B-Telescope O B-Telescope O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model I-Model I-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O O O O O B-Model O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O B-Citation I-Citation I-Citation I-Citation O O O O O B-Model I-Model I-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O B-Citation I-Citation O B-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation O O O B-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O B-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula O O O O B-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model I-Model O O O O O O B-Model I-Model O O O O O O O O O O O O O

Parkes and ASKAP DM histograms with corresponding modelled DM distributions, d R F /d DM , where R F is the total differential (fluence) event rate in the observer’s frame (d R F /d DM has units of events s −1 (pc cm −3 ) −1 sr −1 ). Table 2. Symbol definitions relevant to the ME 2018 model utilized herein with some minor notational changes and extensions. The DM distribution, for fluences above a minimum survey fluence limit, is dependent upon a number of factors including the underlying redshift distribution of the population (relating to the evolutionary history) and the mean DM gradient, , for an assumed homogeneous IGM. These are dependent upon the source energy distribution function, characterized by the source minimum and maximum energies E min and E max , respectively, the energy power-law index and the spectral index (Macquart Ekers 2018b ). Throughout this work we utilize a ΛCDM universe with cosmological parameters and equations consistent with the Planck Collaboration XVI ( 2014 ) 3 and Hogg ( 1999 ), and symbol definitions of the ME 2018 model with some minor notational changes and extensions as summarized in Table 2 . The FRB redshift and DM distributions, in a survey of limiting fluence, are respectively given by equations ( 2 ) ( 3 ) and where the minimum and maximum of the source energy is related, respectively, to the corresponding minimum and maximum fluence via . Here, ψ n ( z ) and represent redshift evolution (Madau Dickinson 2014 ), via equation ( 4 ), and the mean DM of an homogeneous IGM (Ioka 2003 ; Inoue 2004 ), via equation ( 5 ), respectively and Whilst the underlying redshift distribution of the FRB population is unknown, we follow Macquart Ekers ( 2018b ) and adopt the Madau Dickinson ( 2014 ) formalism for the cosmic star formation history of the Universe. Equation ( 4 ) accounts for the redshift evolution of the rate density for a progenitor population abundance, governed by stellar processes throughout cosmic history, via the relation ψ n ( z )∝Ψ n ( z ). Here, Ψ represents the cosmic star formation rate (CSFR) per comoving volume and the event rate per comoving volume, ψ n ( z ), is related via a power-law index, n (Macquart Ekers 2018b ). We specifically consider three cases: (i) ψ 0 ( z ) – no redshift evolution; (ii) ψ 1 ( z ) – redshift evolution being linearly proportional to the CSFR; and (iii) ψ 2 ( z ) – redshift evolution being quadratically proportional to the CSFR. The case of ψ 0 ( z ) = 1 represents a constant event rate per comoving volume and ψ 2 ( z ) represents a rapidly evolving population. Furthermore, throughout this work, we set the ionized fraction of Hydrogen and Helium to X e, H = 1 for z 8 and X e, He = 1 for z 2.5, respectively, and zero otherwise, and take α to refer to the spectral index of the burst fluence unless specifically noted otherwise. The dimensionless Hubble parameter, E ( z ), permits the Hubble parameter for an arbitrary redshift, H ( z ), to be determined given the


B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O B-Model I-Model B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject I-CelestialObject O O B-CelestialObject O O O B-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject O O O O O O O O O O O O O O B-Telescope B-Wavelength I-Wavelength O O O O O B-CelestialObject O O B-CelestialObject O B-CelestialObject O O B-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Telescope O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject O O B-CelestialObject I-CelestialObject I-CelestialObject O B-CelestialObject I-CelestialObject O O O O O O O B-CelestialObject O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O B-Citation I-Citation I-Citation I-Citation O B-Telescope O O O O O O O O O O O O B-CelestialObject I-CelestialObject O O O O O O B-CelestialObject O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O

Heyer et al. 2008 ; Chapman et al. 2011 ). Using the Chandrasekhar-Fermi method, Chapman et al. (2011) estimated a magnetic field strength of about 25 G in the cloud surrounding the B211 filament, concluding that the former is magnetically supported. Fig. 4 Same as Fig. 1 for part of the Taurus molecular cloud around the B211 (north-west) and the L1506 (south-east) filaments. The numbers and white lines on the total intensity map correspond to the positions of the different cuts used to derive the radial profiles shown in Figs. 5 and 6 . Fig. 5 Same as Fig. 2 for the Taurus B211 filament. Here corresponds to the southern side of the filament crest. The filament is clearly seen in and is located in the area of a steep variation of the emission. The dispersion of the emission is small along the length of the filament. Fig. 6 Same as Fig. 2 for L1506. Here corresponds to the south-eastern side of the filament crest. Figure 4 shows the Planck 353 GHz Stokes parameter maps of the TMC around the B211 and L1506 filaments. The B211 filament is well detected in the and maps, as a structure distinct from its surrounding. On the map, on the other hand, the filament is not seen as an elongated structure, but it is perpendicular to a large gradient that separates two regions of almost uniform . The emission is negative on the northern side of the filament while it is positive on the southern side. This indicates that the -field orientation varies in the cloud surrounding the B211 filament. This variation can be seen very clearly in the radial profiles perpendicular to the filament crest, shown in Fig. 5 . These profiles are derived as explained in the previous section (for the Musca filament). The four and profiles (shown in the middle and right-hand panels of Fig. 5 ) are derived by averaging the cuts within a distance along the filament crest of 3 times the Planck beam (3 4.8). The cloud intensity () increases from the southern to the northern side of the filament, while the emission is similar on both sides of the filament crest. The (negative) emission of B211 is very clearly seen in the radial profiles. The different profiles show the approximate invariance of the emission along the filament crest. The total and polarized emission components are remarkably constant along the length of B211. 3.3. The Taurus L1506 filament The L1506 filament is located on the south-east side of B211 (see Fig. 4 ). Stellar polarization data are presented by Goodman et al. (1990) . The density structure and the dust emission properties have been studied by Stepnik et al. (2003) , and more recently by Ysard et al. (2013) using Herschel data. This filament has mean column densities comparable to those of the Musca filament. Star formation at both ends of L1506 has been observed with the detection of a few candidate prestellar cores ( Stepnik et al. 2003 ; Pagani et al. 2010 ). Figure 6 shows the radial profiles perpendicular to its crest. The colour profiles numbered from


O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O O O B-Grant O O O O O O O B-Organization I-Organization I-Organization I-Organization B-Organization O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O B-Location I-Location B-Person O O O B-Organization O O B-Grant O B-Telescope I-Telescope O B-Telescope I-Telescope I-Telescope I-Telescope I-Telescope I-Telescope I-Telescope B-Telescope O O B-Grant I-Grant I-Grant I-Grant O O O B-Organization I-Organization I-Organization I-Organization O O O O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization B-Telescope O O O O O O B-Observatory I-Observatory I-Observatory B-Organization I-Organization I-Organization I-Organization

This research is supported by the National Natural Science Foundation of China (NSFC) under grant No. 11390371, and was accomplished (in part) by the Chinese Academy of Sciences (CAS), through a grant to the CAS South America Center for Astronomy (CASSACA) in Santiago, Chile. Y.Q.C. acknowledges support from NSFC grant No. 11625313. The Guoshoujing Telescope (the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, LAMOST) is a National Major Scientific Project built by the Chinese Academy of Sciences. Funding for the project has been provided by the National Development and Reform Commission. LAMOST is operated and managed by the National Astronomical Observatories, Chinese Academy of Sciences.


