O O B-Person I-Person B-Person I-Person B-Person I-Person B-Person I-Person I-Person I-Person B-Person I-Person B-Person I-Person O B-Person I-Person O O O O O O B-Person I-Person 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 O O O O B-Fellowship I-Fellowship O B-Organization O B-Grant O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization O O B-Person O O O O B-Organization I-Organization I-Organization I-Organization I-Organization O B-Grant I-Grant O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O O B-Organization I-Organization I-Organization I-Organization O B-Fellowship I-Fellowship I-Fellowship I-Fellowship O O B-Organization O O B-Grant B-Person O O O B-Organization O O B-Grant O B-Organization O O B-Grant O O B-Organization I-Organization O B-Person O O O B-Organization B-Grant I-Grant I-Grant O B-Grant I-Grant I-Grant O O B-Organization I-Organization O B-Organization I-Organization I-Organization I-Organization I-Organization O O B-Grant I-Grant I-Grant I-Grant I-Grant I-Grant O B-Organization I-Organization O O O O O O O O O B-ComputingFacility I-ComputingFacility I-ComputingFacility O B-Grant B-Grant O B-Grant O O O O O O B-Organization I-Organization O O O O O B-Event I-Event I-Event I-Event O O O O O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization O O O O O B-Event I-Event I-Event I-Event I-Event O O O O O O O

We thank Tsang-Keung Chan, Xiangcheng Ma, Daniel Anglés-Alcázar, Freeke van de Voort, Robert Feldmann, Chris Hayward, and Michael Anderson for various constructive suggestions. We thank Romeel Davé for providing details on wind implementation for our simulation comparison section. We thank the anonymous referee for providing suggestions that improved this work. DK was supported by a Hellman Fellowship and NSF grant AST-1412153, and by funds from the University of California San Diego. Support for PFH was provided by the Gordon and Betty Moore Foundation through Grant 776 to the Caltech Moore Center for Theoretical Cosmology and Physics, by the Alfred P. Sloan Foundation through Sloan Research Fellowship BR2014-022, and by NSF through grant AST-1411920. C-AF-G was supported by NSF through grant AST-1412836, by NASA through grant NNX15AB22G, and by Northwestern University funds. EQ was supported by NASA ATP grant 12-APT12-0183, a Simons Investigator award from the Simons Foundation, the David and Lucile Packard Foundation, and the Thomas Alison Schneider Chair in Physics at UC Berkeley. The simulations analysed in this paper were run on XSEDE computational resources (allocations TG-AST120025, TG-AST130039, and TG-AST140023). We would like to thank the Simons Foundation and the participants of the Galactic Super Winds symposium for stimulating discussions. We would also like to thank the Kavli Institute for Theoretical Physics and the participants of the Physics of Star Formation Feedback program for interactions that improved this work.


O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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-Software O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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-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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-ObservationalTechniques O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

Other channels may account for the most carbon-rich early-R stars. 4. Conclusion and Discussion The merger of an HeWD with an RGB star in a CE provides a possible model for the origin of lithium- and carbon-rich stars. By adopting a grid of approximate initial conditions for such mergers informed by previous SPH simulations, we have made one-dimensional mesa calculations of the post-merger evolution of a wide range of possible systems. Using BSPS we have computed the frequency and distribution of HeWD + RGB binary-star systems that are likely to merge. Analysis of the post-merger evolution models show that the final surface abundances depend on the masses of the progenitor HeWDs. The Li-rich giants form from low-mass HeWDs, i.e., ; the C-rich giants form from low-mass HeWDs, i.e., . The pathway to either of these categories is related to the temperature of the helium-core-burning shell and the balance of nuclear products during initial shell burning. Analysis of the distribution of post-merger systems, as given by BSPS and mesa evolution tracks, shows that predictions for HeWD+RGB mergers are consistent with observations of most Li-rich giants in terms of surface effective temperature ( T eff ), surface gravity (log g ), surface luminosity (log L ), surface abundance ( A (Li) and 12 C/ 13 C), and the Galaxy disk space density of . They are also consistent with the properties of some early-R carbon stars, in terms of T eff , log g , C/O, A (Li), 12 C/ 13 C, and a space density of (3.5−5.9) × 10 −7 pc −3 . According to the models, the post-merger objects are helium-core-burning stars, which means that they are all in the red clump stage of evolution, i.e., they are red giants with nondegenerate helium cores. However, only a few Li-rich giants have had their precise evolutionary stage determined by asteroseismology. Those stars that have been analyzed in this way correspond well with our results. Hence, we strongly argue that the Li-rich red clump stars and the majority of early-R carbon stars most likely form following the merger of an HeWD with an RGB star. A few problems still need to be addressed: (i) Post-merger evolution calculations depend on evolution during the CE phase that is determined by the progenitors of the merger, the amount of mass loss during the CE phase, and the structure of the CE. However, our knowledge of CE phase in binary-star evolution is still poor. Future theoretical studies and simulations will improve this deficiency. Also, as the products of post-CE mergers, further observations of Li-rich red clump stars will provide additional data for studies of the CE phase. (ii) Some of the observed Li-rich giants have measured rotation velocities, but we have not calculated rotation speeds for post-merger models immediately following CE ejection. Our model will be improved with more knowledge of angular momentum transport during the merger. (iii) The HeWD+RGB merger model provides a successful explanation for Li-rich red


O O O O O B-Person I-Person O O O O O O O O O O O O O O B-Person O O O O B-Organization I-Organization I-Organization B-Organization O O O O O O O B-Organization I-Organization B-Organization I-Organization I-Organization I-Organization O O B-Observatory I-Observatory B-Grant I-Grant I-Grant B-Person O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O O O B-Grant B-Person O O O B-Person I-Person O O O O O O O O O O O O O O O O B-Organization I-Organization I-Organization B-Organization O B-Telescope O B-URL O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization B-URL O O O O B-Organization O O O O O O O O O O O O O B-Collaboration I-Collaboration I-Collaboration O O O O O O B-Archive I-Archive I-Archive I-Archive O O O O O O B-Software O O O O O O B-Software O B-Citation I-Citation O O B-Software O B-URL O O O O B-Software O O O O B-Citation I-Citation I-Citation O B-Citation O


O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 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 B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O B-Telescope 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 B-Model I-Model 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 O O O O O O O O O O O O O O O O O O O O O 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-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 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 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-CelestialObject I-CelestialObject 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 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 B-Model I-Model 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 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 B-Telescope I-Telescope

high-redshift probe of the first stars. Figure 2. Confronting structure formation theory with observations. Shown is the critical (minimum) DM halo mass required for the runaway collapse of primordial gas versus redshift for different cosmological models (see Fig. 1 ). The three coloured lines represent the critical halo properties for CDM ( blue ) as well as FDM models with ( orange ) and ( green ). The symbols indicate 2σ, 3σ, and 4σ peaks, respectively. The magenta region summarizes estimates for the DM halo mass, hosting UFD galaxies in the Local Group. Complementary to this, the light-grey region delineates the redshift range inferred from the observed EDGES spectral trough in the 21-cm absorption profile (Bowman et al. 2018 ). The dark-grey region shows the epoch of reionization. As is evident, the combined empirical constraints disfavour FDM models with the lightest axion masses. 3.1 Local Group dwarf galaxies The first constraint is the mass limit for the first star-forming haloes, M crit , such that at a given redshift runaway cooling can only occur in sufficiently massive hosts. Observations of UFD galaxies provide non-trivial tests for any model of structure formation, as the model must allow star formation in low-mass host haloes, sufficiently early in cosmic history. Possibly, masses of the UFD progenitors may be as small as at a redshift of z ≈ 10 (Bland-Hawthorn, Sutherland Webster 2015 ). However, observations of individual UFDs in the present-day Universe give relatively uncertain virial masses of the order of (e.g. Wolf et al. 2010 ; Simon et al. 2011 ; Boylan-Kolchin, Bullock Kaplinghat 2012 ), and a recent statistical analysis of local UFDs provides a conservative upper limit of the minimum UFD-hosting halo mass of (Jethwa, Erkal Belokurov 2018 ). We illustrate the plausible range of UFD halo masses in Fig. 2 . Structure formation models represented by curves that lie beneath the upper limit of this region are consistent with the Local Group constraints. In the ΛCDM cosmology, M crit is always below the region constrained by the UFD observations, regardless of overdensity νσ. This is in accordance with the standard picture of hierarchical structure formation. For the FDM model with the lighter axion, , on the other hand, M crit lies above the allowed UFD region for 2σ peaks. In this case, the most frequently occurring haloes would form with masses larger than what is inferred for the UFD hosts. The resulting tension implies that existing UFD observations disfavour the lighter-axion FDM model. Conversely, this tension does not exist in the model with heavier-axion FDM (). Here, values of M crit for reasonable, not too unlikely, σ peaks lie within or below the allowed UFD region. Though it remains unclear whether UFDs alone can rule out FDM entirely, further restrictions for the allowed models are anticipated through observations of lower-mass UFDs with upcoming large-scale surveys, carried out, e.g., with the Large Synoptic


