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

[CII] redshift ( Carilli et al. 2013 ). The rest-frame frequencies of HF J = 1–0 and H 2 O (2 20 –2 11 ) are 1232.476 and 1228.789 GHz respectively. In contrast, the line width of the H 2 O (2 20 –2 11 ) in the QSO is, within the uncertainties, exactly the same as for the other lines. Neither the QSO or the SMG show clear evidence for an outflow in the H 2 O line, although there is a possible excess in the line profile of the QSO seen ∼400 km s −1 blueward of the systemic H 2 O redshift, consistent with the velocities of the weak [CII] outflow ( Carilli et al. 2013 ). 4. Discussion 4.1. HF: Molecular gas irradiated by AGN and young stars The detection of HF emission in the QSO is unusual. In most of the sources observed thus far, the HF J = 1–0 line is observed as an absorption line with little or no emission ( van der Werf et al. 2010 ). Only a handful of sources are known to have HF purely in emission, without any obvious associated absorption. These sources are the Orion Bar ( van der Tak et al. 2012 ; Kavak et al. 2019 ), Mrk 231 ( van der Werf et al. 2010 ), and a few nearby galaxies ( Pereira-Santaella et al. 2013 ; Lu et al. 2017b ). To increase the number of galaxies observed with HF in emission, we extracted the HF emission line fluxes from local galaxies observed with Herschel in the sample of Yang et al. (2013) , which all host AGN. We find that the galaxies that host AGN and the QSO in BR 1202-0725 have an approximately constant ratio of L HF / L IR irrespective of L IR (Fig. 3 ). We note, however, that the exact slope of the relation only considering the local AGN and QSO is dependent on the far-infrared luminosity used. Other estimates of the infrared luminosity of the QSO in the literature would lower L IR / L HF (cf. Salomé et al. 2012 ; Wagg et al. 2014 ; Lu et al. 2017a ). Fig. 3. Relationship between the infrared luminosity and the ratio of the HF luminosity and infrared luminosity of BR 1202-0725, a sample of local AGN ( Yang et al. 2013 ), and the Orion Bar ( Salgado et al. 2016 ; Nagy et al. 2017 ). All sources are labeled. We show a least-squares fit to the local AGN, QSO, and the Orion Bar (black line with the dotted line extension to the Orion Bar), which implies the ratio is constant. We note that fitting the AGN and QSO only yields a similar fit but with a slightly steeper slope. For comparison, we show the ratio L HF / L IR for the entire IR luminosity of the Orion Bar and the luminosity if only 2% of the total IR luminosity is within the Herschel beam used to measure the HF flux (see text for details). The Orion Bar is the only known galactic source or sight-line where HF appears purely in emission (although we note that the absorption of HF and the nearby H 2 O (2 20 –2 11 ) could mask any emission in other galactic and extra-galactic sources; see e.g., Monje et al. 2014 ; Neufeld et al. 2010 ; Sonnentrucker et al. 2015 ). If we compare L HF / L IR and L IR for the Orion Bar ( Salgado et al. 2016 ; Nagy et al.


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afterglow emission takes place when the Lorentz factor of the core of the blast slows down to Γ ∼ 1/ θ v which falls into mildly relativistic domain if θ v is relatively large. Since we wish to follow the blast emission up to, and shortly after, its peak, a treatment that follows the blast deceleration down to a trans-relativistic speed is required. In this work we use a semi-analytical model following the shock jump conditions derived by an approximate trans-relativistic EoS (Uhm 2011 ). This model works well at both high and modest Lorentz factors and can smoothly transform to a Sedov–Taylor solution when the shock is no longer relativistic. Our model assumes one-dimensional radial solution for each blast segment. Therefore, we neglect sideways (lateral) expansion in our model. The sideways expansion of the blast is important only at later stages of the blast evolution and it affects the light curve predictions after its peak (Gill Granot 2018 ). However, the key factor to constrain inclination angle, of interest in this study, is the arising slope before the peak flux, where the jet is still relativistic. So the sideways expansion will not influence our result. To describe the physical quantities more clearly, here we consider two reference frames. One is burst rest frame (hereafter BR frame) which is at rest with the central engine. The other is the shock co-moving frame (hereafter CM frame) which is at rest with respect to the gas just downstream of the forward shock. Primed variables (i.e., denoted with ′) are measured in CM frame, while non-primed ones are measured in BR frame. Under the approximation of neglecting sideways expansion, we can regard the jet evolution at each radial direction as being independent. It is therefore convenient to describe the evolution at each direction by using isotropic equivalence quantities. Consider an isotropic burst of total energy E iso = Γ 0 M ej c 2 , where M ej is the mass of ejecta and Γ 0 is its initial Lorentz factor. The outflow spreads in a cold uniform environment of number density n and forms a relativistic shock. We assume that the blastwave is expanding adiabatically without further energy injection (for considerations of energy injection in the blast see Lamb et al. 2020 ). Energy loss due to radiation is negligible compared with E iso . We define the radius R of the shock by the distance from burst center to the forward shock. All swept-up mass is compressed in the downstream of forward shock, moving with Lorentz factor Γ measured in BR frame, and its isotropic kinetic energy is E k . We also assume that all ejecta are moving together with shocked ambient at the same Lorentz factor behind the contact discontinuity, and its total energy is E ej = Γ M ej c 2 . The trans-relativistic shock jump conditions is (Uhm 2011 ; Ryan et al. 2019 ) where , , and are the number density, internal energy, and pressure of shocked region, respectively. is the dimensionless speed. c is the speed of light.


