For this comparison we rely on HST broad-band magnitudes, Lyα line fluxes, Lyα EW0 estimates, spectral UV slopes β, continuum magnitudes, and Lyα FWHM from the catalog that will be presented by Kerutt et al. (2021). This LAE study is based on the same data and source identification (see Sect. 3) as the current study, but focuses on properties of the emanating Lyα emission. The Lyα emission fluxes correspond to the measured flux within 3D apertures of three Kron (1980) radii as measured by LSDCat when detecting sources in the MUSE data cubes. We use these Lyα fluxes as opposed to obtaining them directly from the TDOSE spectra, as the TDOSE extractions are based on the assumption that the morphological extent of the line emission follows the continuum morphology of the modeled HST images (Sect. 4 and Schmidt et al. 2019). However, Lyα emission is known to be extended beyond the continuum (Steidel et al. 2011; Momose et al. 2014; Wisotzki et al. 2016, 2018; Leclercq et al. 2017, 2020) and fluxes based on the TDOSE spectra would therefore be biased. The LSDCat Kron radii fluxes therefore better represents the actual Lyα flux emitted by the LAEs. As for the secondary UV emission lines, the EW0(Lyα) values were calculated by comparing the fluxes to the continuum flux densities estimated from a continuum represented by a power law fλ ∝ λβ. To obtain the spectral slope, Kerutt et al. (2021) first determined the magnitudes from available ancillary broad-band HST photometry, by fitting the rest-frame UV morphology for each of the LAEs using GALFIT (Peng et al. 2010, 2002). This provided morphological parameters for all LAEs including a measure of their effective radius. The estimated absolute UV magnitude at 1500 Å is also based on these GALFIT models. The spectral slope β was then obtained from fitting the continuum power law to the GALFIT-based HST magnitudes. To avoid large scatter in the EW0 measurements presented and analyzed by Kerutt et al. (2021), the EWs are based on the median β for the full LAE sample of β = −1.97 similar to what was done for the secondary UV emission lines presented here. The FWHM of the Lyα emission was measured for each source by fitting a skewed Gaussian profile (Eq. (2) by Shibuya et al. 2014) to the Lyα line profiles in 1D spectral extractions weighted by the MUSE PSF to maximize S/N. These fits also provide a Lyα redshift which is more precise than the lead line redshits provided by the LSDCat source identification. We therefore use these redshifts for the analysis of the Lyα velocity offsets described in Sect. 8. Finally, Kerutt et al. (2021) provide estimates of the systemic redshifts based on the FWHM and peak separation between any double-peaked LAEs (identified through visual inspection of the 1D spectra) in the sample based on the empirical relations presented by Verhamme et al. (2018). We note that a handful of the z > 2.9 objects studied here are not included in the Kerutt et al. (2021) catalog, as their selection was based only on non-AGN objects with leading Lyα emission based on the LSDCat selections (Sect. 3). Hence, for z > 2.9, the objects with IDs 121033078, 601381485, 720470421, 722551008, 722731033, and 723311101 are not included in the LAE parameter comparisons in the following. For further details and for the full value-added catalog of Lyα-related quantities we refer to Kerutt et al. (2021).
Citation: Leclercq et al. 2017
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