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This paper is based on observations made in the Observatorios de Canarias del IAC with the TNG operated on the island of La Palma by the Fundación Galileo Galilei – INAF, Fundación Canaria in the Observatorio del Roque de los Muchachos . OV thanks to the Spanish TAC for the time allocation (programme number CAT_110) during semester 2010A. 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. We used some data and images from Sloan Digital Sky Survey (SDSS, versions DR8 and DR14), which is a project funded by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. IRAF is distributed by the National Optical Astronomy Observatory, which is operated by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. Thanks are due to the anonymous referee whose recommendations helped us to improve the paper.


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

if using the relationships of the Ca ii triplet due to Paschen blending that may be causing the offset observed between HAeBes and CTTs. Another note of caution is advised when using the He i and O i lines, as their complex line profiles suggest various origins – which may or may not be associated with accretion. The complexities of their profiles are likely the cause of the low detection rate of these lines, as multiple absorption and emission components can contribute to the line equivalent width. An exploration of the line profiles will be presented in a future paper by the authors. 3.3 Emission lines as accretion diagnostics Since all of the emission lines appear to be correlated with the accretion luminosity, it is worth discussing which lines serve as the most sensitive tracers of accretion i.e. most readily detected (and therefore possibly associated directly with accretion). That way the best lines can be prioritized in future observations. In Table 3 , all 32 lines are presented along with details of the number of emission detections. The other columns of the table are split into different categories based on emission detection and UV-excess detection. HAeBe stars that are classed as having an accretion detection are those for which a UV excess was clearly detected in Paper I – 62 stars match this criterion. This includes the seven stars in which an accretion rate could not be determined within the context of MA; it would require an unrealistically high filling factor of shocked material to reproduce their UV excess. The measured Δ D B of these seven objects is likely associated with accretion due to the overall properties of the stars, although the exact mechanism is not known [an alternative could be boundary layer accretion for these hot objects Bertout, Basri Bouvier (see 1988 ); Blondel Djie (see 2006 )]. 2 Table 3. This table details all of the measured emission lines, along with their respective number of detections. The final four columns denote the four categories into which each star of the sample can belong to for a given line; full descriptions are provided in the text. ‘Emis’ denotes emission line, and Δ D B denotes the UV excess. The two categories of emission and accretion can be divided into two outcomes for each case, those with and those without. This gives a total of four possible categories for a star to be in e.g. a star may have a particular line in emission, but no Δ D B was detected in the star. Table 3 gives the number of stars split into each category, for each line, and is presented visually in Fig. 4 . What the four different categories represent are now detailed. The first category contains objects for which both emission lines and a UV excess are detected, represented by the green segments in the diagram. This category measures if the line is a good one to one tracer of accretion i.e. excess is present and so is the emission line. Examples of good tracers are Hα, Brγ and Paβ as their emission detections


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Acknowledgements We would like to thank Douglas C. Heggie for N -body simulations (referred in the text as DH simulations) and for very valuable discussions concerning blue straggler spatial distributions in star clusters. Results from these simulations added much confidence to the validity of the results obtained with the mocca code. The project was supported partially by Polish National Science Center grants DEC-2011/01/N/ST9/06000 and DEC-2012/07/B/ST9/04412. We thank anonymous referee for great comments and suggestions. It helped us to improve the paper.


O O O O O O O O O O O O O O O O O O O O O O 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 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

our current understanding on the formation of wide binaries, when comparing the abundances of their components, we would expect both stars to have similar metallicities, as both stars come from the same parental material. Empirical evidence for this expectation has been reported in the works of Andrews et al. ( 2018a ), Desidera et al. ( 2004 ), and Desidera et al. ( 2006 ), reinforcing the idea that wide binaries can be thought of as the smallest versions of open clusters (cochemical and coeval stars). Fig. 7 shows the metallicity comparison of the data sample pairs on the left (blue), and of the random alignments pairs on the right (red). The 1:1 relation, and a ±0.1 dex displacement from it, are shown as the solid and dashed lines, respectively. It can be seen that the data pairs tend to follow the 1:1 relation, while the random alignments pairs do not. We take this result as a confirmation that our multiple-parameter criteria used to select the data sample pairs is indeed recovering promising wide binary candidates, as for most of the components of the pairs their metallicities tend to be similar (even though the metallicity was not used as a criterion). This result is in agreement with the expectations. In spite of these promising results, some contamination might still be present in our nominal data sample. For instance, one pair in Fig. 7 is located well off the 1:1 relation, with [Fe/H] 1 = −0.132 dex and [Fe/H] 2 = +0.24 dex. Because of this, we decide to assign qualitative flags to our candidates depending on how consistent or inconsistent they appear to be when taking all the parameters into account. For any given pair, we assign it one of three types of flags: ‘ a ’, when it is consistent in all the parameters and most likely is a real binary; ‘ b ’, when it appears to be consistent in some regards but not in others; and ‘ c ’, when even though it passed all the required criteria of the search, it shows clear inconsistencies under a more detailed inspection, and most likely correspond to a chance alignment. Out of the 10 pairs obtained in the 4th row of Fig. 6 , we classify three of them as ‘ a ’, five of them as ‘ b ’, and two of them as ‘ c ’. Fig. 7 also shows the data sample pairs labelled according to this classification. We report the ‘ a ’ and ‘ b ’ pairs in the first block of Table 2 , where we also provide the parameters associated with the pairs and their component stars. The pairs assigned with flag=‘ c ’ are discarded from our candidate list and not further analysed. Table 2. List of our wide binary candidates in the Subsample 1 : ‘PM-π-RV’. We only report the pairs qualitatively flagged as ‘ a ’ and ‘ b ’, as the pairs flagged as ‘ c ’ have been discarded from our candidate list. The table is separated in three blocks, each one of them containing the candidates found in Section 5.1 , Section 5.2 , and Section 5.3 , respectively. In any given block of the table, the pairs are separated by horizontal lines. For each


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

are heated by the nuclear decays of products of the rapid neutron-capture process (Metzger et al. 2010 ). The light-curve properties were interpreted as being produced by dynamical ejecta from the merger and secular ejecta from the merger remnant. The estimated ejecta mass is in the range of 0.03 to 0.05 (Chornock et al. 2017 ; Cowperthwaite et al. 2017 ; Drout et al. 2017 ; Kasen et al. 2017 ; Kasliwal et al. 2017 ; Kilpatrick et al. 2017 ; Nicholl et al. 2017 ; Smartt et al. 2017 ; Tanaka et al. 2017 ; Tanvir et al. 2017 ), which even for asymmetric binaries lies near the high end of the theoretical range expected from simulations. This can be interpreted as tentative evidence for a delayed/no collapse in GW170817 because this merger outcome tends to produce larger ejecta masses as compared to a direct collapse (Bauswein et al. 2013b ; Fernández Metzger 2013 ; Hotokezaka et al. 2013 ; Metzger Fernández 2014 ; Perego et al. 2014 ; Siegel et al. 2014 ; Wanajo et al. 2014 ; Just et al. 2015 ; Sekiguchi et al. 2016 ). We thus use below the assumption of no prompt collapse in GW170817 and leave the detailed interpretation of the electromagnetic emission to future work. Our assumption can be corroborated by refined models and future observations. 3. NS Radius Constraints 3.1. Threshold Binary Mass If GW170817 resulted in a delayed collapse or no collapse, its total mass provides a lower limit on the threshold binary mass for prompt collapse as given by Equation ( 1 ). The threshold binary mass M thres depends sensitively on the EoS (Shibata 2005 ; Baiotti et al. 2008 ; Hotokezaka et al. 2011 ; Bauswein et al. 2013a ). Considering different EoSs, in Bauswein et al. ( 2013a ), we found by hydrodynamical simulations that the threshold binary mass to good accuracy followswith being the radius of a nonrotating NS with a mass of 1.6 and M max being the maximum mass of nonrotating NSs. The relation was derived from simulations of symmetric binary mergers but also holds for moderately asymmetric systems (Bauswein et al. 2013a ; Bauswein Stergioulas 2017 ). We verify through additional simulations for five representative EoSs that strongly asymmetric mergers with mass ratio q = 0.6 have a threshold binary mass, which is systematically lower by 0.1 to 0.3 than M thres of equal-mass binaries. This reduction of M thres for asymmetric binaries is understandable because, according to Kepler ’s law, asymmetric binaries have less angular momentum than equal-mass binaries with the same M tot at a given orbital separation, which implies less stabilization for asymmetric mergers. (With the low-spin priors, the 90% credibility interval of the mass ratio of GW170817 is ). If GW170817 was very asymmetric, one has , which implies that Equation ( 1 ) is conservative because . A similarly accurate description of M thres is given by the fitwith the radius R max of the maximum-mass configuration. Equation ( 2 ) is accurate to better than (Bauswein et al. 2013a , 2016 ). The


