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

distribution. 3 In reality, the whole structure moves on the same short dynamical time-scale of equation ( 1 ) and hence the effective surface density is much reduced if the system as a whole begins to re-expand. We suspected that the choice of fixed initial density may be the reason for the undetectable shift of the peak on Fig. 8 . Our choice of initial conditions implies that the system size R o M 1/3 ; had we chose instead to use an empirical relation such as R o M 1/5 for stellar clusters (Larsen 2004 ), we would have found a scaling of E s / E s a 3 N 7/5 . The same rise in N as before would have produced a shift from 40 to 6.5au in the peak of the distribution, and this is still too large to go undetected. 5 EXTREME TIGHT AND WIDE BINARIES As mentioned in Section 3.2 , Bate ( 2012 ) has found several examples of binaries reducing their separation over time through stellar encounters, from 10au down to 0.5au. Tighter systems were hindered by numerical resolution issues. The regularized treatment of close encounters (which allows us to integrate up to machine precision) of the code nbody 6 means that the same collisional process will be at play in the calculations that we have performed. Since no binaries with semimajor axis a shorter than 1au were inserted in the initial conditions, we focus first on the statistics of binaries that evolved to a 1au. In the second part of this section, we will explore the formation and the evolution of very wide ( a 10 4 au) binaries, many of which end up loosely bound to the stellar cluster as a whole. 5.1 Tight binaries Several binaries with a 1au were detected at the end of the low-density simulations. By comparison, almost none developed in the high-density runs. Their properties are summarized in the left-hand panel of Fig. 10 . The data are taken from N 20k runs but similar statistics were obtained for the other setups. The top row shows the binarys mass as a function of semimajor axis, while the bottom row on that figure graphs the distance of their barycentre to the centre of the cluster. Open circles denote binaries that already existed at t = 0, and became tighter over time, while filled circles are new binaries that formed in the course of the simulation. Inspection of these new, tight binaries shows that both of their components were part of binaries originally inserted in the system. Thus all new tight binaries shown on Fig. 10 are the results of strong binarybinary interactions leading to splitting or exchange. (None of the original binaries that survived to the end of the simulation had a 1/2au.) Figure 10. Left-hand panels: total binary mass (top) and distance to centre of the cluster (bottom) versus the semimajor axis for binaries tighter than 1au at the end of the simulation. Right-hand panels: same layout for binaries wider than 10 4 au. The greyed area in the top panels shows the 90percent probability range of a binary total mass from random pairing given the present IMF. The red


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

lag between the formation of the jet and the outflows. Because our analysis depends on the long-slit data with a specific P.A., the estimated size of the NLR based on [O iii ] may be underestimated if the slit is off from the outflow direction. Figure 8. Photometric size–luminosity relations for AGNs. Black and magenta dots show the measured sizes from Husemann et al. ( 2013 , 2014 ). Green dots present the results from Karouzos et al. ( 2016a ). The measured values from Bae et al. ( 2017 ) are denoted by blue dots. Our measured [O iii ] sizes are shown by red dots. In this plot, the [O iii ] luminosity is the extinction-uncorrected values. Dashed and solid lines present the slope values from linear regression of Husemann et al. ( 2014 ) and Bae et al. ( 2017 ). The flux distribution of [O iii ] is often used to define the size of the NLR. However, the extent of the photoionization region is different from that of gas outflows, as gas can be ionized by the central source while the kinematics of the ionized gas can simply follow the gravitational potential of the host galaxy without showing any outflows. Therefore, Karouzos et al. ( 2016a ) and Bae et al. ( 2017 ) measured the size of the outflows based on the [O iii ] kinematics compared to stellar kinematics instead of measuring the extent of the photoionization region. A detailed comparison between the photoionization and outflow sizes will be presented in the future (D. Kang et al. 2017, in preparation). While the outflow size measured based on the spatially resolved kinematics provides much better representation of the outflow energetics, it requires high quality data with a good spatial resolution, which are missing in our MMT observations. Future IFU observations with high S/N may overcome the limitations of our analysis based on MMT long-slit spectra. 5. Discussion and Conclusions Various studies in the literature showed the connection between gas kinematics and radio emissions. For example, Mullaney et al. ( 2013 ) reported that in AGNs with moderate radio luminosity, the radio luminosity has strong effects on the [O iii ] profile. The morphology and position angle of the radio emission and the ionized-gas emission have strong connections. In the case of the targets in which the jet and ionized-gas emissions are aligned, the radio jets may be responsible for driving outflows and shock ionization, hence driving the correlations between radio emissions and gas kinematics (e.g., Veilleux 1991 ; Bower et al. 1995 ; Zakamska Greene 2014 ). In a radio-loud AGN, 4C12.50 fast outflows in HI gas are detected with an extremely blueshifted velocity, ∼1000 km s −1 relative to the systematic velocity at the location of the southern jet. These outflows are considered as a result of the interaction between radio jet and the ISM (Morganti et al. 2013 ). By using near-infrared data, Tadhunter et al. ( 2014 ) reported the highly distorted kinematic profiles in the H 2 1-0 S(1) λ 2.128 μ m line, showing


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

of both the non-MAD and MAD states. Our main conclusions are summarized as follows: 1. High-energy particles at the first (strongest) shock during the debris circularization phase are unlikely to be produced, because the mass fallback rate exceeding the Eddington rate makes both the Compton drag and the proton–proton collision cooling very efficient. Since the shocked region is far from the black hole, the magnetic field is relatively weak. The weak magnetic field is another reason whythe stochastic acceleration of the protons becomes inefficient. 2. High-energy particles during the super-Eddington accretion phase of the non-MAD state are unlikely to be produced because of very efficient proton–proton collision cooling and Compton drag, even though the stochastic acceleration of the protons is more efficient because of the much stronger magnetic field than that of the first shock case. 3. Neutrinos and gamma-ray photons are produced by pions not only in the super-Eddington MAD scenario but also in the RIAF scenarios of both the non-MAD and MAD cases. However, the gamma-ray photons cannot escape from the source because of the large optical depth in the super-Eddington MAD state and because of the very efficient pair production in the RIAF cases. 4. In the RIAF phase, the protons can be accelerated up to with the other given appropriate parameters. The neutrino energy emitted at the peak of the spectrum is then estimated as . The neutrino emission is proportional to t −10/3 , which is steeper than the standard TDE decay rate. This indicates that one can potentially identify whether an RIAF that existed around an SMBH has a TDE origin or not. 5. In the super-Eddington MAD state, the stronger magnetic field than in the non-MAD case makes it possible to accelerate the protons up to ultrarelativistic energies. The dominant process to prevent the protons from accelerating strongly depends on the black hole mass. If the black hole mass is larger than , synchrotron cooling is the most dominant process. In this case, the protons are accelerated up to an energy of with the other given appropriate parameters. The neutrino energy at the peak of the spectrum is then estimated as . Otherwise, the Compton drag is more efficient process. In this case, the resultant energy of the protons increases at most up to . 6. In the super-Eddington MAD state, if M bh ≳ 10 7.7 M ⊙ , the neutrino light curve is proportional to , which is steeper than the standard TDE decay rate. On the other hand, it follows the decay rate with energy more than if . In both cases, the neutrino luminosity is of the order of the Eddington limit or the super-Eddington limit. Such a high neutrino luminosity and characteristic light curve give us the ability to judge whether the TDE disk is in the MAD state or not. 7. In the radiatively inefficient MAD state, the stronger magnetic field than in the non-MAD case makes it possible to accelerate the protons up to . The neutrino energy estimated