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enhanced, so Tri II does not follow the strange K–Mg anticorrelation in NGC 2419. Note that the halo sample here is different than in Figures 2 and 4 because our usual halo compilation does not have K abundances (Frebel 2010 ). Adapted from Venn et al. ( 2017 ). 4.4. Iron-peak Elements: Cr, Mn, Co, Ni, Zn The Fe-peak abundances were determined with equivalent widths, except for Mn, which is synthesized owing to hyperfine structure (Kurucz Bell 1995 ). In Gru I we can constrain Cr, Mn, Co, and Ni, finding that both stars have essentially identical abundances of these elements. Though the Cr and Mn abundances are similar to those in metal-poor stars in other UFDs or in the Milky Way halo, the Co and Ni abundances are somewhat higher. However, this difference is not very significant, especially for Co, which is derived from only a few bluer lines. One Zn line is marginally detected in GruI-032 with an abundance consistent with the halo trend, though with large uncertainty. In Tri II, we can detect Cr and Ni in TriII-40 and provide upper limits in TriII-46. Mn, Co, and Zn are unconstrained, as they only have strong lines blueward of 5000 Å. The upper limits for Cr and Ni in TriII-46 are uninteresting. For TriII-40, we detect a normal [Cr/Fe] ratio, but Ni appears significantly enhanced ([Ni/Fe] = 0.57 ± 0.16), in agreement with Kirby et al. ( 2017 ) and Venn et al. ( 2017 ). 4.5. Neutron-capture Elements: Sr, Ba, Eu Strontium is detected only in Gru I, as the strong Sr ii lines at 4077 and 4215 Å are out of the range of the Tri II (GRACES) spectra. The abundance of both lines is determined with spectrum synthesis. The Sr abundances in these two stars are very similar, [Sr/Fe] ≈ −2, which is much lower than what is found in most halo stars but similar to most UFDs (Figure 4 ). Barium is measured with four different lines in the Gru I stars including hyperfine structure and isotope splitting (McWilliam 1998 ). We use solar isotope ratios (Sneden et al. 2008 ), but given the low overall abundance, changing this to r - or s -process ratios does not significantly affect our abundances. GruI-032 has a low [Ba/Fe] ≈ −1.6, but GruI-038 has a much higher Ba abundance [Ba/Fe] ≈ −1.0. This is formally only 1.6 σ different, but differential comparison of the line strengths (e.g., the λ 6497 line in Figure 1 ) suggests that the difference is real. We discuss this more in Section 5.1 , but both Ba abundances are low and similar to those in most UFDs. Ba is not detected in either Tri II star, so instead we place 5 σ upper limits. The Ba limit for TriII-40 is [Ba/Fe] −1.25, suggesting a low Ba abundance similar to other UFDs. Kirby et al. ( 2017 ) determined [Sr/Fe] = −1.5 and [Ba/Fe] = −2.4 from their HIRES spectrum of this star, consistent with our upper limit and showing that TriII-40 clearly has very low neutron-capture element abundances. The Ba limit for TriII-46 is only [Ba/Fe] ≲ −0.2, but this is still at the lower envelope of the halo trend (Figure 4 ).


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We thank the anonymous referee for insightful remarks that helped us to improve the paper. B.V. acknowledges the support from an Australian Research Council Discovery Early Career Researcher Award (PD0028506). This work was partially supported by grants ARC FT130101593, and HST /GO 13767, 12905, and 12572. Facilities : HST (ACS), HST (WFC3).


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H β +[OIII] lines after the subtraction of the continuum. The red curve represents the best-fit retrieval model from MC fits, and the shaded area encompass 68% of the MC sample; the black curve shows the [OIII] best fit obtained by Shen (2016) . Table B.1. [OIII] best-fit parameters. Notes. For each component, we report the amplitude (in erg s −1 cm −2 Å −1 ), the centroid, and the width of the best-fit Gaussian profile. B.1. Modelling rest-frame optical spectra The H α +[NII]+[SII] and H β +[OIII]+FeII systems of J0149+1501, J1421+2241, J1431+0535, J1436+6336, and J1220+0004 are redshifted in the K and H bands, respectively. We simultaneously fitted the continuum and all emission lines to reduce the degeneracies between BLR, NLR, and FeII emission. In short, we fitted a (single) power-law continuum, an optical FeII template ( Kovačević et al. 2010 ), and a combination of Gaussian functions to model BLR and NLR emission lines. In particular, depending on the complexity of FeII emission, we considered one or two FeII templates (see e.g. Vietri et al. 2018 ). These were convolved with a Gaussian; the width of this Gaussian, the amplitude normalisations, and velocity offset of the FeII templates were free variables in our fit (see Perna et al. 2017a for further details). Gaussian components were used to reproduce the emission lines. Specifically, we used (1) a systemic narrow ( F W H M 700 km s −1 ) Gaussian component for the [OIII] doublet and for the H β , H α , [NII], and [SII] doublets associated with unperturbed NLR emission; (2) a broad ( F W H M > 2000 km s −1 ) Gaussian component to fit the BLR H β and H α emission; and (3) an outflow ( F W H M > 700 km s −1 ) Gaussian component for all forbidden and permitted emission lines to reproduce prominent and asymmetric wings associated with outflowing gas. One or more additional sets of Gaussian components were considered to reproduce more complex profiles, for instance, asymmetric BLR emission lines (see e.g. J1421+2241, Fig. B.1 ) and extremely broad [OIII] profiles (e.g. J0843+0750, Fig. B.2 ; see also Fig. 11 in Coatman et al. 2019 ). Fig. B.2. Parametrisation of the MgII+FeII+FeIII ( left ) and H β +[OIII]+FeII ( middle and right panels ) of z > 2.5 QSO1 from the sample of Shen (2016) . The red lines show the best-fit from multiple systemic, outflow, and broad Gaussian profiles to the line features, together with a two local power laws to the continuum and one (two) template(s) to the FeII features (see text). Each curve with a different colour represent a distinct Gaussian set (or a FeII template) with same kinematic properties, as labeled in the figure. In the right panel we show, for each target, the spectrum around the H β +[OIII] lines after the subtraction of the continuum. The red curve represents the best-fit retrieval model from MC fits, and the shaded area encompass 68% of the MC sample; the black curve shows the [OIII] best-fit obtained by Shen (2016) . For J2238−0921, we do not


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We thank Joshua Bloom, Saavik Ford, Kohei Inayoshi, Barry McKernan, and Cole Miller for useful discussions. BDM gratefully acknowledges support from NASA Fermi grant NNX14AQ68G, NSF grant AST-1410950, and the Alfred P. Sloan Foundation. Financial support was provided to NCS by NASA through Einstein Postdoctoral Fellowship Award Number PF5-160145 and to ZH by NASA ATP grants NNX11AE05G and NNX15AB19G. ZH gratefully acknowledges support from a Simons Fellowship in Theoretical Physics.