O O O O O O B-Wavelength O O O B-Wavelength O B-Wavelength O O O B-Instrument O O O O O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject B-CelestialObject I-CelestialObject B-CelestialObject I-CelestialObject O O B-CelestialRegion O B-Citation I-Citation I-Citation O B-Database I-Database I-Database O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O B-Wavelength O B-Wavelength O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O O O O O B-Wavelength O B-Wavelength O O O O O O O O O O O O O O O O O O O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject O B-CelestialObject I-CelestialObject O O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O B-Citation O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model I-Model O O O O O B-Model O O O O O O O O B-Model O O O O O O O O O B-Wavelength B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O B-CelestialObject I-CelestialObject B-CelestialObject I-CelestialObject O B-CelestialObject I-CelestialObject O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O B-CelestialObject I-CelestialObject O O O O O B-CelestialObject I-CelestialObject O O O O O O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O B-Wavelength O O O O O O O O O O B-Wavelength O B-Wavelength O O O O O O O O O

magnitude is defined as QT = F814W 0 , where F555W − F814W) 0 for the ACS/WFC. We plotted QT magnitude versus (F555W–F814W) 0 diagrams of the resolved point sources in Figures 4 (e)–(h). Foreground reddenings are known to be very small: , 0.028, 0.035, and 0.007 for NGC 3021, NGC 3370, NGC 1309, and the HXDF, respectively (Schlafly Finkbeiner 2011 , NASA/IPAC Extragalactic Database). Internal reddenings of the selected outer regions are expected to be negligible so that these are assumed to be zero in this study. 3.2. Distance Estimation We determined the distances to the target galaxies using the TRGB method (Lee et al. 1993 ; Madore Freedman 1995 ). We selected resolved stars in the shaded regions of Figure 4 . The shaded regions for F814W – (F555W – F814W) CMDs were designed to sample blue RGB stars with near the TRGB level because the color (metallicity) dependence of the TRGB at the blue side is estimated to be small (Jang Lee 2017 ). In the cases of QT – (F555W – F814W) 0 CMDs, we set slightly wider shaded regions, sampling RGB stars with near the TRGB level. Figure 5 displays F814W (a)–(c) and QT (d)–(f) luminosity functions of the selected RGB stars in the CMDs. The luminosity functions for all three galaxies show abrupt increments at mag, which correspond to the TRGB. We applied an edge detection algorithm for the quantitative TRGB detection. We used a Sobel filter employing the zero-sum kernel of [−1, −2, −1, 0, +1, +2, +1] with a bin size of 0.05 mag. Output edge detection responses are shown as red lines in Figure 5 . Figure 5. (a)–(c) LFs (histograms) and edge detection responses (curved lines) of the RGB stars in NGC 3021 (a), NGC 3370 (b), and NGC 1309 (c). Estimated TRGB magnitudes are marked by vertical dashed lines in each panel. (d)–(f) Same as (a)–(c), except for the QT magnitude. Mean TRGB magnitudes and associated uncertainties were measured by running 10,000 simulations of bootstrap resampling as done for our previous studies (Lee Jang 2012 , 2013 ; Jang Lee 2015 ). In each simulation, we made a new sample of RGB stars by sampling a half size of stars randomly from the original RGB sample. We obtained TRGB magnitudes from the new samples as done for the original sample. We generated a histogram of the TRGB magnitudes obtained from the simulations and fitted a Gaussian function to the histogram, quoting the Gaussian mean as a mean TRGB magnitude and the Gaussian width as 1 σ uncertainty. Measured TRGB values are F814W TRGB = 28.179 ± 0.049, 28.252 ± 0.035, and 28.457 ± 0.044 mag for NGC 3021, NGC 3370, and NGC 1309, respectively. Similarly, QT RGB = 28.146 ± 0.033 mag for NGC 3021, 28.212 ± 0.041 mag for NGC 3370, and 28.398 ± 0.040 mag for NGC 1309 were obtained. Derived TRGB magnitudes from the QT luminosity functions are systematically brighter than those from F814W luminosity functions, because the QT system uses foreground extinction corrected F814W magnitude (F814W 0 ). We detected small photometric offsets from the


O O O O O O B-Telescope I-Telescope O O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization B-Organization I-Organization I-Organization I-Organization I-Organization O B-Location B-Observatory I-Observatory I-Observatory I-Observatory B-Observatory O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O B-Organization I-Organization I-Organization B-Organization O O O O O O O O O O O O O O O O O O B-Organization O B-Organization B-Location B-Person O B-Person O O O O O B-Organization B-Organization B-Organization O O B-Grant I-Grant B-Person B-Person O B-Person O O B-Organization O O O O O O B-Grant O O B-Grant

Based on observations obtained at the SOAR telescope, which is a joint project of the Ministério da Ciência, Tecnologia, e Inovação (MCTI) da República Federativa do Brasil, the US National Optical Astronomy Observatory (NOAO), the University of North Carolina at Chapel Hill (UNC) and Michigan State University (MSU). We thank an anonymous referee for important comments and suggestions. Partial financial support for this research comes from CNPq and PRONEX-FAPERGS/CNPq (Brazil). BB and BD acknowledge partial financial support from FAPESP, CNPq, CAPES, and the LACEGAL project. LK, BB, and BD also thank CAPES/CNPq for their financial support with the PROCAD project number 552236/2011-0.


O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Survey O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject O B-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength O O O O O B-Wavelength

) as well as the line and continuum fluxes using the normalization to the maximum continuum ( right ). The spectra cover ∼8 yr in the QSO rest frame. The shading of the markers indicates the progression of time. The first epoch available (SDSS, MJD 52200) is represented by the light blue marker in the centre of the plot. The initial rise in the continuum is to the epoch of maximum continuum (top right). The gradient of this response is approximately unity. In the next spectrum the continuum has collapsed, and the line has also almost disappeared (bottom left corner). When the continuum rises again, the gradient is considerably steeper. Figure 10. Left : The changing Mg ii line flux in J022556. The high cadence of observations for this object allows us to track the line flux as the continuum falls and rises over the course of ∼8 yr in the QSO rest frame. Right : The Mg ii line fluxes normalized to the maximum continuum. The epochs of the spectra are indicated with the colour, increasing chronologically from light to dark. This plot is based on the normalization of the fluxes to the epoch of maximum continuum. A 1:1 response is indicated with the dashed grey line. The initial increase in line flux is matched approximately 1:1 by the Mg ii line. Following a collapse in line and continuum, however, the gradient of the line responsivity is considerably steeper as the continuum recovers. The epoch-dependent responsivity visible in J022556 (and J002311) indicates that the scatter around the responsivity functions (in Figs 5 and 6 ) could be the result of sampling the varying objects at different stages during the BLR response to the continuum. The response of the line to the continuum does not follow a single gradient for the same object; therefore, we can expect considerable scatter around any linear response function fitted to a large ensemble. 5.3 The iBE A final measure for the responsivity is the iBE, which measures the change in EW compared to the change in continuum luminosity for individual objects. For the full population sample, the iBE is calculated as ΔEW/Δ L 2798 for each spectral pair. For the supervariable sample, the same is done for each chronologically sequential pair. The results for the full population sample are shown in Fig. 11 . Figure 11. A histogram of the intrinsic Baldwin effect for the full population sample. The number of spectral pairs, N , and the sample average, μ, are listed in the top right corner. The iBE is calculated as ΔEW/Δ L 2798 for each pair. Although there are some strong outliers, the distribution is clearly centred around −0.5. This is significantly lower than the slope of the ensemble BE of −0.16 calculated for the data from Shen et al. ( 2011 ). The distribution is largely symmetric and centred around a slope of −0.5. For the supervariable sample, the average slope is −0.54. Unfortunately, there are no literature values of the Mg ii iBE to compare these results to. For other UV lines such as C iv λ1549


O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O B-Tag O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model O O O B-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model O O O B-Formula I-Formula I-Formula O O O O O O O O O O O

⊙ and 0.2 × 10 6 M ⊙ , respectively; the Plummer equivalent co-moving gravitational softening is 2.66 and 1.33 kpc, limited to a maximum physical softening of 0.7 and 0.35 kpc, respectively. The simulations assume the cosmological parameters of Planck Collaboration ( 2014 ), and the minor differences with the Planck Collaboration ( 2016 ) parameters adopted in that paper are unlikely to be important. To compare to the data presented earlier, we need to identify both DLAs and LAEs in eagle . Since neither neutral hydrogen nor Lyα radiative transfer is directly incorporated in eagle , we compute these quantities in post-processing as explained next. 4.1.1 Identifying DLAs in the <sc>eagle</sc> simulations The ionizing background in eagle is implemented in the optically thin limit. Self-shielding of gas, allowing for the appearance of DLAs, is computed in post-processing using the urchin radiative transfer code described by Altay Theuns ( 2013 ). Briefly, this algorithm allows each gas particle to estimate the local ionizing intensity it is subject to by sampling the radiation field in 12 directions, with neutral gas in neighbouring gas particles potentially decreasing the local photo-ionization rate below the Haardt Madau ( 2001 ) optically thin value. Assuming the neutral fraction of a particle is set by the balance between photo- and collisional ionization versus recombinations, a reduced ionization rate increases the particle’s neutral fraction, which in turn affects the ionization rate determined by the particle’s neighbours. The impact of a change in the neutral fraction on the photo-ionization rate and vice versa is iterated until the neutral fraction of each particle converges from one iteration to the next. This post-process step thus yields the neutral hydrogen fraction of each SPH particle. Further details on how radiative transfer affects the neutral fraction as a function of column density and physical processes (e.g. the relative importance of collisional ionisation and photoionsation) can be found in the literature (e.g. Fumagalli et al. 2011 ; Rahmati et al. 2013 ). The resulting H i volume density is then projected onto an 8192 2 grid along the coordinate z -axis of the simulation box, using the Gaussian smoothing described by Altay Theuns ( 2013 ). Applying a column density threshold of allows us to identify DLAs. 2 We also calculate the -weighted z -coordinate and velocity of particles along each DLA line of sight to obtain the 3D position of each DLA (two spatial coordinates x and y , and a redshift coordinate z ). The redshift of each DLA allows us to compare DLAs to galaxies in redshift space, although we note that observed DLA redshifts are derived from low-ionization metal lines rather than H i directly, yet these elements are believed to trace the same phase of the gas. To compare to the muse observations, we analyse the L0025N0752 eagle snapshot at z = 3.027, which is closest in redshift to the data. Similarly to the