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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 B-Software 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 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 B-Software 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 B-Software O O O O O O O O O B-Wavelength 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 B-Software 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 I-Formula I-Formula 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 B-Software O B-Software 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 B-Software 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-Survey O O O O O O O O O O O O O O O O O O O O O O O O O O

derived from CfA3 in red. 5.3 Comparison of light-curve fitter results To make any cosmological statements based on the results in the previous section is beyond the scope of this paper, as this would require a detailed study and justification of the utilized light-curve fitters and their parameters, among many other considerations. It is interesting and possible, however, to compare results from the two light-curve fitters we employ to check for consistency. As the principal quantity of interest when fitting the light curves of SNe Ia is distance, we will focus our comparison on the derived distance moduli. The left-hand plot in Fig. 12 compares the distance moduli from snoopy and mlcs2k2 after correcting to put the measurements on the same scale (so that relative distance moduli are compared, independent from assumptions about the Hubble constant). This correction consists of adding an offset to the distance moduli from each fitter such that the value of H 0 measured from each set of results yields 65 km s −1 Mpc −1 . We perform this comparison only for spectroscopically normal SNe Ia in our sample for which snoopy finds Δ m 15 1.7 mag and for which z > 0.01. Of course, further restrictions should be placed when selecting a sample for cosmological purposes, but our selection is reasonable for performing a general comparison. We find strong agreement between the two sets of corrected distance moduli – a Kolmogorov–Smirnoff test gives a P -value of 1.000. The median residual is −0.026 mag with a statistical dispersion of 0.135 mag. Figure 12. Comparison of the (scaled) distance modulus and host-galaxy reddening results from both light-curve fitters for the selected subset of our data set. If we were to ensure consistency in choosing the parameters for each light-curve fitter, the residuals would almost certainly decrease. In particular, when fitting with mlcs2k2 , we place an exponentially decaying prior on A V , but no such prior was imposed with snoopy . This difference may well manifest in statistically and systematically different results for host-galaxy reddening and distance moduli between the two fitters. We compare host-galaxy reddening results in the right-hand panel of Fig. 12 , where for mlcs2k2 we have converted to reddening using E ( B − V ) host = A V / R V , with R V = 1.7. The agreement is reasonable, with a median residual of −0.056 mag and statistical uncertainty of 0.055 mag. Furthermore, the facts that the median residual ( snoopy minus mlcs2k2 ) is negative and that the disagreement is most severe for small E ( B − V ) host are consistent with what one might expect given the prior imposed by mlcs2k2 . 6 CONCLUSION In this paper, we present BVRI (along with some unfiltered) light curves of 93 SNe Ia derived from images collected by the LOSS follow-up program primarily over the interval from 2009 to 2018, but with several instances as early as 2005. Careful and consistent observational and processing techniques ensure


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

gravitational instabilities (GI) operating in the outer disc, driving material towards the protostar, and the magneto-rotational instability (MRI) operating in the inner disc region around the young protostar when the conditions are appropriate for a sufficient ionization fraction (Armitage et al. 2001 ; Zhu et al. 2009a , b , 2010a ; Zhu et al. 2010b ; Stamatellos et al. 2011 ; Mercer Stamatellos 2017 ). As the disc increases in mass by accreting infalling gas from the envelope it becomes gravitationally unstable, as suggested by the formation of the spiral structures seen in the quiescent phase snapshots in the left column of Fig. 1 . Thus, angular momentum is redistributed outwards efficiently resulting in inward gas flow. The inner disc is hotter and gravitationally stable such that there is no mechanism available to redistribute angular momentum, and material accumulates around the protostar (∼1 au). As more gas flows into this region, compressive, viscous, and protostellar heating raise the local temperature further. Once a threshold temperature of 1400 K is reached, this region is sufficiently ionized for the MRI to be activated (Zhu et al. 2009a , b , 2010a ; Zhu et al. 2010b ). The MRI increases the viscosity (the effective viscosity parameter becomes α MRI = 0.1; Shakura Sunyaev 1973 ), providing a way to redistribute angular momentum and resulting in rapid gas accretion onto the protostar. During the outburst phase, the accretion luminosity increases dramatically (∼10 3 L ⊙ ), heating the disc and disrupting the spiral structure (outbursting phase snapshots in the left column of Fig. 1 ; see also MacFarlane Stamatellos 2017 ). Once the gas from the inner region has been accreted, the protostar returns to the quiescent phase. The process of quiescent to outbursting phase repeats multiple times during the evolution of the YSO (Stamatellos et al. 2012 ). Outbursts happen every ∼1000 yr initially, whereas at later stages (but still during the Class O/I stage) every ∼10 000 yr (see Stamatellos et al. 2011 , 2012 ). This is similar to what is inferred from observations (e.g. Scholz, Froebrich Wood 2013 ; Hillenbrand Findeisen 2015 ; Fischer, Safron Megeath 2019 ; see also Peña, Naylor Morrell 2019 , for longer outburst time-scale estimates for older, Class I/II, YSOs). It is assumed that in the quiescent phase gas accretes onto the protostar at a rate of (this is a free parameter in our calculation) and the protostellar luminosity is then on the order of ∼1 L ⊙ . As a comparison, at the same time the accretion rate onto the outer disc is on the order of ∼10 −5 −10 −4 M ⊙ yr −1 . During the outburst phase the accretion onto the protostar is significantly enhanced. This model is different than the models of Vorobyov Basu ( 2005 , 2006 , 2010 ). In their models the GIs alone are responsible for the observed outbursts: GIs create clumps in the disc of a young stellar object that eventually fall onto the protostar, resulting in outbursts


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

time variations appear for all radii, with typical amplitude changes in η R / η max of ∼0.2, except for the innermost radial bin. The thick solid grey curve indicates the mean bar half-length variations (black curve from Fig. 5 ), showing a very good agreement with the amplitude fluctuations. Note that as the bar decreases in length, so does its amplitude. Very similar time variations appear for all radii, with typical amplitude changes in η R / η max of ∼0.2, except for the innermost radius considered. The thick solid grey curve in Fig. 7 represents the mean bar half-length variations (black curve from Fig. 5 ), which can be seen to agree very well with the amplitude fluctuations, including the short and long periods. The fluctuations seen in the bar amplitude at fixed radii (Fig. 7 ) are more similar to the bar length time variations than the η max , which can vary with radius (see Fig. A6 ). This can generally be seen for Model2 as well in Fig. 8 . One key difference between the two simulations is the fact that for Model1 all radii peak at nearly the same time, while in Model2, they are delayed with the lowest radius of 3 kpc always peaking last. Such a pattern suggests a spiral arm contribution. Indeed, we established in Section 3.4 that the Model2 bar true length is about 3 kpc; therefore, the region examined in Fig. 8 lies at or outside the true bar, yet in the regime where our three measurement methods detect a bar. The solid grey curve in Fig. 7 shows the bar length time variations, seen to follow the overall trend in η R / η max , in best agreement with the two outermost radii. Figure 8. As Fig. 7 , but for Model2. The solid grey thick curve indicates the mean bar half-length variations (black curve from Fig. 6 ), showing an overall good agreement with the amplitude fluctuations. Since the true bar length is ∼3 kpc, the outermost three radial bins for which η R was estimated correspond to the spiral arms, as evident from the systematic time offset among different curves. 4.4 Bar pattern speed We estimated the instantaneous bar pattern speed using the modified TW method by Sanders et al. ( 2019 ), who applied it to both MW data and N -body simulations. The top left-hand panel of Fig. 9 shows the configuration we used to measure Ω p , over the stellar density of Model1. As done by Sanders et al. ( 2019 ), we assumed a bar angle of 33°, a Galactic latitude range | b | 5°, and a solar Galactocentric distance of R 0 = 8.12 kpc. The rotation is clockwise. Estimates are done in bins of Galactic longitude dl = 2° in the radial range indicated by the two arches centred on the Sun (at distances of 4.12 and 8.12 kpc), which is sitting at ( x, y ) = (8.12, 0). The straight black line over the bar has a half-length of 3.2 kpc, which corresponds to l ∼ 17° for our bar angle. The bar angle is kept the same at each time output. The white circles show the bar time-median CR, 4:1 OLR, and 2:1 OLR at R CR = 3.25, R 4: 1OLR = 4.2, and R 2: 1OLR =


O O O O O O O O O B-Person O B-Person O O O O B-Organization B-Organization O B-Organization B-Location

We thank an anonymous referee for the constructive report. L.F.R. and L.L. acknowledge the support of DGAPA, UNAM, and CONACyT, México.