O B-Person O B-Person I-Person O B-Person I-Person O O O B-Person O B-Person O O O O O O B-Organization B-Grant B-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant O B-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant B-Person O O O O O O B-Grant I-Grant I-Grant O B-Grant I-Grant O O O O O O B-Wavelength I-Wavelength I-Wavelength I-Wavelength B-Wavelength O O O B-Database I-Database I-Database B-Database O O O O O B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization O O O O B-Organization I-Organization I-Organization I-Organization I-Organization O O O O O O O O B-Instrument O O O O B-Telescope O B-Organization O O B-Telescope I-Telescope B-Telescope O O O O O B-Organization I-Organization I-Organization B-Organization O B-Location O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O B-Location O O B-Organization I-Organization I-Organization O O O O O O O B-Organization I-Organization I-Organization I-Organization O O O B-Organization I-Organization I-Organization O B-Location O O O O O B-Organization I-Organization I-Organization B-Instrument O B-Instrument O O O O O O O O O O O O B-Organization B-Grant I-Grant I-Grant I-Grant I-Grant I-Grant

Acknowledgements MS thanks Keiichi Umetsu and Peter Melchior for useful discussions. SE and MS acknowledge the financial contribution from contracts ASI-INAF I/009/10/0, PRIN-INAF 2012 ‘A unique dataset to address the most compelling open questions about X-Ray Galaxy Clusters’, and PRIN-INAF 2014 1.05.01.94.02 ‘Glittering Kaleidoscopes in the sky: the multifaceted nature and role of galaxy clusters’. SE acknowledges the financial contribution from contracts NARO15 ASI-INAF I/037/12/0 and ASI 2015-046-R.0. This research has made use of NASA's Astrophysics Data System (ADS) and of the NASA/IPAC Extragalactic Database (NED), which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. This work is based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/IRFU, at the Canada–France–Hawaii Telescope (CFHT) which is operated by the National Research Council (NRC) of Canada, the Institut National des Sciences de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii. This research used the facilities of the Canadian Astronomy Data Centre operated by the National Research Council of Canada with the support of the Canadian Space Agency. CFHTLenS and RCSLenS data processing was made possible, thanks to significant computing support from the NSERC Research Tools and Instruments grant program.


O O O O O 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 O O O O O O O O O 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 O O O O O O O O O O B-Model O O B-CelestialObject 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 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 B-Model 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 B-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 O O O O O O O O O O O O O O O O O O O O O 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 O O B-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 O 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 B-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 B-Model O O O O O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula O O O O O O O O O O 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 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 O O O O O O O O O O O O O O

repeated for 10 shots. This plot indicates that for increasing bias voltage (which is proportional to the axial magnetic field), the wavelength increases. This phenomenon is consistent with the MRTI theory, since Equation ( 5 ) shows that the increase of magnetic field causes the corresponding fastest-growing wavelength to increase. For a sufficiently large magnetic field, the wavelength is larger than the loop dimensions and the MRTI cannot occur. This is most likely the reason for the absence of the MRTI in previous solar loop simulation experiments where a much larger axial magnetic field was used (e.g., Stenson Bellan 2012 ; Wongwaitayakornkul et al. 2017 ). In Equation ( 5 ), besides B 0 , the other two parameters, ρ , g , also influence the fastest-growing wavelength. In order to remove the influence of these parameters and verify that the increasing wavelength corresponds with the MRTI theory, we introduce the parameter s = λρg . Using Equation ( 5 ), the fastest-growing mode corresponds toTo determine s , the quantities λ and g are obtained from the image measurement, while n is determined as a relative density from the light intensity that scales as n 2 . Keeping other experimental parameters the same, we set V b = 30, 40, 50, 60 V for 10 shots at each voltage to obtain s . Figure 3 (c) shows s plotted versus . The error bars are determined by the shot-to-shot variation of measured data and the line shows the best fit. From this figure, it is clear that s scales as as predicted by Equation ( 10 ). As the geometry of the experiment is more like a cylinder, the experimental results can also be used to compare with the MRTI under cylindrical geometry derived by Zhai Bellan ( 2016 ). Using the notation in Zhai Bellan ( 2016 ), the growth rate iswhere , , , and a is the radius of the cylinder. Consider a system with certain values Φ 2 and α subject to a random perturbation that contains all possible x = ka . The component x that gives the largest is defined as x *, and the fastest growth rate is defined as γ *. Figure 4 (a) shows the dependence of the fastest-growing mode on α for fixed Φ 2 = 3.77. Note that α is proportional to the axial magnetic field and x corresponds to 1/ λ . Figure 4 (a) shows that with the increase of axial magnetic field, the wavelength increases and the growth rate decreases, the same trend as predicted for the MRTI in planar geometry. Figure 4. (a) x * and γ * vs. α with Φ 2 = 3.77. (b)–(f) Comparison between the observed growth rate and the calculated growth rate from the MRTI theory under cylindrical geometry (each data point is from 10 shots and the error bar represents the spread over these shots). We assumed all of the experiments have the same parameters except for axial field with , , I = 10 4 A, , and that the observed mode is the fastest-growing mode. The only free parameter in the determination of Φ 2 is a . From the experimental results, x * can be obtained and the corresponding α and γ * can be


O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 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 B-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation 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 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 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 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 I-Citation I-Citation O O O O O O O O O O O O O O O O O O O B-Wavelength O B-Citation I-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 O O O O O O O O O O O O O O O O O O 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 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 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 B-Citation I-Citation I-Citation I-Citation 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 B-Citation I-Citation I-Citation I-Citation O O O O O O O O B-Software 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 O O O B-Wavelength O O O O B-Wavelength O B-Wavelength O O B-Citation

may favour jet production. If a jet is launched, it is likely to dominate the power output of the event if viewed on-axis, where the radiation will likely be non-thermal, whereas off-axis emission is likely to be thermal. There is also the possibility of radiatively driven winds originating from the accretion disc, but we do not consider these here. Following MacLeod et al. ( 2014 ), if t visc > t fb , no longer traces , with viscous expansion of the disc modifying accretion time-scales according to (Cannizzo Gehrels 2009 ; Cannizzo, Troja Lodato 2011 ): where and α = 0.1 for thick discs. The form of during its rise is currently not well constrained; we model it crudely here using a half-Gaussian centred on t peak with σ = t peak /4, and normalize its peak to L Edd . In this work, we assume that the observable X-ray light curve will trace and plot examples of our simulated light curves following the above description in Fig. 1 . Figure 1. Simulated light curves for WTDEs based on the theory described in Section 2.1 . Higher M bh have faster rises to peak L , with fastest decay rates in light curve for BHs. For comparison of peak luminosities of these events, we normalize each light curve by L 5, peak , the Eddington luminosity of a BH. The WF experiences extreme compression perpendicular to the orbital plane, with this being maximized as it crosses pericenter. This is expected to trigger thermonuclear burning if its time-scale is much shorter than the dynamical time-scale (see eg. Luminet Pichon 1989a ; Brassart Luminet 2008 ; Rosswog et al. 2009 ; Haas et al. 2012 ). This burning originates in the tidal debris, with emission likely resembling type 1a SNe-like light curves in the optical band (Rosswog et al. 2008 , 2009 ; MacLeod et al. 2016 ; Kawana et al. 2018 ). Whilst thermonuclear burning may affect the amount of bound debris and subsequent accretion rate, no robust models of this currently exist and we neglect its impact in this work. 2.1.2 Spectral properties Following the modelling of emission from thick accretion discs (see Balbus Hawley 1998 for a review), the innermost sections of the disc, R 5 R S (as in Ulmer 1999 and Khabibullin et al. 2014 ), radiate as a blackbody at temperature: where L Edd is the Eddington luminosity of the BH. For IMBHs with masses of , this results in X-ray spectra with temperatures 0.2 keV. The soft emission from these events can be significantly affected by the interstellar medium’s (ISM’s) absorption along the line of sight (Auchettl, Guillochon Ramirez-Ruiz 2017 ). For each TDE, we set the Galactic neutral hydrogen column density, N H , to , close to the estimated extra-galactic median of N H (Esquej et al. 2008 ). We model the WTDE’s spectrum using the xspec model tbabs(zbbody) , but neglect modelling any spectral evolution. An optically thick extended envelope may form from stellar debris around the BH, reprocessing a fraction of the X-ray accretion flare into the UV and optical bands (eg. Loeb


