The nature of luminous Lyman-alpha emitters at z~2-3: maximal dust-poor starbursts and highly ionising AGN
David Sobral Jorryt Matthee Behnam Darvish Ian Smail Philip N. Best Lara Alegre Huub Röttgering Bahram Mobasher Ana Paulino-Afonso Andra Stroe Iván Oteo


firstpage–lastpage
Alignment between satellite and central galaxies in the SDSS DR7: dependence on large-scale environment
    Peng Wang1,2,3,
Yu Luo1,
Xi Kang1,
Noam I. Libeskind2,
Lei Wang1,
Youcai Zhang4,
Elmo Tempel2,5,
Quan Guo6
    Received: date / Accepted: date
==============================================================================================================





Deep narrow-band surveys have revealed a large population of faint Lyα emitters (LAEs) in the distant Universe, but relatively little is known about the most luminous sources (L_ Lyα 10^42.7 erg s^-1; L_ Lyα L^*_ Lyα). Here we present the spectroscopic follow-up of 21 luminous LAEs at z∼2-3 found with panoramic narrow-band surveys over five independent extragalactic fields (≈4×10^6 Mpc^3 surveyed at z∼2.2 and z∼3.1). We use WHT/ISIS, Keck/DEIMOS and VLT/X-SHOOTER to study these sources using high ionisation UV lines. Luminous LAEs at z∼ 2–3 have blue UV slopes (β=-2.0^+0.3_-0.1), high Lyα escape fractions (50^+20_-15%) and span five orders of magnitude in UV luminosity (M_UV≈-19 to -24). Many (70%) show at least one high ionisation rest-frame UV line such as Civ, Nv, Ciii], Heii or Oiii], typically blue-shifted by ≈100-200 km s^-1 relative to Lyα. Their Lyα profiles reveal a wide variety of shapes, including significant blue-shifted components and widths from 200 to 4000 km s^-1. Overall, 60±11 % appear to be AGN dominated, and at L_ Lyα>10^43.3 erg s^-1 and/or M_UV<-21.5 virtually all LAEs are AGN with high ionisation parameters (log U=0.6±0.5) and with metallicities of ≈0.5-1 Z_⊙. Those lacking signatures of AGN (40±11 %) have lower ionisation parameters (log U=-3.0^+1.6_-0.9 and logξ_ ion=25.4±0.2) and are apparently metal-poor sources likely powered by young, dust-poor “maximal" starbursts. Our results show that luminous LAEs at z∼ 2–3 are a diverse population and that 2× L^*_ Lyα and 2× M_ UV^* mark a sharp transition in the nature of LAEs, from star formation dominated to AGN dominated.
 



Galaxies: high-redshift; evolution; ISM; starburst; active; Cosmology: observations. 




§ INTRODUCTION


There has been a steady increase in the number of sources identified at moderately high redshifts (z 2–3) over the past twenty years (e.g. ). Most have been found using the Lyman-break technique <cit.>, combined with deep, multi-band imaging with the Hubble Space Telescope (HST). However, spectroscopy of faint continuum-selected candidates has progressed at a much slower pace as spectroscopic continuum detections are difficult for such faint sources. A different approach is to find and study sources with bright Lyα in emission <cit.> across a range of redshifts <cit.>. While these can now be found with wide-field ground-based surveys <cit.>, much is unknown about their nature, metallicity and stellar populations <cit.>.

Significant spectroscopic progress has also been made by targeting lensed galaxies <cit.>, allowing the detection and study of intrinsically very faint lines. Combining results from intrinsically bright and faint sources reveals a picture in which galaxies appear to have ubiquitous high equivalent width nebular emission lines at high redshift <cit.>. This may be due to high redshift galaxies producing more ionising photons per UV luminosity <cit.>. Recent results also highlight that high redshift galaxies can have hard ionising spectra, as indicated by UV emission lines such as Ciii], Civ, Oiii] or Heii <cit.>. This is in agreement with more detailed, larger statistics results, which show an increase in the ionisation parameter with redshift, traced by e.g. [Oiii]/[Oii] <cit.> or evidence for hard spectra from iron-poor stellar populations <cit.>. Understanding the origin of the strong evolution relative to local galaxies is still a major open question. Many mechanisms/physical processes have been proposed, including binary stars, bursty star formation histories, active galactic nuclei and several effects at low metallicity <cit.>.

Furthermore, the common approach of selecting Lyman-break galaxies has resulted in statistically large samples, but failed to reveal a convincing population of Lyman continuum (LyC) leakers <cit.>, required for re-ionisation <cit.>. This may be a consequence of selection, as Lyman-break galaxies (LBGs) are biased against sources leaking significant amounts of LyC photons <cit.>. LBGs tend to be more evolved and show little to no Lyα in emission <cit.>. In addition, recent theoretical and observational work suggest an important link between LyC and Lyα escape fractions <cit.>, implying that Lyα emitters (LAEs) contribute significantly to the LyC luminosity density. The faint end slope of the Lyα luminosity function (LF) is steep (α∼-2), implying a large number of faint LAEs <cit.> and LAEs produce typically many more ionising photons per UV luminosity than LBGs <cit.>. The combination of recent results on LAEs is particularly promising and further enhances the motivation to study those: the high equivalent width (EW) LAEs may be exactly what is needed to re-ionise the Universe, having “high” escape fractions <cit.>, high production of ionising photons <cit.>, and large number densities <cit.>.

Despite recent progress, little is known about the nature and redshift evolution of the most luminous LAEs (L_ Lyα∼10^43-44.5 erg s^-1). At z∼ 2–3 spectroscopic studies have mostly focused on the follow-up of fainter, more numerous LAEs typically below the characteristic Lyα (L_ Lyα≲10^43 erg s^-1) and UV luminosities at that redshift <cit.>, or by blindly finding and studying faint LAEs with deep but small volume searches with IFU instruments such as MUSE <cit.>. Important progress has also been made by studying extremely rare quasars found with SDSS <cit.>, ≈7-10 orders of magnitude brighter in the UV and revealing large Lyα haloes with L_ Lyα∼10^43-44 erg s^-1 <cit.>. Still, little is known about the general population of bright LAEs, although there is some evidence for these sources to have a significant AGN contribution <cit.>.

In this paper we study bright LAEs at z∼ 2–3 through relatively deep spectroscopic follow-up, in order to unveil their nature and physical properties. These bright sources span the parameter space between faint LAEs and rare quasars. The paper is organised as follows. In <ref> we present the observations of our sample of bright Lyα candidates with WHT/ISIS, Keck/DEIMOS and VLT/X-SHOOTER, followed by the respective data reduction. In <ref> we present the measurements and analysis. Results are presented in <ref>. The nature of bright LAEs is studied in <ref>, based on high ionisation UV lines. We discuss our results in <ref>. Conclusions are presented in <ref>. Throughout this paper, we use AB magnitudes <cit.>, a Salpeter <cit.> IMF and a ΛCDM cosmology with H_0=70 km s^-1 Mpc^-1, Ω_ M=0.3 and Ω_Λ=0.7.





§ OBSERVATIONS AND DATA REDUCTION
 



 §.§ Sample selection


Our luminous LAEs are selected from wide-field narrow-band Lyα surveys. Candidate bright LAEs at z∼2.2 are selected from the 1.43 deg^2 CALYMHA survey <cit.>. We select those with Lyα luminosities above 10^42.8 erg s^-1 (up to 10^43.6 erg s^-1); see Figure <ref>. Luminous z∼3.1 Lyα candidates are selected from a total of ∼3.1 deg^2 over the GOODS-N, SA22 and Boötes fields <cit.> to have luminosities in excess of 10^42.7 erg s^-1 (up to 10^44.2 erg s^-1). Our targets have number densities of 10^-4–10^-6 Mpc^-3 <cit.>, and have been found in a total volume of ≈4×10^6 Mpc^3. We note that due to the selection applied to obtain candidate LAEs from the full sample of emission line candidates <cit.> our samples will be biased against potential (galaxy-galaxy) lensed sources, as the continuum of the foreground lens will lead to classifying lensed LAEs as low redshift interlopers. 

In total, we have targeted 23 sources as candidate luminous LAEs. We present their Lyα luminosities and rest-frame Equivalent Widths (EW_0) in Figure <ref>, compared to the parent sample of more typical, lower luminosity LAEs at both z∼2.2 <cit.> and z∼3.1 <cit.>. As Figure <ref> shows, our sample is representative of the most luminous LAEs, covering 1.5 dex in Lyα luminosities (10^42.7-44.2 erg s^-1) and 1.2 dex in rest-frame Lyα EW_0 (20-400 Å).







 




 §.§ Spectroscopic observations




  §.§.§ WHT/ISIS


We used the Intermediate dispersion Spectrograph and Imaging System (ISIS) on the William Herschel Telescope (WHT) to observe z∼ 2–3 Lyα candidates. ISIS is a double-armed, medium-resolution spectrograph, which allows simultaneous observing with the blue and red arms.

A total of six z∼ 2–3 Lyα candidates were selected from GOODS-N and Boötes. We observed each source for roughly one hour during May 4-6 and Jun 30-Jul 01 2016; see Table <ref>. All observations were done under clear conditions and the seeing varied between ∼0.4” and ∼1.5” (typical seeing ≈0.9”). We used a 1” slit for all observations.

The blue and red arms were used with the R600 gratings, with central wavelengths 4800 Å (R∼2400) and 7000 Å (R∼3900) on the first three nights and with the R300B/R316R gratings with central wavelengths 5000 Å (R∼1200) and 8000 Å (R∼2200) for the final two nights. We obtained biases, arcs and flats for each grating, arm and central wavelength, at the start and end of each night.