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

confined the jet to propagate along high-density walls (similar to model B simulations in BTG17 ). Our simulations, performed in both 2D and 3D, follow jets from the compact object to a scale 10 3 larger. These large scale simulations allow us to follow the jet acceleration through conversion of its magnetic energy into kinetic energy. In the context of short GRB jets, as the jet breaks out from the confining medium, it essentially travels through vacuum (or at least very low ambient gas). This is quite advantageous since BTG17 have shown that these type of jets are almost identical in 2D and 3D runs and that they are fairly axisymmetric (see also Bromberg Tchekhovskoy 2016 ). For this reason, we focus our efforts on axisymmetric 2D simulations, which are considerably less computationally expensive and can be better resolved numerically. We mimicked the boundary of the dynamical ejecta by setting the ambient gas density of our previous simulations (see BTG17 model B-2D-vhr for details on jet and ambient gas parameters and numerical resolution) to be essentially zero beyond 100times the size of the compact object as displayed in Fig. 2 , which shows both density and velocity (Lorentz factor) contours. After the jet breaks out from the dynamical ejecta, a rarefaction wave crosses the jet and it spreads sideways and accelerates further (Komissarov etal. 2010 ; Tchekhovskoy etal. 2010 ). For this work, we simulate steady state jets that will maintain the conditions at the central engine constant. This means that the rotation of the black hole and the magnetic field strength is kept constant, so that the jet has a constant power throughout the duration of the simulation. Future simulations will explore short-lived jets. Figure 2. Numerical simulation of a jet that is collimated by and breaks out from the dynamical ejecta. We show 2D cuts of density (left-hand panel) and Lorentz factor (right-hand panel), where r 0 stands for a few times the radius of the central compact object. The jet accelerates as it breaks out from the dynamical ejecta and spread sideways. At large distance the jet turns conical and its lateral structure is fixed. The distance where the radiation from the jet takes place is uncertain; the prompt emission may originate at the transparency radius of the jets or further out, at optically thin conditions (see the next section). The distance at which the jet produces the -ray radiation lies beyond our simulated region. However, we argue that the dynamical range of our current simulations is sufficient for the objectives of our estimates. This is due to the fact that after the phase of lateral expansion and the crossing of the rarefaction wave, the jet becomes approximately conical and its properties freeze out as a function of angle (see Fig. 3 ). Therefore, the lateral structure of the jet, which is the key aspect of our study, is set at this distance. It is no longer necessary to follow the jet beyond this point since its


O O O O O O O O O O O O O O O O O O O B-Wavelength O O O O B-Wavelength O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O B-Software O O O O B-Dataset I-Dataset O O B-Wavelength O O O O O O O O B-CelestialObject O O O B-Wavelength 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 B-Software O B-Software O O O B-Dataset I-Dataset 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 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 B-Wavelength O O B-Wavelength O B-Wavelength I-Wavelength I-Wavelength O O O O O O O O O O B-Wavelength O O O O O O B-Software O B-Software 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 B-Software 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-CelestialObject B-CelestialObject O B-CelestialObject O O O O O O O O B-Wavelength O O O O O B-Software O O O O O O O O O O O O O O B-Wavelength 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 B-Wavelength O O O B-Wavelength O O O O O O O B-Software O O O O O O O B-Wavelength O O O O O O B-Software O O O O O O O O O O O B-Wavelength O O O O O O O O O B-CelestialObject O B-CelestialObject O O O O O O O O O O O O O O O O O O O O O B-Wavelength 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 B-Software 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 B-Software 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

code. We adopt the high- z edition, which includes the modeling in the radio bands, as well as the Lyman absorptions in the rest-frame UV from the intergalactic medium ( da Cunha et al. 2015 ). We plotted the best-fit models in Fig. 6 , along with the photometric measurements, and the fitting results of HYPERZ and those using the infrared templates. Fig. 6. UV-to-radio SEDs for each of our sample SMGs except ALESS66.1 for which the UV-to-NIR photometric measurements are contaminated by a foreground quasar Simpson et al. (2014) . Sources that are identified to host an AGN are marked with an asterisk after the ID. The measurements are plotted as black points and the best-fit models from MAGPHYS , HYPERZ , and the IR templates compiled by Swinbank et al. (2014) are plotted as gray, blue, and red curves, respectively. For clarity, we do not show the uncertainty, however, it is discussed in the text, including the fact that the IR luminosities that were estimated by the two methods are in agreement with each other within the uncertainty. The insets are zoom-ins in the OIR regime from 0.3 to 10 μ m in log–log scale. We find significant differences in higher L IR sources between the best-fit models of MAGPHYS and HYPERZ ; also, in all of these discrepant cases, the HYPERZ modeling provides a better fit with a lower χ 2 . We first compare the infrared luminosities estimated from the SED templates 8 and those from MAGPHYS . We confirm that both values are statistically consistent with each other in all sources. We then turn to A V in which we find significant differences in some sources. As seen in Fig. 6 , ALESS67.1, ALESS75.1, and AS2UDS412.0 appear to have different best-fit models in the UV-to-NIR regime, although the fit from HYPERZ shows better agreement with the data. Interestingly, in these three cases where the A V differ, the values obtained from MAGPHYS are all higher. We note that given the different assumptions of the attenuation curves in these two codes, the A V values from the UV-to-NIR regime should also ideally be deduced from MAGPHYS by turning off the fitting of the MIR-to-radio part. Unfortunately, the public version of MAGPHYS does not support this option. However, the fact that the A V values are in excellent agreement with each other in ALESS17.1 and AS2UDS292.0, which is as expected from a good match shown in Fig. 6 , suggests that the systematic difference between the A V values can be neglected. We also tried to homogenize the two codes by running the HYPERZ fitting that only uses the τ -decay SFHs that are similarly adopted by MAGPHYS , thus definitively removing the bursting SFH in our adopted method for HYPERZ . We find that the output values vary within uncertainties and the conclusions remain unchanged. Since stellar mass is not one of the direct outputs from HYPERZ, we estimated the stellar masses by converting the absolute magnitude, which is one of the outputs from HYPERZ based on some estimates of mass-to-light


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

Acknowledgements It is a pleasure to thank A. Beresnyak, B. Burkhart and A. Schekochihin, as well as the anonymous Referee, for helpful comments and discussion. JS was funded in part by the Gordon and Betty Moore Foundation through Grant GBMF5076 to Lars Bildsten, Eliot Quataert and E. Sterl Phinney. Support for PFH was provided by NASA Astrophysics Theory Grant NNX14AH35G National Science Foundation Collaborative Research Grant #1411920 and CAREER grant #1455342. Numerical calculations were run on Caltech cluster ‘Zwicky’ (NSF MRI award #PHY-0960291) and XSEDE allocation TG-AST130039 supported by the NSF.