O O O O O O O O B-Telescope O O O O O O O O O O O O O O O O O B-Organization I-Organization I-Organization I-Organization O O O O O O O O O O O O O O O O O O O O O O O O O B-Location I-Location O B-Grant O O O O B-Grant B-Grant O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O O O B-Grant O O B-Organization O B-Grant B-Grant B-Person O O O O B-Organization O B-Grant I-Grant I-Grant O O O O O O O O O B-Grant I-Grant B-Grant I-Grant I-Grant I-Grant I-Grant I-Grant O O O O B-Organization I-Organization I-Organization O O O B-Grant O O O B-Organization I-Organization I-Organization O O O O B-Organization I-Organization I-Organization I-Organization O O O B-Grant O O O O O O B-Organization O O B-Grant B-Grant B-Grant

ACKNOWLEDGEMENTS The authors wish to thank the entire Kepler team, without whom these results would not be possible. Funding for this Discovery mission is provided by NASA’s Science Mission Directorate. Special thanks to the referee for pertinent comments on earlier versions of the manuscript that greatly improved the presentation. The research is supported by the European Community Programme ([FP7/2007-2013]) under grant agreement no. FP7-SPACE-2012-312844 (SPACEINN) and by Fundação para a Ciência e a Tecnologia (FCT) through national funds (UID/FIS/04434/2013) and by FEDER through COMPETE2020 (POCI-01-0145-FEDER-007672). MC also acknowledges support from FCT through Investigador FCT contractIF/00894/2012/CP0150/CT0004. This work was also supported in part by the ASTERISK project (ASTERoseismic Investigations with SONG and Kepler ) funded by the European Research Council (grant agreement no. 267864). Funding for the Stellar Astrophysics Centre is provided by the Danish National Research Foundation (grant agreement no. DNRF106). We also acknowledge supports by the NSFC grants (No. 11473053, 11233005, U1331201).


O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O B-Citation O O O O O O O O O O O O O O O O O O O B-Dataset I-Dataset O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation O O O O O O O O O O O O O O O O B-Instrument O B-Citation O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

( UVJ colour selected) at = 1.6. They found a mean age of 1.1 Gyr. As stated by the authors, this value is in excellent agreement with the age of local counterparts, if high- massive quiescent galaxies evolve passively. We verified that more than 80 of their sample is composed of massive passive galaxies with pc, thus we can reasonably compare their results with ours. If we assume passive evolution between and , the mean age of their massive quiescent galaxies rises to 3.1 Gyr. This is in fair agreement with the mean age of high- MPGs we find at ( Gyr) (see also Whitaker et al. 2013 ). Different conclusions were reached by F16. Using stacked spectra, the authors constrained the stellar population ages for dense and less dense passive galaxies in the zCOSMOS sample from to . They found that the age of dense massive quiescent galaxies increases less than would be expected from passive evolution alone. Moreover, they found no correlation between the age of stellar population and the dimension of the source. The present analysis differs from the F16 analysis in a number of ways: the selection of passive galaxies (no emission lines plus no MIPS in F16 vs. NUV colour in our work); the selection of the dense sub-population (cut at fixed or along the SMR vs. cut at fixed ); and the procedure adopted to constrain the stellar population age. Unfortunately, we cannot exactly reproduce their analysis with our data set. In Appendix B, we checked how our results change if we adopt the same criteria used by F16 to select dense and less dense galaxies. We found that the mean age of dense MPGs is consistent with passive evolution and that less dense MPGs are younger than dense MPGs, independently of the criteria used to divide the sub-populations. However, as stated above, we stress that the previous checks rely on a sample of MPGs selected in a different way and adopt different techniques to constrain the stellar population age. In fact, we cannot repeat the same analysis with our data set, so we cannot fully account for the effect of these two factors on the results. Fig. 9 Evolution of the number density of MPGs (filled red circles) and of star forming massive galaxies (MSFGs, blue filled stars). Open circles show the expected growth in the abundance of MPGs below , assuming that this is fully due to the observed decline of MSFGs. Solid and open circles have been shifted for visualisation purposes. 6. Where do new large MPGs come from? The evidence that the new MPGs are systematically younger than high- MPGs contrasts with the hypothesis that all massive galaxies are assembled mostly through dry mergers (e.g. Hopkins et al. 2009 ; Cappellari et al. 2012 ). In fact, dry mergers should dilute any trend between stellar population age and time of appearance by mixing up the stellar population of pre-existing systems. In fact, more recently new pieces of evidence have come to light supporting a scenario in which PGs are mostly the final evolutionary stage of


O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation O B-Citation I-Citation I-Citation O B-Citation O O O O O O O O O O O O O O O O O B-Wavelength O O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O B-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation O B-Citation O B-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O B-Wavelength O O O O O O O O O O O O O O B-Telescope B-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O B-Wavelength O O O O O O O O O O O O O O O O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Tag O O O O O O O B-Telescope I-Telescope I-Telescope B-Citation I-Citation I-Citation I-Citation O O O O

of H 2 in the interstellar medium (Habart et al. 2005 ), several studies have attempted to gain insight into the conditions in PNe where this species is found. The correlation between the bipolar morphology of PNe and the H 2 detection is well documented (Kastner et al. 1996 ), suggesting that the H 2 -bright waists of bipolar PNe are the remnants of dense molecule-rich circumstellar discs. Alternatively, it has been claimed that the preferential detection of H 2 emission in bipolar PNe may be an effect of the typically higher effective temperature of their central stars (Phillips 2006 ; Aleman Gruenwald 2004 , 2011 ). The consensus is that the brightest H 2 emitters tend to be bipolar PNe, but deep near-IR imaging of the 2.122 μm H 2 emission line shows that this emission is not exclusive to this morphology (Marquez-Lugo et al. 2013 ). Besides the excellent near-IR spectroscopic survey of PNe and study of upper vibrational levels carried out by Hora, Latter Deutsch ( 1999 ), an actual investigation of the excitation mechanism of H 2 in PNe and calculations of its excitation temperature have been made in the context of other detailed studies (see e.g. Hora Latter 1994 , 1996 ; Shupe et al. 1998 ; Rudy et al. 2001 ; Lumsden, Puxley Hoare 2001 ; García-Hernández et al. 2002 ; Davis et al. 2003 ; Likkel et al. 2006 ; Ramos-Larios, Guerrero Miranda 2008 ; Aleman et al. 2011 , and references therein). Mid-IR spectroscopy is a powerful tool for the study of the thermal and molecular emission from PNe, since such observations are much less affected by dust extinction. Mid-IR studies of PNe have focused on imaging surveys (e.g. Hora et al. 2004 ; Phillips Ramos-Larios 2008 , 2010 ; Zhang Kwok 2009 ; Zhang, Hsia Kwok 2012 ), but mid-IR spectroscopy of PNe has only been carried out for individual objects for which chemical abundances and H 2 excitation temperatures were obtained (Cox et al. 1998 ; Matsuura Zijlstra 2005 ; Hora et al. 2006 ; Phillips, Ramos-Larios Guerrero 2011 ). Currently, mid-IR studies of the excitation temperature of H 2 in PNe are scarce. Using archival Spitzer mid-IR spectroscopy, we have conducted a spectroscopic survey of PNe to assess the presence of ionic species, polycyclic aromatic hydrocarbons (PAHs), and molecular hydrogen. The H 2 excitation temperature has been derived using its mid-IR emission lines. These temperatures shed light on the purely rotational component of the excitation temperatures to complement the rotational–vibrational studies obtained by near-IR observations. Section 2 details the criteria for target selection and data processing. Section 3 describes the mid-IR spectroscopic properties of each PN in our sample. A review of the theory behind the data analysis is given in Section 4 and the final discussion is presented in Section 5 . 2 ARCHIVAL DATA: SELECTION AND REDUCTION 2.1 The <italic>Spitzer</italic> archive This study made use of the Spitzer Space Telescope (Werner et al. 2004 ) data base. We