Our targets are all too faint (typically I∼23-24 mag) in the continuum to be directly acquired using WHT/ISIS, and thus we identified a relatively nearby star (I∼13-16 mag, ∼20-60” away from our target) which we used for acquisition. We conduct our observations by first acquiring the offset star, taking a 30-60 s (depending on its magnitude) exposure on the star, then blindly offsetting the telescope to the target and taking one 900-1000 s exposure of the target. After each science exposure, we go back to the star, offset along the slit by ±10”, acquire the star again, take another star spectrum, and then offset to the science target to take another exposure. This procedure allows us to use the star as a flux calibrator and slit loss estimator. Our procedure also allows us to extract the trace and its curvature in an optimal way, which we use to combine and extract the spectra (see <ref>).




  §.§.§ Keck/DEIMOS


DEIMOS was used to spectroscopically target eight luminous Lyα candidates at z∼3 in five different masks for the Boötes field, and in one mask for GOODS-N over three different nights in June 2, July 6 and July 29 in 2016. We have also observed other line emitters; see Table <ref> and . Observations were conducted under clear conditions. The seeing was in the range ≈0.6”-0.9”. We used a central wavelength of 7200 Å and the 600L grating (R∼2400), with a pixel scale of 0.65 Å pix^-1, which allowed us to probe from 4550 Å to 9850 Å. We used the 0.75” slit, in the same mode as used by <cit.>.

We obtained biases, arcs and flats at the start of each observing night. Typical science exposures of 900 s were obtained with a ±2.5” dithering for two of the nights and without dithering for the final observing night on 30 July 2016. Observations are listed in Table <ref>.



  §.§.§ VLT/X-SHOOTER


We used X-SHOOTER <cit.> to observe eleven candidate luminous z=2.2-3.1 LAEs in October 2016, January, June-July, December 2017 and January 2018 (see Table <ref>). X-SHOOTER allows to simultaneously obtain a relatively high resolution spectrum with the UV/blue (UVB), visible (VIS) and near-infrared (NIR) arms, providing a coverage from 3000 to 24,800 Å. The seeing varied between 0.8” and 1.5” (median seeing 0.9”) and observations were done under clear conditions. We used the low read-out speed without binning. Typical exposure times of 200 s, 300 s and 4×80 s in the UV, optical and NIR arms were used, respectively; see Table <ref>. We first acquired a star (with I-band magnitudes 16-17 AB) and applied a blind offset to the target. We nodded along the slit from an A to a B position (typically 4-6” apart), including a small jitter box in order to always expose on different pixels. We used 1 ” slits for both the optical and near-infrared arms (resolution of R∼2500 and R∼4400, for the optical and near-infrared arms, respectively) and the 1.2 ” slit in the UV (R∼4400). The total exposure times for each source are given in Table <ref>.



 §.§ Data Reduction




  §.§.§ WHT/ISIS: the William Herschel ISIS pipeline


We developed a python pipeline to reduce ISIS spectra[The William Herschel ISIS pipeline (see Appendix <ref>).] and exploit our observing setup/methodology. We reduce the data on a night by night basis, and only combine data from different nights for extracted 1D spectra. Our pipeline follows standard steps: we bias-subtract, flat-field and wavelength-calibrate the spectra using appropriate calibration frames. Additional wavelength calibration is performed by exploiting the sky lines in deep spectroscopic exposures. We describe the processes in more detail in Appendix <ref>. In Figure <ref> we show our reduced 2D spectra, centred on the Lyα line within a window of ±4000 km s^-1.

We flux calibrate our spectra by using the blind offset stars and their SDSS magnitudes. The resolution (FWHM) of each arm/grating is estimated with un-blended sky lines and found to be 2 and 1.8 Å for the R600B/R600R gratings spectra and 4.0 and 3.6 Å FWHM for the R300B/R316R gratings. We bin our 1D spectra by roughly one third of the corresponding FWHM, which, in practice, results in binning by 2 spectral pixels. We show the typical rms per binned resolution element in Table <ref>.







 





  §.§.§ Keck/DEIMOS: spec2d pipeline


All Keck/DEIMOS data were reduced using the DEIMOS spec2d pipeline <cit.>, which follows very similar steps to our WHT/ISIS data reduction. Briefly, each observed spectra were flat-fielded, cosmic-ray-removed, sky-subtracted and wavelength-calibrated <cit.>. We used standard Kr, Xe, Ar and Ne arc lamps for the wavelength calibration. We also checked the wavelength solution at the end of the pipeline reduction, taking advantage of the numerous OH sky lines. For the observations obtained with a dithering pattern, we find significant offsets between the observed sky line positions and the correct OH line wavelengths of over 10-20 Å, varying in a non-linear way in the blue and in the red. Therefore, for all observations for which we dithered we identify ∼100 unblended OH lines and obtain a final wavelength calibration, which produces an rms of ≈0.5 Å, about ∼6-7 times better than the resolution.

For the final night of observations with Keck/DEIMOS, no dithering pattern was used for sky subtraction. Without dithering, the wavelength calibration provided by the pipeline was found to be accurate within 0.5 Å, and no further correction was necessary. We show the reduced 2D spectra in Figure <ref>.

The pipeline also generates the 1D spectrum extraction from the reduced 2D spectrum, following the optimal extraction algorithm of <cit.>. This extraction creates a one-dimensional spectrum of the target, containing the summed flux at each wavelength in an optimised window. We flux calibrate the data with bright enough sources within the masks, and also observations of the Feige 66 standard star. We bin our spectra to one third of the observed resolution (FWHM) of 3 Å (which results in binning 2 spectral pixels, ≈1 Å). Our final resolution binned spectra have a typical rms per binned resolution element (1 σ) of 3-5×10^-19 erg s^-1 cm^-2 Å^-1 (see Table <ref>) and thus typically a factor ∼10 deeper than WHT/ISIS.







 






  §.§.§ VLT/X-SHOOTER: ESO pipeline


We use the ESO X-SHOOTER pipeline <cit.> to reduce the UVB, VIS and NIR spectra separately <cit.>. The data reduction steps follow closely those implemented for both ISIS and DEIMOS data, with the necessary differences, particularly for the X-SHOOTER NIR arm which allow to obtain [Oiii] and Hα for the z∼2.2 LAEs (NIR spectral properties will be fully discussed in Matthee et al. in prep.).

In short, we start by grouping frames. We then identify and process the bias frames (to create master biases in the UVB/VIS arms) and dark current (NIR arm). We produce master flats per arm and flat-field the data. Finally, sky subtraction and wavelength calibration are done. In order to be able to flux calibrate the spectra, several standard stars have been observed (see Table <ref>). We use the X-SHOOTER pipeline to reduce the standard stars in the same way as the science targets and combine the exposures from single observing blocks.

In the case that a source has been observed by multiple observing blocks, we co-add the frames by weighting each frame with the inverse of the variance (noise) in 2D. Corrections for slight positional variations based on the position of the peak of observed Lyα lines were applied. We show the reduced 2D spectra in Figure <ref>, ordered by their narrow-band-derived Lyα luminosity.

We extract 1D spectra by summing the counts in an optimised spatial window, which typically corresponds to a total of ∼10 spatial pixels (1.8”). We use isolated sky lines together with arc lines to find that the resolution of our spectra (FWHM) is 1.6 Å in the UVB and VIS arms and 3.6 Å in the NIR arm. We finally bin our spectra to one third of the FWHM which, in practice, corresponds to binning 3 and 2 spectral pixels for the UVB/VIS and NIR arms, respectively. Table <ref> provides the typical rms per binned resolution element for our binned spectra.






§ MEASUREMENTS AND ANALYSIS
 



 §.§ Spectroscopic redshifts and line identification




All our spectra are calibrated to air wavelengths. Before we determine redshifts, we first convert from air wavelengths to vacuum <cit.>, and then use vacuum rest-frame wavelengths for the rest of the paper (see Table <ref>).

We start by obtaining a redshift using the Lyα emission only (z_ Lyα), and identifying its peak (see Figures <ref>, <ref> and <ref>). We store these as the redshift of the Lyα emission line, and use those as a first approximation of the redshift of the source. We then look for other lines (see Table <ref>) by searching and fitting Gaussians (or double Gaussians) and deriving a redshift for them, allowing for velocity offsets up to ±1000 km s^-1.














 §.§ Contaminants


We confirm that the vast majority (91%) of our 23 candidates are luminous LAEs, but we also find two contaminants. These include one low redshift [Oii] emitter at z=0.056 (CALYMHA-438) and a star with a large number of absorption bands (CALYMHA-85); both with very low EWs (see Figure <ref>). These imply an overall contamination of ≈10 %, likely lower at z=3.1 than at z=2.23 (a consequence of the very low EW cut used for z=2.23; see discussion in ). We further study the potential contamination and completeness of the larger sample of bright narrow-band selected sources from the parent samples <cit.> by using the follow-up of other sources with Keck/DEIMOS <cit.>. Based on one missed real LAE and 2 extra [Oii] contaminants <cit.>, we estimate a conservative contamination of ≈16 % (four contaminants in a sample of 25 sources) at z∼ 2–3 for our parent sample of bright LAEs and a completeness of >90% (only one real LAE missed by our selection).