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The Swedish 1-m Solar Telescope is operated on the island of La Palma by the Institute for Solar Physics of Stockholm University in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias. The author is grateful to Mikael Ingemyr and Pit Sütterlin for help with the observations, to Guus Sliepen for making it possible to do the DA scans, and to Göran Scharmer for discussions and helpful suggestions.


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

He atom, which includes 4 levels for He II and 1 level for He III, as well as a 5-level-plus continuum H atom. By calculating the full non-LTE radiative transfer for each model we find the energy level populations and thus ionization densities for both atomic species. The cylinder is orientated such that its axis is parallel to the solar surface. We then calculate the brightness temperature for a set of horizontal lines-of-sight through the prominence cylinder. We follow the same methods for brightness temperature calculation as outlined in Rodger Labrosse (2017) with one notable change in the calculation of the thermal gaunt factor. In this study we no longer estimate the thermal gaunt factor through the assumption given in Dulk (1985) for plasma of temperature 2 × 10 5 K, but instead take our values by interpolating the table of calculated thermal gaunt factors of van Hoof et al. (2014) , as described in Gayet (1970) and Simões et al. (2017) . Whilst the optical thickness diagnostic discussed in this study assumes purely thermal bremsstrahlung absorption, the results from these numerical models are calculated using both thermal bremsstrahlung and neutral hydrogen absorption. For this analysis we first consider a set of isothermal prominence models to see how well they agree with Eq. ( 4 ) and see how this changes when considering a multi-thermal plasma instead. Whilst nominally the models used here describe solar prominences, the results are applicable to any off-limb solar atmospheric structure. For on-disc structures, the spectral gradient will follow a similar relation to Eq. ( 4 ) with an additional term corresponding to the contribution of the background solar continuum spectrum. On-disc structures would therefore require knowledge of the brightness temperature of the structure and the background emission illuminating it from the solar disc. This will likely be problematic unless the structure in observation is formed above the chromosphere, the forming region for most millimetre radiation, or where the structure is transient in nature such that measurements of both the background and enhanced brightness temperature phases are obtainable. 3.1. Isothermal models The set of isothermal models we use here are the same as the “ t ” models as described in Gouttebroze Labrosse (2009) . They each consider a prominence cylindrical cross-section of radius 0.5 Mm at an altitude of 10 Mm. The isobaric pressure is 0.1 dyn cm −2 , the helium abundance is 0.1 and the micro-turbulent velocity is 5 km s −1 in all models. The set of temperatures considered is {6000, 8000, 10 000, 15 000, 20 000, 30 000, 40 000, 50 000, 65 000, 80 000, 100 000} K. From Fig. 1 it can be seen that whilst the relationship between the modelled spectral gradient and the optical thickness follows a similar trend to that expected by Eq. ( 4 ) the values are slightly lower. This discrepancy is caused by the assumption that the gaunt factor is approximately constant over the


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

that R 90 is highly dependent on the finding algorithm. Interacting galaxies show a very wide f Y distribution for all quantities studied. There is an evident difference between host and satellite galaxies, which peak at f Y > 1 and f Y 1, respectively. These differences are mainly caused by inadequate particle assignment in halomaker , which we show our improved version of velociraptor handles better. halomaker artificially increases (decreases) the estimated values of M * , SFR, and R 50,90 for host (satellite) galaxies in interacting systems. Differences between the catalogues are amplified at higher redshifts, where the f Y distributions of interacting and isolated galaxies widen. Galaxy population statistics . We investigate how the choice of finder affects the overall galaxy population statistics. We explore the GSMF, SFRF, and mass–size relation for R 50 and R 90 . At M * 10 11 M ⊙ the z = 0 GSMFs of halomaker and velociraptor agree well, while at higher stellar masses the former predicts from 20 per cent to 100 per cent more galaxies than the latter. At higher redshifts differences are amplified. At z = 4 halomaker ’s GSMF predicts a number density of galaxies at least 30 per cent higher than that of velociraptor over the whole mass range, increasing to 100 per cent at M * ≳ 10 10 M ⊙ . The SFRF at z = 0 is also fairly similar between the finders, with differences increasing with redshift. At z = 2, the peak of the cosmic star formation history, halomaker predicts up to 50 per cent more galaxies at than velociraptor . This is important as these galaxies are expected to dominate the cosmic SFR. We compare the R 50 and R 90 size–mass relation predicted by both finders. We find that the R 50 mass–size relations resulting from the two finders are similar, except at the high-mass end, M * ≃ 10 12 M ⊙ , where halomaker’s galaxies are 20 per cent larger than velociraptor’s . These differences increase by 30 per cent when we study R 90 . This results from the fact that the stellar content and structure in the outskirts of galaxies are very sensitive to the choice of finder. Although we see that the overall z = 0 galaxy statistics are not greatly impacted by the choice of finder, individual galaxies can display differences in mass and size of more than a factor of 3 between the two finders studied here. We suggest that the tuning of simulations of galaxy formation is relatively robust as it has consistently focused on population statistics. However, comparisons of galaxy subpopulations with observations, specifically in the context of pairs, groups, and clusters, can be greatly affected by the choice of finder. We showed that our new algorithm outperforms 3D finders and provides extensive evidence of this. One of our key findings is that the stellar outskirts of galaxies is greatly affected by the choice of finder. In upcoming studies we will explore in detail the diffuse IHSC, the stellar streams, and the outer stellar profiles of


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This research was supported in part by the Natural Science Foundation of China under Grants Nos 11175270 and 11475065, and the Program for New Century Excellent Talents in University under Grant No. NCET-12-0205.