O B-Instrument O O O O O O O B-Organization I-Organization I-Organization I-Organization B-Location I-Location B-Organization I-Organization I-Organization I-Organization B-Location O B-Organization I-Organization I-Organization I-Organization B-Location O B-Organization I-Organization I-Organization I-Organization I-Organization B-Location I-Location B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Location I-Location I-Location O B-Organization I-Organization I-Organization I-Organization B-Location I-Location O B-Organization I-Organization I-Organization I-Organization B-Location O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Location O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Location O O O O O O O O B-Location B-Organization B-Location B-Organization B-Location B-Organization B-Location B-Organization B-Location B-Organization O O B-Organization I-Organization I-Organization O O O O O O B-Organization I-Organization I-Organization I-Organization O B-Organization O B-Organization I-Organization I-Organization I-Organization O B-Organization O O B-Mission I-Mission O B-Organization O O O O O O O O O O B-Mission I-Mission O O O O O O O B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization

Acknowledgements OSIRIS was built by a consortium of the Max-Planck- Institut für Sonnensystemforschung, Göttingen, Germany, CISAS University of Padova, Italy, the Laboratoire d’Astrophysique de Marseille, France, the Institutode Astrofísica de Andalucia, CSIC, Granada, Spain,the Research and Scientific Support Department of the European Space Agency, Noordwijk, The Netherlands, the Instituto Nacionalde Técnica Aeroespacial, Madrid, Spain, the Universidad Politéchnica de Madrid, Spain, the Department of Physics and Astronomy of Uppsala University, Sweden, and the Institut für Datentechnik und Kommunikationsnetze der Technischen Universität Braunschweig, Germany. The support of the national funding agencies of Germany (DLR), France (CNES), Italy (ASI), Spain (MEC), Sweden (SNSB) and the ESA Technical Directorate is gratefully acknowledged. We thank the Rosetta Science Ground Segment at ESAC, the Rosetta Mission Operations Centre at ESOC and the Rosetta Project at ESTEC for their outstanding work enabling the science return of the Rosetta Mission. The research was carried out at the Jet Propulsion Laboratory, California Institute of Technology under a contract with the National Aeronautics and Space Administration.


O O O O O O O O O O O B-URL O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O 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 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 B-Model O O B-Formula I-Formula I-Formula I-Formula B-Formula I-Formula I-Formula 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 B-Model I-Model I-Model I-Model B-Model O O B-Model B-Model B-Model O O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula B-Formula I-Formula I-Formula I-Formula I-Formula B-Formula I-Formula I-Formula I-Formula O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O B-Citation I-Citation I-Citation I-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 B-URL O O O O O O O O O O O O O O O O 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 B-Model O O O O O O O O O O O O B-Model O O O O O O O B-Model 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 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 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 B-Model 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 B-Model I-Model I-Model 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 B-Model O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 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 B-ObservationalTechniques O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 B-Wavelength B-Citation I-Citation I-Citation I-Citation O B-Wavelength I-Wavelength I-Wavelength B-Wavelength O O B-Telescope I-Telescope I-Telescope I-Telescope I-Telescope O B-Observatory I-Observatory 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-Instrument O O O O O O O O O O O O O O O O O O O O O B-Survey B-Citation I-Citation I-Citation I-Citation O O O O O B-Wavelength B-Wavelength O O O B-Wavelength I-Wavelength O B-Wavelength I-Wavelength O O O O O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Software B-Software O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O B-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-Instrument O O O O O O O O O O O B-Instrument O O O O O O O

spectrum and 27 have multiple archival spectra. As we are refining our CLAGN candidates by selecting candidates where the archival spectra already show some signs of change, there is the potential to miss CLAGNs where the spectra have changed after the last archival spectra was taken and this will decrease our completeness. Of the AGNs that were not identified by our CLAGN candidate selection methods and have multiple archival spectra, we identified AGNs that appeared to have some small variations in the spectra, however, these variations were not significant enough to require further investigation (i.e. changes in spectral class were 0.1 or less). Thus, while our three candidate selection criteria select many AGNs that are not CLAGNs, our selection criteria are not missing a large number of nearby CLAGNs. 3 SPECTROSCOPIC FOLLOW-UP Once candidates were identified using the colour and flux criteria discussed in Sections 2.2– 2.4 , we inspected the archival spectra of these objects in order to identify potential CLAGNs without obtaining new spectra. It should be noted that we did not follow up candidates where archival spectra from the past two decades showed no variability (irrespective of the selection criteria). We used the Wide Field Spectrograph (WiFeS, Dopita et al. 2010 ) integral field unit (IFU) on the Australian National University’s 2.3-m telescope at Siding Spring to obtain new spectra of our candidates to confirm that they are indeed CLAGN. WiFeS has a field of view of 25 × 38 arcsec 2 , divided into 950 spaxels. The advantage of using an IFU for follow-up observations of candidates is that extraction aperture size can be matched to previous observations (e.g. the 7-arcsec fibre of 6dF, Jones et al. 2009 ). The wavelength coverage is 3800–9200 Å, which spans the H α , H β , and O iii lines at z 0.04, and we expect H α to show the most clear signs of change in CLAGNs. We observed in nod-and-shuffle mode taking at least three frames with 60s on object, 60s on sky, and 10 cycles per frame. This results in 40 min on object, 40 min on sky, and ∼15 min on overheads including telescope nod time, guide star re-acquisition and CCD readout. In total we allow ∼100 min per galaxy. Our observations were taken between 2018 July and 2019 March. We reduced our data with PyWiFeS, Python-based pipeline (Childress et al. 2014 ). We observed 15 CLAGN candidates over multiple observing sessions, the AGNs are presented in Table 4 . Table 4. CLAGN candidates that were observed with WiFeS between 2018 July and 2019 March. a New CLAGN that we have identified. b Known CLAGN. 4 SPECTRAL VARIABILITY AND NEW CLAGNS We next present the spectra of the new CLAGNs that we have identified using the selection criteria mentioned in Sections 2.2 – 2.4 , where we compare archival spectra of the galaxies with spectra taken using WiFeS. We plot archival spectra, where available, with the spectra taken using WiFeS to display the change. Multiplicative scaling has


B-Person 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 B-Person O O O O B-Person I-Person O O O O O O B-CelestialObject O O O O O O O O B-Organization I-Organization I-Organization B-Organization O O B-Grant I-Grant I-Grant I-Grant O O O O O O O B-Grant

J.L. thanks O. Venot, T. Cavalie, S. Guerlet, A. Spiga, and T. Fouchet for helpful discussions. J.L. is also indebted to S. Guerlet for making the radiative data for Saturn available. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 679030/WHIPLASH)


O O O O O O O O O O O O O B-Dataset 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-CelestialObject O O O O O O O B-Dataset I-Dataset O O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O B-Wavelength I-Wavelength I-Wavelength O O O O O O O O O O O O O O B-Tag B-Survey I-Survey I-Survey O O O O O O O O O O B-Dataset I-Dataset O O O O O O O O O O O O O O O O O B-CelestialObject 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 B-Wavelength I-Wavelength O B-Wavelength I-Wavelength I-Wavelength O O O O O O O O O O O O O O O O B-CelestialObjectRegion I-CelestialObjectRegion B-CelestialObjectRegion O B-CelestialObjectRegion O O O O O O O O O O O O O O O O O O O B-CelestialObjectRegion I-CelestialObjectRegion O B-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion O O B-CelestialObject I-CelestialObject I-CelestialObject B-CelestialObject O B-CelestialRegion O O B-CelestialObject I-CelestialObject I-CelestialObject B-CelestialObject O 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 B-CelestialObjectRegion I-CelestialObjectRegion O O O O O O O O O O B-Wavelength O O O O O O B-Dataset I-Dataset O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Dataset I-Dataset O O O 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-Dataset O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