 §.§ Final Lyα sample


Out of the 23 targeted sources, we spectroscopically confirm 21 as LAEs[For one LAE, BH-NB392-55, we do not have coverage of the Lyα line itself, but rather confirm it through strong Civ emission; see Figure <ref>.], with seven sources at z≈2.2 and 14 sources at z≈3.1. Our final sample of bright LAEs (L_ Lyα10^42.7 erg s^-1; L_ Lyα L^*_ Lyα) is thus composed of 21 sources. We present the sample in Table <ref> and provide both the catalogue and the reduced 1D spectra on-line, with the published version of the paper.







 





 §.§ Line measurements and upper limits


We explore our 1D spectra to fit single Gaussians and/or double Gaussians, depending on whether the emission is a doublet or not (Table <ref>). When fitting a double Gaussian, we fix the doublet separation and set the FWHM to be the same for both lines. In order to avoid problems with OH sky lines and very low signal to noise (S/N) regions of the spectra, we mask regions with the strongest OH lines. We perturb each spectra in a window of ±4000 km s^-1 around each line being evaluated (see Table <ref>) by independently varying each spectral element/data-point along their Gaussian probability (flux) and re-fit. We do this 10,000 times per source and per line and take the median, 16th and 84th percentiles as the best values and the lower and upper errors. We also compute the 0.6th and 99.4th percentiles, roughly corresponding to -2.5 σ to +2.5 σ. Whenever the flux of the 0.6th percentile of a given line is consistent with zero or below we assign that line its 99.4th flux percentile as an upper limit. Table <ref> provides the list of the lines that we use. As a further step, we visually inspect all lines and the best fits.

Not surprisingly, our most significant line is Lyα, with a median S/N (integrated) of ∼20 (ranging from ∼4 to ∼60) across the entire sample and all instruments. The second most common line at high S/N is Civ (see Table <ref>) significantly detected in about half of the sample with a S/N from ∼3 to ∼30. Other high ionisation UV lines like Nv, Heii and Ciii] are detected in ∼4-6 sources at typical S/N of ∼3-10 (BR3 yields S/N ratios of up to 50 in these lines). Niv is only significantly detected with a S/N ∼7 in BH-NB5-4 (BR3), although tentatively detected at S/N∼2.5 in another source; see Tables <ref> and <ref>.




 §.§ UV luminosities and UV β slope


We compute the UV luminosity at rest-frame ≈1500 Å (M_ UV) for all our luminous LAEs. We use the magnitude in the closest observed band (m) to rest-frame 1500 Å, which approximately corresponds to g for z=2.2 and R for z=3.1 and compute:

    M_UV=m - [5log_10(D_L[z])-5-2.5log_10(1+z)]+f,

where D_L is the luminosity distance in parsec, and f is a correction factor from the fact that our filters may not trace 1500 Å exactly and have different widths. We use the results from <cit.> and Lyα selected sources from <cit.> to compare M_ UV values computed using g and R and M_ UV computed from the full SED fitting. We find averages of f≈0 for z≈2.2 (g) and f≈-0.2 for z∼3.1 (R). The dispersion on f is ≈0.2. Errors on M_ UV are computed by perturbing the appropriate m and f along their Gaussian distributions independently 10,000 times and calculating the 16th and 84th percentiles (see Table <ref>).

We estimate the rest-frame UV β slope <cit.> with:

    β=-m_1-m_2/2.5log_10(λ_m_1/λ_m_2)-2,

by using R (m_1) and I (m_2) for z≈2.2 and I (m_1) and z (m_2) for z≈3.1 (observed λ_R≈6100 Å, λ_I=7600 Å, λ_z=9000 Å, rest-frame ≈1800,2200 Å at each of the two redshift groups). We use these filters as they avoid strong contamination from Civ, which would make strong Civ emitters artificially blue if we obtain β using rest-frame ≈1500,2200 Å. Errors on β are computed with the same methodology as for M_ UV. Due to the slight differences in the filters and rest-frame, we add 0.1 mag in quadrature to the final error (see Table <ref>).




 §.§ Estimating the Lyα escape fraction and ξ_ ion


We obtain a rough proxy for Lyα f_ esc,UV based on M_ UV (a more detailed investigation will be presented in Sobral et al. in prep., exploring Hα and Balmer decrements). We obtain f_ esc,UV by 1) converting M_ UV to SFR (in M_⊙ yr^-1) following <cit.> with a Salpeter IMF[Note that the choice of IMF is irrelevant due to step 2.]:

    SFR=(1.4×10^-28)(4π×9.521×10^38)10^-0.4(M_UV+48.6)

and by correcting for dust extinction; 2) converting Lyα to SFR assuming a 100% escape fraction, case B and Salpeter IMF (see e.g. ), and 3) by obtaining the ratio between 2) and 1). For comparison, we also compute f_ esc using the Lyα rest-frame EW as in <cit.> <cit.> and find excellent agreement.

Here we correct for dust extinction <cit.> based on our β measurements. We use A_ UV≈4.43+1.99β <cit.>, resulting in a bootstrapped A_ UV≈0.5^+0.6_-0.2 (corresponding to the median β=-2.0±0.2[We exclude AGN and compute the bootstrapped median of β as -2.0±0.2. If we use the entire sample we obtain a bootstrapped median of β=-2.1±0.2], or E(B-V)≈0.05; ). This implies a correction to UV SFRs of our LAEs of 1.5^+1.1_-0.3, and thus Lyα escape fractions (for our observed Lyα luminosities) lower by these factors compared to the no dust correction assumption.

Finally, we also estimate the ionisation efficiency (ξ_ ion) of LAEs by following <cit.>, using Lyα luminosity and the escape fraction to estimate the LyC luminosity and compare it to the dust corrected UV luminosity. 






§ RESULTS
 



 §.§ AGN among the most luminous LAEs










Some of the most luminous LAEs may be powered by AGN activity. We identify AGN within our luminous LAEs at z∼ 2–3 as sources with i) broad Lyα lines (FWHM >1000 km s^-1; e.g. Figure <ref> and Table <ref>), ii) X-ray detections or iii) emission line ratios associated with AGN activity, by exploring high ionisation lines (Nv, Heii, Civ and Ciii]); see Figure <ref> <cit.>. 




  §.§.§ Broad-line and X-ray AGN



We start by identifying AGN using the broadness of the Lyα line (see further details in Appendix <ref>). We find that seven out of the 20 with Lyα FWHM measurements have FHWM clearly above 1000 km s^-1 (see Figure <ref> and also Figures <ref> and <ref> for 2D information), and thus we class them as broad-line AGN[Stellar winds may typically lead to de-projected gas velocities of ∼100 to ∼1000 km s^-1, although in principle they can reach up to ≈3000 km s^-1 <cit.>. However, outflows are expected to lead to highly asymmetric lines, while the Lyα profiles of the broad-line LAEs are all very symmetric.] (BL-AGN) – see Table <ref>. These sources have FWHMs ranging from ∼1300 to ∼4000 km s^-1 (Figure <ref>). Our results imply a BL-AGN fraction of 35±11 % within our full sample.

Our SA22 sources do not have X-ray coverage, as they are significantly away (∼1 deg in three different directions) from the SSA22 Chandra follow-up <cit.>, but they all show very broad Lyα emission (FWHM 1800 km s^-1), and thus are cleanly identified as AGN. Our GOODS-N sources have good Chandra coverage <cit.>, but none of our three sources is detected in the 2 Ms depth data. Our three sources in COSMOS are also not detected in deep X-ray observations <cit.>, with the same holding for our three UDS sources, although for UDS only shallower XMM observations (≈3 times shallower than COSMOS) are available <cit.>. Finally, for our Boötes sources, we find one X-ray detection (BH-NB5-6, a broad-line AGN), while the other sources are not detected in the X-rays <cit.>. Therefore, using the available X-ray data, we find a single X-ray source (BH-NB5-6) out of 18 which have X-ray coverage, but we note that the available data are very heterogeneous, do not cover our most luminous LAEs in SA22, and are generally not deep enough to detect lower accretion and lower black mass AGN. Furthermore, the short duty cycles of X-rays can also lead to underestimating the AGN fraction using X-rays only <cit.>.




  §.§.§ Narrow-line AGN


Our spectroscopy allows us to explore the nature of the sources further and search for AGN activity by using other emission lines besides Lyα. We start by identifying sources with significant Nv (ionisation energy of 77.4 eV) which, with observed ratios of N v/Lyα0.1 we robustly class as AGN. This is because even the most extreme stellar populations fail to produce significant Nv emission (N v/Lyα<0.001) due to the sharp cut-off of ionising photons at energies significantly below 77.4 eV <cit.>. This makes Nv one of the cleanest lines to identify AGN activity. We find that sources SA22-NB5-18, BH-NB5-6, -10, -16, -27 and CALYMHA-415 all show significant Nv emission (observed ratios N v/Lyα≈0.1-0.6). Half of these sources are BL-AGN (see Section <ref>), while BH-NB5-6 is also an X-ray source. We therefore find an AGN fraction of 32±11 % based solely on high N v/Lyα ratios (N v/Lyα0.1).