O B-Collaboration I-Collaboration I-Collaboration I-Collaboration I-Collaboration O O O O O O B-EntityOfFutureInterest B-EntityOfFutureInterest O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation O B-Citation O B-Citation O B-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Instrument I-Instrument O B-Instrument I-Instrument O B-EntityOfFutureInterest 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 B-EntityOfFutureInterest O O B-CelestialObject 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 O O O O O 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 I-Instrument O O O B-Location I-Location B-Location O B-Location O O O B-Instrument I-Instrument O O B-Location O O O O O O O O O O B-EntityOfFutureInterest O O 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 I-Instrument O B-Instrument I-Instrument O O O O O O O O O O B-Collaboration I-Collaboration I-Collaboration B-Collaboration O O B-URL I-URL O O O B-Database I-Database I-Database B-Database O O B-URL O O O O O O O B-Dataset I-Dataset I-Dataset B-Dataset O O O B-URL 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-Citation I-Citation I-Citation I-Citation O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O B-Dataset O O O O O O O B-EntityOfFutureInterest O O O 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-URL 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 B-EntityOfFutureInterest O O O O O O O O


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migration rate is removed, the bumps are smoothed out. The 100-d population between 50 and 60 R ⊙ is negligible, due to the small number of such planets in the observed WJ period distribution. 7 COMPARISON TO OBSERVATIONS The model described here is motivated by the claimed deficit of WJs around moderately evolved stars (Johnson et al. 2007 , 2011 ), as seen in Fig. 1 and Section 2 . We postulate that the reason for this deficit is that the observed eccentricity distribution of WJs around main-sequence stars is really a snapshot of a population whose eccentricities are oscillating via the KL mechanism while they migrate inwards due to tidal friction. The fact that the oscillation time-scale is short compared to the characteristic time-scale for the stellar evolution means that planets are removed from the observed sample when their periapsides oscillate to the minimum value and interact with the host star. Fig. 15 shows the result of such a model and demonstrates that, under these conditions, a pre-existing WJ population will be largely removed by the time the stars evolve to 4 R ⊙ , in contrast to the case where the eccentricities of the observed population do not oscillate. The exact location of WJ removal depends on the details of tidal forces and the perturber, but the general behaviour is well described by Fig. 16 . However, our results do not match all observations. Figs 17 and 18 show the distribution of eccentricities for our simulated systems and observed WJs (from the Exoplanet Orbit Database), respectively, with our simulated population drawn from the same period distribution. In both cases, the systems are restricted to the Jupiter mass range (0.3–3) and the period range of 10–100 d. Comparison of these two populations using the Kolmogorov–Smirnov (KS) test gives a p -value of 1 × 10 −4 , indicating they are unlikely to be drawn from the same underlying population. The discrepancy is primarily due to the significant fraction (15 per cent) of simulated WJs with high eccentricity ( e > 0.8), while no observed WJs have such high values. The lack of high-eccentricity WJs has also been noted by Dawson, Murray-Clay Johnson ( 2015 ). Figure 18. The eccentricity distribution for observed WJs, taken from the Exoplanet Orbit Database. The small number of highly eccentric planets differs significantly from the oscillating distribution, but that may be a result of low DE. The observed population also includes an excess number of low-eccentricity planets, which is difficult to reconcile with the orbital behaviour of our planets. Many of the simulated planets, even those started with eccentricity of 0.05, had a minimum eccentricity peak above 0.1, similar to the eccentricity distribution shown in Fig. 7 . This figure also shows the cumulative distribution of eccentricity values; blue, green, and red dashed lines indicate the cumulative observed distribution at 75, 90, and 98 per cent of WJs, respectively, for the simulated planet (dotted lines)


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This study is based on data collected as part of the CLASH Multi-Cycle Treasury Program with the Hubble Space Telescope, as well as on data collected at the ESO-VLT (prog. ID 186.A-0798). This analysis relies on the work done within the CLASH and CLASH-VLT collaborations, who prepared the imaging and spectroscopic data. We thank the referee for the useful comments that improved our publication. The paper is based on the Master’s thesis of VM, who thanks the University of Vienna for the grant near completion of studies. This publication is supported by the Austrian Science Fund (FWF).


O O O O O O O O O O O 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 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 B-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 O O O O O 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 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 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 B-Tag I-Tag I-Tag 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 B-Citation O O B-Citation 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 O O O B-Citation 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 B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula B-Citation O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O B-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-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 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 B-Software O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula

show a comparison between the new and the old interpolation method to approximate the temporal evolution of the mass (Fig. A1 ) and the Helium core radius (Fig. A2 ) of a star with mass M ZAMS = 70 M ⊙ and metallicity Z = 2.0 × 10 −2 . It is apparent that the new interpolation method works much better than the previous one, especially for estimating the values of the physical parameters that are important for evolved stars (such as the Helium core radius). It is worth noting that the new version of sevn can also interpolate tables at different metallicity. That is, if the pre-evolved tracks are not available for the metallicity Z s , sevn first evaluates and , where Z 1 ≡ Z s − Δ Z , Z 2 ≡ Z s + Δ Z and Δ Z is step in the metallicity grid. Then, the value is where and . APPENDIX B: THE FITTING FORMULA FOR PPISNE AND PISNE The new version of sevn includes a fitting formula to derive M rem accounting for PPISNe and PISNe. This formula has been obtained by fitting the masses of the compact remnants shown in tables 1 and 2 of Woosley ( 2017 ) as a function of the final Helium mass fraction and of the Helium core mass M He,f of the stars. Using the following fitting formulas, we get the parameter α P so that M rem = α P M rem, no psn , where M rem, no psn is the mass of the compact remnant we would obtain without PPISN/PISN (see equation 1 ). First, we define the following quantities We then express α P as a function of , , and M He,f : APPENDIX C: COMPARISON WITH <xref ref-type="bibr" rid="bib62">W17</xref> In this appendix, we compare our results with those presented in Woosley ( 2017 ). Fig. C1 is a detail of Fig. 2 , where we also plot the compact remnant masses taken from table 2 of W17 (black points). W17 explores the evolution of stars at Z ≃ 0.1 Z ⊙ in the mass range 70 M ZAMS / M ⊙ 150, also varying the amount of mass-loss through stellar winds to mimic the results expected from stars at lower metallicity. The fitting formula we implemented in sevn gives results in agreement with those of W17 . We obtain a comparable maximum BH mass (this work:∼55 M ⊙ , W17 : 58 M ⊙ ) and a similar mass range where a dearth of compact remnants is observed (this work: 55 ≲ M rem / M ZAMS ≲ 120, W17 : 58 M rem / M ⊙ 133). The differences between this work and W17 are due to the parameters M He,f and used for the PPISNe and PISNe fitting formula (see Appendix B ). Indeed, the values of M He,f and M fin , for different M ZAMS and metallicity, strongly depend on the adopted stellar evolutionary models. Figure C1. A detail of Fig. 2 that shows the ranges 40 ≤ M ZAMS / M ⊙ ≤ 160 and 0 ≤ M rem / M ⊙ ≤ 75. Black points are the compact remnant masses taken from table 2 of Woosley ( 2017 ). APPENDIX D: STELLAR EVOLUTION TABLES Tables D1 , D2 and D3 show the final parameters of various progenitor stars and the mass of their compact remnants when PPISNe and PISNe are turned on and when PPISNe and PISNe are switched off in sevn , for Z = 2.0 × 10 −2 , 2.0 × 10 −3