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We thank the anonymous referee for helpful comments that greatly improved the presentation of this paper. This work is supported by 973 Program (No. 2015CB857002), National Science Foundation of China (grant Nos. 11203054, 11128306, 11121062, 11233005, and 11073017), NCET-11-0879, the Strategic Priority Research Program “The Emergence of Cosmological Structures” of the Chinese Academy of Sciences, grant No. XDB09000000 and the Shanghai Committee of Science and Technology, China (grant No. 12ZR1452800). We also thank the support of a key laboratory grant from the Office of Science and Technology, Shanghai Municipal Government (No. 11DZ2260700). H.J.M. would like to acknowledge the support of NSF AST-1517528. A computing facility award on the PI cluster at Shanghai Jiao Tong University is acknowledged. This work is also supported by the High Performance Computing Resource in the Core Facility for Advanced Research Computing at the Shanghai Astronomical Observatory.


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

We thank the anonymous reviewer for their helpful comments, which improved the content of this paper. AHP and SZ thank the Lady Davis Foundation and The Netherlands Organization for Scientific Research (NWO) VICI grant for the financial support. LVEK and BKG acknowledge the financial support from the European Research Council under ERC-Starting Grant FIRSTLIGHT – 258942. AGdB, SY, MM and VNP acknowledge support by the ERC for project 339743 (LOFARCORE). VJ acknowledges the NWO for the financial support under VENI grant – 639.041.336 . ITI was supported by the Science and Technology Facilities Council [grant number ST/L000652/1 ]. The LOFAR was designed and constructed by ASTRON, the Netherlands Institute for Radio Astronomy, and has facilities in several countries, which are owned by various parties (each with their own funding sources) and are collectively operated by the International LOFAR Telescope (ILT) foundation under a joint scientific policy.


O O B-Model I-Model O O O O O O O O O O O B-CelestialObjectRegion I-CelestialObjectRegion O O B-CelestialObjectRegion I-CelestialObjectRegion O O O O O O O O B-CelestialObjectRegion I-CelestialObjectRegion O O O O O O O O O B-CelestialObjectRegion I-CelestialObjectRegion 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 B-CelestialObjectRegion I-CelestialObjectRegion O O O B-CelestialObjectRegion I-CelestialObjectRegion 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 B-CelestialObjectRegion 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 B-Model I-Model O O O O B-CelestialObjectRegion I-CelestialObjectRegion O O O O O O O O B-CelestialObjectRegion I-CelestialObjectRegion I-CelestialObjectRegion O B-CelestialObject O O O O O O O O O B-CelestialObjectRegion I-CelestialObjectRegion O O O O O O O O O O O O O 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-CelestialObjectRegion O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 B-CelestialObjectRegion O O O O O O O O O O O O O O O O O O O O B-CelestialObjectRegion I-CelestialObjectRegion O O B-CelestialObjectRegion O O O O O O O O O O O O O O B-CelestialObjectRegion O O O O O O O O O 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 I-Citation O O O O O O O O O O O O O B-CelestialObjectRegion I-CelestialObjectRegion I-CelestialObjectRegion 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 B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation O B-Citation I-Citation O B-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 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-CelestialObjectRegion I-CelestialObjectRegion I-CelestialObjectRegion O O O O O O

when the Chabrier IMF is adopted. However, we argue that a 20% contribution from the thick disk at the local disk is seriously overestimated. Our results suggest that the thick disk contributes only a few percent mass density at the disk midplane, which is consistent with many literature results (e.g., Jurić et al. 2008 ; Chen et al. 2017 ). We emphasize that our results are obtained at solar radius but not the “solar neighborhood.” Our sample stars have a good coverage at 400–800 pc away from the Sun in the azimuthal direction but have poor coverage within 400 pc. A likely explanation of the higher density found by this work than the solar-neighborhood values in the literature is that the Sun is located in a local low stellar density region, which has a density of 0.0164 M ⊙ pc −3 (or 0.0106 M ⊙ pc −3 if the Chabrier IMF adopted) lower than the nearby disk. Such a difference must be contributed by the Local stellar arm. Our Sun is either located at the inner boundary of the Local arm or embedded in a cavity of stars in the arm, and it needs to be further studied using data with improved spatial coverage to clarify which is the real case. Note that the literature results for the solar-neighborhood density are usually determined within a complex volume, which varies with different types of stars. It is thus difficult to make a direct comparison of our relatively well defined volume density with the literature results. To test whether the difference is caused by the possibility that the literature results are actually averaged values in a larger volume, we have also examined the mean stellar mass density within 7.8 kpc R 8.2 kpc and pc, and we find a density of 0.0549 M ⊙ pc −3 (0.0496 M ⊙ pc −3 from the Chabrier IMF), which is still significantly higher than the “solar-neighborhood” values in the literature. We also emphasize that since the stellar mass density decreases quickly with increasing height above the disk plane, the “underlying” midplane density should be higher than the current estimates of average values within pc. The midplane density is expected to be comparable to the measured values without correction for contaminations of main-sequence stars (Section 4 ). Assuming a gas density of 0.05 M ⊙ pc −3 as widely adopted (Holmberg Flynn 2000 ; Flynn et al. 2006 ), the expected mass density of baryon matter (star and gas) in the nearby disk plane within a few hundred parsecs is thus 0.109 M ⊙ pc −3 (0.104 M ⊙ pc −3 for the Chabrier IMF). Such a value is highly consistent with the local total mass density yielded by stellar dynamics, which suggest a typical value of 0.1 M ⊙ pc −3 , with an uncertainty of ∼0.01 M ⊙ pc −3 (Bienayme et al. 1987 ; Kuijken Gilmore 1989c ; Pham 1997 ; Holmberg Flynn 2000 ; Read 2014 ; McKee et al. 2015 ; Widmark Monari 2017 ; Kipper et al. 2018 ). Our results thus leave little room for the existence of a meaningful amount of dark matter in the nearby disk midplane. However, since our results show that


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ACKNOWLEDGEMENTS This work received generous support from the National Natural Science Foundation of China, project nos 11763007, 11863005, 11803026 and 11503008. We would also like to express our gratitude to the Tianshan Youth Project of Xinjiang, no. 2017Q014.


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-Organization B-Grant O O B-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant B-Grant O O O O O O O B-Grant O B-Grant B-Person O O O O B-Location B-Organization I-Organization I-Organization I-Organization I-Organization O O B-Grant O B-Grant B-Person O O O O O B-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant B-Person O O O O B-Organization O O B-Grant O O B-Collaboration I-Collaboration I-Collaboration O O B-Grant B-Person O O O B-Person I-Person I-Person B-Person I-Person O B-Person I-Person I-Person O O O O O B-Person I-Person O O O O B-Model I-Model I-Model O O O B-Person I-Person I-Person 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 B-Archive I-Archive I-Archive I-Archive O B-URL O O B-Dataset I-Dataset B-Archive I-Archive I-Archive B-Archive B-URL O O B-Dataset I-Dataset B-Archive I-Archive I-Archive O B-URL O O O B-Database I-Database I-Database O B-URL O O B-Software O B-Software O B-Software I-Software O B-Telescope B-Instrument


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We are grateful to the University of Catania for providing the funds necessary to carry out the Observational Campaign in La Palma. The Swedish 1-m Solar Telescope is operated on the island of La Palma by the Institute for Solar Physics (ISP) of Stockholm University in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias. We are also grateful to Professor Giovanni Gallo of the University of Catania for his contribution in the implementation of the new segmentation algorithm. This research has received funding from the EC 7th Framework Programme FP7/2007–2013 under the grant agreement SOLARNET (project No. 312495). This work was also supported by the Istituto Nazionale di Astrofisica (PRIN INAF 2014), and by the Italian Ministry of University and Research (PRIN MIUR 2012).


