counts, distribution analysis, and optical counterpart identification, aiding studies of X-ray sources and galaxy evolution.
Contribution
The study provides the first extensive X-ray point-source catalog for the DEEP2 fields, with detailed source counts, distribution analysis, and a novel Bayesian method for optical counterpart association.
Findings
2976 X-ray sources detected with ~1% false positives.
Good agreement of source counts with other deep fields.
71.4% of X-ray sources have secure optical counterparts.
Abstract
We present the X-ray point-source catalog produced from the Chandra Advanced CCD Imaging Spectrometer (ACIS-I) observations of the combined \sim3.2 deg2 DEEP2 (XDEEP2) survey fields, which consist of four ~0.7-1.1 deg2 fields. The combined total exposures across all four XDEEP2 fields range from ~10ks-1.1Ms. We detect X-ray point-sources in both the individual ACIS-I observations and the overlapping regions in the merged (stacked) images. We find a total of 2976 unique X-ray sources within the survey area with an expected false-source contamination of ~30 sources (~1%). We present the combined logN-logS distribution of sources detected across the XDEEP2 survey fields and find good agreement with the Extended Chandra Deep Field and Chandra-COSMOS fields to f_{X,0.5-2keV}\sim2x10^{-16} erg/cm^2/s. Given the large survey area of XDEEP2, we additionally place relatively strong constraints…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
