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# Nearly all the sky is covered by Lyman-α emission around high-redshift galaxies

### Subjects

An Author Correction to this article was published on 30 October 2018

## Abstract

Galaxies are surrounded by large reservoirs of gas, mostly hydrogen, that are fed by inflows from the intergalactic medium and by outflows from galactic winds. Absorption-line measurements along the lines of sight to bright and rare background quasars indicate that this circumgalactic medium extends far beyond the starlight seen in galaxies, but very little is known about its spatial distribution. The Lyman-α transition of atomic hydrogen at a wavelength of 121.6 nanometres is an important tracer of warm (about 104 kelvin) gas in and around galaxies, especially at cosmological redshifts greater than about 1.6 at which the spectral line becomes observable from the ground. Tracing cosmic hydrogen through its Lyman-α emission has been a long-standing goal of observational astrophysics1,2,3, but the extremely low surface brightness of the spatially extended emission is a formidable obstacle. A new window into circumgalactic environments was recently opened by the discovery of ubiquitous extended Lyman-α emission from hydrogen around high-redshift galaxies4,5. Such measurements were previously limited to especially favourable systems6,7,8 or to the use of massive statistical averaging9,10 because of the faintness of this emission. Here we report observations of low-surface-brightness Lyman-α emission surrounding faint galaxies at redshifts between 3 and 6. We find that the projected sky coverage approaches 100 per cent. The corresponding rate of incidence (the mean number of Lyman-α emitters penetrated by any arbitrary line of sight) is well above unity and similar to the incidence rate of high-column-density absorbers frequently detected in the spectra of distant quasars11,12,13,14. This similarity suggests that most circumgalactic atomic hydrogen at these redshifts has now been detected in emission.

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## Data availability

The observations of the HUDF discussed in this paper were made using European Southern Observatory (ESO) Telescopes at the La Silla Paranal Observatory under programme IDs 094.A-0289, 095.A-0010, 096.A-0045 and 096.A-0045. The corresponding data are available on the ESO archive at http://archive.eso.org/cms.html. The data of the HDFS were obtained during MUSE commissioning observations and are available at http://muse-vlt.eu/science/hdfs-v1-0/.

## Change history

• ### 30 October 2018

Change history: In this Letter, author M. Akhlaghi should be associated with affiliation (2) rather than (3). This error has been corrected online.

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## Acknowledgements

We thank the ESO staff for the support that made these observations possible. L.W., J.K., R.S. and T.U. acknowledge support by the Competitive Fund of the Leibniz Association through grants SAW-2013-AIP-4 and SAW-2015-AIP-2. R.B., H.I., F.L. and M.A. are supported by the ERC advanced grant 339659-MUSICOS. J.B. acknowledges support by FCT grants UID/FIS/04434/2013 and IF/01654/2014/CP1215/CT0003 and by FEDER through COMPETE2020 (POCI-01-0145-FEDER-007672). J.R. acknowledges support from the ERC starting grant 336736-CALENDS. P.M.W. received support through BMBF Verbundforschung, grant 05A17BAA. T.C., N.B. and B.G. acknowledge support by ANR FOGHAR (ANR-13-BS05-0010-02). T.C. and N.B. were also supported by OCEVU Labex (ANR-11-LABX-0060), and by the A*MIDEX project (ANR-11-IDEX-0001-02) funded by the “Investissements d’avenir” French government programme. A.M.I. acknowledges support from MINECO through project AYA2015-68217-P. S.C. acknowledges support from Swiss National Science Foundation grant PP00P2_163824.

### Reviewer information

Nature thanks G. Micheva and the other anonymous reviewer(s) for their contribution to the peer review of this work.

## Author information

Authors

### Contributions

L.W. conceived the project. R.B. led the data acquisition and data reduction. R.B., J.B., E.C.H., H.I., J.K., K.B.S., T.U. and L.W. developed and performed the sample selection. L.W. analysed the data, with input from R.B., J.B. and P.M.W. S.C., P.R., J.S., M.S. and L.W. worked on the interpretation of the results. L.W. wrote the manuscript and produced the figures, with K.B.S. contributing to their design. All coauthors provided critical feedback to the text and helped shape the manuscript.

### Corresponding author

Correspondence to L. Wisotzki.

## Ethics declarations

### Competing interests

The authors declare no competing interests.

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

## Extended data figures and tables

### Extended Data Fig. 1 Spatial distribution and redshifts of the Lyα emitter sample.

a, The region observed with MUSE in the Hubble Ultra Deep Field (HUDF), b, the same for the Hubble Deep Field South (HDFS). Each Lyα emitter is represented by a circle colour-coded by redshift (key at right) and with a radius scaled by the integrated Lyα flux of the object. α, right ascension; δ, declination. The objects shown here constitute the full sample. There are several cases of significant crowding of unequal-redshift objects separated by less than a few arcseconds in projection. The underlying greyscale images show the two fields as seen with the HST.

### Extended Data Fig. 2 Lyα sky coverage from direct projection.

ac, Data from HUDF; df, data from HDFS. Greyscale images display the projected and coadded Lyα emission over the redshift range 3 < z < 6 separately for the two observed fields: ad, without any spatial filtering; be, after Gaussian filtering with FWHM = 1.4″. The image b is identical to the blue overlay in Fig. 1. The light brown areas delineate the MUSE field of view and indicate masked bright foreground objects. cf, the resulting fractional sky coverage; the black dashed line representing the unfiltered images and the thick black solid line representing the spatially filtered images. The thin grey line shows the result from the stacking analysis (Fig. 3) for comparison, and the thick grey line is a fiducial reconstruction of the sky coverage derived from a noisy and filtered version of the stacking-based model images. See the discussion in Methods for an interpretation of these figures.