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We thank the US National Science Foundation (AST-1505502) for support in conducting the present experiments. The authors would like to acknowledge the W. M. Keck Foundation for financing the experimental setup.


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( 2015 ), Lestrade Thilliez ( 2015 ), Booth et al. ( 2017 ), Chavez-Dagostino et al. ( 2016 ), and this paper (see Table 2 ). In the case of the observed millimeter emission, the rapid rise of the flux density with frequency (a spectral index of 4.9 ± 1.8) favors emission from warm dust (e.g., Ricci et al. 2010 ). In contrast, the centimeter emission is remarkably flat (a spectral index of −0.07 ± 0.25), suggesting an optically thin free–free nature. Below we examine the expected properties of the free–free emission. Figure 2. Spectrum of the emission associated with Eridani at centimeter and millimeter wavelengths from the references given in the text. The long-dashed lines are separate power-law fits to the centimeter and to the millimeter emission. The data point at 3 GHz (0.48 in the logarithm) is a 3 σ upper limit and was not taken into account in the fit. 4.1. Optically Thin Free–Free Emission The free–free power per unit volume per Hz is given bywhere Z is the ion charge, n e and n i are the electron and ion number density, respectively, T is the plasma temperature, and is the velocity-averaged Gaunt factor. The total power per unit volume is obtained integrating over the frequency where is the frequency average of the velocity-average Gaunt factor, which is in the range 1.1–1.5. Choosing gives a 20% accuracy (Rybicki Lightman 1986 ). The power per unit volume over a frequency range is given bywhere the normalized energy is u = hν / kT . For an optically thin plasma at a constant temperature, the luminosity in a normalized energy range ( u 1 , u 2 ) is obtained by integrating the emissivity over the volume V : The X-ray luminosity of Eridani has been measured with XMM-Newton in the energy range [ E 1 , E 2 ] = [0.2, 2] kev, with values in the range (1.5–1.68) × 10 28 erg s −1 (Poppenhaeger et al. 2010 ; Loyd et al. 2016 ). Let L R be the luminosity in the frequency range [ ν 1 , ν 2 ] = [6, 43] GHz where the spectrum is flat. Then, from Equation ( 5 ), the ratio of the free–free luminosity in the X-ray range L X and in the radio range L R is given bywhere the lower value corresponds to T = 2 × 10 6 K and the upper value corresponds to T = 3 × 10 6 K. These temperatures are similar to those measured by Schmitt et al. ( 1996 ) for the peak of the temperature distribution of the coronal material of Eridani. The observed radio luminosity in the range 6–43 GHz is given bywhere D = 3.2 pc is the distance to Eridani. Then, this radio luminosity implies a free–free emission in X-rays offor a temperature in the range (2–3) × 10 6 K, in agreement with the observed X-ray luminosity observed by XMM-Newton . Therefore, the radio emission in the flat-spectrum region is consistent with free–free emission for this range of plasma temperature. Note that line X-ray emission is also important in hot plasmas (e.g., Mewe et al. 1985 ; see their Figure 1). Thus, the total X-ray emissivity should be larger than the continuum free–free emission calculated in


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lower-mass stars with which to anchor the comparison to the models. Still, it does appear that the model is significantly overpredicting the spin-down for the 0.6–0.8 M ⊙ stars, with the predicted median star in that mass range having a P rot = 21.0 days at 1.344 Gyr, ≈4.5 days more than what is observed. The four lower-mass NGC 752 members have rotation periods that are more consistent with what is predicted by the Matt et al. ( 2015 ) model, with the median 0.4–0.6 M ⊙ star predicted to have a P rot = 17.2 days. One possible interpretation is that we are seeing the evolutionary stalling observed in the comparison of Praesepe and NGC 6811 for 0.8–0.9 M ⊙ stars shifted to lower masses, with the 0.6–0.8 M ⊙ stars being the ones now rotating significantly faster than expected at this age. 6.2. Comparing Magnetic Activity in NGC 752 and in the Hyades and Praesepe Studies of observational tracers of coronal or chromospheric activity have uncovered a mass-dependent transition between active and inactive stars in open clusters (e.g., Kafka Honeycutt 2006 ; Douglas et al. 2014 ; Núñez Agüeros 2016 ; Núñez et al. 2017 ). The dividing line between these two populations shifts to lower masses in older clusters, indicating that lower-mass stars possess longer activity lifetimes. For FGK stars, these lifetimes are ≤650 Myr, as calibrated by observations of open clusters younger than NGC 752 (Hawley et al. 1999 ; Douglas et al. 2014 ; Núñez et al. 2017 ). Extending such measurements to older open clusters is a primary motivation of this work. Our knowledge of the chromospheric activity lifetimes of lower-mass stars currently relies on indirect calibrations, such as modeling the vertical gradient in H α emission line strengths as a consequence of dynamical heating in the Galactic disk (e.g., West et al. 2008 ). Our spectroscopic campaign confirms that the boundary between active and inactive stars has shifted well into the M dwarf regime in NGC 752. As noted above, there are three stars in our spectroscopic sample with formal detections of H α emission, but we do not consider these stars indicative of the location of the active/inactive boundary in this cluster. As Figure 11 demonstrates, even the modest activity signatures measured from these stars (EW >2 Å) make them clear outliers from the dominant cluster locus, and their moderate membership probabilities (50 P mem 80%) indicate that these stars may not be bona fide cluster members. Calculating the mean H α EW for NGC 752 members in bins of ( r − K ), as shown in Figure 15 , indicates that there is no transition to activity in NGC 752, at least within the domain of our spectroscopic survey, which includes stars with SpTs as late as ≈M2. Figure 15. Average H α EW as a function of logarithmically binned ( r − K ) for stars in NGC 752 compared to the younger Praesepe and Hyades clusters. The number of stars in each bin is along the top; the vertical bars show the σ for the bin, and the horizontal bars show


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We are grateful to Włodek Kluźniak for helpful comments. We thank Maciek Wielgus for his help with PDs and Fig. 6 . The anonymous referee’s report was very helpful. This research was supported by the Polish NCN grants UMO-2013/08/A/ST9/00795 and DEC-2012/04/A/ST9/00083. J.P.L. was supported in part by a grant from the French Space Agency CNES. R.S.S.V. was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), grants 2010/00487-9, 2013/01001-0 and 2015/10577-9. R.S.S.V. is grateful for the hospitality at Harvard-Smithsonian Center for Astrophysics and at Nicolaus Copernicus Astronomical Center. A.S. acknowledges support for this work by NASA through Einstein Postdoctoral Fellowship number PF4-150126 awarded by the Chandra X-ray Center, which is operated by the Smithsonian Astrophysical Observatory for NASA under contract NAS8-03060. A.S. acknowledges computational support from NSF via XSEDE resources (grant TG-AST080026N), and from NASA via the High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.