O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model I-Model B-Citation I-Citation I-Citation I-Citation O O O O O B-Dataset I-Dataset I-Dataset B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O B-Dataset I-Dataset I-Dataset O O O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O O O B-Model I-Model O O B-Model I-Model O O O O B-Model I-Model B-Citation I-Citation O O O B-Model I-Model B-Citation I-Citation I-Citation I-Citation O O O B-Model O O O O O O O O O O O O B-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O B-Survey O O O O O B-Wavelength B-Wavelength I-Wavelength O B-Wavelength B-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O O B-Model O O O O O O O O O O O O O O O O O O O O O O B-Model I-Model O O O O B-Software B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O B-Model O O O O O O O B-Model O O O O O O B-Survey O O O O O O O O O O O B-Survey B-Observatory O B-Instrument O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model I-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Survey O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Dataset I-Dataset O O O B-Dataset O O O O O O O O O O O O O O

Since there are many possible choices for stellar libraries, IMFs, and isochrones, many SPMs are available. The systematic differences in AGN identification due to the choice of SPM are explored in detail by Chen et al. ( 2018 ). SPMs based on theoretical stellar libraries are subject to model dependence on line profiles and opacity uncertainties. Empirical stellar libraries are not model dependent but need a large number of observed stars that cover the parameter space as completely as possible. The MILES SPM (Vazdekis et al. 2010 ) is constructed from the MILES stellar library (Falcón-Barroso et al. 2011 ), currently the largest and most well-calibrated empirical stellar library. The MILES stellar library consists of 985 stars with a wavelength range of 3525–7500 Å and a spectral resolution of 2.5 Å. In this work, we use the MILES SPM, with a unimodal IMF of slope 1.3, the Salpeter IMF (Salpeter 1955 ), and the Padova isochrone (Girardi et al. 2000 ). It contains SSPs with ages from 63 Myr to 17.78 Gyr and metallicities ranging between [M/H] = −2.32 and +0.22. For each spectrum in our galaxy sample, wavelength ranges with emission lines and telluric contamination bands are masked. Since each galaxy from 6dF was observed in two bands, V (4000–5500 Å) and R (5500–7500 Å), we combine them into a single spectrum by matching in the overlap region and smooth the combined spectrum to the lower ( R -band) resolution, before fitting. The SSPs are broadened to match the spectral resolution of the observed spectra. Each data spectrum is fit as a linear combination of the MILES SSPs using the full-spectrum-fitting program pPXF (Cappellari Emsellem 2004 ). A large fraction of the spectra are fit by a linear combination of one or two SSPs, and nearly all have fewer than five SSPs in the linear combination. For the SDSS spectra only an overall normalization is added to the templates. For 6dF, CTIO, and FAST spectra that do not have absolute flux calibration, the fitting algorithm adds a polynomial, of up to eighth order, to account for the instrumental effects on the spectral shape. The fitting algorithm further broadens the templates with a Gaussian kernel to mimic the stellar velocity dispersion in the integrated spectrum of the host galaxy. The fits are required to yield a physical stellar velocity dispersion, σ fit 1000 km s −1 , in order to be considered acceptable. The fitting routine uses the error spectrum, provided with the data, to calculate a reduced χ 2 value for each acceptable fit. The acceptable fit with the lowest reduced χ 2 is taken to be the best-fit spectrum for the galaxy. Figure 4 shows a typical spectrum from the SDSS sample (black), the error (blue), the best fit (red), and the residual spectra after subtraction in the regions around the emission lines used for AGN identification. Figure 4. Full-spectrum fitting of an illustrative SDSS DR8 spectrum. (a) The DR8 data spectrum is shown as a black line, the error spectrum is shown as


O O O O O O O O B-Organization B-Grant I-Grant I-Grant

Funding for this work was provided by the NASA Planetary Atmospheres Program.


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ACKNOWLEDGEMENTS We would like to thank the anonymous referee for their thorough feedback that has improved the clarity of our paper. Funding for SDSS-III has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, and the U.S. Department of Energy Office of Science. The SDSS-III web site is http://www.sdss3.org/ (Eisenstein et al. 2011 ). SDSS-III is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS-III Collaboration including the University of Arizona, the Brazilian Participation Group, Brookhaven National Laboratory, Carnegie Mellon University, University of Florida, the French Participation Group, the German Participation Group, Harvard University, the Instituto de Astrofisica de Canarias, the Michigan State/Notre Dame/JINA Participation Group, Johns Hopkins University, Lawrence Berkeley National Laboratory, Max Planck Institute for Astrophysics, Max Planck Institute for Extraterrestrial Physics, New Mexico State University, New York University, Ohio State University, Pennsylvania State University, University of Portsmouth, Princeton University, the Spanish Participation Group, University of Tokyo, University of Utah, Vanderbilt University, University of Virginia, University of Washington, and Yale University. We acknowledge studentship fundng by the Science and Technology Facilities Council (STFC), travel support provided by STFC for UK participation in LSST: All Hands Meeting through grant ST/N002512/1 and NASA’s SkyView facility located at NASA Goddard Space Flight Center. We also would like to thank Min-Su Shu at the University of Michigan, James Schombert at the University of Oregon, Edward L. Wright at the University of California, Los Angeles (Wright 2006 ) and Dat Tran ( https://github.com/datitran ) for allowing free distribution of their code.


O O O O O O O O B-CelestialObject O O O O O O O O O B-Wavelength O O O O O O B-Wavelength B-Telescope O O O O O O O O O O O O O O O O O O O B-CelestialObject O O O O O O O O O B-Telescope O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Telescope B-Wavelength O B-Wavelength I-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Telescope O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O B-Model I-Model O O O B-Formula I-Formula I-Formula O O O O B-Software O O O O O O O O B-Citation I-Citation I-Citation O O B-Model I-Model I-Model I-Model O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Telescope B-Instrument B-Wavelength O B-Wavelength I-Wavelength I-Wavelength O O O O O B-CelestialObject O O O O O O O O B-Model I-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O B-Model I-Model O O B-Software O O O O O O B-Model I-Model I-Model B-Citation I-Citation I-Citation I-Citation O O B-Software O O O O O O O O O O B-Wavelength I-Wavelength I-Wavelength O O B-Instrument B-Wavelength O B-Wavelength I-Wavelength I-Wavelength O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula O B-Formula I-Formula I-Formula I-Formula O O O O O O O O B-Formula I-Formula I-Formula O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O B-Model I-Model O O O O O O O O O O O O O O O O B-Model I-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

the observed light curves, RVs, and SED of Mon-735. Jointly modelling the SED allows us to propagate our optical spectroscopic light ratio constraints into the IR Spitzer light-curve bands and use them to help constrain the fundamental parameters of both stars. This is particularly important for Mon-735, as the system displays near-equal eclipse depths in the Spitzer light curves, which can lead to a degeneracy between the radius ratio, surface brightness ratio, and inclination when modelling the data. Details of the modelling are given in Sections 3.1 – 3.3 below. 3.1 Light curves The Spitzer 3.6 and 4.5 μ m light curves are shown in Fig. 2 . In addition to eclipses on both the primary and secondary stars, both light curves display reasonably rough aperiodic out-of-eclipse (OOE) variations, which are similar to Spitzer light curves of other young EBs (e.g. Morales-Calderón et al. 2012 ; Gillen et al. 2017a ). Given the rough OOE variations, we opted to use a Matérn kernel with smoothness parameter ν = 3/2 (as approximated within the celerite package), which is appropriate for such rough variations (Rasmussen Williams 2006 ). The Matérn 3/2 covariance kernel k is given by where τ = | t i − t j | is the time interval between times t i and t j , and A and l are the characteristic amplitude and time-scale of the variations, respectively. Figure 2. Spitzer /IRAC 3.6 and 4.5 μ m relative flux light curves of Mon-735 (black points, top and bottom, respectively) with the gp-ebop model in red and residuals below. In both light curves, the red line and pink shaded regions show the mean and 1σ and 2σ confidence intervals of the predictive posterior distribution. The system displays near-equal eclipses on both stars, which are ∼36–37 per cent deep, as well as relatively rough short time-scale out-of-eclipse variability. We applied theoretical constraints on the quadratic limb darkening parameters using the predictions of Claret, Hauschildt Witte ( 2012 ). We used the Claret tables rather than ldtk because the specific intensities of the PHOENIX model spectra (Husser et al. 2013 ), which ldtk is based on, only extend up to a wavelength of 2.6 μ m, so the IRAC 3.6 and 4.5 μ m bandpasses are not covered. We assumed T eff = 3200 K and log g = 4.0 for both the primary and secondary stars (setting Z = 0.0, which is the closest value available to the cluster metallicity; King et al. 2000 ). 2 The T eff and log g values were set based on preliminary fits to the SED data (using PHOENIX models) and the light curves and RVs, respectively, and then rounded to the nearest value in the Claret tables. Uncertainties on the limb darkening coefficients (LDCs) were set based on the spread of coefficient values within a representative range in T eff and log g , which were determined from initial modelling of the light curves and RVs, and further inflated by comparing the Claret LDC values using both the least-square and flux conservation methods. In practice, given the