time-series, but all data points available in the original time-series are published in DR2. Consequently, all measurements are shown in the figures displaying Gaia light curves in this paper, and the disregarded measurements are identified by magenta crosses. Fig. 3 Skydistribution in Galactic coordinates of all LPV candidates published in Gaia DR2. Each star is drawn with a purple–red–yellow colour-grading scale according to the median ( G BP ) −median ( G RP e ) colour scale shown on the right of the figure. 3 Overview of the <italic>Gaia</italic> all-sky LPV survey We present in this section an overview of the all-sky Gaia DR2 catalogue of LPV candidates, together with light-curve examples. Validations on catalogue subsets according to distance to the Sun or stellar populations are presented in the next sections. 3.1 Sky distribution overview The sky distribution of all DR2 LPV candidates is shown in Fig. 3 , colour-coded with the G BP − G RP e colours 1 of the stars according to the colour-scale on the right of the figure. The Galactic disc, bulge, and halo are clearly visible, as well as the extra-galactic populations of the Magellanic Clouds (the two concentration areas below the Galactic plane at Galactic longitudes of about 285° for the Large Magellanic Cloud (LMC) and 303° for the Small Magellanic Cloud (SMC)) and of the Sagittarius dwarf galaxy (elongated tail below the Galactic bulge). The reddest LPV candidates (yellowish colour in the figure) are seen to be distributed in the Galactic plane, where dust leads to high extinctions. Fig. 4 Histogram of G time-series durations, in days, of all Gaia DR2 LPV candidates. The dashed blue histogram represents the subset of the catalogue published with periods for the sources. 3.2 Light-curve overview The histogram of the G -band time-series durations of all LPV candidates is shown in Fig. 4 , with the subset of sources with published periods shown by the dashed blue histogram. Only 27 sources have durations shorter than one year, while 90% of the sources have observationsover more than 1.5 yr. The time coverage of the measurements over the observation duration is equally important. To compute the time coverage, we divided the time-series into 20 equally spaced sub-time intervals, and computed the fraction of sub-time intervals that have non-zero measurements. The histogram of the resulting time coverage is shown in Fig. 5 . It shows a distribution of the number of stars with time coverages between 35% and 90% that is about equal. Fig. 5 Histogram of the time coverage (see Sect. 3.2 ), in percentage, of measurements in the cleaned G time-series of all Gaia DR2 LPV candidates (grey bars) and of the subset with published periods (blue bars). Fig. 6 Sky distribution of the G -band time-series durations of each DR2 LPV candidate, according to the colour scale shown on the right of the figure. Time-series with durations shorter than 500 d are plotted in yellow (they are mostly located in 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 B-CelestialObject I-CelestialObject I-CelestialObject 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 B-Wavelength O O O O O O B-Observatory I-Observatory I-Observatory I-Observatory I-Observatory B-Observatory 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 B-CelestialObject I-CelestialObject I-CelestialObject O O O O O B-CelestialObject I-CelestialObject I-CelestialObject O B-CelestialObject I-CelestialObject O O O B-Wavelength 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 O O B-CelestialObject 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 B-Observatory O O O O O O O O B-Observatory O B-Identifier B-Wavelength I-Wavelength B-Identifier B-Wavelength I-Wavelength B-Identifier B-Wavelength I-Wavelength O B-Identifier B-Wavelength I-Wavelength O B-Wavelength 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 O O O O O O O O O O O B-Wavelength O O O B-CelestialObject I-CelestialObject I-CelestialObject I-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 B-Wavelength I-Wavelength B-Wavelength I-Wavelength B-Wavelength I-Wavelength B-Wavelength I-Wavelength B-Wavelength I-Wavelength B-Wavelength I-Wavelength B-Wavelength I-Wavelength O B-Wavelength I-Wavelength B-Wavelength I-Wavelength O O B-Observatory O B-Wavelength I-Wavelength B-Wavelength I-Wavelength O O O O O O B-CelestialObject O O B-CelestialObject 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

and low column densities, which appear to support that the hot core is externally heated. The strong bursting observed in the water masers located in the direction of the HMC in Orion-KL could be caused by the interaction between the explosive outflow and the ambient quiescent gas (Hirota et al. 2011 , 2014 ). In this study, using the tremendous sensitivities, a better uv-plane coverage, and a very broad covering of frequency range at (sub)millimeter wavelengths offered by the recent operational Atacama Large Millimeter/Submillimeter Array observatory (ALMA), we carried out a search for compact and faint continuum sources (in five different continuum bands of ALMA) that are probably associated with (proto)stellar objects and hot molecular gas within the HMC in Orion-KL. We report, in addition to Orion Source I and Orion BN, the detection at submillimeter wavelengths of three new compact continuum sources (ALMA1-3) that are located in the vicinities of the HMC, but not with associated hot molecular gas. Additionally, one of these compact sources seem to be associated with high-mass stars, but it does not account for the internal heating of the HMC. We thus conclude that the hot molecular core in Orion-KL is indeed heated externally, as suggested by many observational works. 2. Observations The observations were carried out with ALMA between 2014 and 2015 as part of the ALMA programs: 2013.1.01034.S (Band 4), 2012.1.00146.S (Band 6), 2013.1.00048.S (Band 8), and 2012.1.00123.S (Bands 7 and 9). The total bandwidth used to estimate the continuum emission in the ALMA observations was more than 2 GHz (see Table 1 ). However, as there are many lines detected in the spectral windows, and there is probably some contamination from very faint lines. In order to search for compact millimeter sources within the hot molecular core in Orion-KL, we constrain the uv-range of the observations (see Table 1 and Figures 1 – 3 ). We chose the uv-range based on a trade-off between removing as much extended emission as possible and keeping enough visibilities to obtain a good map. The resulting synthesized beams are presented in Table 1 . The number of antennas used during the observations varied between 31 and 40 (see Table 1 ). Weather conditions were very good and stable, with an average precipitable water vapor of 6 mm (Band 3), 1 mm (Band 6), 0.3–0.7 mm (Band 7), 0.3 mm (Band 8), and 0.15 mm (Band 9). Figure 1. ALMA continuum band 4 (3.0 mm) contour and color-scale images of the HMC located in Orion-KL. Upper panel: continuum image using the full uv-range from the ALMA observations. The contours start at 15% and go up to 90% in steps of 5% of the intensity peak. The intensity peak is 0.150 Jy Beam −1 . The half-power contour of the synthesized beam of the image is shown in the bottom-left corner. Lower panel: continuum image using only part of the uv-range (>150 kλ ) from the continuum observations. The contours start at 15% and go up to 90% in steps of 5% of


O O O O O O O O O O B-CelestialObject I-CelestialObject O O B-Telescope O O O B-Wavelength O O B-Observatory O B-Telescope O O O O O O O B-Wavelength O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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-Telescope O O B-CelestialObject I-CelestialObject 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 B-Survey I-Survey I-Survey I-Survey I-Survey I-Survey 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-CelestialObject O O O O O B-CelestialObject O O O O O O O O O O O O O O B-Software B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O B-Wavelength O O O O O O O O O O O O O O O O O O O O O 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 B-Citation I-Citation I-Citation I-Citation O O O O B-CelestialObject I-CelestialObject O O O O O O B-Software B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength 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 B-Telescope B-Wavelength B-Wavelength I-Wavelength O B-Observatory B-Wavelength B-Wavelength I-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 B-Formula I-Formula I-Formula I-Formula I-Formula O O B-Telescope O O B-Wavelength O O O

manuscript, we report on the results of the monitoring of MAXI J1631-472 with the MeerKAT interferometer, complemented with X-ray data from Swift and MAXI . We show the evolution of the radio and X-ray emission throughout its outburst and provide a physical interpretation of the data set. We also compare the behaviour observed with other known outbursting BH systems. The paper is structured as follows: in Section 2 , we describe the observations and details of the data reduction. In Section 3 , we present the results of the two wavebands and highlight some of the interesting behaviour. In Section 4 , we summarize our conclusions. 2 OBSERVATIONS 2.1 MeerKAT The MeerKAT monitoring of MAXI J1631-472 was performed weekly, with the observations carried out at a central frequency of 1.28 GHz and bandwidth of 856 MHz. These observations were taken as part of the ThunderKAT Large Survey Programme on MeerKAT (Fender et al. 2016 ). Each observation consists of a 15-min scan of the target, and a 2-min scan of the phase calibrator, in this case J1726-5529. The primary calibrator used was J1939-6342, which was observed at the start of each observation for 5 min. We used casa (McMullin et al. 2007 ) to perform the data reduction. We performed flagging of radio frequency interference, where we removed the first and last 150 channels (channel width ∼ 209 kHz) of the band. The autoflagging algorithms, rflag and tfcrop , were used for subsequent flagging. We then performed calibration, where the flux density on the primary calibrator was set using the known model. The phase-only and antenna-based delay corrections on the primary calibrator were then solved for, then the bandpass corrections for the primary were then applied. We solved for the complex gains on the primary and secondary, then proceeded to scale the gain corrections from the primary to the secondary and target source. Finally, the imaging was performed using wsclean (Offringa et al. 2014 ). Flux densities for MAXI J1631-472 were extracted from the images using pybdsf (Mohan Rafferty 2015 ); these are presented in Table 1 . We were able to extract an in-band spectral index (α, with the flux density S ν scaling with frequency ν as S ν ∝ ν α ) at the four brightest epochs using a fit to eight uniformly spaced channels across the 856 MHz bandpass. To determine the spectral index, we performed a least-squares fit using the scipy and curve-fit module and function, respectively, in python to calculate the slope and its associated error bar. The results from these fits are presented in Table 2 and indicate that the source was optically thin during the times of strongest radio flux density. Table 1. MeerKAT radio (1.28 GHz) and Swift X-ray (1–10 keV) fluxes of MAXI J1631-472. The spectral states of each of the observations are indicated in the final column: Soft (S), intermediate (I) and Hard (H). Table 2. Spectral indices during the strongest radio flux: S ν ∝ ν α . 2.2 MAXI We used X-ray data from the