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ACKNOWLEDGEMENTS We thank Vikram Ravi for useful discussions. We also thank the referee for comments which improved the clarity of the presentation. This research benefited from interactions at the ZTF Theory Network Meeting, funded by the Gordon and Betty Moore Foundation through Grant GBMF5076. WL was supported by the David and Ellen Lee Fellowship at Caltech.


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

ULIRGs. They find the presence of molecular outflows with mass outflow rates of several 100 yr, which are similar or larger than the star formation rates in these systems. For the ULIRGs that we study in this paper, we derive outflow rates of molecular gas that are a factor of a few lower than the star formation rates (Sect. 4.1 ). Therefore, our H results appear at odds with the CO results from Cicone et al. (2014) . Of course, the H 2.12 m line only traces a small fraction of the total molecular gas mass, and its strength is subject to the local gas temperature and excitation (see, e.g., Rigopoulou et al. 2002 ). Complementary CO or mid-IR H observations of our sample sources are needed to further investigate the hot-to-cold molecular gas mass ratio. Some of the most spectacular molecular gas outflows in ULIRGs have been detected with the Herschel Space Observatory in the OH line (e.g., Sturm et al. 2011 ; Spoon et al. 2013 ; Veilleux et al. 2013 ; González-Alfonso et al. 2017 ). The outflow velocities that we observe in the H line with SINFONI are within the range of the OH outflows detected with Herschel. However, the mass outflow rates derived from OH measurements by Sturm et al. (2011) and González-Alfonso et al. (2017) are nearly ubiquitously 100 yr. Our SINFONI data suggest also here that either molecular outflow rates in nearby ULIRGs are much more moderate than predicted based on OH studies, or that our assumed hot-to-cold gas mass ratio for H outflows in ULIRGs is too large. Alternatively, the OH studies may trace faster outflows that originate closer to the galaxy core, with higher and smaller . González-Alfonso et al. (2017) indeed found evidence for higher maximum outflow velocities seen in OH compared to CO in several nearby ULIRGs. According to González-Alfonso et al. (2017) , this could suggest that OH and CO trace outflows in different regions of the galaxy. After all, they argue that as the outflowing gas expands and breaks up into clumps, it will “cover a decreasing fraction of the far-IR continuum”. Unlike the CO, the OH molecules are radiatively excited, and hence “produce lower absorption and emission” the further out the gas flows ( González-Alfonso et al. 2017 ). This scenario may also explain the fact that the molecular mass outflow rates that we derive from H appear on average lower than those based on OH studies. Our results suggest that consensus has yet to be reached on how effective molecular gas outflows are in influencing the star formation properties of nearby ULIRGs. We argue that detailed 3D-imaging of the different gas phases is a valuable tool to help determine the evolutionary role of multi-phase gas outflow in the evolution of these IR-luminous galaxies. 5. Conclusions We presented the detection and characterization of massive outflows of hot molecular gas in three out of four nearby ULIRGs. We imaged the molecular outflows at sub-kpc resolution with VLT-SINFONI, using the H 1–0 S(1) 2.12 m line. We


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We thank the anonymous referee for very constructive feedback and comments that helped to improve the paper significanty. We thank Rosine Lallement for providing us with the extinction map of the solar neighborhood. This work was supported by the program Physique et Chimie du Milieu Interstellaire (PCMI) funded by the Conseil National de la Recherche Scientifique (CNRS) and the Centre National d’Etudes Spatiales (CNES) of France. This research was undertaken, in part, thanks to funding from the Canada Research Chairs program. N.W.M. was supported in part by the Natural Sciences and Engineering Council of Canada.


O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 O O O O O O O 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 B-CelestialObject 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 B-Wavelength I-Wavelength O O O O O O O O O O O O O O B-CelestialObject O O O O B-Formula I-Formula I-Formula 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 O O O O O O O O O O O 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 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-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 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 O O O O O B-Identifier I-Identifier O O O O O O O O O O O O O O O O O O O O O O O O O O

be determined by scaling the weighted frequency. The quantities c S (), c A (), and c T () are the sound speed, Alfvén speed, and tube speed, respectively, and γ , k B , T 0 , μ , m H , B 0 , μ B , and ρ 0 are the specific heat ratio, Boltzmann’s constant, temperature, mean molecular weight, hydrogen atomic mass, magnetic field strength, magnetic permeability, and density, respectively. The subscript 0 indicates the equilibrium quantity. The () is the buoyancy frequency, where g = 0.274 km s −2 . The parameters Λ p () and Λ ρ () are the pressure and density scale heights, respectively. The prime indicates the derivative with respect to the vertical direction. As we assume the uniform vertical field in a non-isothermal stratified medium, and , giving . Hence the expression for the angular cutoff frequency is reduced towhere . Equation ( 2 ) describes umbral oscillations in the photosphere, accounting for the finite β effects. Equation ( 2 ) shows that f cutoff is directly related to Λ p and Λ ρ , which all can be determined from observations. In other words, and Λ ρ = γ Λ p . Thus, Equation ( 2 ) becomes a function of X . The sound speed c S is estimated from the plasma temperature. The temperature is obtained from the ratio of HMI continuum intensity to the quiet Sun’s, by applying the Planck function (Mathew et al. 2004 ). In other words, we solve the equation , where I , h , c , λ , k B , , and are the intensity ratio, Planck’s constant, speed of light, wavelength of Fe i line continuum (6172.1 Å), Boltzmann’s constant, the temperature at a given position, and the temperature of the quiet Sun (6000 K), respectively. Using μ = 1.3 and γ = 5/3, we obtain the sound speed as km s −1 . We look for a positive solution for X of Equation ( 2 ) by changing the scaling of in the range below 1.0. We found that positive solutions for all pixels inside the umbra exist when the scaling is in 0.5–0.55. Thus we take 0.55 as the upper limit of the scaling. The solution allows us to calculate the Alfvén speed, using the expressions ), the plasma- β , as , and the mass density as for each pixel of the umbra. The magnetic field strength B 0 is obtained as the de-projected HMI magnetogram, which may correspond to the magnetic field slightly above the height of continuum formation (Norton et al. 2006 ). Slightly different values of equilibrium quantities do not give us significantly different results. For example, when δT 0 = ±100 K, and are less than 50 m s −1 , and is less than 0.02 for the given sunspot. When we choose δλ = −2 Å, the absolute values of deviation of speeds and plasma- β are less than 0.1 m s −1 and 10 −4 , respectively. 3. Results We illustrate the application of the developed method to a sunspot located near the disk center, observed during 00:00–01:00 UT on 2014 August 28, in NOAA 12149. The center of a sunspot is tracked synodically, accounting for the effect of the solar differential rotation. We used the differential rotation law, in μ rad