O O O O O O O O O O O O O O O O O O B-Instrument O O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O B-Wavelength I-Wavelength O O O O B-Observatory B-Telescope I-Telescope I-Telescope B-Telescope O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O B-Telescope O O O B-CelestialObject O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O B-Telescope O B-Observatory B-Telescope O O O O O O O O O O O O O B-Telescope O O O O O O O O O O O O O O O O O O O O B-Observatory B-Telescope O O O B-Software I-Software O O O O O O O O O O O O O O O O O O O O O O O O O B-Model I-Model I-Model I-Model B-Model O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O B-Observatory B-Telescope O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Identifier I-Identifier O O O O O O B-Observatory B-Telescope O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

to study the variation of LOS plasma velocity during the formation of the penumbra, we also analyzed the SHARPs Dopplergrams, which are taken in the Fe i 617.3 nm with a resolution of 1′′. The velocities inferred by the Dopplergrams were calibrated by assuming that the plasma flow in the sunspot umbrae is at rest. We set the umbra region at rest in order to avoid the effect of plasma convection blueshift in the quiet Sun region (Dravins et al. 1981 ). We also used the images of the He ii 30.4 nm line taken by the SDO /Atmospheric Imaging Assembly (AIA) to investigate the upper atmospheric layers above the developing sunspot. The He ii 30.4 nm line is one of the strongest lines in the AIA observed in the solar spectrum, providing information on the upper chromosphere or lower transition region (Andretta et al. 2012 ; Lemen et al. 2012 ). The NST/TiO and SDO /HMI observations were coaligned by using the first image of TiO taken by the NST at 16:38 UT on 2016 August 11 as a reference and the continuum intensity images at 16:36 UT taken by SDO /HMI. We used the IDL Solarsoft mapping routines to solve the problem of the differential rotation. In addition, we traced the photospheric horizontal motions of the plasma flow by using the Fourier local correlation tracking (FLCT) method in the TiO images (Welsch et al. 2004 ; Fisher Welsch 2008 ). 3. Results Figure 1 shows the surroundings of the interesting sunspot in the continuum intensity images and LOS magnetograms taken by SDO /HMI. The black boxes in Figure 1 outline the region of the interesting sunspot. The interesting sunspot was a developing sunspot. The developing sunspot had two umbrae with some preexisting penumbral filaments. It was formed as a result of the coalescence of sunspots “S1” and “S2” (see Figure 1 (a1)). The newly formed penumbra sector was located at the northwest side of the developing sunspot, as shown by the red boxes in Figures 1 (a2) and (b2). The developing sunspot changed its initial shape in the process of new penumbra sector formation, as shown in Figures 1 (a1)–(a3). With the growth of the developing sunspot, sunspots S1 and S2 gradually combined. The developing sunspot was characterized by negative polarity. Some thin filaments around the developing sunspot stretched to the region that was characterized by positive polarity (see Figures 1 (a1), (b1), (a2), and (b2)). Figure 1. Evolution of active region NOAA 12574. (a1–a2): continuum intensity images observed by SDO /HMI. (b1–b2): corresponding LOS magnetograms. The white contours indicate the boundary of the umbra as seen in the continuum intensity images. The developing sunspot is marked by the black boxes. The two sunspots in the black box of Figure 1 (a1) are marked “S1” and “S2”. The black boxes also indicate the field of view of Figures 2 – 5 , 7 , and 8 . Each red box in Figures 1 (a2) and (b2) indicates the position of the newly formed penumbra sector. Figure 2 shows the evolution of the developing


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We are grateful to the following people who took part in the infrared photometry programme at Sutherland, Brian Carter, Dave Laney and Enrico Olivier. MWF and PAW gratefully acknowledge a research grant from the SA National Research Foundation. We thank an anonymous referee for comments and specifically for raising the question of the helium abundance. We made use of the VizieR and SIMBAD databases of the CDS in preparing this paper. This paper uses observations made at the South African Astronomical Observatory (SAAO).


O O O O O O O O O O O O O O O O B-Model I-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model I-Model B-Citation I-Citation O B-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula O O O O O O O O O O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O B-Model I-Model O B-Formula I-Formula I-Formula O B-Model I-Model O B-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O B-Citation I-Citation O O O O O B-Citation I-Citation I-Citation O O O O O B-Citation I-Citation O O O O O O B-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model I-Model O O B-Model I-Model I-Model O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O B-Wavelength O O O O O

spectra are known in detail. Most importantly, geometrical effects cause the spectra to differ from a Planck spectrum. In particular, in the case of the photosphere occurring in the coasting phase, i.e. above the saturation radius, r s , the spectrum is significantly different from a Planck function (Goodman 1986 ; Beloborodov 2011 ; Lundman, Pe’er Ryde 2013 ). Its spectral shape is much broader, while the asymptotic, low-energy spectral slope is still very hard, with α ∼ 0.4. The most common way to assess different emission models in GRBs is by studying the sub-peak spectral shape. This is characterized by the photon index, α , of the Band function or, similarly, of the cut-off power-law function (Band, Matteson et al. 1993 ). The values of α can vary significantly depending on the emission process that is taking place. In an optically thick, thermal scenario, the Rayleigh–Jeans limit has α = 1, the Wien limit has α = 2, and the non-dissipative photosphere in the coasting phase has the expected α of 0.4. Non-thermal emission is always in the regime α 0. The limiting value can be reached by synchrotron emission in many specific cases, such as from electrons with a small pitch angle distribution (Lloyd Petrosian 2000 ), jitter radiation (Medvedev 2000 ), with attenuation by scattering (Dermer Böttcher 2000 ), and thermal synchrotron emission (Petrosian 1981 ). Likewise the limiting values of α = 0 can be reached by synchrotron self-Compton emission from monoenergetic electrons scattering off a self-absorbed seed photons field (Stern Poutanen 2004 ). More generally, instantaneous or fast synchrotron cooling can explain α −3/2 and slow synchrotron cooling is expected to occur at α −2/3 (e.g. Tavani 1996 ). However, before comparing predictions of physical emission models to the observed characteristics of bursts, such as the distribution of α values, limitations of the detector and the analysis methods must also be taken into account. Such limitations could cause spuriously deviation from the expected α (e.g. Preece et al. 1998 ; Lloyd Petrosian 2000 ). One such limitation is due to the limited band-width of the detector which prevents the full spectrum to be detected. Another limitation is due to the typically empirical models that are used to fit the data; the Band function and the cut-off power-law function (see e.g. Yu et al. 2016 ). If these empirical models do not match the true spectral shape, such as its curvature, then the fitted parameters might not be readily interpreted. There are two possible routes to address these limitations. One way is to fit physical models directly to the data, which eliminates the need for fits to empirical functions (e.g. Lloyd Petrosian 2000 ; Zhang Yan 2011 ; Ahlgren et al. 2015 ; Giannios 2006 ; Vianello et al. 2018 ; Burgess et al. 2018 ; Ahlgren et al. 2019 ). However, such analysis is computationally very demanding and, moreover, with the present, limited understanding of GRBs it is not clear what