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We thank the anonymous reviewer for comments that improved this Letter. This work has been supported by Polish National Science Centre MAESTRO grant DEC-2012/06/A/ST9/00276. KG thanks the Poznań Supercomputer and Network Centre for computing grant no. 195. We acknowledge the use of the HPC cluster HAL9000 of the Computing Centre of the Faculty of Mathematics and Physics at the University of Szczecin.


We are grateful to the anonymous referee for her/his constructive critical comments and suggestions, which helped improving the paper.


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ACKNOWLEDGEMENTS K. C-j has been supported by the Kim Il Sung University during this investigation, and would like to thank Jo Jong-won for providing Korean historical data and Mun Ui-ri for help with the English. The authors are grateful to an anonymous referee for detailed and helpful comments.


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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-Wavelength 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 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 B-Telescope 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 B-Wavelength I-Wavelength O O O O O B-Wavelength O B-Wavelength I-Wavelength O O O O O B-Model O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O B-Wavelength O O O O O O O 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 O O O O O 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 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 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

e.g., or Mm, the 1027 line reaches higher layers. We also included, as reference, an isothermal contour at 7000 K that seems to follow relatively closely the height where the optical depth is unity for these lines. In the case of Ca ii , the near-UV transition forms at heights similar to those covered by the O i lines, while the infrared spectral line scans lower layers in the low to mid chromosphere. In the region , magnetic loops are stratified and the TR shifts to higher layers. Following this trend, the spectral lines also form higher in the atmosphere, with the exception of Ca ii IR, which is sensitive to the low chromosphere. 3.3.3. Inferring the LOS Velocity One of the main targets of future spectroscopic observations (e.g., done by Solar-C (EUVST) and SO/SPICE) is to examine the dynamics of the solar phenomena from the chromosphere to the outer atmosphere. We aim to estimate the capabilities of the spectral lines of interest to tackle this task. We do this by computing the Doppler shift of the line core of Lyman β and the two O i 1027 and 1028 Å lines. We believe a single Gaussian fitting is not accurate enough for Lyman β because the line shows multiple lobes, similar to the Mg ii UV spectral lines. Therefore, using the analysis of the IRIS observations as a reference, we perform the following steps. First, we detect the extrema of each spectral profile. Among them, we select the extremum that is nearest to the line core rest wavelength, and we perform a parabola fitting around the extremum to obtain the corresponding line core wavelength. In the case of the O i transitions, we compute the line core Doppler shift using a single Gaussian fitting of the intensity profile. We tried more complex procedures than we do for Lyman β , but we did not achieve noticeable improvements. The inferred LOS velocities for the entire snapshot FOV are plotted in the upper row of Figure 9 . We include in the middle row the LOS velocity at the height where the optical depth is unity for the line core wavelength (similar to what we did for the temperature in Figure 6 ). Additionally, we show in the bottom row the joint probability density functions (JPDFs) of the velocity obtained by the fitting and that from the B ifrost atmosphere (top and middle rows). In some pixels, the derived velocities were larger than 20 km s −1 . We believe those large values correspond to a bad fit of our method. The pixels where the velocity is larger than 20 km s −1 were excluded from the JPDF plots and from the computation of the Pearson correlation rate (although they are shown in the top row panels). Examining the JPDF results, we can say that both methods provide a similar spatial distribution of the LOS velocity for the three spectral lines. We can trace the velocities along the loop-like structures as well as inside the magnetic field elements. The differences among these LOS velocities can be seen in the JPDF plots and the Pearson correlation between both cases. For the


O O O O B-Wavelength I-Wavelength O O O O B-Model O O B-Wavelength I-Wavelength O O O B-Model O O O B-Model O O O O O O O O O O B-Wavelength I-Wavelength O B-Wavelength I-Wavelength O O B-Wavelength I-Wavelength B-Wavelength O O O 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 O O O O O O O B-Wavelength O O O O O B-Wavelength O B-Wavelength O O O O B-Instrument I-Instrument I-Instrument O O O O O O O B-Telescope I-Telescope I-Telescope I-Telescope B-Telescope O O O O O O B-Identifier I-Identifier I-Identifier I-Identifier I-Identifier I-Identifier I-Identifier 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 B-Wavelength O B-Wavelength 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 B-Citation I-Citation I-Citation I-Citation O B-Citation I-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 O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O B-Citation I-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 I-Citation 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 B-Wavelength 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-Citation O O O O B-Dataset B-Dataset 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 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 B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O B-Model I-Model O B-Model 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-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O B-Wavelength O B-Wavelength O O B-Wavelength I-Wavelength O B-Observatory B-Telescope 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


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This work was supported by the Science Development Foundation under the President of the Republic of Azerbaijan –Grant No EIF-2013-9(15)-46/14/11 .


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This research was supported by the Recruitment Program of Global Experts of China, NSFC under grants 41374173 and 41774179, and the Specialized Research Fund for State Key Laboratories of China. We acknowledge the use of data from SOHO , Wind , ACE , Ulysses , and GOES .