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We are deeply grateful to Patrick Boehnke for his contributions to the CHILI measurements and for helpful discussions. The manuscript benefited significantly from very detailed and constructive comments by an anonymous reviewer. We also acknowledge Roberto Gallino for his adept remarks. We thank Elmar Gröner for technical support on the NanoSIMS. This work was supported by NASA (grants NNX15AF78G, 80NSSC17K0250, and 80NSSC17K0251 to A.M.D.). LLNL-JRNL-768104.


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Support for this work was provided by NASA through Chandra Award Numbers GO6-17112A and GO6-17112B issued by the Chandra X-ray Observatory Center, which is operated by the Smithsonian Astrophysical Observatory for and on behalf of the National Aeronautics Space Administration under contract NAS8-03060. Additional support was provided by NASA through grants from the Space Telescope Science Institute (HST-GO-13578, HST-GO-14352), which is operated by the Association of Universities for Research in Astronomy, Incorporated, under NASA contract NAS5-26555. The South Pole Telescope is supported by the National Science Foundation through grant PLR-1248097. Partial support is also provided by the NSF Physics Frontier Center grant PHY-1125897 to the Kavli Institute of Cosmological Physics at the University of Chicago, the Kavli Foundation and the Gordon and Betty Moore Foundation grant GBMF 947. S.W.A. and A.B.M. acknowledge additional support from the U.S. Department of Energy under contract number DE-AC02-76SF00515. J.H.L. is supported by NSERC through the discovery grant and Canada Research Chair programs. W.F. acknowledges support from NASA contract NAS-08060 and the Smithsonian Institution. The Munich group acknowledges the support by the DFG Cluster of Excellence “Origin and Structure of the Universe”, the Ludwig-Maximilians-Universität (LMU-Munich), and the Transregio program TR33 “The Dark Universe.” T.S. acknowledges support from the German Federal Ministry of Economics and Technology (BMWi) provided through DLR under projects 50 OR 1210, 50 OR 1407, and 50 OR 1610. The Melbourne group acknowledges support from the Australian Research Council’s Discovery Projects funding scheme (DP150103208). B.B. is supported by the Fermi Research Alliance, LLC under Contract No. De-AC02-07CH11359 with the U.S. Department of Energy.


O O O O B-CelestialObject O O O O O O O B-Survey I-Survey I-Survey O O B-Identifier B-Citation I-Citation I-Citation I-Citation O O O B-Instrument O O O O B-Identifier B-Citation I-Citation I-Citation I-Citation O B-Citation O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O B-Survey O O B-CelestialObject O O O O O O O O O O O O B-Wavelength I-Wavelength O B-Wavelength I-Wavelength O O O B-Wavelength I-Wavelength O O O O O B-Wavelength I-Wavelength O O O B-Wavelength I-Wavelength O O O O O B-Wavelength I-Wavelength 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 B-CelestialObject O O O O O O O O O O O O O O O B-Instrument B-Wavelength I-Wavelength I-Wavelength 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 B-Telescope O O O O O O O O O O O B-Wavelength I-Wavelength 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 B-Wavelength I-Wavelength I-Wavelength O O O O O O O O O O O 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 B-CelestialObject O O O O O O B-Software O O O B-Software I-Software I-Software I-Software B-Software O O O B-Software O B-Citation I-Citation I-Citation I-Citation O O O O B-Model I-Model I-Model I-Model I-Model I-Model O O B-URL 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 B-Software 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 B-Software O O O O B-Dataset O B-Dataset O O O O O O O B-Dataset O O O O O O O O O O O O O O O O O O O O O B-Dataset 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 B-Instrument 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 B-Software 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 B-Person I-Person I-Person O O O O B-Survey B-Dataset O O O O O B-Person I-Person O O O O O B-Organization O O B-Grant O O O B-Organization I-Organization I-Organization I-Organization O O B-Organization O B-Grant O B-Grant O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O B-Grant O O O B-Person I-Person O O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization B-Organization B-Organization I-Organization I-Organization

We thank Huib T. Intema for help with the TGSS ADR1 catalog masks and survey details. Prabhakar Tiwari acknowledges the support by the PIFI (Project No. 2019PM0007) program of the Chinese Academy of Sciences and the NSFC grants 11720101004 and 11673025, and the National Key Basic Research and Development Program of China (No. 2018YFA0404503). The work of Pankaj Jain is supported by a grant from the Science and Engineering Research Board (SERB), Government of India.


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Acknowledgments Georgia Southern University provided start-up funds in support of this work. Additionally, Prof. T. Daniel Crawford of Virginia Tech provided some computer hardware necessary to complete some of this work. The authors are grateful for the support from both.


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Acknowledgements We would like to thank Andrew Cunningham, Patrick Hennebelle, Shu-Ichiro Inutsuka, Ralf Klessen, Pak Shing Li, Zhi-Yun Li, and Andrew Myers for helpful discussions. We particularly thank Kengo Tomida for pointing out that the angular momentum lost in the growth of sink particles could significantly affect disc formation in numerical simulations and for providing valuable references. Helpful comments by the referee are gratefully acknowledged. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 (WJG and RIK). Support for this work was provided by NASA through Astrophysics Theory Program (ATP) grant NNX-13AB84G (RIK and CFM) and Theoretical and Computational Astrophysics Network (TCAN) grant NNX-14AB52G (CFM and RIK) and the NSF through grant AST-1211729 (CFM and RIK). Supercomputing support was provided by NASA, through a grant from the ATP, from Lawrence Livermore National Laboratory, and from NERSC. The figures and analysis presented here were created using the yt analysis package (Turk et al. 2011 ).