O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation O O O O O O O O O O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

by a characteristic timescale, t esc . The evolution of the particle number density, , in the CR can then be conveniently described by the kinetic equation (Kardashev 1962 )where is the energy loss rate due to synchrotron and SSC processes. Assuming a power law dependence of escape timescale with energy , a semianalytical solution of Equation ( 8 ) can be attained when the loss processes are confined within the Thomson regime (Atoyan Aharonian 1999 ). However, detection of the source at VHE energies suggests that the Thomson scattering approximation of SSC process may not be valid and one needs to incorporate Klein–Nishina correction in the cross-section (Tavecchio et al. 1998 ). Hence, we numerically solve Equation ( 8 ) using a fully implicit finite difference scheme (Chang Cooper 1970 ; Chiaberge Ghisellini 1999 ), while incorporating the exact Klein–Nishina cross-section for IC scattering (Blumenthal Gould 1970 ). The case (no escape) gives rise to a BPL with the break occurring at the energy where the observation time is equal to the cooling timescale of the particle, while for the case (constant t esc ), a steady state BPL particle distribution is eventually attained where the break corresponds to the particle energy at which the escape timescale equates to its cooling timescale. However, in these cases, the spectral transition at the break energy is too sharp to reproduce the observed SED, and a gradual transition can be achieved by considering . We found that the smooth spectral curvature demanded by the observation can be attained by fixing . In Figure 7 , we show the resultant model SED corresponding to (blue line) and , along with the observed fluxes for the state s3. The underlying particle distribution corresponding to these values of ξ is shown in Figure 8 . Figure 7. Model curves obtained by changing the energy dependence of the escape timescale for the state s3. The blue line is obtained for a energy independent escape (), and fails to reproduce the observed spectrum. The best match between the data and the model is obtained for and is represented by the solid green line. The magnetic field B is assumed to be 0.4 G and the Doppler factor . The injected particle spectrum is a power of index 2.1. Figure 8. Underlying particle spectra for the model curves shown in Figure 7 . The dashed blue line is obtained for an energy independent escape ( which fails to reproduce the observed SED), and the solid black line corresponds to the particle spectrum that best models the observed SED (). Alternate to this interpretation, a smooth curvature in the particle distribution can also be a result of time averaging of an evolving particle distribution. For instance, an episodic injection of a power-law particle distribution into CR can cause the high energy cutoff to shift toward lower energy with time, which will be reflected as a smooth curvature at high energy in the time averaged spectrum. Also, an episodic injection with an


O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject O O O O O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O B-CelestialObject I-CelestialObject O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model I-Model O O O O O O O O O B-CelestialObject O O B-CelestialObject I-CelestialObject O O O O O O O O O O O O B-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation O B-Citation I-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject O O O O O O O O O B-CelestialObject I-CelestialObject I-CelestialObject I-CelestialObject O O O O O O O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O B-CelestialObject O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O B-CelestialObject I-CelestialObject O O O O B-CelestialObject I-CelestialObject I-CelestialObject I-CelestialObject O O O B-CelestialObject O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O B-CelestialObject I-CelestialObject I-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O B-CelestialObject I-CelestialObject O O O O O O O O O B-CelestialObject O O O B-Citation I-Citation I-Citation O O O O O O O O O O B-CelestialObject O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O B-CelestialObject O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O B-CelestialObject O O B-Wavelength O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

gas: we see the bubble expanding in two directions. Since the [C II ] emission from NGC 1977 is fainter than that of M 42, we have opted to determine the expansion velocity from spectra towards this region ( Fig. 18 ), resulting in v exp ≃ 1.3 km s −1 . This is consistent with the pv diagram shown in Fig. 17 , from which we obtain the bubble radius r ≃ 500′′ ≃ 1.0 pc with the expansion velocity of v exp ≃ 1.5 km s −1 . As for the Veil shell and M 43, the systematic uncertainty of the mass estimate are of the order of 50%, systematic uncertainties of the estimates of the extent of the shell and of the expansion velocity are about 30%. Table 4 Gaussian fit parameters of spectrum in Fig. 18 . 4 Discussion OMC1, including the Trapezium cluster, is the nearest site of active intermediate- and high-mass star formation (e.g., Hillenbrand 1997 ; Megeath et al. 2012 , 2016 ; Da Rio et al. 2014 ; Großschedl et al. 2019 for discussions of the stellar content). Most of the stars formed and forming are low-mass stars, but also some high-mass stars, that have profound impact on the characteristics and evolution of their environment. Outside the Huygens Region, a significant massive (triple) star is the O9.5IV star θ 2 Ori A, located just to the southeast of the Orion Bar. The radiation of this star dominates the ionization structure of the gas towards the south-east of the HuygensRegion ( O’Dell et al. 2017 ). It also possesses strong winds. The most dominant star in the Orion Nebula is the O7V star θ 1 Ori C, the most massive Trapezium star. It is itself a binary, with possibly a third companion ( Lehmann et al. 2010 ). While its exact peculiar velocity is controversial, the θ 1 Ori C is plowing away from the molecular cloud, the site of its birth, and will have travelled some 25 pc before it explodes as a supernova ( O’Dell et al. 2009 ; Kraus et al. 2009 ; Pabst et al. 2019 ). While the small, 0.5 pc sized Huygens Region has been extensively studied, studies on the much fainter EON are less numerous. O’Dell Harris (2010) determine the temperature of the ionized gas within the large EON H II region to be T ~8.3 × 10 3 K, while electron densities decrease from n e ~ 3000 cm −3 at the Trapezium stars to about n e ~ 30 cm −3 20′ away, roughly as d −2 , with d the projected distance. Güdel et al. (2008) report that the EON exhibits significant X-ray emission, emanating from hot ( T ~ 2 × 10 6 K), dilute ( n e ~ 0.1−0.5 cm −3 ) gas. While, in principle, ionization followed by thermal expansion of the H II region can create a bubble of ~ 2 pc size, the hot gas is the tell-tale signature that the stellar wind of massive stars, rather than stellar radiation, is driving the expansion and forming the EON cavity. As Güdel et al. (2008) note, the emission characteristics in conjunction with its structure and young age render it unlikely that the bubble is a supernova remnant. While the observed morphology is in qualitative agreement with simple models for stellar


O O B-Wavelength I-Wavelength O B-Model I-Model I-Model I-Model I-Model I-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialRegion I-CelestialRegion O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O B-Instrument O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O O B-Wavelength I-Wavelength I-Wavelength O O O O O O O B-Wavelength I-Wavelength I-Wavelength O O B-Wavelength I-Wavelength I-Wavelength I-Wavelength O O O O B-Telescope O B-Instrument O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialRegion I-CelestialRegion I-CelestialRegion O O O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O B-Telescope O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialRegion I-CelestialRegion I-CelestialRegion O O O O O O O O O O O O O O O O O O O O O O B-CelestialRegion I-CelestialRegion O O O O O O O O O B-Wavelength I-Wavelength O O O O O O O O B-Wavelength I-Wavelength I-Wavelength O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O O O O O

extrapolation to 150 GHz. The Planck 2013 best-fit CDM CMB model based on temperature anisotropies, with a tensor amplitude fixed at , is overplotted as a black line. 6.2. Statistical estimate of the dust B-mode level in the BICEP2 field We have seen in Sect. 5.2 that the dust spectra amplitudes statistically follow an empirical scaling law of the mean dust intensity for the patch on which they are computed. We can use this scaling law to assess the most probable dust value for . For this field, which has a mean dust intensity of = 0.060 , the expected value at 353 GHz is K at , taking into account the uncertainty on the fitted amplitude from Sect. 4.3 . In order to extrapolate this value to the BICEP2 observing frequency, 150 GHz, we proceed as in Sect. 5.3 , using the same typical dust SED from Planck Collaboration Int. XXII (2015) . For patches the size of the expected dispersion of (Sect. 2.2.1 ) is 0.11, which introduces an uncertainty in the extrapolation. The extrapolation, unlike in that section, is made to 150 GHz taking into account the BICEP2 bandpass 16 . The conversion factor from the Planck 353 GHz band to the 150 GHz BICEP2 band, taking into account both Planck and BICEP2 colour corrections, as well as the statistical error on , is thus in the SED, and therefore this value squared in . The resulting expected dust amplitude at 150 GHz is K at . The uncertainty quoted here applies to the most probable value for patches with a similar , but it ignores the intrinsic dispersion around this value (see Sect. 5.2 ). Therefore, a direct measurement of the dust spectrum in is required to complete the assessment of its polarized dust level. In Sect. 5.3 , we have localized the amplitudes from the analysis of patches on a map. The pixels falling inside the approximate BICEP2 deep-field region shown in Fig. 8 give a mean value of , i.e., an expected dust power of K at 150 GHz and ; we note that in this region the Planck estimate of the dust contamination is significantly higher, by a factor of about 2, than it is in some more optimal patches. Nevertheless, a more accurate estimate of the dust polarization amplitude in the BICEP2 observed field requires the direct computation of the angular power spectrum on a similar region. 6.3. BB angular power spectrum of dust in the BICEP2 field We now compute the spectrum of the dust at 150 GHz on presented in Sect. 6.1 , using the Planck 353 GHz data. For this purpose, we compute the 353 GHz spectrum by cross-correlating the two DetSets that have independent noise at this frequency in the three -bins defined by the intervals between multipoles 40, 120, 250, and 400. The -bin sizes were increased with respect to the previous sections in order to increase the S/N, especially around the range of the CMB recombination bump. Appendix D.1 confirms that the result does not depend on the method of computing the power spectrum. This power spectrum is extrapolated to 150 GHz as in Sect. 6.2 , with an


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ACKNOWLEDGEMENTS We thank Emanuele Giallongo, Andrea Grazian, Frederick Davies, and the anonymous referee for useful comments. This work is carried out within the Collaborative Research Centre 956 ‘The Conditions and Impact of Star Formation’, sub-project C4, funded by the Deutsche Forschungsgemeinschaft (DFG). We are thankful to the community developing and maintaining software packages extensively used in our work, namely: matplotlib (Hunter 2007 ), numpy (Walt, Colbert Varoquaux 2011 ), scipy (Jones et al. 2001 ), yt (Turk et al. 2011 ).