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

are from MERLIN 5 GHz observations of the radio jet (Gallimore et al. 2004 ); the MERLIN beam is 4.2 pc FWHM. Upper right: spectral map from a simulation of a bipolar outflow with the axis tilted 5° from the plane of the sky and rotated to PA 33° (see the text for details). Colors are as for the left panel. The outflow axis of ionized gas traced by optical emission lines in the narrow-line region is inclined 5° out of the plane of the sky (Crenshaw Kraemer 2000 ), and we assume the same for the CO outflow. Can such a small inclination produce the red–blue spatial separation observed in CO? To test this possibility we conducted a numerical simulation of a bipolar outflow. We employ a truncated cone geometry with a disk base diameter of 1 pc (comparable to the H 2 O maser disk), 4.4 pc total bicone height (based on the spread of CO features in Figure 2 ), and half-opening angle of 30°. To model the outflow, we randomly placed a total of 10 4 clumps inside the cone. Clumps were evenly distributed in cylindrical radius ρ (i.e., radius projected onto the disk plane) and distance along the polar axis. The direction of motion for a clump is vertical for clumps directly above and below the disk (i.e., clumps with ρ ≤ 0.5 pc) and radial from the edge of the disk for clumps with ρ > 0.5 pc. We further assume uniform acceleration from 30 km s −1 at the molecular disk to 800 km s −1 at the cone height; these values were selected from interactive trials to give a reasonable match to the observations. Finally, all clumps are equally luminous point sources of CO emission, added as beam-shaped, two-dimensional Gaussians to the planes of a simulated data cube. The cone was then inclined by 5°, and we repeated the cube analyses on the simulated data. To simulate the effects of measurement uncertainty, each measured peak position was displaced randomly, assuming 0.5 pc errors, comparable to the relative, observed position uncertainties. The simulation results shown in the right panel of Figure 2 broadly reproduce a parsec-scale asymmetry of redshifted and blueshifted peaks similar to that observed (left panel). This simple simulation was not meant to replicate any physical model or explain every aspect of the data; in particular, the systemic-velocity emission is concentrated to the east, at odds with the random distribution we use. Our simulation is only meant to demonstrate that the small 5° tilt detected in narrow-line observations is sufficient to produce the red–blue asymmetry of the excited CO emission. In addition to the outflow component described above, we also find evidence for rotation consistent with the compact H 2 O maser disk. Figure 3 shows the position–velocity ( p – v ) diagram constructed by slicing the CO spectral line cube along the axis tracing the extended systemic emission. Surface brightnesses were averaged within the three-pixel extraction width (green dashed lines in Figure 1 ). The data were smoothed using a Savitzky–Golay


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

ACKNOWLEDGEMENTS We thank Prof. W. A. Coles and the anonymous referee for very helpful discussions on the interpretation of curvature variation. This work was supported by the National Natural Science Foundation of China (U15311243), the National Basic Research Program of China and the 973 Program (2015CB857101, XDB23010200, 11690024, 11373011, 11303093, U1431113, 11178001 and 11573008). KJL is supported by the Max-Planck Partner Group.


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

but not part of the interacting pair (UGC 10549, z = 0.009, 50 kpc projected separation). The integrated spectrum shows a somewhat complex profile, with the velocity of the peak emission at ≳50 km s −1 lower velocity than the redshifts of the two components of dm1647+21. This peak corresponds to the redshift of UGC 10549, suggesting a substantial amount of the single-dish H i flux is associated with that galaxy. In support of this interpretation of the single-dish profile, follow-up interferometric observations with the Very Large Array (VLA) reveal a clumpy H i distribution in dm1647+21 and emission associated with UGC 10549 (S. Stierwalt et al. 2017, in preparation). Unfortunately, the VLA observations (taken in the B-array) do not recover the total single-dish H i flux, so we cannot reliably separate the single-dish H i mass into contributions from dm1647+21 and UGC 10549. Considering the uncertain distribution of the H i mass, the single-dish measurement implies an upper limit to the gas depletion time of 2 Gyr when considering only the SFR of dm1647+21. The true gas depletion time for dm1647+21 is likely shorter than this estimate. 3.3. ISM Properties We use the line images created from the MUSE data to construct optical line ratio maps, based on classic optical diagnostic plots (e.g., Baldwin et al. 1981 ; Veilleux Osterbrock 1987 ; Kewley et al. 2006 ). Maps of [O iii ]/H β , [N ii ]/H α , and [S ii ]/H α are shown in Figure 2 . The system-integrated values for these ratios are: log 10 ([O iii ]/H β ) = 0.51, log 10 ([N ii ]/H α ) = −1.8, and log 10 ([S ii ]/H α ) = −1.0. In Figure 3 , we show the line diagnostic diagrams with the distribution of values from Figure 2 and the source separation lines from Kewley et al. ( 2006 ). The line ratios in the ratio maps and diagnostic diagrams are all consistent with excitation from star formation, and we see no evidence for LINER-like or Seyfert emission. Figure 2. Optical line ratio images. First row, from left to right: [O iii ]/H β , [N ii ]/H α , [S ii ]/H α . Second row, from left to right: A H α and [S ii ] 6718/[S ii ] 6732. The ratio maps were all masked to the fainter of the two lines (Figure 1 ). No extinction corrections have been applied. Figure 3. Optical line diagnostic diagrams based on the narrow-band images in Figure 2 . Left: [O iii ]/H β vs. [N ii ]/H α . Right: [O iii ]/H β vs. [S ii ]/H α . The colored contours and small points show the distribution of values for individual 02 × 02 spaxels in the data cube; the number in the bottom left gives the number of spaxels shown in each panel. The plotted spaxels are those with a ≥5 σ detection in [N ii ] 6585 (left) or [S ii ] 6718 + 6732 (right). The cyan crosses mark the locations of the three brightest clumps identified from the H α map (Section 3.2 , 15 diameter apertures). The colored lines are the Kewley et al. ( 2006 ) separations between star-forming galaxies, Seyferts, and LINERs. The line ratios are consistent with


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

events for both the pn and MOS. The events detected in the two MOS cameras were combined into a single data set, and we used averaged response files. Since with the ML analysis it is possible to derive an accurate estimate of the background at the source position, it was not necessary to remove time intervals of high background. We applied the ML in a circular region positioned to avoid the gaps between the CCD chips (radius of 60, center at R.A. = 11 h 54 m 232, decl. = −62°49′47′′). For the spectral extraction we fixed the source position at the coordinates found by the ML in the pn+MOS image in the 0.4–2 keV range (R.A. = 11 h 54 m 204, decl. = −62°50′044). This position is consistent with that found with the SAS pipeline. In the energy range 0.4–2 keV the source was detected with 113 ± 21 counts (pn) and 66 ± 15 counts (MOS), which correspond to a total count rate of (3.4 ± 0.5) × 10 −3 count s −1 . The energy bins for the spectral analysis were chosen from the requirement to have a signal-to-noise ratio greater than 2.5 σ in each spectral channel. This resulted in four energy bins for the pn and three for the MOS. Below 0.4 keV and above 2 keV, the source detection was below our significance threshold; therefore we derived upper limits on the source counts in these energy bins. 3. Possible Optical Counterparts In the Gaia database there are no stars closer than 4′′ to the corrected X-ray position; see Figure 1 . The closest object, at 406, is Gaia DR 2 5334588220496359424 which has g = 17.48. A slightly brighter star, Gaia DR2 5334588151811060992 with g = 14.15, is located at 429. It has B = 16.4, I = 13.11, J = 11.937, and K = 10.951, while the fainter source has B = 19.6, I = 16.08, J = 14.07, and K = 12.86 (Epchtein et al. 1999 ). Based on the color differences I − J and J − K , we identify the brighter star as a main sequence star of spectral type K5 and the fainter one as an M5 star. We fitted the spectra of our X-ray source with thermal plasma models ( apec by Smith et al. 2001 ; mekal by Mewe et al. 1985 ), as expected in the case of coronal emission from normal stars. Acceptable fits could be obtained with temperatures in the range kT = 0.23–0.26 keV, absorption N H ∼ 10 22 cm −2 , and flux ∼3 × 10 −15 erg cm −2 s −1 . The resulting X-ray-to-optical flux ratios (Agüeros et al. 2009 ) were −3.34 and −2.6 for the K and M star, respectively. These values are compatible with X-ray emission from late-type stars and therefore we cannot exclude these objects as potential counterparts of the X-ray source based on spectral and/or flux arguments. However, we note that both stars are outside the 3 σ confidence level error circle of the X-ray source and therefore we consider that PSR J1154–6250 is much more likely responsible for the detected X-ray emission. 4. Results The results of the spectral analysis obtained with the two methods are summarized in Table 3 . The absorption column density was poorly constrained due to the small