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This study is based on observations obtained in Rozhen Observatory, European Southern Observatory program 074.D-0114 and Asiago Observatory. We acknowledge with thanks the variable star observations from the AAVSO International Database contributed by observers worldwide and used in this research. This research has made use of the NASA's Astrophysics Data System, and the SIMBAD astronomical data base, operated by CDS at Strasbourg, France. Some of the data presented in this paper were obtained from the Mikulski Archive for Space Telescopes (MAST). STScI is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555. Support for MAST for non- HST data is provided by the NASA Office of Space Science via grant NNX09AF08G and by other grants and contracts. We are thankful to U. Munari who made available the Asiago spectra of AG Peg obtained in 2002. We are grateful to the anonymous referee for valuable comments and suggestions. TVT is very grateful to Svet Zhekov for the many useful discussions and Sz. Zywica for some help with English.


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We acknowledge the support by the INFN project TAsP (Theoretical Astroparticle Physics Project). M.G. would like to thank the Max Planck Institute for Astronomy (Heidelberg), where part of this work wsa performed, and Luigi Mancini for hospitality. We also thank the anonymous referee for the constructive comments.


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We would like to thank Farhan Feroz for numerous helpful discussions during the inception of the polychord algorithm.


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Acknowledgments TAD acknowledges support from a Science and Technology Facilities Council Ernest Rutherford Fellowship, and thanks F. van de Voort for useful discussions and comments on early versions of this manuscript. MB was supported by the consolidated grants Astrophysics at Oxford ST/H002456/1 and ST/K00106X/1 from the UK Research Council. MC acknowledges support from a Royal Society University Research Fellowship. This paper makes use of the following ALMA data: ADS/JAO.ALMA#2015.1.00598.S. ALMA is a partnership of ESO (representing its member states), NSF (USA) and NINS (Japan), together with NRC (Canada), NSC and ASIAA (Taiwan) and KASI (Republic of Korea), in cooperation with the Republic of Chile. The Joint ALMA Observatory is operated by ESO, AUI/NRAO and NAOJ. This paper also makes use of observations made with the NASA/ESA Hubble Space Telescope , and obtained from the Hubble Legacy Archive, which is a collaboration between the Space Telescope Science Institute (STScI/NASA), the Space Telescope European Coordinating Facility (ST-ECF/ESA) and the Canadian Astronomy Data Centre (CADC/NRC/CSA). This research has made use 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.


O O O O O O O O O O O O O O O O O O O O O O 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 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 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 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 B-CelestialObject I-CelestialObject 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 B-CelestialObject I-CelestialObject 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 B-CelestialObject I-CelestialObject 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 B-CelestialObject I-CelestialObject 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-CelestialObject I-CelestialObject 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 B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation 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 B-Citation I-Citation I-Citation I-Citation O O B-Model I-Model I-Model 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-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 B-CelestialObject I-CelestialObject B-CelestialObject I-CelestialObject B-CelestialObject I-CelestialObject B-CelestialObject I-CelestialObject 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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

galaxies which already had a dynamical detection of their black hole mass. We modelled their one-dimensional surface brightness profiles with a combination of analytic functions, using one function per galaxy component. Spheroid luminosities were converted into stellar masses using individual, but almost constant mass-to-light ratios (∼0.6; Meidt et al. 2014 ). Figure 5. Black hole mass plotted against spheroid stellar mass for 45 + 3 early-type galaxies (from Savorgnan et al. 2015 ). The black solid line is the bisector linear regression for all galaxies except Mrk 1216, NGC 1271, and NGC 1277. The dashed lines mark the 1σ and 3σ deviations, where σ (0.51 dex) is the total rms scatter about the correlation in the black hole mass direction. The red symbols mark five galaxies that were claimed to be extreme outliers in this diagram: four intermediate-scale disc galaxies (Mrk 1216, NGC 1271, NGC 1277, and NGC 1332) and one elliptical galaxy (NGC 4291). All five reside well within a 3σ deviation from the correlation when using their correct spheroid mass. For NGC 1277, we show the previously reported spheroid stellar mass (van den Bosch et al. 2012 ) in grey. The green colour is used to show the location of four additional intermediate-scale disc galaxies mentioned in Section 2 . In Fig. 5 , we show the galaxies Mrk 1216, NGC 1271, and NGC 1277, which were not a part of the original sample of 45 early-type galaxies. For the galaxy NGC 1271, we use the black hole mass measurement and the stellar mass-to-light ratio obtained by Walsh et al. ( 2015b ). For the galaxy NGC 1277, we use the black hole mass measurement obtained by Walsh et al. ( 2015a ) and the stellar mass-to-light ratio obtained by Martín-Navarro et al. ( 2015 ). Note that for NGC 1277, we recover a spheroid stellar mass of 2.7 × 10 11 M ⊙ , in agreement with the value of ≈ 1-2 × 10 11 M ⊙ obtained by Emsellem ( 2013 ) from his multi-Gaussian expansion models. 5 For the galaxy Mrk 1216, we use the upper limit on the black hole mass and the stellar mass-to-light ratio obtained by Yldrm et al. ( 2015 ). For the first time, Fig. 5 reveals that when the four intermediate-scale disc galaxies Mrk 1216, NGC 1271, NGC 1277, NGC 1332, and the elliptical galaxy NGC 4291 are properly modelled, they no longer appear as extreme outliers above the (black hole mass)–(spheroid stellar mass) correlation for early-type galaxies, i.e. they all reside well within a 3σ deviation from the correlation. 4 ORIGIN OF COMPACT MASSIVE GALAXIES Acknowledging the correct structure of galaxies with intermediate-scale discs is important to properly understand their origin. According to the current paradigm of cosmological structure evolution, the genesis of massive early-type galaxies is characterized by two distinct phases: ‘ in situ ’ and ‘ ex situ ’. The first phase takes place in a young Universe (within its first 4 Gyr), when cold gas inflows produced short and intense bursts of star formation that created