O O O O O O O O B-Person O B-Person O B-Organization O B-Grant B-Person O O O B-Organization I-Organization I-Organization O B-Grant O O O B-Fellowship I-Fellowship I-Fellowship I-Fellowship I-Fellowship I-Fellowship I-Fellowship O O B-Person I-Person B-Person I-Person B-Person I-Person B-Person I-Person O B-Person I-Person O O O O O O O O O O O B-Person I-Person I-Person B-Person I-Person O B-Person I-Person O O O O O O O O O O O O O O O O O O B-Observatory I-Observatory I-Observatory I-Observatory O O O O O O O O O B-Organization I-Organization I-Organization I-Organization O B-Organization I-Organization I-Organization O O B-Organization I-Organization I-Organization I-Organization I-Organization O O O O O O O O O O O O B-Organization I-Organization I-Organization I-Organization O O O O O O O O O O O O O O O O O O B-Location I-Location O O O O O O B-Location O O O O O O O O O O O O O O O O O O O O O B-Database I-Database I-Database B-Database

ACKNOWLEDGEMENTS We thank the referee for their comments. JPB and AJR acknowledge NSF grant AST-1616598. AJR was supported by National Science Foundation grant AST-1616710 and as a Research Corporation for Science Advancement Cottrell Scholar. We thank A. Ferre-Mateu, A. Wasserman, V. Pandya, L. Chevalier, and S. Bellstedt for their help with the mask design and/or observations. We thank P. van Dokkum, P. Kroupa, and H. Haghi for their comments on an early version of this paper. The data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation. The authors wish to recognize and acknowledge the very significant cultural role and reverence that the summit of Mauna Kea has always had within the indigenous Hawaiian community. We are most fortunate to have the opportunity to conduct observations from this mountain. This research has made use the NASA Extragalactic Database (NED).


O O O O O O O O O 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 B-Citation I-Citation I-Citation I-Citation O B-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 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 B-Model I-Model I-Model O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-EntityOfFutureInterest O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 B-Formula I-Formula I-Formula I-Formula 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 B-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

our calculations on a detailed level, we show below that the envisioned picture generally holds. We note that orbital excitation by sweeping secular resonances has previously been studied within the context of the solar system (see, e.g., Ward et al. 1976 ; Ward 1981 ; Nagasawa Ida 2000 ; Nagasawa et al. 2002 ; Minton Malhotra 2011 ; Agnor Lin 2012 ). In contrast with our work, these studies do not observe capture and instead report impulsive excitation of the orbital parameters upon encounter. However, these analyses are consistently based on a second order (Lagrange–Laplace) expansion of the Hamiltonian and therefore cannot properly model the establishment of secular commensurabilities, because homoclinic curves do not exist in phase space within this framework, disallowing a resonant domain to even be defined. A counter example is provided by the N -body simulations of Nagasawa et al. ( 2005 ), where long-term capture into first-order secular eccentricity resonances is observed. A final point worthy of attention is that as the host star spins down, the assumed angular momentum hierarchy (Equation ( 2 )) breaks down. Therefore, the assumption that the stellar spin axis remains fixed in inertial space does not formally apply toward the end of the evolutionary track of δ . If m is taken to approach a typical hot-Jupiter-like mass, however, it can be shown that by the time the angular momentum hierarchy is severely violated, the value of δ is already very close to that given by Equation ( 19 ). Accordingly, this complication does not pose a practical limitation. 3.1.2. Eccentricity Evolution Thus far, we have neglected orbital eccentricities in order to obtain an integrable Hamiltonian. Recalling that eccentricity and inclination terms are decoupled to second order in either quantity (Murray Dermott 1999 ), this assumption is justified as long as the eccentricities remain small. However, the ultimate result of adiabatic capture into a secular inclination resonance raises the question of whether or not similar dynamics can occur in the degree of freedom associated with the outer orbit’s eccentricity. Fortunately, very similar techniques to those already employed above can be used to attack this problem. In direct analogy to Equation ( 8 ), the inner orbit’s longitude of perihelion will not remain stationary in time, and will instead precess at a constant rate: π = μ t . In contrast with nodal regression, however, the rate of apsidal precession comprises numerous contributions (Ragozzine Wolf 2009 ):where quantities with the subscript p refer to the planet, and c is the speed of light. For simplicity, in the above expressions we have assumed that the planetary obliquity is null (and therefore only contributes to apsidal precession and not nodal regression), the rotation rate is synchronous with the orbital frequency (Hut 1981 ), and that eccentricities are sufficiently low to warrant the retention of only leading-order terms in e (see Kopal 1978


O O O O O O 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 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 I-Software O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O B-Survey B-Citation I-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O B-Survey B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation I-Citation 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 B-Telescope O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject B-CelestialObject I-CelestialObject I-CelestialObject O B-EntityOfFutureInterest O O O B-CelestialRegion I-CelestialRegion 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 B-CelestialObject I-CelestialObject I-CelestialObject O O O O B-Telescope O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Telescope O B-CelestialObject I-CelestialObject I-CelestialObject O B-CelestialObject I-CelestialObject O O B-Telescope O B-CelestialObject I-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O 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