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

signatures associated with relativistic protons. In this study, we have demonstrated how high-energy neutrino observations may be used to assess p at SN shocks propagating in dense CSM. In particular, the IceCubes measurement of the diffuse neutrino flux already constrains p 0.3(0.04/) or p 0.2(0.04/) when including the up-going muon neutrino sample from the Northern Sky (Section 3.1 ). Even more stringent constraints on the acceleration efficiency may be placed by direct observations of close-by SNe IIn with neutrino telescopes (Section 3.2 ). The neutrino flux from an SN IIn depends on its distance, shock velocity, mass-loading parameter and proton acceleration efficiency (Section 3.2 ). All parameters, except for the latter, can be, in principle, inferred from radio and optical observations of SNe IIn. For example, v sh is routinely inferred from the width of optical emission lines, while K w can be derived by the fitting of radio observations (Chevalier 1998 ; Chevalier, Fransson Nymark 2006 ; Chandra etal. 2015 ). Besides the intrinsic source parameters that affect the neutrino luminosity, as exemplified through scenarios S1 and S2, the actual distance of the source has the strongest impact on the IceCube expected neutrino rate (see equation 12 ). The IceCube event number expected within the first year in both scenarios discussed in Section 3.2 is plotted in Fig. 9 (bottom panel) as a function of the source distance. Different types of lines correspond to three values of the proton acceleration efficiency marked on the plot. The curves are obtained after scaling the total number of muon neutrinos obtained in S1 and S2 (see Table 2 ) with the source distance and p . The top panel in Fig. 9 shows the all-sky number of SNe IIn expected over 8years up to a distance D L (black thick line); the number is derived using the CC SN rate of HB06 and 0.04. For p values allowed by the diffuse flux measurements, i.e. p 0.2(0.04/), only S1-like SNe IIn at distances 18Mpc are strong enough neutrino emitters to constrain less efficient acceleration scenarios, in agreement with the predictions by Murase etal. ( 2011 ). If p 0.2, IceCube would be capable of claiming a neutrino detection from an S1-like SN IIn exploding at 10Mpc. For SNe IIn with lower mass-loading parameter K w , as discussed in S2, the neutrino rate decreases significantly, even for p 0.2. This restricts the accessible distance to no more than 4Mpc. Figure 9. Bottom panel: Expected IceCube event number as a function of luminosity distance D L for the two SN scenarios discussed in the text (S1: blue lines; S2: cyan lines). For the second scenario, the number of neutrinos expected only within the first year is shown. For both scenarios, the results for three different values of the proton acceleration efficiency are presented (see the legend). The horizontal black and red lines indicate the number of neutrinos required to reach IceCubes sensitivity and 5 discovery potential,


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The THÉMIS observations were supported by the Programme National Soleil-Terre (PNST) of the French Centre National de la Recherche Scientifique (CNRS).


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y ∈ [−50, 50] L 0 yieldswhich is in good agreement with the growth rate shown in Figure 16 . Evidently, the growth rate for this instability derived in the Boussinesq regime, which is admittedly inapplicable in our simulation, produces values that are in good agreement with our simulation results. Thus, both the fastest growing parallel and perpendicular wavenumbers and growth rates of the instability observed in our simulation are in reasonable agreement with theoretical predictions of these same quantities in the undular instability. 3.6. Interaction of the Lobes The emergence of magnetic lobes was found by Archontis et al. ( 2013 ) to result in significant reconnection and a jet-like disturbance in the corona. In our simulation, we see a similar event around t = 820 t 0 that may affect the linear evolution of the undular mode, which stops around the same time. Figure 17 shows the magnetic energyand kinetic energyin the corona as a function of time. The decrease in the magnetic energy that starts around t = 824 t 0 (green line) corresponds approximately to the same magnitude increase in the kinetic energy which peaks at t = 864 t 0 (blue line). In Figure 18 , we plot a series of field lines, seeded along a vertical line at ( x = y = 0, z > 0) in the corona on top of vertical cuts of the vertical velocity V z . The field lines are colored by B z . Early in the interaction, at t = 824 t 0 , the field lines only barely extend above the photosphere. They slowly rise, and it is clear that by t = 860 t 0 , the two primary lobes are interacting, and field lines with opposite signs of B z begin to reconnect. This creates a significant upflow, as the newly reconnected concave up field lines release their tension. This upflow is only seen low down in the corona before t = 860 t 0 , and with much smaller magnitude, since the field is not significantly expanding into the corona, but by t = 880 t 0 and t = 900 t 0 there is a clear upflow visible in the corona along with a concave-down arcade overlying the interacting loops. This type of event likely represents an Ellerman bomb, which is associated with this type of topology (Pariat et al. 2004 , 2006 , 2009 ; Isobe et al. 2007 ; Archontis Hood 2009 ; Danilovic 2017 ). Figure 17. Magnetic energy (black) and kinetic energy (red) in the corona as a function of time. The green (blue) line at t = 824 t 0 ( t = 864 t 0 ) shows the local maximum of the magnetic (kinetic) energy. Figure 18. Field lines colored by B z overplotted on a vertical plane of V z and a photospheric magnetogram at several times before and during the reconnection event. 4. Conclusions In this paper, we simulated the buoyant rise and emergence of an untwisted toroidal flux rope from deep in the convection zone. The flux rope is able to rise coherently through the convection zone, emerge through the photosphere, and form a relatively large (≈40 Mm across) active region. The emergence mechanism of our flux rope is identified to be the undular


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We thank the US National Science Foundation for its financial support through grant NSF AST-1518057, and NASA for its financial support through the WFIRST Preparatory Science program, grant No. NNX15AJ79G. This work is based in part 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 #14201. Support for program #14201 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. T.J. thanks the LSSTC Data Science Fellowship Program; her time as a Fellow has benefited this work. We thank an anonymous referee for their helpful review, and Chun Ly for pointing out a possible systematic effect of recently revised atomic physics on our results. This work has made use of data from the Sloan Digital Sky Survey (SDSS). Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS website is www.sdss.org.SDSS-IV and is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration including the Brazilian Participation Group, the Carnegie Institution for Science, Carnegie Mellon University, the Chilean Participation Group, the French Participation Group, Harvard-Smithsonian Center for Astrophysics, Instituto de Astrofísica de Canarias, The Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe (IPMU)/University of Tokyo, Lawrence Berkeley National Laboratory, Leibniz Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie (MPIA Heidelberg), Max-Planck-Institut für Astrophysik (MPA Garching), Max-Planck-Institut für Extraterrestrische Physik (MPE), National Astronomical Observatories of China, New Mexico State University, New York University, University of Notre Dame, Observatário Nacional/MCTI, The Ohio State University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, Universidad Nacional Autónoma de México, University of Arizona, University of Colorado Boulder, University of Oxford, University of Portsmouth, University of Utah, University of Virginia, University of Washington, University of Wisconsin, Vanderbilt University, and Yale University.


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ACKNOWLEDGEMENTS Judith Biernaux acknowledges the support of the F.R.I.A. fund of the F.N.R.S.


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We acknowledge useful comments from an anonymous referee and discussions with Harry Warren, Jim Klimchuk, Karel Schrijver, Amy Winebarger, and Craig Deforest. Part of the work was supported by the NASA contracts NNG04EA00C of the SDO /AIA instrument and NNG09FA40C of the IRIS mission. Note added in proof. While this manuscript went into print, we were informed that work in progress shows that no clear evidence of observed features smaller than about 3.5–4.5 Hi-C pixels (≈250–330 km) was found in an ongoing study, using a (Fourier-based) noise-gating technique (Craig DeForest, private communication, 2017). In our view, this corroborates our result of a lower loop width cutoff w min below the peak (or most frequent) width of w p = 550 km.


