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We present the MUSE-Wide survey, a blind, 3D spectroscopic survey in the CANDELS/GOODS-S and CANDELS/COSMOS regions. Each MUSE-Wide pointing has a depth of 1 hour and hence targets more extreme and more luminous objects over 10 times the area of the MUSE-Deep fields (Bacon et al. 2017). The legacy value of MUSE-Wide lies in providing "spectroscopy of everything" without photometric pre-selection. We describe the data reduction, post-processing and PSF characterization of the first 44 CANDELS/GOODS-S MUSE-Wide pointings released with this publication. Using a 3D matched filtering approach we detected 1,602 emission line sources, including 479 Lyman-α (Lya) emitting galaxies with redshifts 2.9≲z≲6.3. We cross-match the emission line sources to existing photometric catalogs, finding almost complete agreement in redshifts and stellar masses for our low redshift (z < 1.5) emitters. At high redshift, we only find ~55% matches to photometric catalogs. We encounter a higher outlier rate and a systematic offset of Δz≃0.2 when comparing our MUSE redshifts with photometric redshifts. Cross-matching the emission line sources with X-ray catalogs from the Chandra Deep Field South, we find 127 matches, including 10 objects with no prior spectroscopic identification. Stacking X-ray images centered on our Lya emitters yielded no signal; the Lya population is not dominated by even low luminosity AGN. A total of 9,205 photometrically selected objects from the CANDELS survey lie in the MUSE-Wide footprint, which we provide optimally extracted 1D spectra of. We are able to determine the spectroscopic redshift of 98% of 772 photometrically selected galaxies brighter than 24th F775W magnitude. All the data in the first data release - datacubes, catalogs, extracted spectra, maps - are available at the website.
AfricaRice is a leading pan-African rice research organization committed to improving livelihoods in Africa through strong science and effective partnerships. AfricaRice dataverse makes studies in rice research open availabe. With the focus on agronomy, breeding, entomoloy, grain quality, pathology, physiology and socio-economics of rice.
In order to meet the needs of research data management for Peking University. The PKU library cooperate with the NSFC-PKU data center for management science, PKU science and research department, PKU social sciences department to jointly launch the Peking University Open Research Data Platform. PKU Open research data provides preservation, management and distribution services for research data. It encourage data owner to share data and data users to reuse data.