is one possible strategy, it is important to remember that not all input features provide insight in all evolutionary phases (i.e. the small separation loses its diagnostic potential in subgiants, White et al. 2011 ). Furthermore, not all quantities can be defined in every system. We can improve the accuracy of spi if a priori knowledge of the evolutionary stage can be supplied. This ensures that the input features and training data are exploited optimally. We have implemented an RF classifier in the spi pipeline to determine the evolutionary phase based on ν max , T eff , Δν, and . Evolutionary phases were divided according to three sampling regimes listed in Section 4.1 . Detailed results are presented in Appendix C , however, we note here that the classifier accurately distinguishes between main-sequence and subgiant stars thus ensuring with high probability that the correct phase is included in the training data. 5 OBSERVATIONAL SURVEYS AND TARGETS The new spi input features have been designed to better extract information from the stellar interior. Moreover, in this work, one of the aims is to determine how asteroseismic precision impacts the determination of key CBM properties, which amongst other things is crucial for reliable stellar ages. To this end, we have reprocessed the results from Bellinger et al. ( 2019 ) with the new pipeline which include data from the KAGES (Silva Aguirre et al. 2015 ; Davies et al. 2016 ) and Legacy (Lund et al. 2017 ; Silva Aguirre et al. 2017 ) surveys. A majority of stars in the TESS field will be observed for 27 d, far shorter than the four-year timeseries of Kepler . The duration and cadence will reveal ridges in the echelle diagram although not with the precision required to probe the interior in detail. Many targets, however, will lie in the repeated/continuous viewing zones resulting in timeseries longer than 54 d. For these stars, we can expect a comparable frequency resolution to previously studied RV targets (e.g. Procyon A, α Cen A) or solar-like oscillators in the CoRoT field which we analyse with spi below. We summarize the main properties of these stars in Table 4 , while in Fig. 4 , we compare their measurement precisions with the precision obtained for 16 Cyg A – one of the Kepler benchmarks. The combination of different surveys, precisions, and observations essential for our scientific goal. Figure 4. The frequency precision for oscillation modes with different spherical degrees as a function of radial order. Here, we compare seven CoRoT stars, α Cen A, and Procyon A with the Kepler Star 16 Cyg A. The shaded regions indicate the uncertainty stemming from different mode identifications in the oscillation spectra (see Table 4 ). Table 4. An overview of CoRoT and RV stars analysed in this study. a In the supplementary online material. b Denotes that the star is likely a subgiant. c We have used these frequencies but relabelled the radial order based on an expected regular pattern. 6 RESULTS


O O O O O O O O O O O B-Location I-Location B-Grant I-Grant I-Grant B-Grant O O O O B-Grant I-Grant

The research leading to these results has received funding from the European Union’s Seventh Framework Programme (FP7/2007-2013) under grant agreement No. ERC-2012-AdG- 320951-DREAMS.


O O O O O O O O O O O B-Wavelength I-Wavelength O B-Wavelength O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject O O O O O O O O O B-CelestialObject I-CelestialObject 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 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 B-Wavelength I-Wavelength O O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation 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-Wavelength I-Wavelength O B-Citation I-Citation I-Citation I-Citation 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-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula B-Citation I-Citation I-Citation 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 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 B-Citation I-Citation I-Citation I-Citation 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-Citation I-Citation I-Citation I-Citation O O O O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O B-Telescope O O O B-CelestialObject I-CelestialObject O O O O O O O B-Wavelength B-Wavelength B-Wavelength O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O O B-Wavelength I-Wavelength O O O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O B-CelestialObject I-CelestialObject O O O O O O B-Database I-Database I-Database B-Database O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula O O O O B-Citation I-Citation I-Citation I-Citation O O O B-Tag O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject O O O O O B-Telescope 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 O O O O O O B-Software I-Software I-Software I-Software O B-Software 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

it with the stellar mass derived using the optical colors. The H α and NUV emission were used to derive the SFR in the disk. We then discuss the importance of NGC 4701 for understanding the morphological classification of late-type dwarf galaxies and accretion-driven star formation in extended H i disks. Throughout the paper we will assume the distance of NGC 4701 to be 17.1 Mpc. 2. The Bulgeless Spiral Galaxy NGC 4701 NGC 4701 was studied as part of a follow-up H i study of bulgeless disk galaxies (Das et al. 2012 ). It is a nearby spiral galaxy that has often been classified as a blue dwarf galaxy (Vanzi et al. 2009 ) on account of its bright, star-forming disk and small size. It has a small, stellar disk of diameter 8.3 kpc in the K band but in the B band the disk appears far more extended and has a diameter of 13.7 kpc (Table 1 and Figure 1 ). The inner disk has a very compact bright nucleus that is due to nuclear star clusters (Georgiev Böker 2014 ); such clusters have been observed in many bulgeless galaxies (Walcher et al. 2005 ). The nucleus has a bright, slightly off-center hard X-ray source (Lemons et al. 2015 ) that may be due to an active galactic nucleus (AGN; Desroches Ho 2009 ). The disk is very rich in H i gas and has a flux of S ν = 58.2 Jy km s −1 (Popping Braun 2011 ), which corresponds to a mass of M (H i ) = 4 × 10 9 M ⊙ . The H i spectral line width indicates that the disk is possibly extended. The molecular hydrogen gas has a double-horned structure about the nucleus (Vanzi et al. 2009 ) and has a flux of 2.90 K km s −1 (Böker et al. 2003 ) or 13.92 Jy km s −1 . At a distance of 17.10 Mpc (Tully et al. 2009 ), this corresponds to a molecular gas mass of M (H 2 ) = 4.48 × 10 7 M ⊙ . The molecular gas appears to be centrally concentrated, with a total width of ∼150 to 170 km s −1 and a rotation velocity ∼100 km s −1 (Popping Braun 2011 ). Figure 1. HCT optical images of NGC 4701. Clockwise from the top left are the B-, V-, I -, and R- band images. The dashed ellipse in white is the R 25 radius of the galaxy in the B band and is 108′′. The V -band emission extends out to 1/2 R 25 and the B -band extends to 2/3 R 25 approximately. Table 1 Parameters of NGC 4701 Notes. The parameters are from the NASA Extragalactic Database (NED). a The inclination was calculated from the galaxy major and minor axis ratios in the optical band i.e., inc = Cos −1 (179/216). b Tully Fisher distance (Tully et al. 2009 ). 3. H <sc>i</sc> Observations and Data Analysis 3.1. Observations and Moment Maps The H i observations of NGC 4701 were carried out with the GMRT during 2009 November. The baseband bandwidth used was 8 MHz for the H i 21 cm line observations, giving a velocity resolution of 13.6 km s −1 . Further details on the observations are given in Table 2 . To reduce the data the Astronomical Image Processing System ( AIPS ) software package was used. The flux densities are on the scale of mJy (Baars et al. 1977 ), with flux density


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The authors thank The Pennsylvania State University, NASA Astrobiology Institute (NNA09DA76A), and the Penn State Astrobiology Research Center for their support. Portions of this research were conducted with Advanced CyberInfrastructure computational resources provided by The Institute for CyberScience at The Pennsylvania State University ( http://ics.psu.edu ). Special thanks go to Prof. Eric Ford for directing us to Dimitri Veras’ work on including Galactic tides in Mercury . In addition, we thank the anonymous referee for thorough and helpful comments that contributed to the content and clarity of this work.