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of the observations. Notes .The airmass column contains the value at the start and end of the observations. The seeing value is corrected for the airmass and corresponds to the seeing at the zenith. Table 2. Comparison of the modelling parametrization of the telluric correction methods. Notes .Molecfit and TelFit packages allow for fitting the atmospheric transmission to the target spectrum. A summary of the capabilities and models employed by each package is shown in Table 2 . Appendix A presents the spectra of the telluric standard and the synthetic transmission spectra obtained with each of the packages. 3.1. TelFit The Python package TelFit ( Gullikson et al. 2014 ) models the atmospheric transmission and fits it to a spectrum with the Levenberg–Marquardt algorithm. TelFit can adjust the wavelength solution of the data to the telluric lines or vice versa with a polynomial function. The order of the polynomial can be set by the user, but the values of the coefficients have to be directly set in the code. TelFit offers a parametric model of the line shape through a Gaussian function and a non-parametric model with the singular value decomposition mode. For each observation, TelFit uses, by default, an average atmospheric profile for mid-latitudes. The website of the Global Data Assimilation System (GDAS) 6 enables the use of a custom atmospheric profile, adapted to the location and time of the observations. The GDAS profiles are available for observations taken since 2004 and are updated every three hours. We used the atmospheric profile that was closest to our observations, with a time difference inferior to 2 h, to first fit the spectrum of the standard star. We experimented with the parametric and non-parametric options for the line shape and attained the same level of correction. Since the other models studied in this work use parametric correction, and to provide a more meaningful comparison, we selected the parametric correction. To perform the fit of the standard star, we left the parameters of the wavelength solution, the continuum level, line shape, resolution, and the mixing ratio of the molecule relevant for the wavelength range considered (H 2 O or O 2 ) as free parameters. TelFit does not allow a different parametrization of spectral orders separated by wavelength gaps. Therefore, each of the three CRIRES detectors is treated independently because the parameters of the wavelength solution differ from one detector to the other. As such, for each fit we obtain a different value for the following parameters: molecule abundances, resolution, temperature, and pressure profiles. We homogenize these parameters by taking their mean values weighted by the inverse of the χ 2 calculated for each detector. Then, we use the homogenized values of the parameters to compute a final atmospheric transmission for each detector. We divide the stellar spectrum by the atmospheric transmission to correct for the telluric lines. After the


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ACKNOWLEDGEMENTS DN would like to thank Kate Rubin, Gwen Rudie, and Alice Shapley for insightful discussions and suggestions, as well as the anonymous referee for a constructive report. SG, through the Flatiron Institute, is supported by the Simons Foundation. The primary TNG simulations were realized with compute time granted by the Gauss Centre for Supercomputing (GCS): TNG50 under GCS Large-Scale Project GCS-DWAR (2016; PIs Nelson/Pillepich), and TNG100 and TNG300 under GCS-ILLU (2014; PI Springel) on the GCS share of the supercomputer Hazel Hen at the High Performance Computing Center Stuttgart (HLRS). GCS is the alliance of the three national supercomputing centres HLRS (Universität Stuttgart), JSC (Forschungszentrum Jülich), and LRZ (Bayerische Akademie der Wissenschaften), funded by the German Federal Ministry of Education and Research (BMBF) and the German State Ministries for Research of Baden-Württemberg (MWK), Bayern (StMWFK), and Nordrhein-Westfalen (MIWF). Additional simulations were carried out on the Draco and Cobra supercomputers at the Max Planck Computing and Data Facility (MPCDF).


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J.L.D. acknowledges support for this work provided by NASA through Hubble Fellowship grant HF-51303.01 awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA, under contract NAS5-26555. B.D.S. acknowledges support from the National Aeronautics and Space Administration (NASA) through Einstein Postdoctoral Fellowship Award Number PF5-160143 issued by the Chandra X-ray Observatory Center, which is operated by the Smithsonian Astrophysical Observatory for and on behalf of NASA under contract NAS8-03060. C.L. acknowledges support from NSF grant AST-1004583. Finally, we thank the anonymous referee for discussions and comments that improved the paper.


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We wish to acknowledge the referee for his very fruitful comments that improved our work. We thank C. Brogan for supplying us with the VLA 330 MHz image. This research has been funded by Argentina grants ANPCYT-PICT 0795/08 and 0571/11. G.C. is Member of the Carrera of Investigador Científico of CONICET, Argentina. L.S. is a Ph.D. Fellow of CONICET, Argentina. The GOODS-Herschel data was accessed through the Herschel Database in Marseille (HeDaM – http://hedam.lam.fr ) operated by CeSAM and hosted by the Laboratoire d’Astrophysique de Marseille. We thank the staff of the GMRT, who have made these observations possible. GMRT is operated by the National Centre for Radio Astrophysics of the Tata Institute of Fundamental Research. This work made use of the High Performance Computing facility, funded by grant 12-RD-TFR-5.02-0711, at National Centre for Radio Astrophysics of the Tata Institute of Fundamental Research.


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ACKNOWLEDGEMENTS PMY thanks the University of Tasmania for a Dean’s Summer Research Studentship and an Australian Postgraduate Award. SSS and MGHK thank the Australian Research Council for an Early Career Fellowship (DE130101399). We also thank an anonymous referee for his useful comments. This research was carried out using the Tasmanian Partnership for Advanced Computing high-performance computing clusters.


O O O O O O O O O O O O O O O O O O O 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 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 B-Model O O O O O O O B-Model O O O O O O O O O O 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 O O O O O O O O O O O O O O O O O O O O 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