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

for such an effect. We point out that these X-ray reprocessing models cannot simultaneously explain several other aspects of AGN UV/optical variability, including the timescale dependent color variations (i.e., the lamp-post SSD can explain the variable spectra, but cannot account for the fact that the color variations are timescale dependent; see, e.g., Zhu et al. ( 2018 ) and the anti-correlations between variability amplitude and L (e.g., MacLeod et al. 2010 ; Sun et al. 2018b ). Below, we discuss the alternative disk-corona magnetic coupling scenario (Sun et al. 2020a ), which has shown to be successful in reproducing the color variations and the dependences of the variability amplitude upon L (Sun et al. 2020b ), to understand our results in Figure 1 . 3.2. Implications for the Magnetohydrodynamic Accretion Physics Theoretically speaking, disk temperatures ( T ) should vary in response to the time-dependent magnetohydrodynamic (MHD) turbulent heating with a response on the thermal timescale ( τ TH ). For an SSD, , where α , G , and R are the dimensionless viscosity parameter, the gravitational constant, and the distance to the central black hole, respectively. Therefore, the short-wavelength emission, which is produced by the inner hotter plasma, has a smaller response thermal timescale than the long-wavelength emission. The differences in the response thermal timescale would add an additional inter-band time lag ( τ add ), beyond the light-travel time lags. On short timescales ( t dur ), the observed UV/optical variations are mainly produced in the similar small- R regions with τ TH ≤ t dur as the gas in these regions can vary its temperature significantly, and τ add is small and negligible (and vice versa). For an SSD, at the characteristic radius R λ (with k B T ( R λ ) = hc / λ , where k B and h are the Boltzmann and Planck constants, respectively; and ), τ TH ( R λ ) scales as α −1 L 0.5 λ 2 . Therefore, τ add would only be prominent for AGNs with small L (i.e., short τ TH ( R λ )) or large t dur . Below, we consider a specific thermal-fluctuation model to qualitatively reproduce the observed result. In earlier work, we proposed the corona-heated accretion-disk reprocessing model (hereafter the CHAR model) by assuming the accretion disk and the extremely compact X-ray corona are magnetically coupled (Sun et al. 2020a ). Magnetic fluctuations in the corona can alter the disk surface magnetic field, drive variations in the disk MHD turbulent dissipation, and eventually induce coherent multi-band variations. We have predicted that τ dif increases with decreasing L for sources with similar monitoring durations (see Figures 8 and 16 of Sun et al. 2020a ). The first two model parameters, M BH and , are fixed according to the observational constraints. The only free parameter, α , might be 0.1–0.4 according to studies of the outbursts of dwarf nova or soft X-ray transients (e.g., King et al. 2007 ). We fix 10 10 Note that the CHAR model


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

4 . The two small circles in the NUV spectral window mark the downflow components in the Mg ii h and k lines. Figure 4. Average IRIS spectra at specific locations of two slits as marked in Figures 2 and 3 . The black lines represent the spectra of the typical plage region, whereas the green lines represent the spectra of a typical umbral region (marked on the right side of each panel of Figure 2 ). The red and blue lines are the average spectra of two regions where supersonic downflows are observed. These two regions are marked at the right side of each panel of Figures 2 and 3 , respectively. The red spectra show a downflow only in TR lines, whereas the blue spectra show a downflow in TR lines as well as in the chromospheric C ii and Mg ii h and k lines. Two arrows in the NUV spectral window mark the downflow components seen in the Mg ii h and k lines (spectra shown in blue). For the identification of different lines, we refer to Tian ( 2017 ). 3.2. Detection of Supersonic Downflows and Multi-Gaussian Fitting to Their Spectra To derive spectroscopic parameters of the supersonic downflows, we have selected a small spectral window of 1399.31–1403.89 Å, which contains the O iv 1400/1401 Å doublet and Si iv 1403 Å spectral lines. The primary reason for selecting this wavelength range is that Si iv 1403 Å is one of the strongest TR lines in the IRIS spectral range. Also, the O iv 1400/1401 Å doublet lines are useful to determine the electron density of the TR plasma. Figure 5 presents some examples of the spectra in the selected window. A total of six isolated components corresponding to the three spectral lines O iv 1400 Å, O iv 1401 Å, and Si iv 1403 Å and their satellite lines (due to supersonic downflows) can be seen at some locations. To increase the signal-to-noise ratio), we have made a three-point running smoothing along the wavelength and also along the slit dimensions. Figure 5. IRIS spectra containing two O iv lines and one Si iv line acquired along the vertical solid lines marked in Figure 1 . The spectral line profiles at the location indicated by the dashed line (also shown with the red dots in Figure 1 ) of each left panel are shown in the corresponding right panel. A six-component Gaussian fit to the spectra of the regular and downflow components of the O iv 1400/1401 Å and Si iv 1403 Å lines is shown as the overplotted blue line in each right panel. The fitting parameters (i—peak intensity, v—Doppler shift, w—line width) are also printed. The spectra within the red square box contain the Si iv line and its downflow component, which are used for the initial detection of the supersonic downflows (see the text for details). The detection of supersonic downflows is sometimes difficult, as the signal within sunspots is very weak (though it also depends on the exposure, binning of the spectra, etc.). Also, the TR is very dynamic and often shows broad line profiles due to different activities. To ensure that we primarily detect


O O O O 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 B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O B-Wavelength O O O O O O B-Formula I-Formula I-Formula B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O B-Formula I-Formula I-Formula 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 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 B-CelestialObjectRegion I-CelestialObjectRegion 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 B-Formula I-Formula I-Formula 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-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 B-Wavelength O O B-Formula I-Formula I-Formula O B-Telescope O O O O O O B-CelestialObject O O O O O O O O O O O O O O B-Formula I-Formula I-Formula B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation O O O O O O O B-Wavelength O B-Wavelength O O O O O O O O O O O B-Survey I-Survey O B-Formula I-Formula I-Formula O O B-Wavelength B-Instrument O O O O O B-Wavelength O B-Instrument B-Wavelength O O B-Wavelength I-Wavelength B-Wavelength O O O O B-Wavelength 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 B-Survey O O O O O O O B-Formula I-Formula I-Formula O O O O

allows for the simultaneous determination of Z g and Z ⋆ , tracing the ratio of oxygen to iron (O/Fe) in young stars and the surrounding ISM (Steidel et al. 2016 ). The O/Fe ratio is of interest because it is a sensitive probe of the star formation and chemical enrichment history of galaxies. Typical O/Fe ratios at high redshift are expected to be enhanced relative to the solar value due to the fact that the element abundance ratios in relatively young star-forming systems will be dominated by core-collapse supernova (CCSNe) yields (Maiolino Mannucci 2019 ). Indeed, this result has already been reported in the literature. Based on a simultaneous rest-frame FUV+optical analysis of 30 star-forming galaxies at z ≃ 2.4, Steidel et al. ( 2016 ) found O/Fe ≈ 4−5 × O/Fe ⊙ . Similar levels of O/Fe-enhancement have been reported for individual galaxies at z ≃ 2.3 in more recent studies (Topping et al. 2020a , b ). The observed O/Fe-enhancement (also referred to as α-enhancement) has a number of important implications. First, it places robust constraints on the typical star-formation histories at early cosmic epochs, confirming results from previous photometric analyses that the stellar populations at high redshift are typically 1 Gyr old (Reddy et al. 2012 ). Secondly, a deficit of Fe relative to O will mean that the stellar ionizing spectrum of typical high-redshift galaxies is harder at fixed oxygen abundance compared to galaxies in the local Universe. This relative hardening of the ionizing continuum at fixed O/H offers a natural explanation for the observed offset of z > 2 star-forming galaxies relative to z ≃ 0 galaxies in the common line ratio diagrams (e.g. the BPT diagram; Topping et al. 2020a ; Runco et al. 2021 ). Non-solar α/Fe ratios will also force us to re-think current stellar population techniques when applied to high-redshift galaxies. Almost universally, current stellar population synthesis models assume solar abundance ratios; accurate analyses of FUV-optical spectra at z > 6 with JWST will require new models allowing for non-solar abundance ratios. In this paper, we expand upon a number of previous works at z ≃ 2.5 (Steidel et al. 2016 ; Topping et al. 2020a , b ) and present a simultaneous analysis of FUV and optical spectra for a sample of 33 star-forming galaxies drawn from the VANDELS survey at z ≃ 3.4. Combining ultra-deep optical VIMOS/VANDELS spectroscopic observations (tracing the rest-frame FUV) with MOSFIRE H - and K -band near-IR follow-up (tracing the rest-frame optical), our analysis provides the first investigation of Z g and Z ⋆ for galaxies at z > 3, and we present the first estimates of O/Fe at these redshifts. In addition, we present both the stellar and gas-phase MZRs for our sample, tracing O/Fe as a function of stellar mass. The structure of this paper is as follows. In Section 2 , we discuss our combined VANDELS+MOSFIRE spectroscopic data set and describe our final z ≃ 3.4 galaxy sample (referred to