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

in the legend. The silicon line is solid, the oxygen line is dashed (quiet Sun adjustment) and dotted–dashed (active region adjustment). The two events above were not associated with Fe xxi emission. However, in the same raster set there is a flare with Fe xxi emission. We picked the non-flare data because the explosive events in these data are more impressive than in the flare. We have also examined the flare discussed by Polito et al. ( 2016 ). The spectrum for exposure 5 and raster 15 in Figure 7 of Polito et al. ( 2016 ) shows dynamical Si iv activity at apparent footpoints of a loop or loops emitting in Fe xxi . One footpoint region has a strong continuum, and visual inspection of the Si iv spectrum reveals just a small downflow extension to the stationary component. The other footpoint shows a fairly symmetric and highly broadened Si iv line. Thus, the nature of explosive events appears to be highly variable from event to event. The events we have discussed also include visual inspection of the C ii and Mg ii lines observed by IRIS , and these lines show strong dynamical effects. So the events seen at Si iv and O iv temperatures also extend to lower temperatures. 4. DISCUSSION AND CONCLUSIONS The IRIS spectra indicate that explosive events in active regions contain plasma at densities near 10 12 cm −3 flowing outwards at speeds on the order of 100 km s −1 . The early Skylab observations butress the high density explanation. The behavior of density with upflow speed in Figure 9 and Figure 13 can be qualitatively explained by an evaporation scenario. In this scenario the evaporation initially occurs in a high density region near 10 12 cm −3 and flows upwards into an expanding flux tube which causes the density to decrease. The speed decreases as the plasma reaches the top of the loop or loop segment. However, the amount of plasma at the loop top builds up in volume, which results in a higher intensity than at the site of evaporation. Therefore, the intensity in the line profile increases toward zero upflow speed. The mystery problem is the high electron densities. This was encountered by Peter et al. ( 2014 ) in explosive events that appear like Ellerman bombs. Peter et al. ( 2014 ) simply found that the O iv line was so weak relative to the Si iv line that a very high density was implied. So he put the event in the photosphere, which was challenged by Judge ( 2015 ) for many reasons. Judge ( 2015 ) correctly pointed out that the O/Si ratio is not an ideal density diagnostic because of its temperature dependence. However, this issue has been addressed extensively above with the Skylab data, and these data seem to make clear that very small O/Si ratios are due to high electron densities, and perhaps not an FIP effect (e.g., Laming 2015 ) or non-ionization equilibrium effect (e.g., Olluri et al. 2013 ; Dudík et al. 2014 ; Martínez-Sykora et al. 2016 ). However, if a non-ionization equilibrium calculation were applied to all the ions


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This project was enabled by significant assistance from a wide variety of sources. Gautam Upadhya, Aviv R. Cukierman, Merle Reinhardt, George Chapman, William Januszewski, and Ken Sembach provided help with the HST observations. We thank Ryan Foley and Yen-Chen Pan for obtaining spectra of two reference stars with SOAR and Peter Challis for taking a few spectra of stars that were not ultimately used here. We thank Ed Nelan, Matt Lallo, Fritz Benedict, and Barbara McArthur for productive discussions about the behavior of the FGS. We also thank Leo Girardi, Alessandro Bressan, and Paola Marigo for the use of and assistance with their Padova isochrone database, Anne Robin for assistance with the Besancon Galaxy Model, Eddie Schlafly and D. Marshall for input on the extinction along the line of sight to these stars, and Nolan Walborn for useful discussions on the classification of hot stars. We thank Richard Anderson for useful discussions. We thank Scott Engle for observations relating to Cepheid period observations and Richard Gray for help with MK classification. We thank Kris Stanek for additional observations from the ASAS. Support for this work was provided by the National Aeronautics and Space Administration (NASA) through programs GO-12879, 13334, 13335, 13344, 13571, 13678, 13686, 13928, 13929, 14062, 14394, 14648, and 14868 from the Space Telescope Science Institute (STScI), which is operated by AURA, Inc., under NASA contract NAS 5-26555. A.V.F.’s group at UC Berkeley is also grateful for financial assistance from NSF grant AST-1211916, the TABASGO Foundation, the Christopher R. Redlich Fund, and the Miller Institute for Basic Research in Science (UC Berkeley). S.C. and A.G.R. gratefully acknowledge support by the Munich Institute for Astro- and Particle Physics (MIAPP) of the DFG cluster of excellence “Origin and Structure of the Universe.” Research at Lick Observatory is partially supported by a generous gift from Google. This research is based primarily on observations with the NASA/ESA Hubble Space Telescope , obtained at STScI, which is operated by AURA, Inc., under NASA contract NAS 5-26555. Some of the data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and NASA; the Observatory was made possible by the generous financial support of the W. M. Keck Foundation. This publication makes use of data products from the Wide-field Infrared Survey Explorer ( WISE ), which is a joint project of the University of California (Los Angeles) and the Jet Propulsion Laboratory/California Institute of Technology, funded by NASA. It has also made use of the SIMBAD database, operated at CDS, Strasbourg, France.


O O O O O O O O O B-Collaboration I-Collaboration I-Collaboration O B-Person I-Person B-Person I-Person B-Person I-Person O B-Person I-Person O O O O O O O O O O O B-Observatory O O O O O O O B-Grant I-Grant O B-Organization I-Organization O O O O O B-Organization I-Organization I-Organization O O O O O B-Grant B-Grant B-Grant O O B-Person O B-Person O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization O B-Grant B-Person O O O O O B-Organization I-Organization B-Person O O O O B-Organization O O B-Grant O O O O O O O O O B-Database I-Database O O O O O B-Organization I-Organization B-Citation I-Citation I-Citation I-Citation O B-Citation O O B-Survey O O O O B-Grant I-Grant I-Grant I-Grant B-Person O O O B-Organization O B-Grant I-Grant I-Grant I-Grant I-Grant O O O O O O O O O O O O B-Archive I-Archive I-Archive I-Archive I-Archive I-Archive I-Archive B-Archive O O O O O O B-Organization I-Organization I-Organization O B-Organization O O B-Organization I-Organization I-Organization I-Organization O O B-Observatory I-Observatory I-Observatory O O O O 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 B-Software I-Software I-Software I-Software B-Software O O O O O O B-Organization I-Organization I-Organization I-Organization B-Organization B-Location O O B-Survey O O O O O B-Organization I-Organization I-Organization I-Organization O B-Organization I-Organization O B-Organization I-Organization I-Organization O O B-Location B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O B-Survey O O O B-URL O B-Survey O O O O B-Collaboration I-Collaboration I-Collaboration O O O O O O B-Collaboration I-Collaboration O O B-Organization I-Organization I-Organization O B-Collaboration I-Collaboration I-Collaboration B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization O B-Collaboration I-Collaboration I-Collaboration O B-Collaboration I-Collaboration I-Collaboration B-Organization I-Organization O B-Organization I-Organization I-Organization I-Organization I-Organization O B-Collaboration I-Collaboration I-Collaboration I-Collaboration I-Collaboration B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization O B-Collaboration I-Collaboration I-Collaboration B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization O B-Organization I-Organization

We would like to thank the members of the Fermi LAT Collaboration – David Thompson, Denis Bastieri, Jeremy Perkins, and Filippo D’Ammando – for a critical review of the manuscript. Part of the Swift observations have been supported by the contract ASI-INAF I/004/11/0. The Metsähovi team acknowledges the support from the Academy of Finland to our observing projects (numbers 212656, 210338, 121148, and others) Y.Y.K. and M.M.L. are partly supported by the Russian Foundation for Basic Research (project 13-02-12103). Y.Y.K. is also supported by the Dynasty Foundation. B.M.P. is supported by the NSF through grant AST-1008882. This research has made use of data from the MOJAVE database that is maintained by the MOJAVE team (Lister et al. 2009 ; 2013 ). The MOJAVE program is supported under NASA Fermi grant NNX12AO87G. J.L.R. acknowledges support from NASA through Fermi Guest Investigator grant NNX13AO79G. This research has made use of data and/or software provided by the High Energy Astrophysics Science Archive Research Center (HEASARC), which is a service of the Astrophysics Science Division at NASA/GSFC and the High Energy Astrophysics Division of the Smithsonian Astrophysical Observatory. 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. This research has made use of the XRT Data Analysis Software (XRTDAS) developed under the responsibility of the ASI Science Data Center (ASDC), Italy. Funding for SDSS-III has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, and the US Department of Energy Office of Science. The SDSS-III web site is http://www.sdss3.org/ . SDSS-III is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS-III Collaboration including the University of Arizona, the Brazilian Participation Group, Brookhaven National Laboratory, Carnegie Mellon University, University of Florida, the French Participation Group, the German Participation Group, Harvard University, the Instituto de Astrofisica de Canarias, the Michigan State/Notre Dame/JINA Participation Group, Johns Hopkins University, Lawrence Berkeley National Laboratory, Max Planck Institute for Astrophysics, Max Planck Institute for Extraterrestrial Physics, New Mexico State University, New York University, Ohio State University, Pennsylvania State University, University of Portsmouth, Princeton University, the Spanish Participation Group, University of Tokyo, University of Utah, Vanderbilt University, University of Virginia, University of Washington, and Yale University.