O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O B-Telescope O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Software I-Software I-Software I-Software O O B-URL O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O B-Model I-Model O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject O O O O O B-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject O B-CelestialObject O B-CelestialObject O B-CelestialObject O O B-CelestialObject O O O O O O O O O O O O O O O B-CelestialObject O O O O O O O O O O O O O

on the age and wind velocity of the driving W-R star and also on the initial density of the surrounding molecular cloud. Figure 6 (b) shows the 13 CO spectrum of the G27 region. The molecular cloud hosting this particular region is located at a velocity range of 88–95 km s −1 (see Dewangan et al. 2016 ). The spectrum is constructed by combining all 13 CO emission within a 45′′ diameter (i.e., the beam size of the GRS data) centered on the W-R star. Two emission peaks are clearly visible in the spectrum. We estimated the kinematic distance corresponding to the velocity of the trough ( v LSR ∼ 92.0 km s −1 ; see Figure 6 (b)) using the “Kinematic Distance Calculation Tool” 10 10 http://www.treywenger.com/kd/index.php of Wenger et al. ( 2018 ), which evaluates a Monte Carlo kinematic distance adopting the solar Galactocentric distance of 8.31 ± 0.16 kpc (Reid et al. 2014 ). The calculation yields a near kinematic distance ( d near ) of 5.2 ± 0.6 kpc. The spectrophotometric distance of the W-R star associated with the reference region is 5.2 ± 0.5 kpc (Dewangan et al. 2016 , see also Table 1 ). A well-matched distance of a W-R star with the velocity of the trough in the 13 CO spectrum implies a physical association of the W-R star with this particular molecular cloud, and more precisely, with the trough at a v LSR of 92.0 km s −1 . The 13 CO spectrum (Figure 6 (b)) also exhibits two emission peaks corresponding to blueshifted (90.2 km s −1 ) and redshifted (93.2 km s −1 ) parts of the cloud, possibly dispersed by the energetics of the W-R star. Evidence of the influence of the W-R star was already found for this region by Dewangan et al. ( 2016 ). Hence, any region with a double-peaked 13 CO spectrum toward the position of a W-R star exhibiting a trough might be explored for any impact of W-R stars on their parent molecular clouds. The 13 CO spectra for our selected regions are constructed by integrating all emission within a 45′′ diameter, centered on the positions of the W-R stars (Figure 7 ) for velocity ranges where dust clumps are generally identified (see Section 2 ). All spectra show similar double-peaked spectral signatures as seen in the spectrum toward the reference region (see Figure 6 (b)) except for the G34 region. The spectrum for the G34 region constructed for a 45′′ diameter shows three peaks (see Figure 7 (c)). However, the highest velocity peak (at v LSR of ∼61 km s −1 ) dissolves when the spectrum is produced for a 240′′ diameter. This implies a small component of molecular gas along the sight line to the W-R star, which is peaking at a v LSR of 61 km s −1 . The emission peaks, troughs, and corresponding velocities are marked and labeled in Figure 7 . Figure 7. 13 CO spectra of our five selected regions (a) G15, (b) G24, (c) G34, (d) G35, and (e) G51. The spectra were constructed following the same procedure as that applied to the reference region, G27 (see the caption of Figure 6 ). Velocities corresponding to the blue- and


O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Telescope I-Telescope I-Telescope I-Telescope O O O O B-Archive I-Archive I-Archive I-Archive I-Archive I-Archive I-Archive I-Archive O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O B-Organization O B-Grant I-Grant O O O O O O B-Identifier O B-Observatory I-Observatory I-Observatory I-Observatory O O O O O O O O B-Organization I-Organization I-Organization I-Organization O B-Organization I-Organization I-Organization O O B-Organization I-Organization I-Organization I-Organization I-Organization O O O O O O O O O O O O B-Organization I-Organization I-Organization I-Organization O O O O O O O O O O O O O B-Location O O O O O O B-Location O O O O O O O O O O O O O O O O O O O O O O B-Archive I-Archive I-Archive B-Archive O O O O O B-Observatory I-Observatory I-Observatory I-Observatory O O B-Organization I-Organization I-Organization I-Organization B-Organization O O O O B-Organization I-Organization I-Organization I-Organization I-Organization O O O O B-Person I-Person O O O O B-Observatory O B-Identifier I-Identifier O O O O B-Observatory O B-Person I-Person O O O O O O O B-Telescope O O O O O O O O O O B-ObservationalTechniques O O O O O O B-Person I-Person I-Person O B-Organization O O O O B-Identifier O O O O O B-Instrument O B-Person O O O O O B-Person I-Person O O O O B-Survey O O B-Person I-Person I-Person I-Person O O O B-Person I-Person O O O O O O O B-Person I-Person O B-Person I-Person O O O O B-Person O O O B-Person I-Person I-Person I-Person O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization O O B-Organization I-Organization I-Organization B-Person O O O O O B-Location B-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O O O B-Grant O O O O O O O B-Location I-Location I-Location O B-Person O O O O B-Organization I-Organization I-Organization B-Person O O B-Fellowship I-Fellowship I-Fellowship O B-Organization I-Organization I-Organization I-Organization B-Person O O O O O B-Grant B-Person O O O O O O B-Organization I-Organization I-Organization O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O O O O O O O O O B-Grant O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O O B-Grant O O B-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant B-Grant I-Grant B-Grant O O O O O O O O B-Organization O B-Grant O O O B-Identifier O O O B-Organization O O O O O B-Organization I-Organization I-Organization I-Organization O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O B-Organization O B-Grant I-Grant O B-Telescope B-Instrument O B-Telescope B-Instrument O O B-Software I-Software B-Software I-Software B-Citation I-Citation O B-Software I-Software

The authors would like to offer their thanks to the anonymous referee of the original manuscript for their constructive comments and suggestions. Based on observations made with the NASA/ESA Hubble Space Telescope , obtained from the Data Archive at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are associated with program #14125. The W. M. Keck Observatory is operated as a scientific partnership among the California Institute of Technology, the University of California and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation. The authors wish to recognize the significant cultural role that the summit of Maunakea has always had within the indigenous Hawai’ian community. We are most fortunate to have the opportunity to conduct observations from this mountain. This research has made use of the Keck Observatory Archive (KOA), which is operated by the W. M. Keck Observatory and the NASA Exoplanet Science Institute (NExScI), under contract with the National Aeronautics and Space Administration. The authors also acknowledge Shri Kulkarni as the PI of Keck program ID C254LA. We also acknowledge the Keck observer Yi Cao. The authors would like to thank the HST staff for their heroic efforts scheduling our early-time, and disruptive, spectroscopic observations. Particular thanks are given to Charles R. Proffitt, the STScI Contact Scientist for programme #14125, for his support with the STIS observations. M.J.D. would like to personally thank Julianne Dalcanton for guidance with the PHAT extinction studies, Laura Darnley (née Wisson) for reading chemistry(!), Toby Moore for useful discussions about interstellar extinction, and Steve Shore and Iain Steele for their spectroscopic insight. P.G. wishes to thank William (Bill) P. Blair for his kind hospitality in the Rowland Department of Physics Astronomy at the Johns Hopkins University. M.H. acknowledges the support of the Spanish Ministry of Economy and Competitiveness (MINECO) under the grant FDPI-2013-16933 as well as the support of the Generalitat de Catalunya/CERCA programme. N.P.M.K. acknowledges funding from the UK Space Agency. S.C.W. acknowledges a visiting research fellowship at Liverpool John Moores University. K.H. was supported by the project RVO:67985815. V.A.R.M.R. acknowledges partial financial support from the Radboud Excellence Initiative, from Fundação para a Ciência e a Tecnologia (FCT) in the form of an exploratory project of reference IF/00498/2015, from Center for Research Development in Mathematics and Applications (CIDMA) strategic project UID/MAT/04106/2013 and from Enabling Green E-science for the Square Kilometer Array (ENGAGE SKA) ROTEIRO/0041/2013/022217. This work has been supported in part by NSF grant AST-1009566. Support for program #14125 was provided by NASA through a grant from the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. Facilities: HST (STIS) , Keck:I (LRIS) . Software: gnuplot (v5.0.6), IRAF (v2.16.1, Tody 1993 ), PGPLOT (v5.2).