O O B-Person I-Person I-Person O O O O O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Grant O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O O B-Grant B-Grant B-Grant O B-Grant O O B-Organization I-Organization I-Organization I-Organization I-Organization O O B-Grant O O B-Organization O B-Grant O B-Person I-Person O O O O O O B-Mission O O O O B-Person I-Person I-Person O B-Person I-Person I-Person O O O B-Organization B-Person I-Person I-Person B-Person I-Person O B-Person I-Person O O O B-Instrument O O B-Person I-Person O B-Person I-Person I-Person O O O B-Telescope O O O O B-Mission O B-Mission O O B-Organization B-Database O O O O

We thank J. T. Gosling for many helpful discussions. This work is supported by the Science and Technology Development Fund of Macao SAR (080/2012/A3), the National Natural Science Foundation of China (NSFC) under grants 41204123, 41374174, 41231068, and 41331070, and the Science Foundation of Jiangxi Province under grant 20144BAB2110005. We acknowledge NASA contract NAS5-02099 and V. Angelopoulos for use of data from the THEMIS Mission. Specifically, we thank C. W. Carlson and J. P. McFadden for use of ESA, K. H. Glassmeier, U. Auster, and W. Baumjohann for use of FGM data, and D. Larson and R. P. Lin for use of SST data. We also thank ACE and Wind teams and NASA CDAWeb for providing the data.


O O O O O O B-Person I-Person B-Person I-Person B-Person I-Person B-Person I-Person B-Person I-Person B-Person I-Person B-Person I-Person B-Person I-Person B-Person I-Person B-Person I-Person B-Person I-Person B-Person I-Person O O O O O O O B-Organization O B-Event I-Event I-Event B-Organization O O O O B-Organization I-Organization I-Organization O O O B-Grant I-Grant B-Person O O O B-Grant I-Grant I-Grant O B-Grant B-Person O O O B-Grant I-Grant I-Grant

ACKNOWLEDGEMENTS We thank useful discussions with Phillip Busch, Neal Dalal, Benedikt Diemer, Bhuvnesh Jain, Andrey Kravtsov, Yen-ting Lin, Hironao Miyatake, Ryoma Murata, Masamune Oguri, Masahiro Takada, Simon White, Ying Zu, and the organizers and participants of the KITP program: The Galaxy–Halo Connection. KITP is supported by the National Science Foundation under Grant No. NSF PHY17-48958. TS is supported by Kakenhi grants 15H05893 and 15K21733. SM is supported by Kakenhi grant 16H01089.


O O O O B-ComputingFacility I-ComputingFacility I-ComputingFacility I-ComputingFacility O B-Organization I-Organization O O O B-Organization I-Organization I-Organization I-Organization O O O O B-Organization B-ComputingFacility I-ComputingFacility I-ComputingFacility O B-URL O O O O O O B-Organization B-ComputingFacility I-ComputingFacility O O B-Grant B-Organization O O B-Grant O B-Organization B-Grant I-Grant I-Grant I-Grant O B-Organization I-Organization B-ComputingFacility O O O O B-ComputingFacility I-ComputingFacility O O O B-Organization O O O O O B-ComputingFacility I-ComputingFacility I-ComputingFacility I-ComputingFacility I-ComputingFacility I-ComputingFacility I-ComputingFacility O O O O O O O B-Organization I-Organization I-Organization O O B-Location I-Location B-Grant I-Grant I-Grant B-Grant O O B-Grant O O B-Location B-Organization O O B-Grant O B-Grant O O O B-Organization I-Organization I-Organization I-Organization B-Grant I-Grant I-Grant B-Person O O B-Fellowship I-Fellowship I-Fellowship I-Fellowship I-Fellowship

This work used the DiRAC Data Centric system at Durham University, operated by the Institute for Computational Cosmology on behalf of the STFC DiRAC HPC Facility ( www.dirac.ac.uk ). This equipment was funded by BIS National E-infrastructure capital grant ST/K00042X/1, STFC capital grant ST/H008519/1, and STFC DiRAC Operations grant ST/K003267/1 and Durham University. DiRAC is part of the National E-Infrastructure. We also acknowledge PRACE for access to the resource Curie at Trés Grand Centre de Calcul. This work received financial support from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013)/ERC Grant agreement 278594-GasAroundGalaxies, from the UK STFC (grant numbers ST/F001166/1 and ST/I000976/1), and from the Belgian Science Policy Office ([AP P7/08 CHARM]). RAC is a Royal Society University Research Fellow.


O O O O O O O O O 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 B-Instrument 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 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 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 O B-Wavelength I-Wavelength O O O B-Wavelength I-Wavelength O O B-Wavelength I-Wavelength O O O O B-Wavelength I-Wavelength B-Wavelength I-Wavelength O B-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Database I-Database I-Database I-Database B-Database 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 O O O O 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

listed in Cols. 2 and 3, respectively. Column 4 shows the isotopic ratio, while Col. 5 gives the references for the different elements. Table 2 Elemental abundances for individual lines in the solar spectrum. Notes. Columns 26 list the single abundances for the different instruments and resolutions. Columns 7 and 8 show the median abundance values for MIKE spectra for the different observation runs and the one dispersion, respectively. The mean abundances are used as solar abundance for MIKE spectra observed in the run with (see Table 1 in Bensby et al. 2014 ) since no solar spectra is available in this setting. Col. 9 lists the solar abundances values from Asplund et al. (2009) . 2.2. Spectral line synthesis The spectral lines from the heavy neutron-capture elements are usually located in the blue regions of the visible spectrum. The blue region is very crowded with spectral lines and is especially so for metal-rich disk stars, meaning that blends from other species are frequent. The crowdedness of the blue spectral regions also makes the placement of the continuum difficult. In addition, heavy elements usually consist of several isotopes, and their spectral lines can be affected by hyperfine splitting (hfs). Therefore, to determine abundances from these lines, one has to use spectral line synthesis in order to accurately account for wavelength shifts of the different isotopes, hyperfine components, and other blending features. Table 1 lists the spectral lines that we use in this study. It shows the analyzed lines with the isotopic ratios of the elements, ionisation stages, wavelengths, and excitation potential, along with reference work where these details were gathered. For Sm and Nd, which suffer in large part from isotopic shifts and also hfs, we use data from Roederer et al. (2008) , for La we used hfs-only components from Ivans et al. (2006) since La has only one naturally-occurring isotope, and for Eu we used shift correction for isotopic and hfs substructures from Lawler et al. (2001) . However, some of the lines of the elements affected by hfs are treated as single lines because the wavelength splitting is small enough to be ignored. In our linelists the lines treated as single lines are La ii at 4748 Å, Nd ii at 5130 Å, and at 5319 Å, and Sm ii at 4523 Å, 4577 Å, and 4669 Å. All lines from Sr ii , Zr ii, and Ce ii lines are treated as single lines since there is no information available on their hyperfine structure and isotopic shifts or because they do not suffer from any of these problems. Atomic data for blending lines and other nearby lines were taken from the compilation available in the Vienna Atomic Line Database (VALD, Piskunov et al. 1995 ; Ryabchikova et al. 1997 ; Kupka et al. 1999 , 2000 ). The complete linelists with hyperfine components can be found in Appendix A . 2.3. Abundance determination The methodology for abundance determination is the same as in Battistini Bensby (2015) where we analyzed Sc, V, Mn, and Co for