### Extended Data Fig. 3 Number of images contributing to the median stacks.

ac, Data for redshift ranges 3 < z < 4 (a), 4 < z <5 (b) and 5 < z < 6 (c). The colour code represents, for each pixel in a median-stacked image, the number of original image pixels contributing to it. This number differs from the total number of objects in a given stack because of the masks applied to several of the contributing images.

### Extended Data Fig. 4 Error calibration and sensitivity of azimuthally averaged profiles.

Shown are ‘zoom views’ into the profiles (surface brightness versus radial distance) at very low surface brightnesses, with linear ordinate scaling so that negative measurements can be displayed. Data for three redshift ranges are shown: top, 3 < z < 4; middle, 4 < z < 5; and bottom, 5 < z < 6. The small open circles represent the surface brightnesses measured in 40 realizations of a median-stacking analysis of empty regions as described in Methods. The filled symbols reproduce the data points from Fig. 2c. The horizontal bars again indicate the widths of the annuli, and the vertical error bars are based on the 1σ scatter of the empty field median-stack profiles; these were also adopted as error bars for the data points in Fig. 2c.

### Extended Data Fig. 5 A test of the self-similarity assumption for different Lyα luminosities.

ac, Comparison of azimuthally averaged radial profiles of median-stacked Lyα images above a minimum Lyα luminosity L (open circles) and with no such cut (‘full sample’, filled circles), for three redshift ranges (top, 3 < z < 4; middle, 4 < z < 5; and bottom, 5 < z < 6). As in Fig. 2, the vertical bars on the data points quantify the 1σ surface brightness measurement errors, while the horizontal bars (drawn only for the filled symbols) indicate the widths of the annuli. Inverted triangles indicate upper limits. The right-hand ordinate provides the conversion from apparent surface brightnesses to redshift-corrected surface luminosities, evaluated at the central redshift of each bin.

### Extended Data Fig. 6 Comparison of approaches to determine the Lyα emission incidence rates.

Each panel shows the cumulative incidence rate as a function of limiting surface luminosity for the specified redshift range (left, 3 < z < 4; middle, 4 < z < 5; and right, 5 < z < 6), estimated by different methods: direct summation of Lyα cross-sections over the sample without correcting for incompleteness (equation (1) in the Methods section, thin lines), and integrating over the completeness-corrected luminosity function following equation (2) in the Methods section, using lower integration limits of min= 41.0 (best guess, thick solid line) and min = 40.0 (asymptotic case, dashed line), respectively. The shaded error bands for direct summation are dominated by field-to-field variance between the HUDF and the HDFS, with the upper envelope tracing the HUDF and the lower envelope tracing the HDFS results. For the luminosity function integration the error bands on these curves incorporate only the statistical uncertainties of the median-stacked profiles. The two thick dotted lines indicate the finally adopted lower and upper 2σ bounds on the ‘best guess’ results shown in Fig. 4.

### Extended Data Fig. 7 Cumulative contributions to incidence rates for different radii.

Each panel (left, 3 < z < 4; middle, 4 < z < 5; and right, 5 < z < 6) shows the cumulative fractional contributions of objects with different isophotal radii to the integrated Lyα emission cross-section dn/dz, using equation (2) with min = 41. The four lines in each panel represent, from left to right and with decreasing line width, surface luminosity limits log10[SLyα (erg s−1 kpc−2)] = 38.5, 38, 37.5, 37.

### Extended Data Fig. 8 Bias of estimated cross-sections if the emission is non-axisymmetric.

a, Model image of an elongated surface brightness distribution, normalized to an integrated flux of 1, following an elliptical Sersic law with axis ratio q = 0.5 and smoothed with a Gaussian of 0.8″ FWHM. The colour code represents relative surface brightness (SB), and the red-dashed contours trace the isophotes at 0.5 dex separation. The black circles represent the radii where an azimuthally averaged profile over circular annuli gives the same surface SB values as the corresponding isophote. b, Radial profiles of the model image. The red-dashed line represents the input SB law as a function of generalized radius $${r}_{{\rm{ell}}}=\sqrt{ab}$$ where a, b are the major and minor axes of an isophote. The black line shows the profile obtained from azimuthal averaging over circular annuli against radius rc. c, Ratios between the true isophotal cross-sections πab and those estimated from the circularized profile as $${\rm{\pi }}{r}_{{\rm{c}}}^{2}$$ (that is, the ratios of the areas of the black circles and the corresponding red-dashed ellipses in b), as a function of surface brightness. d, Median-stacked image of an ensemble of 180 model objects with properties each as in a, but rotated in position angle between 0° and 180° in steps of 1°. The colour code again represents relative SB, and the black circles show the resulting isophotes at 0.5 dex separation. e, The black line traces the radial profile of the median-stacked image in d. The red-dashed line is the true elliptical SB distribution of a single object (same as in b). f, Ratios of cross-sections obtained from the median stack to the true isophotal ones in a single image, as a function of surface brightness.

## Supplementary information

### Supplementary Information

This file contains a description of the Supplementary Data .csv file.

### Supplementary Data

This file contains a catalogue of the sample of objects (Lyman-α emitters) used in this study.

## Rights and permissions

Reprints and Permissions

Wisotzki, L., Bacon, R., Brinchmann, J. et al. Nearly all the sky is covered by Lyman-α emission around high-redshift galaxies. Nature 562, 229–232 (2018). https://doi.org/10.1038/s41586-018-0564-6

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### Keywords

• Surface Brightness Levels
• Multi Unit Spectroscopic Explorer (MUSE)
• Hubble Ultra Deep Field (HUDF)
• Hubble Deep Field South (HDFS)
• Median Stacking

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