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2010 ) can become carbon-rich, although the transition luminosity is lower in metal-poor populations. Sextans A appears to have a higher relative fraction of carbon stars compared to Leo A (Table 9 ), and its evolved stellar population (above the TRGB) is more luminous. In both galaxies, there are a few stars with bolometric magnitudes brighter than the traditional AGB luminosity limit of (Wood et al. 1983 ). These bright sources represent a small population of RSGs or hot-bottom-burning AGB stars (with ), whose ages are consistent with a recent increase in the SFR ∼1 Gyr ago (Dolphin et al. 2005 ; Cole et al. 2007 ). The discrepancy in the size of the AGB populations unlikely due to the difference in stellar mass of the host galaxy. More likely it is due to differences in both the mean metallicity and SFH. 4.2. Dust Production Stars with have a measurable IR excess due to dust. There are 32 stars in Leo A and 101 stars in Sextans A, which meet this criteria, with a low-moderate relative uncertainty in the DPR. As the uncertainty in the chemical classification is high for most sources (Figure 9 ), we compute four values for the total dust-production rate: (1) using the best-fit models irrespective of dust chemistry; (2) assuming all stars are O-rich; (3) assuming all stars are C-rich; and (4) only including stars identified as variable. Table 10 lists the total DPRs for each galaxy. These estimates exclude any source with a relative uncertainty in the DPR > 0 (see Figure 8 ). Table 10 The Global Dust-production Rates for Leo A and Sextans A Note. Best-fitting chemical type: 25 C-rich and 6 O-rich in Leo A, and 68 C-rich and 33 O-rich in Sextans A. The total DPR in Sextans A should be considered a lower limit, as we do not detect AGB stars to the tip of the RGB. In both galaxies, the total dust input into the ISM is dominated by one or two stars. In Leo A, the star with the highest DPR is LeoA-143, with a DPR of . This is two orders of magnitude greater than the second-highest DPR in Leo A. This object has a rising SED and was identified as a candidate PNe from H α observations by Magrini et al. ( 2003 ), hence we exclude this source from the global dust-budget estimate. In Sextans A, the two sources with the highest DPRs are IDs 17 and 448 (SSTDUSTG J101059.43-044249.3 and J101058.05-044304.1, with and , respectively). These also have rising SEDs; however, both of these sources have been identified as variable x-AGB candidates by DUSTiNGS (Boyer et al. 2015c ). Our fitting routine classified SextansA-17 as an oxygen-rich AGB-star; it is responsible for 89% of the global dust production of Sextans A. If this source is instead carbon rich, then its DPR is significantly lower: . If SextansA-17 is confirmed to be an oxygen-rich AGB star, then it conclusively shows that individual metal-poor ( to −1.40) evolved stars can produce significant amounts of dust, and contribute substantially to the enrichment of the ISM in their host system. Figure 11


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yet implemented in SPECTRUM or AWSoM. The comparison of the coronal hole emission with the EIT images is also misleading for two reasons. First, the SPECTRUM calculations have been carried out with the two fundamental limitations discussed above; second, the coronal hole count rates of the EIT images are affected by instrument-scattered light (Shearer et al. 2012 ), and thus they are an overestimate of the real emission of coronal holes. These limitations prevent us from drawing any conclusions from the comparison with EIT. Finally, we assumed that the kinetic proton and ion temperatures are equal. However, in the region of the data extraction, the proton temperature anisotropy, T ⊥ / T ∥ , is between 1 and 1.3. In regions where there is temperature anisotropy, the kinetic proton and ion temperatures are not equalized by Coulomb collisions. 4.1.3. Sulfur The total intensity of the S x 264.2 Å line is significantly underestimated in both models even if lines formed at similar temperatures are in agreement with observations for the west limb. The reason for this discrepancy is likely due to the assumed abundance of sulfur. The values adopted in this study are photospheric, but the abundance of this element is notoriously difficult to determine because sulfur behaves in an anomalous way with regard to the FIP effect. In fact, sometimes it can behave as a high-FIP element, and sometimes as a low-FIP element, depending on the properties of the region where it is emitted (Laming 2015 , and references therein). Therefore, while the comparison of the predicted intensity of this element is expected to follow the behavior of the other ions formed at similar temperatures (e.g., Fe xi–xii ), the uncertainties in the element abundances make its interpretation more difficult. 4.2. Narrowband and Spectral Imaging SPECTRUM has the capability to apply instrument effective areas on the calculated intensities and to create 2D narrowband images, such as those observed by SoHO /EIT or the Solar Dynamic Observatory /Atmospheric Imaging Assembly ( SDO /AIA). To obtain such images, we need to save the 3D data domain surrounding the Sun. Then we calculate synthetic spectra for each pixel, weighting it by the effective area of the instrument and calibration factors. Figure 13 was created based on a box with sides of 3 R ⊙ in length, with 200 cells along each side. SPECTRUM calculated the full spectra from 165 to 350 Å for each cell within the box and convolved them with the instrument’s response function to obtain the observed data number count (DN) measured with the imager. The top left panel in Figure 13 shows the simulated plasma conditions of the solar corona as observed from Earth on 2007 November 4 19:12:27 UT, the top right panel corresponds to 2007 November 12 12:32:02 UT, and the bottom one is at 2009 April 23 13:13:36 UT, corresponding to the closest time to the spectral observations when narrowband observations were taken at the 195 Å wavelength. The


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in the water column density (mainly due to airmass variations). As we can see with panel c, all the telluric lines are corrected to the noise level (including the telluric lines blended with stellar lines). 4. Methods In this section, we describe how the transmission spectrum was derived and how we can search for water vapor in it with the cross-correlation technique. 4.1. Transmission spectrum The transmission spectrum ( Seager Sasselov 2000 ; Brown 2001 ) was obtained during the transit, when the planet passes in front of the star. It is defined as the area occulted by the planet over the stellar disk as a function of wavelength and probes the highest layers of the atmosphere. We computed the transmission spectrum following the same formalism as Wyttenbach et al. (2017) . Once the spectra are corrected from telluric features, weseparated in-transit spectra from out-transit spectra. Anin-transit spectrum, , is a spectrum obtained when the planetoccults a part of the stellar disk, while an out-transit spectrum, ,corresponds to the full-disk stellar spectrum. We corrected each spectrum for the stellar reflex motion induced by the planet, using the orbital parameters in Table 1 . Then, we created the normalized master out-transit spectrum which is the sum of the out-transit spectra: We normalized all the in-transit spectra to the continuum level of the master out-transit spectrum with a fourth-degree polynomial. This normalization was made from 5338 Å to 6900 Å, which corresponds to the red CCD. We applied a sigma-clipping rejection algorithm on the spectra in order to replace all the cosmic ray hits by the mean value of the other spectra at each wavelength. A normalized in-transit spectrum is noted . Then, we computed the transmission spectrum as the sum of each individual transmission spectrum (), after applying a Doppler shift to the planet rest frame to compensate for the planet orbital motion during transit: Finally, we expressed the variation of the occulted area by the planet as a function of wavelength on an absolute scale, by using the known white-light radius ratio (Table 1 ) : 4.2. Cross-correlation function The study of water vapor in the transmission spectrum in the visible is difficult considering the low intensity of the water bands and the noise level, even if we are able to resolve each line. To detect water vapor we need to co-add hundreds of lines to maximize the signal-to-noise ratio (S/N). To do so we used the cross-correlation function (CCF), expressed by: This technique ( Baranne et al. 1996 ; Pepe et al. 2002 ) consists of projecting a binary mask (with an aperture width of one pixel) on the spectrum and to sum the transmitted flux at each wavelength. The mask contains the theoretical wavelengths of water vapor transitions, and is Doppler shifted successively to scan a radial velocity range of –80 to 80 km s with a step of 0.82 km s. This step corresponds to the size of one pixel on the CCD of HARPS. In this study,