given by We define z ph to be where the scattering optical depth s 1 (where subscript s denotes scattering) and set f cor / f cor,0 1. Near the photosphere, magnetic pressure begins to play a major role in hydrostatic equilibrium (e.g. Blaes, Hirose Krolik 2007 ), and near the effective photosphere, the gas temperature begins to diverge from the radiation temperature, so we acknowledge that the assumptions underlying our scheme do not reflect the detailed physics in this region. But since our goal is only to calculate spectra, for optical depths s 1, the accuracy of this scheme is not important. We can assess the validity of this scheme in the region s 1 by comparing the flux from spectral calculations with the intended flux given by equation ( 9 ), or, equivalently, by comparing the corresponding Eddington ratios. In Section 3.1 , we make this comparison for each set of scaling parameters we use and find that they generally agree to within 10percent. More importantly, we find that normalizing the spectra at different radii so that their corresponding Eddington ratios match has a negligible impact on the observed spectrum when contrasted with the discrepancies between spectral calculations with and without bulk velocities. In other words, because the potential error is significantly less than the effect we are measuring, our scaling scheme is adequate. These are the appropriate equations for scaling data to a different set of fundamental shearing box simulation parameters, in particular, z , x v y and . If we substitute in equation ( 9 ) for , we can alternatively regard F as a fundamental parameter instead of . Shearing box scalings in terms of F are given in Appendix C . This substitution is useful in order to scale to a different set of fundamental accretion disc parameters, since it is straightforward to express F in terms of accretion disc radius, mass and accretion rate. The scalings for z , x v y and F for both Newtonian and Kerr discs, allowing for a non-zero stress inner boundary condition, are given in Appendix D . The final scalings for , T g , v and v s in terms of fundamental accretion disc parameters are given in Appendix E . We only use Kerr scalings for our spectral calculations, but the Newtonian scalings are potentially useful for the purpose of comparing with other works in which Newtonian parameters are used and also for developing physical intuition. 2.3 Dependence of turbulent Comptonization on radius To characterize the contribution of turbulent Comptonization, we must model spectra at multiple radii. Our choice of radii is guided by the scaling of the ratio of bulk to thermal electron energies. We estimate this effect for a disc with no spin and a stress-free inner boundary condition with the Newtonian scalings in Appendix E . The bulk velocity scaling is The photosphere thermal velocity scaling is The scaling for the ratio of bulk velocity to thermal velocity at the photosphere is We also calculate the scaling for


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observations of the six targets were obtained between 2016 and 2020 using a variety of instruments: X-shooter on the Very Large Telescope (VLT; Vernet et al. 2011 ) observatory at Cerro Paranal, Chile; the Intermediate-dispersion Spectrograph and Imaging System 1 (ISIS) on the William Herschel Telescope (WHT) at Roque de los Muchachos Observatory (ORM) in La Palma, Spain; the Optical System for Imaging and low-Intermediate-Resolution Integrated Spectroscopy (OSIRIS; Sánchez et al. 2012 ) on the Gran Telescopio Canarias (GTC) at the ORM; the High Resolution Echelle Spectrometer (HIRES; Vogt et al. 1994 ) on the 10-m Keck I telescope at Mauna Kea Observatory, Hawaii; the Magellan Echellette (MagE) spectrograph on the 6.5-m Baade Magellan telescope at Las Campanas Observatory, Chile; and the FAST spectrograph on the 1.5-m Fred Lawrence Whipple Observatory telescope on Mount Hopkins, Arizona (Fabricant et al. 1998 ). The observation log is reported in Table 1 , and sample spectra are displayed in Figs A1 and A2 in the online appendix. Table 1. Log of spectroscopic observations. X-shooter observations were carried out using a 1-arcsec slit aperture for the ultraviolet (UV)-blue (UVB) arm and 0.9 arcsec for the visible (VIS) arm. In all cases flux in the NIR arm was insufficient for any meaningful analysis. On average the resolving power of our X-shooter spectra is R ≃ 4000–5500 in the UVB arm and R ≃ 6500–8000 in the VIS arm. All data were reduced using the standard procedures within the reflex 2 reduction tool developed by ESO. Telluric lines removal was performed on the reduced spectra using molecfit (Kausch et al. 2015 ; Smette et al. 2015 ). ISIS observations were obtained using the R600B and R600R gratings, in the ISIS blue and red arms, respectively; two central wavelength settings were used for each arm, nominally 3930 and 4540 Å in the blue and 6562 and 8200 Å in the red, which were chosen to cover important atmospheric lines, such as the Balmer series and Ca HK, as well as the Ca ii emission triplet in addition to other potential emission features (e.g. Fe ii /Mg i 5175 Å). The slit width varied between 1 and 1.5 arcsec depending on the observing conditions and we employed a binning of 2 × 2, resulting in an average resolution of ≈2 Å. ISIS spectra were debiased and flat-fielded using the standard starlink 3 packages kappa, figaro , and convert . We carried out optimal spectral extraction using the package pamela . Wavelength and flux calibration were performed using the routines within the software molly 4 (Marsh 1989 ). The OSIRIS spectroscopy of WD J0846+5703 was obtained using the R2500I grism with a 0.6-arcsec slit, and binning the detector 2 × 2. This set-up provides wavelength coverage over Å at a resolution of R ≃ 2500. The data were bias and flat-field corrected using the standard tools within iraf . 5 We performed sky background subtraction and optimal spectral extraction (Horne 1986 ) using the pamela data reduction


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

host mass and distance is shown in Figure 7 , as well as the limits on θ E , π E , and the lens flux. We infer that the host is a dwarf, likely in the Galactic bulge at kpc. Using the mass ratio and scaled instantaneous projected separation from the model, we find that the planet mass is , and it orbits its host beyond the snowline at a projected separation of au. The estimated physical properties are summarized in Table 2 . Figure 7. Posterior probability distributions of the host mass and distance derived from the Bayesian analysis. Also shown are the limits on the lens flux (blue), on θ E for either bulge or far disk sources (red), and on the microlens parallax for a bulge source (green). Table 2 Physical Properties One of the main uncertainties in our Galactic model is the source distance. However, we note the the posterior probability for the lens mass (and thus the planet mass) is weakly dependent on the source distance. For a source at 8 kpc the mass is only 10% lower than for a source at 15 kpc, well within the range of our uncertainty. The lens distance, and consequently the projected separation between the planet and its host, is more sensitive to the source distance, with a difference of 45% between a bulge source and a far disk source. Future observations can resolve this and give a better estimation of the source distance, as we discuss below in Section 7 . 6. Extinction Law Recent studies of dust properties in the inner bulge suggest deviations from the standard extinction law (Nataf et al. 2016 ; Alonso-García et al. 2017 ). The extinction coefficient measured in our field, , is lower than the value of 1.37 from Nishiyama et al. ( 2009 ). This offset is a disconcertingly large ∼0.4 mag in K S . The offset relative to the value of predicted by Fitzpatrick ( 1999 ) is even larger—about 1.4 mag in K s . The magnitude of the RC can also be predicted in the YJ bands by assuming the color–color relations from Nataf et al. ( 2016 ) and the extinction coefficients from Fitzpatrick ( 1999 ). These are Y RC ≈ 14.63 + 1.63 + (7.35–3.12) ≈ 20.49 and J RC ≈ 14.63 + 1.63 + (5.44–3.12) ≈ 18.58, where we add the corresponding intrinsic color offsets and reddening offsets, respectively, to the observed clump H -band magnitude. Given that the limiting magnitudes for the DECam and VVV data sets are, respectively, Y ∼ 21.2 and J ∼ 19.4 (see Section 4.2 above), the RC should be clearly detected in each of these bandpasses by a wide margin of 0.7–0.8 mag, respectively. However, the photometry in both cases barely covers the RC. Figure 8 shows the HK s CMD of our field (gray points), with the sources detected in Y shown as yellow circles in the left panel, and the points detected in J shown as purple in the right panel. We conclude that the extinction toward this field is steeper than standard (as defined by Fitzpatrick 1999 ). Figure 8. Detection limits of DECam Y -band data (left) and VVV J -band data (right). These limits are brighter than