O O O O O O O O O O O O O O O B-Person I-Person O O O O O O O O O O B-Person O B-Person O O O O O B-Location B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O B-Grant I-Grant I-Grant I-Grant B-Person O O O O O B-Grant I-Grant I-Grant I-Grant B-Person O O O O B-Organization B-Grant I-Grant I-Grant I-Grant I-Grant B-Person B-Person O B-Person O O O B-Organization O O B-Grant I-Grant I-Grant I-Grant I-Grant O B-ComputingFacility I-ComputingFacility I-ComputingFacility O O O O B-Location I-Location I-Location I-Location I-Location O O O O O O O O O O O O O O O O O O O O O O O O B-Proposal I-Proposal I-Proposal I-Proposal I-Proposal I-Proposal I-Proposal I-Proposal I-Proposal I-Proposal O O O O B-Person I-Person I-Person

ACKNOWLEDGEMENTS We gratefully acknowledge the anonymous referee for useful comments and suggestions. We also thank E. Bonnasieux, who carefully read the manuscript, helping us to improve it. FL and AB acknowledge financial support from the Italian Minister for Research and Education (MIUR), project FARE SMS, code R16RMPN87T. AB acknowledges financial support from the ERC-Stg DRANOEL, no 714245. IP acknowledges funding from the INAF PRIN-SKA 2017 project 1.05.01.88.04 (FORECaST). IP, FL and MM acknowledge support from INAF under the MAIN STREAM PRIN project ‘SAUROS’. The TRG computer cluster was funded by the Autonomous Region of Sardinia (RAS) using resources from the Regional Law 7 August 2007 n. 7 (year 2015) ‘Highly qualified human capital’, in the context of the research project CRP 18 ‘General relativity tests with the Sardinia Radio Telescope’ (P.I. of the project: Dr. Marta Burgay).


B-Software O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Software O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Software O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Software O O O B-Software O B-Model O O B-Citation I-Citation I-Citation O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O B-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O B-Model O O O B-Citation I-Citation I-Citation O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O B-Citation I-Citation O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O B-Software O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation O B-Model I-Model I-Model I-Model B-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Software I-Software I-Software I-Software I-Software B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Software O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O O

GARSTEC increase the grid size considerably. The advantage of one such giant grid is that we can reuse it for the newly observed stars unlike the grid constructed using the MESA. The disadvantage is that we need much larger disc space (current grid needs 4TBs of disc space to store the local properties of the models needed for the frequency computation). Furthermore, the models on a track have poorer temporal resolution. We obtained models for the individual stars from the above tracks following the same procedure as for the MESA, i.e. we scanned all the models in a track and located the age range where T eff , [Fe/H] s , and 〈Δν〉 were all within 4σ of the observed values, subsequently we fitted the surface-corrected model frequencies (Kjeldsen et al. 2008 ) to get a representative model for the star. Repeating this for all the 6000 tracks, we obtain several tens to few hundred models per star. 3.3 YREC models We used YREC with OPAL high-temperature opacities (Iglesias Rogers 1996 ) supplemented with low-temperature opacities of Ferguson et al. ( 2005 ). The metallicity mixture from Grevesse Sauval ( 1998 ) was used. We used the 2005 version of the OPAL equation of state (Rogers Nayfonov 2002 ). All the nuclear reaction rates were from Adelberger et al. ( 1998 ) except for the 14 N( p , γ) 15 O reaction, for which we used the updated rates of Formicola et al. ( 2004 ). A step overshoot (Maeder 1975 ) of α OV = 0.2 H p , where H p is the pressure scale height, was used for all the stars. The YREC models were used to isolate the impact of the atomic diffusion on Y s determination by using the models with and without diffusion. The adiabatic oscillation frequencies were calculated using a code described in Antia Basu ( 1994 ). The Yale Monte Carlo Method (Silva Aguirre et al. 2015 ) was used to get a set of representative models for each star. We started with using the average large frequency separation and frequency of maximum power along with the spectroscopically determined effective temperature to get an estimate of the mass and radius of the star using the Yale Birmingham Grid-Based modelling pipeline (Basu, Chaplin Elsworth 2010 ; Gai et al. 2011 ). Since each of the observables has the associated observational error, we created thousands of realizations of M, R, T eff , and [Fe/H] s . For each realization, we used the YREC in an iterative mode to obtain a model of given M and [Fe/H] s that had the required R and T eff . This was done in two different ways: in the first approach, we kept α MLT fixed at different values and iterated over Y i to get the model; and in the second approach, we kept Y i fixed at different values and varied α MLT to get the required model. Finally, a set of representative models of the star was obtained based on the merit function, where and are the reduced chi-squares for the oscillation frequencies and frequency ratios, r 02 and r 01 (for the definition of ratios, see Roxburgh Vorontsov 2003 ). The was computed


O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation B-Citation B-Citation O O B-Citation O B-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Telescope O B-Formula I-Formula I-Formula I-Formula O B-Observatory O O O O O O O O O O O O O B-Survey I-Survey O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation B-Observatory O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-TextGarbage I-TextGarbage O O O O O O O O O O B-TextGarbage I-TextGarbage O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-TextGarbage I-TextGarbage O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

corresponding to the 1σ uncertainties of log A and γ at z ∼ 6 from the [C ii ] power spectrum in the fiducial survey. The L18, deL14d, deL14 z , O17, and V15 relations are assumed for generating the input power spectrum. In each panel, the regions with dark (light) colour refer to using the full power spectrum (shot noise only). We use δν 0 = 1.0 GHz to translate the [C ii ] luminosity into the flux per beam; see the top x -axis. We also mark with vertical lines the detection limits by HST ( M UV ∼ −16.5, dashed–dotted), ALMA (∼10 8 L ⊙ , dashed), and the 5σ level of the underlying IM survey (solid), respectively. Figure 10. The 1σ constraint contours of the log A– γ parameters from the full power spectrum for the five relations. The ‘ + ’ symbols mark the input values. Ideally, this is the key result that we can expect from our fiducial-like IM experiment combined with the existing upper limits on the LF coming from pointed observations. We warn that these results depend on the underlying assumption of a single power-law form for –SFR relation, , and shown in Fig. 2 . At present, this remains only an educated guess for high-redshift galaxies, as also hinted by the more complex shape found by state-of-the-art simulations in P15 , and more recently by Pallottini et al. ( 2019 ). ALMA surveys covering a larger area and/or reaching to fainter fluxes, plus a more accurate determination of the galaxy SFR, would be of fundamental importance for this issue. 4.2 Survey strategies We finally investigate how to optimize a survey for a [C ii ] IM experiment. Generally, given the observation time and bandwidth, when , , a narrow and deep field has larger S/N. However, when , , wider field has larger S/N. For some applications, though, a highest S/N is not necessarily the first priority indicator for optimizing surveys; instead, a wide survey is preferred in order to sample long-wavelength k -modes carrying cosmological information and break parameter degeneracy, even at the price of lowering the S/N. We discuss this issue in the context of recovering a fundamental physical quantity as the [C ii ] luminosity density, 10 the first moment of the LF We compute the expected relative variance of the recovered [C ii ] luminosity density, , as a function of t obs for four different surveys with different telescope diameter D , survey area Ω survey , or bandwidth. These cases allow us to compare the survey performances in terms of small and large diameters (S1 versus S3), narrow and wide field (S1 versus S2), low and high angular resolution (S1 versus S3), and number of bolometers and higher noise level (S4). We use the L18 relation to make the input signal. The details of each survey are listed in Table 3 . The results (in units of percentage) are plotted in Fig. 11 , where the relative variances obtained from the shot noise only (power spectrum at k max ) and from the full power spectrum are shown separately by thin and thick lines, respectively. Figure 11.