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Acknowledgements The author wishes to thank Phuc H. Nguyen for his assiduous and comprehensive assistance in carrying out the calculations, and for providing beneficial feedback regarding this work. The helpful and encouraging comments provided by Abraham Loeb, Ed Turner, Steinn Sigurdsson and Lakshminarayanan Mahadevan are acknowledged. The author is also grateful to the referee for an insightful and detailed review of the paper. This work benefited from the support provided by the University of Texas at Austin, Princeton University and Harvard University.


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

dust and PAH flux might be illumination of nearby cloud material by DoAr 21, rather than material associated with the system in a circumbinary disk distribution. Our results agree that heating of ambient local cloud material is a possible origin for the H 2 seen around DoAr 21. 4.4.4. GG Tau A GG Tau A is a subarcsecond triple system in the Taurus–Aurigae association (ensemble average distance of 140 pc; Table 7 ). It is composed of the M0 primary star GG Tau Aa and the nearly equal-mass Ab1+Ab2 binary (White et al. 1999 ; Di Folco et al. 2014 ). GG Tau A is famous for its spectacular and massive circumsystem ring of material that encompasses the three stars. A distribution of dust has been seen near the north of the stars in the scattered light maps of GG Tau A, revealing that material exists at locations that should be dynamically cleared in this complex multiple system (Krist et al. 2002 ; Duchêne et al. 2004 ). The GG Tau system also includes GG Tau Ba and Bb at a ∼10′′ projected separation to the south (White et al. 1999 ). Thus, GG Tau is a very young quintuple-star system. The GG Tau Bb component has a very late spectral type, making it a likely brown dwarf. The v = 1–0 S (1) line emission was measured in GG Tau A by Bary et al. ( 2003 ) with a flux of 6.9 × 10 −15 erg cm −2 s −1 . They interpreted the mission as arising from gas in the inner disks from one or more of the stars. Beck et al. ( 2012 ) presented the H 2 maps from Figure 4 of this study and showed that the extended H 2 emission is strongest from the northeastern region ∼40 au away from the stars. Since the time of that publication, improved maps of the dust and CO gas from ALMA have revealed that the region of brightest H 2 is colocated with the CO streamer connecting the outer circumsystem disk and the inner distribution of dust (Dutrey et al. 2016 ). This H 2 emission may be excited through stellar heating from the young stars, though the 1700 K LTE gas temperature measured from the H 2 line ratios is high for this distance from the stars. Beck et al. ( 2012 ) postulated that the streamers of gas in H 2 could be excited through shocks associated with infalling accreting material in this dynamically complex young triple. 4.4.5. GM Aur GM Aur is a spectral type K5 star at 158.9 pc distance in the Taurus–Aurigae association (Espaillat et al. 2011 ). It is a system in transition from the CTTS phase with a dense inner disk to the more evolved and X-ray-luminous WTTS phase. GM Aur has a ∼35 au cavity in the optically thick dust in the inner disk, though modeling of its SED and strong mass accretion suggest that gas and small particles persist within this cavity region. The hot inner H 2 disk gas was detected in the UV electronic transitions (France et al. 2012 ), with an emission profile showing an origin within the inner disk region. Our high-resolution spectrum presented in Figure 2 reveals the v = 1–0 S (1) H 2 line emission measured in GM Aur. This served as the basis


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The blue line in the middle column is the PSD of the best-fit ARMA model, surrounded by a light blue 68% confidence band. The horizontal dashed line is the Poisson noise level inferred from the data. The vertical dashed line marks the break frequency, corresponding to T break,L from Table 6 , and the width of the gray rectangle symbolizes its standard error. The red line is the Fourier PSD, smoothed with a five-point moving average, to show the relation between the ARMA and Fourier features. The left column displays the ΔBIC scores of the ARMA( p , q ) fits. The right column contains the correlation and partial correlation functions of the fits’ residuals; the dashed lines enclose the 95% confidence region. Figure 17.13. TXS 0506+056, bin = 7 days Results of the ARMA fitting. The blue line in the middle column is the PSD of the best-fit ARMA model, surrounded by a light blue 68% confidence band. The horizontal dashed line is the Poisson noise level inferred from the data. The vertical dashed line marks the break frequency, corresponding to T break,L from Table 6 , and the width of the gray rectangle symbolizes its standard error. The red line is the Fourier PSD, smoothed with a five-point moving average, to show the relation between the ARMA and Fourier features. The left column displays the ΔBIC scores of the ARMA( p , q ) fits. The right column contains the correlation and partial correlation functions of the fits’ residuals; the dashed lines enclose the 95% confidence region. Figure 17.14. TXS 0506+056, bin = 10 days Results of the ARMA fitting. The blue line in the middle column is the PSD of the best-fit ARMA model, surrounded by a light blue 68% confidence band. The horizontal dashed line is the Poisson noise level inferred from the data. The vertical dashed line marks the break frequency, corresponding to T break,L from Table 6 , and the width of the gray rectangle symbolizes its standard error. The red line is the Fourier PSD, smoothed with a five-point moving average, to show the relation between the ARMA and Fourier features. The left column displays the ΔBIC scores of the ARMA( p , q ) fits. The right column contains the correlation and partial correlation functions of the fits’ residuals; the dashed lines enclose the 95% confidence region. Figure 17.15. TXS 0506+056, bin = 14 days Results of the ARMA fitting. The blue line in the middle column is the PSD of the best-fit ARMA model, surrounded by a light blue 68% confidence band. The horizontal dashed line is the Poisson noise level inferred from the data. The vertical dashed line marks the break frequency, corresponding to T break,L from Table 6 , and the width of the gray rectangle symbolizes its standard error. The red line is the Fourier PSD, smoothed with a five-point moving average, to show the relation between the ARMA and Fourier features. The left column displays the ΔBIC scores of the ARMA( p , q ) fits. The right column contains the correlation and partial correlation