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ACKNOWLEDGEMENTS We thank the anonymous referee for the useful report which helped to improve the quality of the paper. We acknowledge Gerrit Schellenberger for the help and fruitful discussion. LL and THR acknowledge support from the German Research Association (DFG) through the Transregional Collaborative Research Centre TRR33 ‘The Dark Universe” (project B18) and support from the German Aerospace Agency (DLR) with funds from the Ministry of Economy and Technology (BMWi) through grant 50 OR 1514. LL also acknowledges support from NASA through contract NNX17AD83G.


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This work was partially supported by FONDECYT trough grant No 1181158, the Advanced Center for Electrical and Electronic Engineering (AC3E, Proyecto Basal FB0008), Núcleo Milenio de Formación Planetaria – NPF and Programa de Iniciación a la Investigación Científica (PIIC) de la Dirección de Postgrado UTFSM convenio No 015/2018. Michel Curé thanks the support from the Centro de Astrofísica de Valparaíso and the Centro Interdisciplinario de Estudios Atmosféricos y Astroestadística.


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

of their stellar mass at the present was already in place by z ∼ 2 via star formation (see Fig. 8 ). Figure 9. The average stellar mass assembly history of central galaxies as a function of redshift for haloes of different present-day masses, predicted by various empirical models as indicated. For Milky Way sized haloes, however, the differences between the model predictions are milder. All the models predict that about half of stellar mass was in place by z ∼ 1. There is a significant difference between L15 -U and other models at high z . For example, L15 -U predicts that about 15 per cent of the final stellar mass was assembled by z ∼ 2, while less than 10 per cent was predicted by the other models. For central galaxies in present-day massive haloes with M h (0) > 10 14 M ⊙ , the predictions of different models again become very different. M13 predicts a much later assembly for these galaxies than any other models. The predictions of B13 look similar to L15 -U, but the increase in stellar mass with time is due to different reasons. While L15 -U predicts that the increase at z 2 is dominated by accretion of stars from satellites, B13 predicts that a significant fraction of the increase at z 2 is actually due to in situ star formation (see Fig. 8 ). This difference is again due to the boost of star formation in low-mass haloes at high z in the L15 -U model. The increased amount of stars formed in progenitors at high z makes the accretion of stars more important in the growth of stellar mass in a massive galaxy, and the fraction of stars formed in situ has to be decreased proportionally in order to match the final stellar mass of the galaxy. The results demonstrate the importance of properly modelling the star formation in low-mass progenitors at high z in order to understand the star formation and stellar mass assembly histories of massive galaxies at the present day. 4.4 Stellar mass functions of high-redshift galaxies Fig. 10 shows the predictions of the empirical models for the SMFs of galaxies at a number of redshifts. The predictions of B13 and M13 are similar in both slopes and amplitudes at the low-mass ends, but B13 predicts many more massive galaxies than M13 , particularly at high redshifts. Y12 predicts significantly flatter slopes at the low-mass ends, and more galaxies in the intermediate mass range, than the other three models. The SMFs predicted by the L15 -U model match the predictions of B13 at M * > 10 10 M ⊙ , but are significantly steeper at the low-mass ends. Figure 10. The model predictions for the field SMFs at high redshifts (solid) in comparison with observations. We select some observational SMFs of high-redshift galaxies from the literature to compare with the model predictions. Specifically, we use the SMFs at 1.3 z 3.5 given by Pérez-González et al. ( 2008 ) and Marchesini et al. ( 2009 ). Pérez-González et al. used a sample combining data in three different fields with a total area of 664 arcmin 2 that have a total


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by Spite (1967) and regularly improved since then. The package allows us to compute synthetic spectra by interpolating over a large grid of hydrostatic, LTE, and plane-parallel or spherical stellar atmospheres models (MARCS, Gustafsson et al. 2008 ). For all the elements studied here, we assumed the standard solar abundances provided by Grevesse et al. (1996) , namely (Fe), (Y), (La), (Ce), (Nd), and (Eu). Recent spectroscopic estimates of solar abundances by Scott et al. (2015) and by Grevesse et al. (2015) indicate very similar abundances. Indeed, the difference in dex ranges from +0.01 for Eu to 0.03 for Fe and Y, to 0.06 for La, and to 0.08 for Nd, while the new Ce abundance is identical to the old one. 2.2.1. Hyperfine structure and isotopic splitting Several lines used in our abundance analysis are affected by hyperfine structure (HFS) and/or isotopic splitting in the line profile. We searched in the literature for atomic data required to compute the fine-structure components that form these lines. We found that several of them are already available and for those that are not available we adopted the same approach discussed in M13 to compute the HFS. The atomic data required to compute the HFS of La and Eu were taken from Lawler et al. (2001a , b) , respectively. For the La line at 6774.27 Å we adopted the HFS already computed by M13. The same outcome applies to Y: we adopted the HFS data given by M13, but they are only available for three (out of six) lines of this element ( = 5119.12, 5289.81, 5728.89 Å). No atomic data have been found in the literature for our lines of Ce and Nd. Only the odd isotopes Nd and Nd have HFS, but their effects can be safely ignored – in the solar system these isotopes constitute only 20.5% of the total Nd abundance, their lines are very narrow, and recent laboratory transition probabilities by Den Hartog et al. (2003) indicate no evident HFS structure for more than 700 lines of Nd II. 2.2.2. Abundances corrected from HFS We derived the abundances of the current sample of 73 Cepheids by accounting for the HFS of the elements and lines mentioned in the previous section. In order to quantify the effects of the HFS on the derived abundances and their dependence on other parameters, we performed a comparison between our abundance results before and after performing the HFS analysis. The mean differences in abundance are summarized in Table 1 . The differences are much larger for some of the La lines, but they are very close to zero for both Y and Eu lines. For the possible dependences on other parameters, we found that these differences and their dispersions become smaller with increasing (specially for > 5500 K), with increasing surface gravity (specially for > 0.5), and with decreasing pulsation period ( 1.0). No clear correlation with metallicity is observed. Finally, we note that the lines selected to measure n-capture elements are typically weak (smaller than 180 mÅ) and unsaturated. This means that