 



For the sources without Nv detections and with narrow Lyα lines (<1000 km s^-1), we explore other UV rest-frame lines of lower ionisation energy. In Figure <ref> we show emission line ratios of high ionisation UV lines which are in principle capable of further distinguishing between sources which are dominated by either AGN or star formation. We show four of our narrow-line emitters where we can measure/constrain both line ratios plotted. For comparison and interpretation, we also show the locations of power-law ionising sources (AGN) from <cit.>, along with the location for SFGs <cit.>. We also provide emission line ratios computed with cloudy to sample both populations (see <ref>). We show our luminous broad-line AGNs for which we can constrain the line ratios for comparison. Apart from BH-NB5-10, which was already classed as a NL-AGN due to the high Nv/Lyα ratio of ≈0.17±0.03, we identify two further narrow-line sources which are consistent with being NL-AGN: BR3, the brightest narrow-line LAE in our sample and GN-NB5-3378, with a much fainter Lyα luminosity. Both BH-NB5-10 and BR3 have emission-line FWHMs of ≈600-700 km s^-1, higher than the other NL-emitters (≈100-300 km s^-1), also being brighter in UV and Lyα. We find one source, BH-NB5-37, which is consistent with being dominated by star-formation, but suggests a relatively high effective temperature (see Figure <ref>) and could still have an AGN source. For the other narrow-line sources without Nv where we do not detect high ionisation UV lines we classify them as SF as our observations should have detected high ionisation lines if they had a significant AGN contribution. Our stack of all these sources (see Figure <ref>) suggests this is a reasonable assumption, as it places the overall sample of sources classified as SF in the SFG region in Figure <ref>. We note, nonetheless, that even the stack of SFGs suggests high effective temperatures, and it is possible that even those LAEs have at least some AGN component.




  §.§.§ Final AGN and SF classifications


Overall, we find seven broad line AGN and five narrow-line AGN, with a total of twelve AGN out of the sample of 20 classifiable sources. Our results therefore imply a total AGN fraction of 60±9 % for luminous LAEs at z∼2-3. Relatively high AGN fractions (∼20-50%) have also been found for bright LAEs at z∼0.3-1 <cit.> and at z∼ 2–3 <cit.>, while for the much fainter, numerous LAEs the AGN fraction is typically no more than a few per cent <cit.>.




 §.§ The UV properties of luminous LAEs




On average, we find a bootstrapped median for the sample of SFGs of M_UV=-20.5^+0.4_-0.3  and M_UV=-21.5±0.4 for the full sample, with M_UV ranging from -19.2 to -23.7; see Table <ref> and Figure <ref>. We note that while luminous LAEs have Lyα luminosities of L_ Lyα^* or higher, they also have UV luminosities of roughly M_ UV^* <cit.> and have a range of M_ UV similar to the full sample of <cit.> and the sample of L_ Lyα^* sources presented in <cit.>, thus sharing properties with larger, photometric samples of LAEs. 

We find a bootstrapped median[The simple average for the full sample is β=-1.9±0.7] of β=-2.0^+0.3_-0.1 (the bluest source having β≈-3.2 and the reddest having β≈0.7; see Figure <ref>), revealing that our luminous LAEs are very blue on average, but with one outlier. The median β that we find for luminous LAEs is in agreement with the full sample of LAEs at z∼2.2 from <cit.>, and consistent with other studies focusing on lower luminosity Lyα selected sources <cit.>. Interpreting β as a dust extinction indicator for the non-AGN sources suggests E(B-V)=0.05^+0.08_-0.05 <cit.> or A_ UV≈0.5^+0.6_-0.2 (see <ref>), implying that the bulk of our luminous LAEs have little to no dust, and thus are potentially similar to fainter LAEs <cit.>. This is also consistent with Balmer decrement measurements/constraints for some of our sources (Matthee et al. in prep.). We list the individual M_ UV and β values for each source in Table <ref>.

In Figure <ref> we show the relation between M_ UV and β for luminous LAEs, and also compare our sources with the literature <cit.>. We find little to no correlation between M_ UV and β for our luminous LAEs as a whole, with our sources being generally very blue, irrespective of UV luminosity (Figure <ref>). We further test this by fitting a linear relation to 10,000 realisations, each varying each individual pair of (M_UV, β) randomly and independently within their full probability distributions. For the full sample (SFGs only) we find a slope of -0.07^+0.11_-0.15 (-0.1^+0.4_-0.2) for the relation between M_UV and β, fully consistent with no relation for either the full sample or just the sample of star-forming galaxies. We also find no significant relation when studying the AGNs only.

Our results are in very good agreement with <cit.> who found a slope of 0.00±0.04 for their global sample, consistent with our results of -0.07^+0.11_-0.15 for a much more luminous sample. Our luminous LAEs are significantly brighter in Lyα than essentially all LAEs in <cit.> which come from a sample that is UV continuum-selected. We also note that we find luminous LAEs to be even bluer than sources studied in <cit.>. While our results for SFGs are in reasonable agreement with those of <cit.> for LBGs within the error bars (see Figure <ref>), LAEs tend to be below the relation found for LBGs. We also find that luminous LAEs deviate most from the <cit.> relation at the brightest UV luminosities, but this may be a simple consequence of the powering nature for these sources (e.g. AGN).




 §.§ The relation between Lyα and UV at z∼2-3


In Figure <ref> we compare the Lyα luminosities of our sources with their rest-frame UV luminosities. Our sources span the relatively unexplored range between the more numerous LAEs, typically an order of magnitude fainter in Lyα and UV luminosities <cit.> and luminous quasars at z∼ 2–3 <cit.>, which can have similar Lyα luminosities to our luminous LAEs <cit.> but UV luminosities ∼-25 to ∼-30, and thus significantly brighter in the continuum.

The brightest LAEs in terms of M_ UV within our sample are also the brightest in Lyα, but the relation shows significant scatter, leading to a 2 dex spread in M_ UV for a ≈1.7 dex spread in Lyα luminosity. Such scatter could be due to variations in dust content, the powering source of the ionising photons and/or due to different ionisation efficiencies <cit.>. One also expects that sources may have different Lyα escape fractions, even though it is known that LAEs (Lyα-selected) tend to have typically high Lyα escape fractions <cit.>. We show indicative lines of constant Lyα escape fraction (correcting for dust extinction by using the UV β slope; see Section <ref>), which, under very simple assumptions, can easily explain the observed scatter. Many of our Lyα sources are consistent with having very high Lyα escape fractions which can be up to ≈100%. The high escape fractions are likely an important factor in explaining why these sources are so Lyα-bright. Alternatively, they may (also) have other powering sources hidden in the UV and/or a higher ionisation efficiency, ξ_ ion <cit.>. By estimating ξ_ ion for the bright LAEs we find a bootstrapped[By correcting for dust extinction we obtain ξ_ ion=10^25.1±0.2 Hz erg^-1.] ξ_ ion=10^25.4±0.2 Hz erg^-1, with individual ionisation efficiencies for the star-forming LAEs varying from ξ_ ion≈10^25.0 Hz erg^-1 to ξ_ ion≈10^25.9 Hz erg^-1. These compare with values of ξ_ ion=10^25.0-25.3 Hz erg^-1 for continuum selected LBGs at z∼2-5 <cit.>, ξ_ ion=10^24.8 Hz erg^-1 for highly star-forming Hα emitters at z≈2 <cit.> and ξ_ ion≈10^25.5 Hz erg^-1 for low luminosity LAEs at z∼3-6 <cit.>.






 










 




Correcting for dust (see <ref>) assuming A_ UV=0.45 (A_ UV=0.0) we find an average Lyα escape fraction of 50^+20_-15% (70^+30_-20%) for our luminous SF LAEs at z∼ 2–3. As an independent estimate, we also use the relation between Lyα escape fraction and the Lyα rest-frame EW presented in <cit.> which is independent of any assumptions regarding dust extinction, to find a bootstrapped Lyα escape fraction that is in perfect agreement (50^+20_-15%)[We find a bootstrapped EW_0=90^+44_-23 Å.]. These high escape fractions are comparable with those found for fainter LAEs. Some of the latest measurements include a Lyα escape fraction of 37±7% for a more general sample of fainter LAEs at z∼2 <cit.> and ≈30% at z∼2-4 <cit.>. These results are much higher than the low escape fractions of ≈2%[Directly measured with Hα.] for a more general population of star-forming galaxies selected through Hα at z∼2 <cit.>, ≈4-5% <cit.> from a comparison of the evolution of the Lyα and UV luminosity functions at z∼2-3, or ≈5% for UV selected sources at z∼ 2–3 <cit.>; see also <cit.> and <cit.>. Our results thus show that luminous LAEs have Lyα escape fractions at least comparable or higher than the numerous low luminosity LAEs, hinting that at least the SF-dominated ones are likely “scaled-up" or “maximal" versions of the faint LAEs.




 §.§ Lyα and UV luminosities as AGN activity predictors for LAEs at z∼ 2–3


Overall, our sample of luminous LAEs at z∼ 2–3 reveals a high AGN fraction of ≈60%. We now investigate how this fraction depends on both Lyα and UV luminosities. As Figure <ref> shows, LAEs are essentially all AGN above a Lyα luminosity of ≈10^43.3 erg s^-1 or for UV luminosities brighter than M_UV≈-21.5, qualitatively similar to results at different redshifts <cit.>. These include both the narrow-line emitters, which are brighter in Lyα than in the UV, and BL-AGN, which are typically brighter in the UV. In Figure <ref> we also show the rough location of the knee of the Lyα <cit.> and UV luminosity functions <cit.>. We find a rise of the AGN fraction from virtually 0 to 100% happening just under 1 dex in UV and Lyα luminosities, with the fraction below the knee of each luminosity function being ≈0%. We quantify the relation between the AGN fraction and UV or Lyα luminosity in a similar way to other relations in this paper. We find that the AGN fraction among bright LAEs rises with M_ UV significantly (∼4 σ) and is well parameterised (from -19 to -23) by f_AGN=(-0.30±0.07)( M_UV+20.5)+(0.35±0.11). The relation between f_AGN and Lyα luminosity (significant at a ∼3-4 σ) is well parameterised (from log_10(L_Lyα) 42.5 to 44.0) by f_AGN=(0.78±0.22)(log_10(L_Lyα)-42.72)+(0.24±0.14).








 










 



We also compare our results with <cit.> at z∼1 and <cit.> at z∼2.3 (Figure <ref>), which show very similar trends <cit.>. By comparing our results with z∼1 (see Figure <ref>) we find little to no evolution in the relation between the AGN fraction and the Lyα luminosity. This is apparently at odds with results from X-rays and radio <cit.>, which would hint for a strong evolution between z∼1 and z∼2-3. However, X-ray and radio selections are only able to recover a fraction of LAEs with AGN activity. Rest-frame UV spectra are crucial to cleanly identify sources with AGN signatures, as many do not show X-ray or radio emission down to even the deepest limits currently achieved over large fields. Our results further stress that X-ray identification of AGN <cit.> must be taken as a lower limit to the AGN fraction, both due to short duty cycles and to the typically high accretion rates needed for detection in the X-rays at high redshift.

In order to further explore the relation between the AGN fraction and UV or Lyα luminosities, we present those together in Figure <ref>. We convert UV absolute magnitudes to luminosity and normalise by the corresponding L^*_ UV (M^*_ UV=-20.5, ). We also normalise the Lyα luminosities by L^*_ Lyα=10^42.72 erg s^-1 <cit.>. The rise in the AGN fraction is found to be smoother with increasing Lyα luminosity than with UV luminosity (Figure <ref>), but the transition happens at the corresponding 2× L^* in both cases and the AGN fraction starts rising above L^*. Using the average L/L^* from combining UV and Lyα leads to the AGN fraction rising even sharply with increasing relative luminosity, from 11±10% below 2× L^* to 100^+0_-7% above 2× L^*, suggesting a difference above 5 σ. By perturbing each bin and re-fitting with i) a linear relation and ii) a step function with a transition at 2× L^*, we find that step functions result in reduced χ^2 typically 2-3 times smaller than linear fits, with 92% of all fits preferring a step-function. We note that combining the information on Lyα FWHMs with either Lyα or UV luminosities also leads to a sharper transition at 2× L^* than when using a single luminosity to predict the AGN fraction.

Our results show that there is a relatively sharp transition in the nature of luminous LAEs at 2× L^*. Such transition suggests that either above L^* AGN activity becomes more and more prominent <cit.>, and/or there is a relatively well defined physical limit in the output/observed luminosities from star-forming galaxies at z∼2-3 which does not apply to AGN. This limit would likely be linked with i) the intrinsic maximal starburst before radiation pressure halts further activity <cit.> and perhaps even more importantly with ii) the maximal “observable" or unobscured starburst which requires the highest possible output of LyC and UV photons without significant dust obscuration, so it can be seen as bright as possible in Lyα and UV. Thus, while there are star-forming galaxies that intrinsically produce much higher UV and Lyα luminosities than the observed 2× L^* in the UV <cit.>, a significant increase in SFR is linked with a similar or even higher increase of dust obscuration <cit.>, leading to an observed UV and Lyα luminosity that can even decrease, thus limiting the maximum observed luminosities <cit.>. If this is the case, the only sources that can still be observable as LAEs brighter than 1-2× L^* require AGN activity. In these cases, due to the physics of the accretion disk or powerful outflows clearing out material, the AGN activity can lead to even larger observed UV and Lyα luminosities. Results from Hα (non-resonant and less affected by dust) selected sources <cit.> show an increase of the AGN fraction with increasing L_ Hα/L^*_ Hα above 2× L^*_ Hα at z∼2 (Figure <ref>), but such increase is significantly slower and the AGN fraction only reaches 100% by 20× L^*_ Hα, a factor 10 larger than seen for LAEs. We discuss these results further and implications for a physical limit for the UV and Lyα starburst observed luminosities in <ref>.




 §.§ The relation between Lyα FWHMs, UV and Lyα luminosities at z∼2-3


In Figure <ref> we investigate how the Lyα FWHM depends on Lyα and rest-frame UV luminosities for bright LAEs at z∼ 2–3. We start by evaluating a potential simple linear relation between FWHM and each luminosity. We find a slope that is significantly (>5 σ) away from zero (no-relation), with no realisation (p<10^-4) consistent with a zero slope. However, the strong trend could be a consequence of a sharp change in the population from narrow to broad-line emitters from low to high luminosities. In order to further investigate the trends we split the sample in i) SFGs, ii) NL-AGN and iii) BL-AGN and repeat the measurements/analysis. Our results show that there is no significant correlation between Lyα FWHM and either Lyα or UV luminosity for SFGs alone (see Figure <ref>), with the best-fit slope being fully consistent with zero within the 16 and 84 percentiles. For NL-AGN we find a strong correlation between FWHM and both Lyα and UV luminosities (see Figure <ref>), with the median slopes of all fits being ≈4-5 σ away from zero and with 100% of realisations resulting in a positive slope. This relation may be related with outflows becoming more prominent and ejecting material at higher velocities for higher luminosity NL-AGN. Alternatively, high velocity outflows may lead to higher Lyα escape fractions, thus explaining the tighter correlation between Lyα luminosity and FWHM than UV luminosity with FWHM. It is worth noting, nonetheless, that there is a significant fraction of SFG LAEs that are well fitted by the range of fits performed to the NL-AGN, with many of these SFGs lying well within the 1 σ range of best fits to the NL-AGN. This could imply that the physics behind the correlation is similar in both NL-SFGs and NL-AGN, and could be driven by low velocity SF-driven outflows which may be roughly proportional to the LyC production (SFRs).

Our results for BL-AGN reveal no significant correlation between Lyα FWHM and Lyα luminosity, with >30% of realisations being consistent with a zero or even an anti-correlation, while we find a relatively significant correlation between FWHM and M_ UV for BL-AGN, with the slope being ∼3 σ away from zero. For BL-AGN, our results may be explained by the physics of the accretion disk and the mass of the super-massive black holes: more massive black holes will produce higher FWHMs and higher UV luminosities, but the observed Lyα output may both be variable and will depend on orientation angle and the likely complex radiation transfer. This could explain why the FWHM correlates well with UV luminosity, but little with observed Lyα.

We also compare our results at z∼ 2–3 with the literature at higher redshift for LAEs with comparable Lyα and UV luminosities (Figure <ref>) and selected in the same way as our sources <cit.>. We find that at z≈5.7-6.6 there is little to no relation between FWHM and UV or Lyα luminosity. Furthermore, we find an offset between the median FWHM at z∼ 2–3 and z∼6-7. Such an offset is particularly striking at the highest Lyα luminosities (>10^43.3 erg s^-1) and the highest UV luminosities (<-21.5), as the FWHMs at z∼6-7 are relatively narrow (∼200-300 km s^-1; ), while the median at z∼ 2–3 is above 1000 km s^-1. This suggests that the powering sources (and the ISM/IGM conditions) needed to result in exceptionally high Lyα and UV luminosities are different at z∼6-7 and z∼ 2–3, and that high Lyα and UV luminosities can be achieved at high redshift without potentially very energetic/high velocity outflows (see <ref>). These may be connected with e.g. higher ξ_ ion, higher Lyα escape fractions <cit.> and potentially lower metallicity environments which ultimately may result in higher luminosities for unobscured starbursts at high redshift (see <ref> for further discussion).







§ THE NATURE OF THE BRIGHTEST LAES WITH REST-FRAME UV LINES
 



 §.§ Velocity offsets of luminous LAEs at z∼ 2–3


We use non-resonant lines (when detected) to derive the systemic redshift of each source, and then use them to calculate the shift of the peak of Lyα from each line (see Appendix <ref>). We find such shifts to be generally positive, i.e., for Lyα to generally be redshifted compared to the other emission lines <cit.>, but we find some notable exceptions, particularly for sources where Civ and/or Heii are redshifted more than Lyα by ∼100 km s^-1 (e.g. GN-NB5-3378). In general, we find Civ to be redshifted by ≈100 km s^-1 compared to other lines which should be tracing the systemic redshift better. This is not surprising since Civ is also a resonant line, and thus has a behaviour similar to Lyα.

For the narrow LAEs at z∼2.2, we find low velocity offsets between Lyα and other rest-frame UV lines from ≈30 km s^-1 to ≈250 km s^-1 with an average of 140^+80_-30 km s^-1; these are sources with the most symmetric and narrowest Lyα FWHM (≈200-300 km s^-1) and also include sources with significant blue wings <cit.>. For the sample at z∼3 we find a larger variety of velocity offsets, ranging from ≈-250 km s^-1 to ≈800 km s^-1 and an average of ≈100^+300_-240 km s^-1. The higher incidence of blue-shifted Lyα in emission for some of the z∼3 sources might be linked with their higher luminosities and potentially higher velocity outflows.

Overall, we find typical Lyα to systemic velocity offsets of ≈120 km s^-1 but with a number of offsets (for seven LAEs) consistent with zero, implying that Lyα is likely escaping close to systemic. The velocity offsets we obtain can be compared with typical velocity offsets of ≈450±50 km s^-1 from UV selected galaxies at similar redshifts <cit.> and ∼200 km s^-1 for much fainter Lyα selected sources <cit.>. We conclude that luminous LAEs have Lyα velocity offsets in respect to systemic which are similar, or even smaller, to those of the faint Lyα selected sources, and much lower than that of the more general Lyman-break population at similar UV luminosities. Such low velocity offsets may be a consequence of the relatively high Lyα escape fractions <cit.>, which in turn provide conditions for the high observed Lyα luminosities.







 






 §.§ The nature of the brightest LAEs with individual emission-line detections


In Figure <ref> we show our most luminous narrow-line LAE (BR3), which shows strong Civ, Heii, Ciii] and weaker Oiii], revealing a highly ionising powering source. No Nv is detected and all lines have FWHMs similar to Lyα, of ≈600 km s^-1. We also show even brighter broad-line emitters, and one of the brightest in the UV (BH-NB5-10), which shows large blue-shifted absorption features at Civ and Lyα. Figure <ref> reveals the large variety in the rest-frame UV spectra of the most luminous LAEs at z∼ 2–3, which we find to be consistent with being powered by AGN. 

In order to interpret the spectra, we conduct photo-ionisation modelling (see also ) using i) power-law spectra (to model AGN), ii) bpass <cit.> stellar models, including binary evolution and iii) black-bodies with a range of effective temperatures. We explore a relatively wide range of physical conditions by using the cloudy (v 13.05) photo-ionisation code <cit.>. Further details are given in Alegre et al. (in prep.) and in Appendix <ref>. We summarise the physical conditions  we explore in Table <ref> <cit.>.

We estimate physical conditions within bright LAEs by using the line ratios presented in Table <ref>. In addition, we use upper limits to provide either upper or lower limits on line ratios. We then explore the multi-dimensional line ratio parameter space to find all cloudy models that produced line ratios consistent with observations within 3 σ of each line ratio, upper or lower limits of the line ratios. We then compute the best physical parameter (see Table <ref>) and typical uncertainties by taking the median, 16 and 84 percentiles of each physical parameter within all models that result in line ratios within 3 σ of the observations. This means that our approach is statistically more robust than simply trying to find the “best-fit” of cloudy outputs to observations and more conservative in uncertainties than focusing on e.g. a single combination of line ratios. We also compute the fraction of emission line ratios that each type of model is able to reproduce within 1σ of the constrained line ratios; we use these to discuss which model best described each source or stack of sources.

BR3 is best described by hot black-body models or power-law models. BPASS photoionisation models fail to reproduce 40% of the emission line ratios available, re-enforcing BR3's AGN nature. Power-law models suggest BR3 has a power-law slope of α=-1.2^+0.2_-0.3, an ionisation parameter of log U=-2.2^+0.2_-0.1 and a gas metallicity of log(O/H)+12=8.5±0.2. Black-body models suggest T_eff=135±10 kK, an ionisation parameter of log U=-2.0^+1.3_-0.3 and a gas metallicity of log(O/H)+12=8.3^+0.4_-0.1. The results suggest that BR3 is a highly ionising source with a high effective temperature, while its gas is consistent with being mildly sub-solar at roughly 0.5 Z_⊙.















 












We perform the same analysis for sources in which we detect at least two other UV emission lines in addition to Lyα, allowing for line ratios between those three or more lines (and constraints on the others) to be used. It is worth noting that requiring at least three UV lines to be detected is expected to select sources with the highest ionisation parameters, AGN nature and/or high effective temperatures. 

In general, we find that our AGN-classified sources have line-ratios which are only reproducible with power-law models or black-bodies with high temperatures around ∼120-140 kK, particularly due to their Nv and Heii fluxes. These sources have line ratios which imply ionisation parameters (log U) from ≈-2 to ≈1 and gas-phase metallicities between ≈0.4 Z_⊙ and ≈2 Z_⊙, mostly driven by the strong Nv detections <cit.>, but also by Civ. These results show that there is a diversity of properties within the AGN population of bright LAEs at least in terms of gas metallicities and ionisation parameters. The derived properties of the AGN in our sample are also very similar to those derived for high redshift radio galaxies <cit.>.

For the only source with at least two UV lines which is likely dominated by star-formation (GN-NB5-6712), we find that BPASS models are able to reproduce the line ratios, although black body models with temperatures ≈70-100 kK also reproduce the constraints on the line ratios. The cloudy-BPASS models suggest a ∼20 Myr-old burst, an ionisation parameter of log U=-3.0^+1.7_-0.8 and sub-solar to solar gas-phase metallicity (0.6^+0.8_-0.4 Z_⊙), and thus similar to properties derived for faint LAEs <cit.>. We note, nonetheless, that GN-NB5-6712 is not necessarily representative of the population of bright LAEs dominated by star-formation, particularly due to the detection of both Civ and Heii.




 §.§ Results from stacks


For a fraction of the LAEs the physical parameters are unconstrained due to many lines being below the detection limit. This can in principle be addressed through stacking similar sources, allowing us to better constrain the general nature of the sources within the population of luminous LAEs as a whole. We stack the sub-samples listed in Table <ref>, and constrain the emission lines following the same methodology as for individual measurements. We stack using the Lyα redshift. As we are only interested in obtaining the stacked flux or luminosity of each line, we bin each spectrum so that we eliminate most of the scatter in velocity offsets between Lyα and other lines (to avoid blurring them out) and also make doublets unresolved. In practice, we bin each spectrum to a resolution of 750 km s^-1 at rest-frame 1500 Å, motivated by the largest velocity offsets in our sample. This also allows us to measure emission-line fluxes with single Gaussians for all stacks.

In order to stack the spectra, we transform flux density into luminosity density taking into account the redshift of each source and average combine spectra weighting by the inverse of the variance, as well as masking strong OH sky lines. We also obtain median stacks which provide similar results but with lower S/N.

We show our results for a range of our stacking analysis as a function of Lyα luminosity in Figure <ref> and the full results in Table <ref>. We find that the strength of rest-frame UV lines roughly scales with Lyα and UV luminosities (mostly driven by AGN activity), but that the dependence with increasing Lyα FWHM appears different, particularly due to the spectra of the broadest line emitters which show relatively symmetric Lyα (implying an average line-of-sight volume with very low column density), symmetric strong Lyβ and broad high ionisation metal lines like Nv, Civ and Ciii] but weak to undetectable e.g. Heii. The most luminous LAEs are also those with the most symmetric Lyα lines and show the strongest Civ, Heii and Ciii] lines, along with significantly blue-shifted ISM lines likely tracing strong outflows of ∼750-1000 km s^-1 <cit.>; see Figure <ref>.

We find that the ionisation parameter increases with increasing Lyα and UV luminosities, being the highest for the stack of AGN sources (log U=0.6±0.5) and the lowest for SFGs (log U=-3.0^+1.6_-0.9). It is therefore likely that trends with luminosity are driven by the prevalence of AGN sources at bright luminosities and at higher FWHMs (see Figures <ref> and <ref>) and not due to a change in properties of star-forming dominated LAEs. We also find evidence for gas-phase metallicities of LAEs to be lower (≈0.1-0.3 Z_⊙) for SFGs (see Table <ref>) and for lower luminosity LAEs <cit.>, and closer to solar or higher for the most luminous LAEs (Table <ref>), but again this is likely caused by the sharp transition between star-forming and AGN-dominated (see Figure <ref>). 




§ DISCUSSION
 



 §.§ Bright LAEs at z∼2-3: the SF-AGN transition and the physical interpretation


Our results show that the AGN fraction of luminous LAEs strongly depends on both UV and Lyα luminosity at z∼2-3. The brightest LAEs in Lyα or in the UV are AGN, and above L_Lyα>10^43.3 erg s^-1 or M_UV<-21.5 virtually all luminous LAEs are AGN, causing an abrupt change in the physical properties of the ionised gas at 2× L^*, as seen in <ref>. This may be explained by the fact that only AGN can reach the highest observed luminosities in either UV or Lyα, and suggests a limiting observed SFR[Obtained converting the observed maximal M_UV=-21.5 or L_Lyα=10^43.3 erg s^-1 to a SFR using a Salpeter IMF.] for star-forming dominated LAEs of ≈20 M_⊙ yr^-1 at z∼2-3. In principle, such a SFR limit could be a consequence of the exponential cut-offs in the galaxy mass and the gas mass fraction functions, and the properties of dust formation in massive starbursts, with both effects potentially evolving with redshift (see <ref>). These likely combine to create a strong threshold on UV luminosity of SF-dominated systems.

If dust is the main driver of a sharp UV and Lyα observed luminosity limit for starbursts (leading to a sharp transition between SF and AGN dominated at 2× L^*), one would expect the limit to be different when looking at Hα luminosity of Hα selected sources, which is significantly less affected by dust. Results from <cit.> show that there is a rise in the AGN fraction of Hα selected sources as a function of Hα luminosity above 2× L^*_ Hα, but such rise is much slower and not as abrupt as the one found for LAEs (see Figure <ref>) with Lyα or UV luminosities. Hα emitters only become 100% AGN dominated at an observed Hα luminosity of about 10^43.8 erg s^-1, corresponding to an observed SFR limit of ≈500 M_⊙ yr^-1 in Hα luminosity, 25 times larger than the limit for the observed UV and Lyα SFRs for LAEs. We therefore interpret the sharp shift from star-forming to AGN dominated sources at 2× L^* for LAEs as likely a combination of two effects: a rise in the AGN fraction with intrinsic luminosity <cit.>, as seen for Hα selected samples, and the dominating factor of increased obscured SFRs as a function of increasing intrinsic SFR <cit.>, leading to a maximal unobscured starburst. 

While intrinsically star-formation dominated sources can still reach even higher SFRs and produce higher UV and Lyα luminosities, such intense starbursts happen in dusty environments or starbursts themselves produce the dust at z∼2-3 <cit.>, thus limiting or even reducing the observed UV and Lyα luminosities. The high intrinsic production of UV and Lyα photons of dusty star-forming galaxies suggests that any escape channel created by intense feedback in those galaxies will still lead to non-negligible UV and Lyα luminosities which are observed in a variety of studies <cit.>, but that given our results will not exceed 2× L^* at z∼2-3.

We conclude that the clear separation between star-forming dominated and AGN dominated LAEs at 2× L^* is caused primarily by obscured star-formation becoming dominant above observed SFRs of ≈20 M_⊙ yr^-1. Prominent dust obscuration will efficiently absorb UV photons and directly or indirectly (via scattering) lead to low Lyα escape fractions <cit.> such that the observed luminosities saturate. Lyα and UV luminosities observed above 2× L^* are thus likely to be produced by different physical processes linked with AGN activity, which in principle do not create dust. These may include strong AGN-driven outflows and radiation from different regions within the accretion disk, as seen from the evidence of the UV bright broad line emitters, while shocks may also play a role. The existence of UV blue, Lyα bright quasars <cit.> implies that the physical processes in accretion disks of massive black holes are scalable to much higher UV luminosities without dust imposing a strong limitation in the observed luminosities. This is likely due to outflows and high ionisation radiation fields which we find to be be present (log U from ≈-2 to ≈1; see <ref> and <ref>) that may destroy dust or open channels for Lyα and UV photons to escape <cit.>. Nevertheless, it should be noted that our most luminous LAEs already have Lyα luminosities as high <cit.> as the ones found for the most UV luminous quasars <cit.>, and reaching down to luminosities below those of fainter AGN <cit.>. Therefore, while the UV luminosity seems to be scalable up from even our brightest UV sources by a few orders of magnitude, there may be a saturation in the observable Lyα luminosity at close to 10^44-45 erg s^-1 for AGN at z∼2-3.



 §.§ Implications for higher redshift: evolution?


Our results and physical interpretation at z∼2-3 may allow us to shed further light into the nature and evolution of higher redshift LAEs selected in the same way. Recently, <cit.> obtained a large sample of ∼4000 LAEs from z∼2 to z∼6 and explored it to infer a strong evolution (a factor of ≈4-5) in the typical Lyα escape fraction of star-forming galaxies, rising as (1+z)^2. This increase is in addition to the likely increase of ξ_ion (tracing high burstiness and/or an average change in stellar populations) by a factor of ∼2, leading to a total observed rise of (1+z)^3 in the Lyα to UV luminosity density ratio with increasing redshift <cit.>. Furthermore, <cit.> finds a factor ∼5 rise in L^*_ Lyα from z∼2 to z∼6, which, under our interpretation of 2× L^*_ Lyα being the limit of the observed Lyα luminosity of a starburst would imply that by z∼6 the limiting observable Lyα luminosity for a starburst will be ≈10^44 erg s^-1. If this is the case, by z∼6 the limiting unobscured SFR would be ≈100 M_⊙ yr^-1, although the UV observed SFR may be limited to a lower value due to the high ratio of LyC to UV photons (ξ_ion) expected by z∼6 <cit.>. These results would provide a natural explanation for the exceptionally high Lyα luminosities of equally selected LAEs at z∼6-7 <cit.> with L_Lyα≈10^43.4-43.9 erg s^-1 that so far show no convincing evidence for being dominated by AGN activity <cit.>. For example, these luminous z∼6-7 LAEs show Lyα profiles which are typically narrow (≈200-300 km s^-1; ), contrarily to the high FWHMs we find at z∼2-3 for the same luminosities (see Figure <ref>). According to our interpretation of an evolving L^*_ Lyα by a factor of 5, the z∼6-7 bright LAEs would easily be consistent with being star-forming dominated, with CR7's Lyα luminosity <cit.> being the closest to our inferred maximal unobscured starburst luminosity of ≈10^44 erg s^-1 at z∼6. Recent deep ALMA observations of CR7 <cit.> are fully consistent with this interpretation, with CR7's obscured SFR being below <4 M_⊙ yr^-1.

Potential mechanisms which may be able to raise the maximal unobscured luminosity of early luminous LAEs are (major) mergers (seen as a single source) and/or significant gas inflows without reducing the Lyα escape fraction and/or without leading to significant dust obscuration. The necessary conditions likely require dust destruction and/or inefficient dust formation at low metallicities <cit.>, which may be more common at higher redshift, including the possibility of witnessing a first significant burst of star-formation. Interestingly, there is evidence for the brightest LAEs at z∼7 being multiple component/mergers <cit.>, while those at z∼ 2–3 are typically very compact and single component dominated <cit.>. At z∼2-3 major mergers lead to very high SFRs but that are significantly obscured <cit.>.

Our scenario of an evolving maximal unobscured star-burst is consistent with results from <cit.> who find that the relation between the X-ray AGN fraction of LAEs and Lyα luminosity declines with redshift or shifts to higher luminosities at higher redshift. Our discussed scenario, along with its physical implications, can easily be tested with the James Webb Space Telescope (JWST). Using JWST's IFU capabilities in the NIR and MIR regimes one can observe CR7, Himiko, VR7, MASOSA and other luminous LAEs <cit.> and establish them as either star-forming or AGN dominated, along with measuring their resolved dust obscuration using the Balmer decrement. Most interestingly, IFU data will allow to start understanding the physical reasons behind a potentially higher maximal unobscured starburst at high redshift and implications for dust formation and stellar populations in early luminous LAEs.





§ CONCLUSIONS
 

We have presented the spectroscopic follow-up of 23 luminous (L_Lyα L^*_Lyα) Lyα candidates at z∼ 2–3 found with large narrow-band surveys in Boötes, COSMOS, GOODS-N, SA22 and UDS. We have used WHT/ISIS, Keck/DEIMOS and VLT/X-SHOOTER to spectroscopically confirm 21 of them as luminous LAEs. We exploit the wide wavelength coverage of our data and the high resolution spectra to measure line profiles, investigate the nature of the sources and explore UV emission line ratios. Our main results are:




  * Luminous LAEs at z∼ 2–3 present a striking diversity in terms of their Lyα and UV properties. They also present a wide diversity in the shape of the Lyα line, ranging from roughly symmetric to highly asymmetric and including 25% of sources with significant blue-shifted Lyα components or double-peaked lines, typically linked with high Lyα escape fractions. 


  * Luminous LAEs are in general very blue (UV slope of β=-2.0^+0.3_-0.1) and span five orders of magnitude in rest-frame UV luminosities, from ∼0.3 M^*_ UV to ∼30 M^*_ UV. They likely have a low dust content, consistent with E(B-V)≈0.05 and have high Lyα escape fractions of 50^+20_-15 % after correcting for dust extinction.


  * Besides Lyα, the most prevalent high ionisation UV line in luminous LAEs is Civ, present in 40% of the sample, but we also find Nv, Heii, Ciii] and Oiii] as relatively common lines, particularly at the brightest UV and Lyα luminosities.


  * Lyα FWHMs of luminous LAEs vary from ∼200 to ∼4000 km s^-1, with the prevalence of broad lines rising significantly with increasing Lyα and UV luminosities. We find significant relations between the Lyα FWHM and Lyα and UV luminosities for NL-AGN, likely driven by outflows.


  * The narrow LAEs have small velocity offsets between Lyα and other lines of only ∼100-200 km s^-1, consistent with Lyα photons escaping relatively close to systemic and providing further evidence for high Lyα escape fractions in bright LAEs.


  * We find a significant increase in the AGN fraction of LAEs with both Lyα and UV luminosities from ∼0 to ∼100%. Above L_ Lyα>10^43.3 erg s^-1 and/or M_UV<-21.5 all luminous LAEs at z∼2-3 are AGN. We find simple relations to predict the AGN fraction of LAEs (within the ranges studied): f_AGN=(-0.30±0.07)( M_UV+20.5)+(0.35±0.11) and f_AGN=(0.78±0.22)(log_10(L_Lyα)-42.72)+(0.24±0.14).


  * The transition from star-forming dominated to AGN dominated happens at 2× L^* and is likely linked with a physical limit for the maximum observed output of an unobscured starburst of ≈20 M_⊙ yr^-1 at z∼2-3. For higher intrinsic UV and Lyα luminosities dust likely prevents such sources from being observed as brighter than 2× L^*.


  * AGN LAEs reveal high ionisation parameters (log U=0.6±0.5) and sub-solar to solar metallicities. Luminous LAEs lacking signatures of AGN (40±11 %) are less ionising (log U=-3.0^+1.6_-0.9 and logξ_ ion=25.4±0.2), apparently metal-poor (12+log(O/H)=8.2^+0.5_-0.3) sources likely powered by young, dust-poor “maximal" starbursts.


  * The ionisation parameter rises with Lyα and UV luminosities by typically 1 dex from the low to high luminosities, while gas-phase metallicities rise with Lyα luminosity from 12+log(O/H)=7.5^+0.5_-0.1 to 12+log(O/H)=8.7^+0.1_-0.1. We interpret these results as a consequence of the transition between star-forming dominated systems to AGN dominated which we find to be particularly abrupt at 2× L^*.





§ ACKNOWLEDGMENTS


We thank the anonymous reviewer for their timely and constructive comments that greatly helped us to improve the manuscript. DS acknowledges financial support from the Netherlands Organisation for Scientific research (NWO) through a Veni fellowship and from Lancaster University through an Early Career Internal Grant A100679. JM acknowledges the support of a Huygens PhD fellowship from Leiden University. BD acknowledges financial support from NASA through the Astrophysics Data Analysis Program (ADAP), grant number NNX12AE20G, and the National Science Foundation, grant number 1716907. IRS acknowledges support from the ERC Advanced Grant DUSTYGAL (321334), STFC (ST/P000541/1) and a Royal Society/Wolfson Merit Award. PNB is grateful for support from STFC via grant ST/M001229/1. We thank Anne Verhamme, Kimihiko Nakajima, Ryan Trainor, Sangeeta Malhotra, Max Gronke, James Rhoads, Fang Xia An, Matthew Hayes, Takashi Kojima, Mark Dijkstra, and Anne Jaskot for many helpful and engaging discussions, particularly during the SnowCLAW Lyα workshop. We thank Bruno Ribeiro, Stephane Charlot and Joseph Caruana for comments on the manuscript. The authors would also like to thank Ingrid Tengs, Meg Singleton, Ali Khostovan and Sara Perez for participating in part of the observations. We also thank João Calhau, Leah Morabito, Sérgio Santos and Aayush Saxena for their assistance with the narrow-band observations which allowed to select some of the sources. Based on observations obtained with the William Herschel Telescope (WHT), program: W16AN004 and with Keck, program C267D. Based on data products from observations made with ESO Telescopes at the La Silla Paranal Observatory under ESO programme IDs 294.A-5018, 294.A-5039, 092.A-0786, 093.A-0561, 097.A-0943, 098.A-0819, 099.A-0254 and 179.A-2005. The authors acknowledge the award of service time (SW2014b20) on the WHT. WHT and its service programme are operated on the island of La Palma by the Isaac Newton Group in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias. The authors would also like to thank all the extremely helpful observatory staff that have greatly contributed towards our observations, particularly Fiona Riddick, Lilian Dominguez, Florencia Jimenez and Ian Skillen.

We have benefited greatly from the publicly available programming language Python, including the NumPy & SciPy <cit.>, Matplotlib <cit.>, Astropy <cit.> and the Topcat analysis program <cit.>. This research has made use of the VizieR catalogue access tool, CDS, Strasbourg, France.

The samples and parent samples used for this paper are publicly available <cit.>. We also make all our 1D (binned to one third of the resolution, flux calibrated, without any slit correction) spectra public on-line with the final refereed version of this paper, together with the catalogue of luminous LAEs and electronic versions of relevant tables (see Appendix <ref>).



mnras








§ OBSERVATIONS AND DATA REDUCTION


Tables <ref>, <ref> and <ref> present the observing logs for WHT/ISIS, Keck/DEIMOS and VLT/X-SHOOTER observations, respectively. In Table <ref> we present the best estimates of the spectral and noise properties of all reduced data for WHT/ISIS, Keck/DEIMOS and VLT/X-SHOOTER.






 







 





 §.§ A python WHT/ISIS pipeline: WHIS


Here we present and explain in detail our python WHT/ISIS data reduction pipeline. On a night by night basis, the pipeline starts by identifying the different calibration and science frames, and groups them appropriately. Bias frames are median combined to produce a master bias. All frames are then bias subtracted. Flats within the linear regime are combined, per arm, grating and central wavelength, after normalising each flat by its median, and then median combined to produce different normalised master flats. All individual raw frames are then flat fielded using the appropriate normalised master flat. Arcs are median combined per arm, grating and central wavelength to produce master arcs. We combine arcs separately for the morning and evening arcs because we notice that small shifts can happen across the night.





 
 


Master arcs are used to extract the 1D arc spectra per night, per grating and central wavelength. Arcs lines are matched to air wavelength CU+CAr lines, matching ∼30 spectral lines covering the full spectral range per arm. We fit 3rd order polynomials and find the rms in the wavelength calibration solution to always be between 0.1-0.2 Å without any noticeable trend. We perform a final check and, if needed, a small correction to the wavelength calibration on a source by source basis (typically <0.5 Å) by exploring the available sky lines obtained from the same frames as the science targets, allowing to trace any small changes.

For each science target, we start by using the corresponding acquisition star frames and bin the 2D spectrally and spatially in order to automatically find the trace of the star in each individual 2D spectra. We find that fitting a line to the trace is able to trace it without any offsets along the wavelength direction. We then use the position of the trace in the spectral centre of the 2D as the centre of the trace for the target. We use those to find the exact location of the trace in the multiply offset spectra and to compute the required offsets in pixels. We use these to subtract both star and science spectra in sets of ABBA and to combine them. We then obtain an average stack (we also obtain median stacks and stacks without sky subtraction), removing individual pixels which are more then 5σ away from the average counts, to obtain a final average stacked 2D of the science target and its appropriate star. We then automatically find the trace in the star 2D spectrum and use it to extract both the science and the star spectra. We also extract the sky spectrum. We use the sky spectra to check the wavelength calibration and to apply any small wavelength offsets needed based on the calibrated ISIS spectra of OH lines. As a final sky subtraction step, we minimise residuals from sky lines by measuring the average counts away from the location of the source (where the average should be zero), and subtract those counts per resolution element. We show 2D spectra in Figure <ref>.

We flux calibrate 1D spectra by using the calibration star and taking full advantage of our observation methodology (of always observing a calibration star prior to each science exposure). We use SDSS magnitudes to produce an artificial spectrum of each star. We then compute the ratio between total counts measured and the flux densities derived from SDSS for each calibration star. We do this after masking all positions of strong lines (e.g. Ca HK, Hδ, Hβ, Hα) and linearly interpolate between those wavelengths. We find the flux calibration to be accurate within ∼10%. By definition, due to the way we extract our science targets (using the trace of the stars which we use for flux calibration) all point sources will be slit corrected. We use our narrow-band imaging to comment on the need for any extra corrections for some of our sources which are not point-like. Our spectra have a typical rms/depth of 1-2×10^-17 erg s^-1 for a 200 km s^-1 line (rest-frame) in both blue and red arms. We show examples of 1D extracted spectra in Figure <ref>.








 







 








 







 




 §.§ Reduced 2D and 1D spectra


We release the binned 1D spectra and we show in figures <ref>, <ref> and <ref> all the 2D spectra for our LAEs, zoomed in at the location of the major emission lines studied in this paper. All velocity offsets shown on the top of each figure are in respect to Lyα (here we use the redshift determined by fitting a Gaussian to the Lyα line). Note that for some lines and for some instrument configurations there is no coverage.




§ MEASURING LINES, FWHMS AND VELOCITY OFFSETS


By fitting Gaussian line profiles, we use the width of the line (σ_λ_0), fitted in Å (rest-frame), and convert it to km s^-1 using:

    σ=c σ_λ_0/λ_0   km s^-1

where c is the speed of light, 299792.458 km s^-1 and λ_0 is the rest-frame wavelength: λ_0=λ/(1+z). The observed full width at half maximum, FW_ obs, is:

    FW_ obs,0=2√(2×ln(2))×σ   km s^-1.


We correct our FW_ obs measurements for the appropriate instrument dispersion/resolution[We estimate the instrument resolution by measuring non-blended arc or OH lines.], FW_ inst (for Lyα: 100-200 km s^-1) using:

    FWHM=√(FW_ obs,0^2-FW_ inst^2)   km s^-1.

For the Lyα line these lead to corrections of <100 km s^-1 from observed to intrinsic FWHM due to the instrument dispersion. Our results are presented in Table <ref> and in Section <ref>.

We use the best fit central wavelength of each line which is significantly detected to obtain a redshift per line (z_ line) and to compute a velocity offset with respect to Lyα by using:


    v_offset,obs=c (1+z_ Lyα/1+z_ line-1)    km s^-1


We provide tables with the measurements presented and used in this work, e.g. Table <ref> in a fits format with the final refereed paper, and also the binned spectra.



















§ CLOUDY MODELLING


We explore stellar-like ionising spectra by using a large range of black bodies, with effective temperatures extending from 20,000 K to 160,000 K in steps of 1,000 K. We explore a wide range of metallicities, from 0.01 Z_⊙ to 3 Z_⊙ in 0.05 steps in log space. We also vary the ionisation parameter U, from 0.00001 to 10 (-5 to 2 in log in steps of 0.2), from lower to high ionisation parameters. We follow known relations between how C/O varies with metallicity, but also run cloudy for different C/O ratios allowed by current data <cit.>. We use densities of 100, 300 and 1000 cm^-2. Here we focus on the emerging emission line ratios. We note that our aim is not to claim “true" physical conditions, but rather to broadly identify which physical conditions may be present. In our derived best physical conditions we also take all the models within 1 σ of the observed line ratios, or that are allowed by the line ratio limits.

In order to compare with more realistic stellar models, we use bpass <cit.>[See also <cit.>.] models that include stellar rotation and binary evolution. These allow us to better constrain realistic ionising fluxes from stellar populations and to provide a link to indicative stellar ages. Furthermore, we also explore power-law ionising sources, which we associate with AGN, and run those models for the same physical conditions. For many emission line ratios the hottest black body ionising sources become very similar to the result of a power-law ionising source, but for the even higher ionisation lines, and for appropriate choices of lines, there is still a good separation. We note nonetheless, that naturally some of the line ratios used to separate stellar from an AGN nature that have used standard stellar populations do not work in the cases where stars can have much higher effective temperatures (due to binary interaction, winds exposing the deeper components of the star, or rotation).