O O O O O O O O O O O O O B-Model I-Model B-Citation I-Citation I-Citation I-Citation O B-Model B-Citation I-Citation I-Citation I-Citation O B-Model B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Model B-Citation I-Citation O B-Model B-Citation I-Citation I-Citation I-Citation O B-Model B-Citation I-Citation I-Citation I-Citation O B-Model B-Citation I-Citation I-Citation I-Citation O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O B-Model B-Citation I-Citation I-Citation I-Citation O O B-Model B-Citation I-Citation I-Citation I-Citation 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 B-Model O O O O O O O B-Model I-Model O O B-Model I-Model B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O B-Model I-Model I-Model B-Model O O O O O O O O O O O O O O B-CelestialObjectRegion I-CelestialObjectRegion B-Model 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 B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O B-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 B-Formula I-Formula I-Formula 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 B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation 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 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 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 B-Model O O B-Citation I-Citation 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 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 I-Model B-Formula I-Formula I-Formula I-Formula B-Formula I-Formula I-Formula I-Formula B-Formula I-Formula I-Formula B-Citation I-Citation I-Citation I-Citation O O O

(dark matter + baryonic gas, excluding stars). We show the following simulation projects: Technicolor Dawn (Finlator et al. 2018 ), GIMIC (Crain et al. 2009 ), EAGLE (Crain et al. 2015 ; Schaye et al. 2015 ), CROC (Gnedin 2014 ), CoDa (Ocvirk et al. 2016 ), Illustris (Vogelsberger et al. 2014 ), Renaissance (Barrow et al. 2017 ), the Katz et al. ( 2017 ) simulations, SPHINX (Rosdahl et al. 2018 ), and bluetides (Feng et al. 2016 ). We also show FLARES with the total resimulated high-resolution volume, as well as a vertical line showing the representative volume, given by that of the parent box. There is a strong negative correlation for periodic volumes between the volume that can be simulated and the resolution that can be achieved. The resimulation approach, with appropriate weighting, allows us to extend the volume axis significantly. In this paper, we introduce FLARES, zoom resimulations during the EoR using the eagle model. 2 The eagle project (Crain et al. 2009 ; Schaye et al. 2015 ) is a suite of smoothed particle hydrodynamics (SPH) simulations, calibrated to reproduce the stellar mass function and sizes of galaxies in the local Universe. EAGLE has been shown to be in good agreement with a large number of observables not used in the calibration (e.g. Lagos et al. 2015 ; Trayford et al. 2015 , 2017 ; Bahé et al. 2016 ; Crain et al. 2017 ; Furlong et al. 2017 ). This includes predictions at high redshift: Furlong et al. ( 2015 ) found reasonably good agreement with observationally inferred distribution functions of stellar mass and SFR out to z = 7. Unfortunately, there are very few galaxies in the fiducial EAGLE volume during the EoR. This is particularly the case for the most massive objects, which predominantly reside in protocluster environments, the progenitors of today’s collapsed clusters (Chiang et al. 2017 ; Lovell, Thomas Wilkins 2018 ). FLARES allows us to significantly increase the number of galaxies simulated during the EoR with EAGLE. It also allows us to test the already incredibly successful EAGLE model in a new regime of extreme, high- z environments, whilst still resolving hydrodynamic processes at resolution, and provide predictions for a number of key upcoming observatories. In this, the first FLARES paper, we introduce the resimulation method, our suite of zoom simulations, and present our first predictions for the distribution of galaxies by stellar mass and SFR using the composite approach. This is the first in a series of papers studying the galaxy properties in the FLARES sample; in Paper II we forward-model the full spectrophotometric properties, and predict the UV luminosity function and its high redshift evolution (Vijayan et al. 2020 ). In future papers, we plan to study the passive and starbursting galaxy population in FLARES, as well as the evolution of galaxy sizes and environmental bias. We assume a Planck year 1 cosmology (Ω 0 = 0.307, Ω Λ = 0.693, h = 0.6777, Planck Collaboration I 2014 ) and a


O O O O O O O O O O O O O O O O O O O O O B-Instrument I-Instrument I-Instrument I-Instrument I-Instrument I-Instrument O O O O O O B-Dataset I-Dataset I-Dataset O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 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 B-Instrument O O O O O O O O O O O O O O B-Database I-Database O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O B-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O B-Model 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 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 B-Instrument 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 B-Dataset I-Dataset I-Dataset O O O O O O O O B-Wavelength I-Wavelength O O 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 O O O O O O O O O O O O O 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 B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O B-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O B-Wavelength O B-Wavelength I-Wavelength O O O O O O

Table 1 Parameters of the model atmosphere. The spatial and temporal variability in the cloud cover is derived from observations by MODIS, the Moderate Resolution Imaging Spectroradiometer (for a detailed description of the MODIS data sets, including retrieval algorithms, see King et al. 2004 ; Parkinson Greenstone 2000 ). We describe a cloud by the pressure of its top, p c , its optical thickness, b c , and the cloud particle size distribution and composition. Each cloudy model pixel has a cloud fraction. This is zero for a cloud-free pixel. Even with as many as 100 pixels along the light equator of the model planet, the pixels are much larger than typical horizontal variations in clouds, and they are much larger than MODIS ground pixels. For a mixture of cloud-free and partly and fully cloudy MODIS ground pixels within a model pixel, we computed the locally reflected Stokes vector for a cloud-free and a cloudy model pixel, and took their weighted sum to compute the reflected Stokes vector for the pixel as a whole. In this way, we accounted for the cloud fraction as reported for all cloudy MODIS ground pixels. The mean cloud fraction of our model planet is about 66%. The MODIS database provides a cloud top pressure for all of its pixels, and we computed p c of a cloudy model pixel by taking the average of the cloud top pressures of the MODIS pixels within our model pixel, weighted by their cloud fractions. To limit the number of different atmosphere-surface models, we divided p c for the model pixels into three categories: 500 mbar for 0 ≤ p c 600 mbar, 700 mbar for 600 ≤ p c 800 mbar, and 850 mbar for p c ≥ 800 mbar (see Table 1 ). We computed b c for a cloudymodel pixel by taking the mean of the cloud optical thickness values of the MODIS ground pixels within the model pixel. In particular, we take the mean of the MODIS logarithmic daily mean data set (see Table 2 ). This data set provides the cloud optical thickness for a given MODIS pixel i as log b c i , where b c i is the cloud optical thickness. When we computed the mean b c , we weighted log b c i of each MODIS pixel with its cloudiness fraction. This logarithmic mean as a good approximation for the cloud optical thickness has been proposed by Hubanks et al. (2015) and Oreopoulos et al. (2007) . The wavelength at which a cloud optical thickness is provided in the MODIS data set depends on the surface: b c pertains to 645 nm above a dry surface, to 858 nm above an ocean, and to 1240 nm above snow or ice. We obtain b c at another wavelength by multiplying the value from the data set with the ratio of the cloud particle extinction cross-section at that other wavelength and at the given wavelength. The cloud optical thickness depends somewhat on the wavelength: for a cloud with b c = 10, composed of particles with r eff = 12.5 μ m and v eff = 0.1, the cloud optical thickness, for example, ranges from 9.775 to 10.002, from 350 to 865 nm. The extinction cross-sections of the cloud


O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization B-Person O O O B-Grant O B-Organization I-Organization I-Organization O O O O O O O O O B-Person O O O B-Grant I-Grant I-Grant O B-Grant I-Grant I-Grant O O O O O B-Software O O O O O B-Software O O O B-Citation I-Citation I-Citation I-Citation I-Citation O B-Software B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O B-Software B-Citation I-Citation I-Citation I-Citation O O B-Software B-Citation I-Citation O O O O B-Survey I-Survey I-Survey I-Survey I-Survey B-Survey O O O O O B-Organization I-Organization I-Organization I-Organization O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O O O O B-Survey O O O O O O B-ComputingFacility I-ComputingFacility I-ComputingFacility I-ComputingFacility O O B-Organization I-Organization I-Organization O B-Survey O O O B-URL O B-Survey O O O O B-Collaboration I-Collaboration I-Collaboration O O O O O O B-Collaboration I-Collaboration O O B-Collaboration I-Collaboration I-Collaboration O B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization O B-Collaboration I-Collaboration I-Collaboration O B-Collaboration I-Collaboration I-Collaboration B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization B-Organization I-Organization O B-Collaboration I-Collaboration I-Collaboration B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization I-Organization B-Organization B-Organization I-Organization I-Organization B-Organization B-Location B-Organization I-Organization I-Organization B-Organization B-Location B-Organization I-Organization I-Organization I-Organization B-Organization B-Observatory I-Observatory I-Observatory I-Observatory I-Observatory B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization B-Observatory I-Observatory B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Observatory I-Observatory I-Observatory B-Collaboration I-Collaboration I-Collaboration I-Collaboration B-Organization I-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization O B-Organization I-Organization

ACKNOWLEDGEMENTS This work was supported by Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). PT-I acknowledges funding from ANILLO-ACT-1417 and Pontificia Universidad Católica for hosting her during the creation of this work. NDP acknowledges support by BASAL CATA AFB-170002 and Fondecyt Regular 1191813. This research made use of astropy , 1 a community-developed core python package for Astronomy (Astropy Collaboration et al. 2018 ), numpy (van der Walt, Colbert Varoquaux 2011 ), scipy (Jones et al. 2001 ), and matplotlib (Hunter 2007 ). Funding for the Sloan Digital Sky Survey IV (SDSS-IV) has been provided by the Alfred P. Sloan Foundation, the US 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 web site is www.sdss.org . SDSS-IV 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, the Korean Participation Group, 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.


O O O O O O O O O O O O O O B-Software O O O O B-Observatory I-Observatory I-Observatory O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O O O B-Grant I-Grant I-Grant B-Grant O B-Organization O B-Grant O O B-ComputingFacility I-ComputingFacility B-ComputingFacility O O B-Observatory I-Observatory I-Observatory I-Observatory I-Observatory I-Observatory O O O O O O O O O O O O O O O O B-Grant I-Grant I-Grant I-Grant I-Grant B-Grant O B-Organization O O B-Organization O B-Organization O O O O O O O B-Organization B-Collaboration O O O O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O O O O O B-Grant I-Grant O O O B-Grant O O B-Person I-Person O B-Person I-Person O O O O O O O B-Grant I-Grant

We thank the referee for their comments that helped us to improve the manuscript. PLUTO is developed at the Turin Astronomical Observatory in collaboration with the Department of Physics of Turin University. We acknowledge the “Accordo Quadro INAF-CINECA (2017)” the CINECA Award HP10B1GLGV and the HPC facility (SCAN) of the INAF – Osservatorio Astronomico di Palermo, for the availability of high performance computing resources and support. This work was supported by the Programme National de Physique Stellaire (PNPS) of CNRS/INSU, co-funded by CEA and CNES. This work has been done within the LABEX Plas@par project, and received financial state aid managed by the Agence Nationale de la Recherche (ANR), as part of the programme “Investissements d’avenir” under the reference ANR-11-IDEX-0004-02. The authors (R. B. and C. A.) acknowledge modest financial contribution from the agreement ASI-INAF n.2017-14.H.O.


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The work presented in this paper has been supported by STFC through the grant ST/K000802/1. The authors would like to gratefully acknowledge the advice received from both J. M. Bizau (Blancard et al. 2012 ) and B. McLaughlin (Covington et al. 2011 ) and also for providing their data sets presented in this paper. The authors would finally like to acknowledge that this work has been carried out on the Cray XC40 Hazel Hen machine in Stuttgart, Germany through the grant number 44009 and the PAMOP project.


O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation O B-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O 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 O O O O O O O O O O O O O O O O O O O O O O O O O O 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 O B-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O B-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-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation 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 B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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-Telescope I-Telescope I-Telescope I-Telescope I-Telescope I-Telescope O B-Citation I-Citation I-Citation I-Citation I-Citation O O O B-Wavelength B-Wavelength O B-Wavelength O O O B-Telescope I-Telescope I-Telescope B-Telescope B-Citation I-Citation I-Citation I-Citation O O O O B-Observatory I-Observatory I-Observatory O B-Observatory 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 B-Telescope B-ObservationalTechniques I-ObservationalTechniques I-ObservationalTechniques B-ObservationalTechniques O O O O O O B-Wavelength I-Wavelength O O O O O O O B-CelestialObjectRegion O

which is proposed and numerically simulated in two dimensions (2D), and 3D (Heyvaerts et al. 1977 ; Shibata et al. 1992 ; Yokoyama Shibata 1995 , 1996 ; Shimojo et al. 1996 ; Nishizuka et al. 2008 ; Pariat et al. 2009 ). In this model, the closed magnetic arch emerges into the ambient unipolar field and then reconnection occurs between the unipolar field and one branch of the arch with an opposite polarity to the unipolar field. The other is the blowout model (Moore et al. 2010 , 2013 ) with two magnetic reconnection processes. The first magnetic reconnection, which is similar to that in the standard model, occurs between the emerging magnetic arch and the ambient unipolar field. Then a filament with a large amount of pent-up free energy by shear (or twist) dominates the second magnetic reconnection (Liu et al. 2011a , 2011b ; Moreno-Insertis Galsgaard 2013 ; Hong et al. 2014 ; Lee et al. 2015 ). Recently, Sterling et al. ( 2015 ) suggested that all of the jets in the coronal hole essentially come from mini-filament eruptions. According to the latest review (Raouafi et al. 2016 ), the standard jets are intensively collimated, usually form an inverse-Y shape with a narrow spire, and seldom rotate. However, the blowout jets strongly rotate and posses a relatively broad spire. As suggested by Pariat et al. ( 2010 ), a jet process is always dominated by a synthetic role from magnetic geometrical characteristics of the jet source, such as size, flux distribution, null point position, and asymmetry. Many observations find that jets could appear with similar morphology and outflow, but might possess distinctive magnetic structures in the low coronal source region (Nisticò et al. 2009 ; Zhang et al. 2012 ). In total, a large number of observations and theoretical models basically describe and explain the morphology, dynamical and physical properties of the jets. However, for the limitation of observational capability, there is no appreciable resolution to distinctly resolve the motions of the plasma blobs (Zhang Ji 2014b ) and the related variation of magnetic topological structure inside a jet. Fortunately, benefitting from the extremely high spatial and temporal resolution in special wavelength observations by the Interface Region Imaging Spectrograph ( IRIS ; De Pontieu et al. 2014 ) and all ultraviolet (UV) and EUV wavelengths of the Atmosphere Imaging Assembly (AIA; Lemen et al. 2012 ) on board the Solar Dynamics Observatory ( SDO ; Pesnell et al. 2012 ), a cusp-shaped structure jet was captured with unprecedented detailed observations. The formation and evolution processes of the jet, including the motions of the blobs and topological variation of its skeleton, are described in Section 2 . Section 3 contains a discussion and conclusions. 2. OBSERVATIONS 2.1. Data From 05:51 UT to 06:39 UT on 2014 August 29, IRIS narrow-band slit-jaw images (SJIs; see Figure 1 ) in the 1330 Å channel captured a cusp-shaped jet located at N08W90 (Solar-X: