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

Previous studies argued that some fraction of PNe were shaped by brown dwarf or planet companions (e.g. Soker 1996 and De Marco Soker 2011 ). The rest were shaped by stellar companions. Under the assumed low mass-loss rate, AGB stars reach much larger radii, in particular, relative to their maximum radius on the RGB. This leaves a relatively large range of initial planetary orbital separations for planets to be engulfed during the upper AGB phase of their parent stars. The much larger radius of the AGB stars not only increases the chance for planetary interaction, but also implies that the envelope is more vulnerable to the influence of the planet towards higher final mass-loss rate. A higher mass-loss rate also implies a faster post-AGB evolution. Both effects make the formation of a PN much more likely. Our assumed low mass-loss rate, therefore, supports the notion that a fraction of elliptical PNe were shaped by sub-stellar companions. The planetary nebula luminosity function (PNLF). Observations show that the brightest PNe in [O iii ] λ5007, i.e. the bright-end cutoff of the PNLF, does not depend on the age or metallicity of the stellar population (e.g. Ciardullo 2010 ). Namely, old stellar populations for which stars of initial mass of M 1, ZAMS ≃ 1–1.2 M ⊙ are forming PNe have their brightest [O iii ] λ5007 PNe as young stellar populations have. This is still a puzzle as the post-AGB stellar luminosity to ionize the nebula should be at least ≈5000 L ⊙ . Our results hint to a possible solution to this puzzle. As evident from the last column of Table 2 , in the case of a reduced mass-loss rate the post-AGB stellar luminosity of stars with initial masses of M 1, ZAMS ≳ 1.05 M ⊙ is L pAGB ≳ 5000 L ⊙ . This, together with the interaction with a low-mass companion on the upper AGB will have the necessary ingredient for a bright PN, a dense nebula of mass ≳ 0.2 M ⊙ and a bright central ionizing star. The full solution to the puzzle might include another component. Miller Bertolami ( 2016 ) finds in a new set of simulations that the post-AGB luminosity values are higher than the values obtained in older simulations. He does not fully address the topic of the PNLF in old stellar populations, whereas we here present preliminary results on the matter. Mendez ( 2017 ) does show a fit to the PNLF of NGC 4697 based on the Miller Bertolami ( 2016 ) tracks, yet notes that it is not a full solution to the PNLF puzzle. It is conceivable that the new simulations of Miller Bertolami ( 2016 ) together with our assumed low mass-loss rate with a late engulfment of a planet (or a brown dwarf or a low-mass star), account for the brightest PNe in old stellar populations. We point out another difference in the two works, where in contrast to Miller Bertolami ( 2016 ), we focus on binary-shaped PNe (non spherical). The initial-final mass relation. There is an observed relation between the initial mass of stars and the mass of their descendant WDs (e.g. Kalirai


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M.N. is supported by the Sloan Foundation. We would like to thank the Flatiron Institute and Columbia University for providing the infrastructure and support for this research. We also thank the anonymous referee for giving important suggestions to improve this work. We are grateful to Glennys Farrar, Angus Beane, and David W Hogg for helpful conversations.


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We gratefully appreciate the comments from the anonymous referee that significantly improved this article. S.O. also thank Dr. Kazuya Saigo for helpful discussions. This paper makes use of the following ALMA data: ADS/JAO.ALMA#2015.1.01025.S. ALMA is a partnership of the ESO (representing its member states), NSF (USA), and NINS (Japan), together with the NRC (Canada), NSC and ASIAA (Taiwan), and KASI (Republic of Korea), in cooperation with the Republic of Chile. The Joint ALMA Observatory is operated by the ESO, AUI/NRAO, and NAOJ. This research has also made use of data from the Herschel Gould Belt Survey (HGBS) project ( http://gouldbelt-herschel.cea.fr ). The HGBS is a Herschel Key Programme jointly carried out by SPIRE Specialist Astronomy Group 3 (SAG 3), scientists of several institutes in the PACS Consortium (CEA Saclay, INAF-IFSI Rome and INAF-Arcetri, KU Leuven, and MPIA Heidelberg), and scientists of the Herschel Science Center (HSC). Data analysis was carried out in part on a common-use data analysis computer system at the Astronomy Data Center (ADC) of the National Astronomical Observatory of Japan. Facilities: ALMA , Herschel .


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


O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation 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 B-Telescope O O O B-Identifier B-Survey O B-Tag 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-CelestialObject I-CelestialObject O O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Survey O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Instrument O O B-CelestialObject I-CelestialObject O O O O O O O B-CelestialObject I-CelestialObject I-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject I-CelestialObject I-CelestialObject O O O O O O O O O O O B-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O 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 B-Instrument I-Instrument I-Instrument 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 B-CelestialObject I-CelestialObject O O O O O O O O O O O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O O O B-Instrument B-Wavelength I-Wavelength I-Wavelength O O O O O O B-Instrument O O O O O O O O O O

P. Bastien et al. 2017, in preparation). The OMC 1 region was observed 21 times between 2016 January 11 and 25 in a mixture of very dry weather (Band 1; ) and dry weather (Band 2; ) under JCMT project reference numbers M16AL004 (BISTRO) and M15BEC02 (POL-2 commissioning). In order to determine the behavior of rms noise in our observations as a function of integration time, we measured the standard deviation on the Stokes Q and Stokes U values in a region with relatively constant signal in both the Stokes Q and the Stokes U maps, located between OMC 1 and the Orion Bar. This region, centered at approximately , was chosen because it was relatively flat, moderately unpolarized, low in emission, and away from the brightest sources, and because there was no region entirely without signal in the central part of the map. Figure 2 shows how the noise integrates down in this 21-repeat (∼14 hr) POL-2 observation. Figure 2. Mean measured rms noise in Q and U as a function of time (in minutes) at a single off-source position. The data points show the scatter on the individual measurements, and the line is the running mean. A behavior consistent with is seen, as in the ideal case. The polarization noise in Figure 2 is seen to integrate down close to , as in the ideal case. The scatter of individual measurements reduces satisfactorily as the data are subsequently combined. We find that there is no evidence of any “noise floor” in long integrations. From this plot we see that this data set has reached 2.1 mJy beam −1 rms noise in 13.5 hr. An rms noise value of ∼2 mJy beam −1 was set as the target value for the BISTRO survey. Appendices A and B list a series of tests that we carried out to confirm the repeatability of our measurements and to demonstrate consistency with previous data. 4. First Data from the Survey Figure 3 shows a polarization map taken with POL-2 of the OMC 1 region of the “integral filament” in the Orion A molecular cloud, with half-vectors rotated by 90° to trace the B-field direction. Only vectors with a signal-to-noise ratio of 3 or greater in polarization fraction are shown (i.e., ). The Orion A molecular cloud is a well-resolved and well-studied region of high-mass star formation (e.g., Bally 2008 ; O’Dell et al. 2008 ). It is the closest region of high-mass star formation, located at a distance of 388 ± 5 pc (Kounkel et al. 2017 ). The half-vector lengths show the percentage polarization, with a 5% scale bar in the corner to give the calibration. The underlying image is an 850 μ m total intensity map of the same region taken using SCUBA-2. Figure 3. Polarization map of the OMC 1 region of the “integral filament” in Orion A, with half-vectors rotated by 90° to show the B-field direction. The Orion Bar can be seen in the southeastern part of the map. Half-vectors with are shown. The background image is a SCUBA-2 850 μ m emission map taken using the standard SCUBA-2 DAISY mapping mode. The half-vector gray-scale is chosen for contrast


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This work is supported by NSFC under contract No. 41304133, 41474147, 41231069, 41222032, 41174148, 41421003, and 41204105. The numerical calculations have been completed on a computing system at Peking University. Figure 3 was partly produced by VAPOR (Clyne et al. 2007 ). L.P.Y., J.S.H., C.Y.T., E.M., and X.W. are also members of the ISSI/ISSI-BJ International Team-304.


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Many thanks are in order to A. Usmanov, G. Zank, and A. Dosch for fruitful discussions. Financial support for the project FI 706/8-2 (within Research Unit 1048), as well as for the projects FI 706/14-1 and HE 3279/15-1 funded by the Deutsche Forschungsgemeinschaft (DFG), and FWF-Projekt I1111 is acknowledged.


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We acknowledge support from the Academy of Finland and the University of Oulu Graduate School. We thank an anonymous reviewer for a constructive report that helped us to improve the paper.


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propagate over a distance that is an order of magnitude bigger than its diameter, as suggested by the weak nonlinear theory and numerical simulations (Stern Radko 1998 ), as well as by experiments in nonrotating water tanks with a rectangular shape (Voropayev et al. 1999 ). More recent water-tank experiments (Cariteau Flór 2006 ) have demonstrated that it still has a finite lifetime, because the secondary component of such strongly asymmetric vortex pair starts to wrap around the principal monopole, creating a strain that eventually gives rise to an elliptic instability due to the parametric resonance between the oscillation of inertial waves and the ambient strain field; for details, see Cariteau Flór ( 2006 ). It should be noted that the behavior of Chaplygin vortices in a fully 3D geometry is still an open question, because no reliable 3D simulations and experiments have been reported in the literature and we are unable to predict whether the dynamical 3D turbulence of the solar wind and of Earth’s magnetosheath is dominated by stable dipolar (Larichev Reznik 1976 ; Petviashvili Pokhotelov 1992 ; Kuvshinov et al. 1999 ) vortices, or by long-lived, mostly monopolar Chaplygin structures. Their monopolar components feature a jump of the plasma density and of the compressional magnetic field B z at the edge. In the presence of a compressional magnetic field, such jumps are associated with a current shaped as a thin hollow cylinder at r = r 0 , which probably reduces its stability in high- β turbulent plasmas. In a high- β plasma, we have found two distinct types of coherent vortices propagating in the perpendicular direction. The first is identified as a generalized shear Alfvén structure that possesses both the torsional and the compressional components of the magnetic field perturbation. It has a zero parallel electric field and, being homogeneous along its axis that is inclined toward the ambient magnetic field, it sweeps along the z -axis with a velocity u z that is in the Alfvén speed range; the transverse phase velocity is equal to , where θ is the (small) pitch angle between the structure and the background magnetic field. While in a sufficiently incompressible plasma , it has the structure of a moving Chaplygin vortex with a monopole superimposed on a dipole; in plasmas with β ∼ 1, its monopolar component is likely to be unstable and short-lived due to the emergence of a thin, (electron-scale) current layer and/or a sharp peak of charge density at its edge. The compressible magnetic field associated with such a vortex is restricted to the interior of the vortex core, while the transverse perturbation “leaks” from the core to larger distances. The second type of propagating structure obtainable analytically possesses a finite compressional magnetic field and parallel electric field, as well as perpendicular fluid velocity and density perturbation, but vanishing parallel ion fluid velocity and transverse perturbations of the magnetic


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DRF acknowledges support from STFC (ST/L00075X/1), including provision of local computing resources. FL thanks the CPER Haute-Normandie/CNRT/Energie, Electronique, Matériaux, and the CNRS national programme ‘Physique et Chimie du Milieu Interstellaire’. We thank Alexandre Faure for providing the IOS results in the appendix.


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

( z ∼ 7) and with the cosmic SFR derived by Bouwens et al. ( 2015 ; or Finkelstein et al. 2015 ) up to z ∼ 10. We conclude that gaea is able to reproduce the overall evolution of the LFs, GSMF, and cosmic SFR over the redshift range 0 z 10. It is worth stressing that the good level of agreement shown in this Letter is obtained without any retuning of the feedback parameters (which have been calibrated by Hirschmann et al. 2016 against lower-redshift observables). Our findings agree with recent results from the MUFASA simulation suite (Davé et al. 2016 ), which implements a kinetic feedback scheme with scalings based on the parameterization provided in Muratov et al. ( 2015 ). They show that the MUFASA runs are able to reproduce the evolution of cosmic SFR and the GSMF at and the evolution of its low-mass end slope up to z ∼ 6 (where the simulated volume is too small to efficiently sample the high-mass end of the GSMF). A critical point of the analysis presented here is the treatment of dust attenuation. In this Letter, we consider both intrinsic and dust-attenuated magnitudes. Despite the simplified dust model adopted, we show that the bright ends of the corresponding LFs bracket the observed LFs. Our results are in qualitative agreement with the Bouwens et al. ( 2009 ) inferences based on the UV continuum of the sources, i.e., that dust attenuation should decrease at increasing redshifts, becoming negligible at . We note that a significant level of dust attenuation is required by the fiducial feedback scheme to match the shape of the observed LFs, in agreement with previous studies (Lo Faro et al. 2009 ; Lacey et al. 2011 ; Cai et al. 2014 ). Intrinsic and attenuated LFs converge below the knee of the LFs, again in qualitative agreement with the estimates by Bouwens et al. ( 2009 ) of a lower dust attenuation for fainter sources. The predicted level of dust attenuation at high redshift thus represents a powerful discriminant between different feedback schemes. Therefore, further insight into our understanding of galaxy evolution at is tightly connected to a better description of this key aspect. From a theoretical perspective, the implementation of a self-consistent dust treatment in theoretical models of galaxy evolution, able to follow dust production and destruction alongside with galaxy assembly (see, e.g., the recent work by Popping et al. 2016 ), represents a promising avenue. In addition, dust provides an important channel for molecular hydrogen formation and can therefore play a crucial role in regulating star formation at different cosmic epochs. This modeling is beyond the aims of this Letter and will be the subject of future work. Here, we just highlight that our conclusions will change dramatically if a substantial fraction of the SFR density is related to highly obscured objects, as some studies suggest at (Rowan-Robinson et al. 2016 ). In order to clearly assess the contribution of dusty sources to the SFR density at ,


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

K, and purple: 7100 K. Table 1 summarizes the brightness temperatures of the sunspot umbra and quiet regions surrounded by the red and white rectangles, respectively, in Figures 2 – 4 . The brightness temperature of the 115 GHz image is also defined by the histogram of the observed level. The quiet region level at 115 GHz was set as 7500 K from Selhorst et al. ( 2005 ). Hence, the quiet-region levels of the radio emissions are defined by the data of the entire disk. Therefore, the brightness temperatures of the quiet regions surrounded by the white rectangles are different from the quiet-region values (9000 K at 34 GHz and 7500 K at 115 GHz). Table 1 Radio Brightness Temperatures of the Umbra and Quiet Regions Note . The umbra and quiet regions are surrounded by red and white rectangles, respectively, in Figures 2 – 4 . In this study, we selected an additional eight active regions observed by the NoRH at 34 GHz, in order to confirm the generality of this finding of low umbral contrast. The selected active regions contained relatively large and well-isolated sunspots including the sunspots observed on 2014 January 8 (see Figure 2 ) and 2014 October 24 (see Figure 3 ). We did not use the data from the sunspot observed on 2014 February 12 (Figure 4 ) because that sunspot was not large relative to the others. Although the NoRH observes the Sun every day, we limited the selection of regions to those with large sunspots located near the disk center for which SDO /AIA data are available. We also eliminated the data affected by flares and the spatial aliasing effect. We chose a 20′′ square region at the center of the umbra for each sunspot and derived the averaged brightness temperature of the center regions. Table 2 lists the 10 selected sunspots. Table 2 Radio Brightness Temperatures and UV/EUV Emissions at 1700 and 304 Å of the 10 Umbrae 4. DISCUSSION 4.1. Image Quality In this study, we applied two types of image synthesis, i.e., the CLEAN and Steer-CLEAN syntheses. Our result shows that the Steer-CLEAN synthesis provides a smoother image. This effect is more apparent in the quiet regions in Figures 1 (a) and (b). The standard deviations of the brightness temperatures of the sky region surrounded by the white rectangles in Figures 1 (a) and (b) are 377 and 284 K, respectively. Hence, the Steer-CLEAN synthesis provides a slightly better image from the same NoRH data. However, the Steer-CLEAN synthesis provides smoother structures in the peak brightness region. Hence, the dynamic ranges of these images (the ratio between the peak brightness and the standard deviation of the sky region) are almost the same (∼21 dB). It should be noted that the sky region surrounded by the white rectangles in Figure 1 partially contains the aliasing structures of the disk. Hence, the noise level of the sky region varies strongly with the region of our focus. Although the best spatial resolution of the NoRH at 34 GHz is about 5′′, the typical spatial resolutions in


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We thank an anonymous referee for a very helpful report that enabled us to significantly improve the manuscript. We thank the NASA AISRP for providing financial assistance for the development of the PINTofALE package and the CHIANTI project for making publicly available the results of their substantial effort in assembling atomic data useful for coronal plasma analysis. J.J.D. and V.L.K. were supported by NASA contract NAS8-03060 to the Chandra X-ray Center during the course of this research. DG was supported by Chandra grants GO1-2021, GO2-3010X, and AR4-5002X.


O O O O O O B-Survey I-Survey I-Survey I-Survey I-Survey I-Survey I-Survey I-Survey B-Survey 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 B-CelestialRegion I-CelestialRegion O O O O B-Wavelength O B-Wavelength I-Wavelength I-Wavelength O O O O O O B-Survey O O O O O O O B-CelestialRegion I-CelestialRegion O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model 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 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 B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O

and abundance of galaxies in the Spitzer Matching survey of the UltraVISTA ultra-deep Stripes (SMUVS) to understand the connection between galaxies and their host dark matter halos. SMUVS provides a unique combination of large area (∼0.66 square degrees of the COSMOS field) and unparalleled depth at 3.6 and 4.5 μ m. This, combined with the latest ultra-deep UltraVISTA data and other ancillary data in the COSMOS field, allows for precise photometric estimates of redshift and stellar mass and robust statistics from such a large catalog ( objects). As a result, our analysis is performed over an unprecedented redshift range () for volume-limited galaxy samples selected by stellar mass. To interpret the observed clustering, we use a well-established five-parameter halo model, although we fix the values of three of these parameters. Novel to our approach is the inclusion of the photometric redshift dispersion, , as a free parameter in the fitting procedure. This parameter is designed to encapsulate the effect of dispersion in the photometric redshifts used in our analysis and allows us to fully exploit the clustering information in our photometric galaxy catalog. This parameter is discussed in more detail in Appendix A . From our best-fit halo models we can derive a number of interesting quantities. The characteristic halo masses, and , are well constrained by our data and exhibit fairly tight linear relationships (in logarithmic space) with stellar mass. This is similar to what has been found in earlier studies with similar analyses (e.g., McCracken et al. 2015 ). The satellite fraction, i.e., the fraction of galaxies in a sample that do not sit at the center of the potential well of their halo, generally increases with cosmic time. This is in broad agreement with other studies in the literature and in line with expectations of hierarchical structure formation. The comoving correlation length, r 0 , [defined such that ], and large-scale effective galaxy bias, , show strong monotonic trends with increasing redshift for a fixed stellar mass over the entire redshift range probed. Projecting ΛCDM halo mass accretion histories computed according to Appendix A of McBride et al. ( 2009 ) through our measurements of the large-scale bias, and combining this with the evolution of stellar mass content based on the cumulative number density (Behroozi et al. 2013a ), we propose an evolutionary path for the dark matter and stellar mass content of galaxies for . This shows a favorable agreement with our independent determinations of the relationship between galaxy bias and stellar mass at these redshifts and appears to be an interesting method to investigate the coevolution of these quantities in the future. Finally, we investigate the SHMR. This indicates the efficiency with which baryons have been converted into stars over the lifetime of a dark matter halo. We fit the SHMR parametrization of Behroozi et al. ( 2013b ) for our two lowest redshift bins ( and ).


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

the SDSS data from at least one star-forming region in each galaxy in the sample suggest that the sample galaxies are undergoing young massive star formation phase having a significant population of WR stars. Figure 8. The blue WR bump detected in the spatially resolved star-forming regions of SBS 1222+614. The dashed-dot line represents the continuum fit. The solid line represents a Gaussian fit to the blue bump. Figure 9. The detection of the red WR bump in the spatially resolved star-forming region of SBS 1222+614. The dashed-dot line represents the continuum fit. The solid line represents a Gaussian fit to the red bump. 3.3 Ionization mechanism The detection of high ionization emission lines of He ii λ4686, [O iii ] λ4363, [O iii ] λ4959, 5007, and [Ar iii ] λ7135 and low ionization emission lines of [O ii ] λ3726, [N ii ] λ6584 and [S ii ] λ6717, 6731 etc., in the galaxy spectrum can be an indication of mix of many excitation sources such as photoionization mainly from massive ionizing stars and shocks generated by WR stars, supernovae explosions, and energetic active galactic nuclei-related mechanisms as discussed by Garnett et al. ( 1991 ), Garnett, Kennicutt Bresolin ( 2004 ), Guseva et al. (2000 ), and López-Sánchez Esteban ( 2010a ). Therefore, it is necessary to identify the dominant excitation mechanism in these galaxies. The nature of the dominant ionizing source can be inferred using the quantitative classification scheme proposed by Baldwin, Phillips Terlevich ( 1981 ) using combinations of line ratios. Subsequently, other similar diagnostic schemes were proposed by Dopita et al. ( 2000 ) and Kewley et al. ( 2001 ). All these diagnostic schemes use the emission line ratios of [O iii ] λ5007/H β, [N ii ] λ6583/H α and [S ii ] λ6717, 6731/H α. The optical emission line ratios for all the spatially resolved ionized regions in our galaxy sample are listed in Table 3 and the locations of all the star-forming regions are presented in Fig. 10 , which shows typical plots for [O iii ] λ5007/Hβ versus [N ii ] λ6583/Hα (top panel) and [O iii ] λ5007/H β versus [S ii ] λ6717, 6731/H α (bottom panel). Here, we used the latest Kewley et al. ( 2001 ) diagnostic criteria to identify source of excitation mechanism. In these figures, it can be seen that the primary and dominating source of ionization is photoionization in all the cases. Figure 10. A comparison of the observed flux line ratios obtained from the star-forming regions in our sample of dwarf galaxies with the diagnostic diagrams proposed by Kewley et al. ( 2001 ). 3.4 Physical conditions of the ionized gas The electron temperature ( T e ) and density ( n e ) of the ionized gas in the H ii regions are estimated here. Since the faint auroral [O iii ] λ4363 emission line along with the [O iii ] λ4959, 5007 emission lines were detected in many cases, the electron temperature could be estimated directly using their relative line intensities. A two-zone approximation was assumed to


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

work is different from traditional KAW theory of , but is close to the theoretical prediction of from Boldyrev Perez ( 2012 ) and Boldyrev Loureiro ( 2019 ) and the simulation from Cerri et al. ( 2019 ). It also corresponds to α = 1.13 in the framework of the model by Landi et al. ( 2019 ). Hence a modified CB premise may be needed to understand the kinetic turbulence in magnetosheath. We note that, for most of the events, the weak and scale-independent anisotropy in the perpendicular plane appears to agree with recent PIC simulation of KAW turbulence (D. Grošelj 2020, private communication) but is inconsistent with results of Boldyrev Loureiro ( 2019 ), which predicts a much stronger anisotropy and a steeper scaling of or L ⊥ ∝ , depending on different current sheet configurations for the tearing instability. Capturing the active signatures of current sheet disruption/reconnection (i.e., Mallet et al. 2017 , Loureiro Boldyrev 2017 ) from in situ observation is a challenging task, but will contribute to understanding its effects on the anisotropy. The spectral anisotropy of kinetic plasma turbulence is believed to be associated with dispersion and intermittency effects (Zhao et al. 2016 ; Landi et al. 2019 ). For example, the anisotropic scalings are different below and above ion cyclotron frequency and also differs for sheet and tube-like turbulence (Zhao et al. 2016 ). To illustrate the possible connection between intermittency and spectral anisotropy, we specifically compare the results from two events. Figure 5 shows the excess Kurtosis and anisotropy relation for the total magnetic field. The excess Kurtosis is defined as , where S 4 ( l ) is the fourth-order structure function. In both panels of Figure 5 , the solid lines represent the results from event 1, which is recorded on 2017 October 4 and is used as our example of spectral anisotropy in Section 3 , while the dashed–dotted lines represent the results from event 2, which is recorded on 2017 December 24. As plotted in three directions l ⊥ , L ⊥ , l ∥ , the value of K ( l ) is around zero at large scales, meaning the roughly Gaussian distribution of the fluctuations. Toward small scales, K ( l ) displays an increase tendency before it drops down. Such non-Gaussian statistics ( K ( l ) > 0) confirms the presence of intermittency in the magnetosheath, while the scale-dependent profile of Kurtosis is similar with solar wind observations (He et al. 2019 ). For the kinetic-scale parallel–perpendicular anisotropy, we find that it can be considerably affected by the intermittency. As shown in Figure 5 , the stronger the intermittency (see the larger Kurtosis of the solid lines in the left panel), the stronger the anisotropy level (see the larger vertical distances between the solid blue curve and the gray line in the right panel). This phenomenon is consistent with previously observations at large scales, which emphasize the key role of intermittency in generating the spectral anisotropy


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

star formation rate per unit area , if we have one supernova per mass M SN of stars formed, then the supernova rate per unit area is . The momentum and energy injected per supernova are p SN and E SN , respectively, giving momentum and energy injection rates per unit area and . The energy injection rate into turbulent motions is (equation 17 ) and the ratio of this to the total supernova energy budget is where the numerical evaluation is for our canonical values p SN 310 5 M kms 1 and E SN 10 51 erg. Thus, for the values of found in our simulation, only a small portion of the supernova energy budget is consumed by driving turbulence. Similarly, the wind kinetic luminosity per unit area is of the order of and the ratio of this to the supernova energy injection rate is where the numerical evaluation is for M SN 100M and v esc 300kms 1 , and is the mass loading factor, which for our simulations is 1. Thus we conclude that neither launching the wind nor driving the turbulence consumes an appreciable fraction of the total supernova energy available. Instead, the energy released by supernovae must either be lost to radiation, or must go into a hot wind that carries it out. Unfortunately, our model does not allow computation of the partition between these two forms of energy loss, and the simulations that have been published to date are not helpful in addressing this question answering it correctly requires simulating with enough resolution to resolve the SedovTaylor phase of supernova remnant expansion, without using any artificial methods to lower the density in the vicinity of the supernovae. As we discuss in Section 4.6 , no published simulations meet these criteria. Observations of superbubbles away from galactic centres suggest that radiation cannot be the primary loss mechanism (Rosen etal. 2014 ), but it is unclear whether we can generalize these conclusions to the very different environment of the CMZ. If radiative losses do not dominate, then the hot wind must carry an energy flux of order , and given our result that 50percent of the incoming gas is converted to stars, this implies an energy flux ergs 1 . This material will mostly be launched from the star-forming ring at 100pc. The non-thermal particle energy injection rate should be 10percent of the hot gas energy budget, implying ergs 1 . Because non-thermal particle acceleration happens even if the hot gas does not vent, and because the non-thermal particles have long mean-free paths and thus should be able to escape the disc, this estimate should hold even if the primary loss mechanism is radiation rather than a hot wind. Cosmic ray escape is confirmed observationally (Crocker 2012 , and references therein): the diffuse non-thermal emission from the CMZ in radio continuum and -ray bands implies that only a small fraction (10percent) of the power injected into non-thermal particles accelerated in the CMZ is lost in situ radiatively; most of this power is carried off by escaping cosmic


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HGM is grateful for support from the UK Science and Technology Facilities Council through the grant ST/I001204/1. LV is supported by the European Research Council under the European Community's Seventh Framework Programme grant FP7-IDEAS-Phys.LSS and acknowledges Mineco grant FPA2011-29678- C02-02. JN is supported in part by ERC grant FP7-IDEAS-Phys.LSS. AC is supported by the European Research Council under the European Community's Seventh Framework Programme grant FP7-IDEAS-Phys.LSS. WJP is grateful for support from the UK Science and Technology Facilities Research Council through the grant ST/I001204/1, and the European Research Council through the grant ‘Darksurvey’. Funding for SDSS-III has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation and the US Department of Energy Office of Science. The SDSS-III website is http://www.sdss3.org/ . SDSS-III is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS-III Collaboration including the University of Arizona, the Brazilian Participation Group, Brookhaven National Laboratory, University of Cambridge, Carnegie Mellon University, University of Florida, the French Participation Group, the German Participation Group, Harvard University, the Instituto de Astrofisica de Canarias, the Michigan State/Notre Dame/JINA Participation Group, Johns Hopkins University, Lawrence Berkeley National Laboratory, Max Planck Institute for Astrophysics, Max Planck Institute for Extraterrestrial Physics, New Mexico State University, New York University, Ohio State University, Pennsylvania State University, University of Portsmouth, Princeton University, the Spanish Participation Group, University of Tokyo, University of Utah, Vanderbilt University, University of Virginia, University of Washington and Yale University. This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231. Results are based on observations obtained with Planck ( http://www.esa.int/Planck ), an ESA science mission with instruments and contributions directly funded by ESA Member States, NASA and Canada. Numerical computations were done on Hipatia ICC-UB BULLx High Performance Computing Cluster at the University of Barcelona.


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D.B. and T.R. dedicate this paper in gratitude to their long-term collaborator and friend Stanislav (Stan) Štefl (1955–2014), with whom this project had been planned like so many others before. The authors thank the BRITE operations staff for their untiring efforts to deliver data of the quality that enabled this investigation. They appreciate the permissions by Tahina Ramiaramanantsoa et al. to mention some early results of their ongoing work on ζ Pup . Coralie Neiner is thanked for the early communication of magnetic-field measurements with ESPaDOnS of Cen. This research has made use of the SIMBAD database, operated at CDS, Strasbourg, France. This research has made use of NASA’s Astrophysics Data System. ACC acknowledges support from CNPq (grant number 307076/2012-1) and FAPESP (grant number 2015/16592-0). GH thanks the Polish NCN for support (grant 2011/01/B/ST9/05448). A.F.J.M. is grateful for financial aid from NSERC (Canada) and FRQNT (Quebec). A.P.i. acknowledges support from the Polish NCN grant No. 2011/03/B/ST9/02667. A.P.o. acknowledges support through NCN grant No. 2013/11/N/ST6/03051. G.A.W. acknowledges Discovery Grant support from the Natural Sciences and Engineering Research Council (NSERC) of Canada. The authors from Poland acknowledge assistance by BRITE PMN grant 2011/01/M/ST9/05914.


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

of ionizing photons drops rapidly, and is therefore quite low when the supernovae start to create clear channels. At these early times, the amount of photons reaching the IGM before the supernova phase is low as well. Similarly, the lower panel of Fig. 9 shows the ionizing duty cycle as a function of halo mass, and , for four regularly log-spaced mass bins centred on log ( M ⋆ /M ⊙ ) = 7.75, 8.25, 8.75 and 9.25. This is in strong disagreement with the recent results of Kimm et al. ( 2017 ), who simulated the formation of mini-haloes and found that f esc can be very high even before the first supernova. However, their study focuses on much lower mass haloes, reaching M vir ≤ 10 8 M ⊙ at most. They also include a description of pop III stars and molecular hydrogen, which can lead to significant differences for haloes below the atomic cooling limit of M vir ∼ 10 8 M ⊙ . Figure 9. Ionizing duty cycle of the two most massive haloes, as a function of the galaxy (upper panel) and halo (lower panel) mass. The blue (red) dashed line shows the fraction of the time a galaxy of a given mass spends with higher than 10 50 (10 48 ) photons per second. On average, a more massive galaxy spends more time leaking LyC photons. On the other side of the mass spectrum, when M ⋆ > 10 6 M ⊙ , the duty cycle saturates, with and . This happens when the galaxy starts to reach a more stable regime, with feedback-regulated star formation, but where the star formation is rarely completely shut off. This means that the gas in the galaxy will usually not have the time to settle down in between two starburst events, leading on average to a more steady production of ionizing photons. 5 LOCAL ESCAPE OF IONIZING RADIATION In Section 4 , we have found that the escape fraction is mainly regulated by the interplay between supernovae, gas accretion and clustered star formation, and we have limited our analysis to the total escape fraction of each galaxy, computed at the virial radius. Because it is strongly linked with ISM-scale phenomena, we will now concentrate on the intrahalo processes leading to the escape of ionizing radiation. For this purpose, we will mainly focus on the most massive galaxy in our sample. 5.1 Does radiation escape from the emission clouds? Before reaching the IGM, the ionizing photons must travel through the complex distribution of gas inside and around the galaxy. Kimm Cen ( 2014 ), Ma et al. ( 2015 ) and Paardekooper et al. ( 2015 ) showed that when f esc is low, most of the photons are absorbed very locally, within 100 pc of their emission point, and that it is indeed crucial to resolve properly the ISM in order to study properly the escape of ionizing radiation. We find very similar results with our simulations, and we suggest that this is the reason behind the strong coupling between the supernova feedback and evolution of f esc . While the idea that clear channels for ionizing radiation from young stars are created by ionizing radiation itself is


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

of the projection effect of looking from the side, this corresponds to x = 11 when viewed from directly above. The line profile over the EB, shown in the left panel , is located at [ x , y ] = [17, 11] Mm and is evident in the line wings. The line core, shown in the right panel of Fig. 4 , shows extensive fibrils, some have about the length of the computational box, 20 Mm, but no evidence of brightening directly above the site of the EB. The two loop systems that meet and are the source of the EB are visible in the center of the right panel of Fig. 4 . They stretch toward greater and lower y -values from their meeting point close to y = 11 Mm? When viewed from directly above, the EB region is bright in H α in the line core as well, but this is due to emission that is formed much higher in the atmosphere, at least 5 Mm above the photosphere: The cool canopy above the current sheet is heated by Ly α and Ly-continuum radiation from the hot plasma of the current sheet below, raising the temperature of the canopy plasma significantly, as is visible in the lower middle panel of Fig. 1 and in the left panel of Fig. 3 . This relatively high-temperature gas excites some H α emission in the region that is heated above the current sheet. This heating at large heights directly above the reconnection region is probably a result of the method we chose for the coronal back-radiation and raises the temperature more than what would occur on the real Sun. The heating does not affect the evolution or diagnostics of the EB or UV burst. Swedish 1-meter Solar Telescope observations (Ortiz et al., in prep.) show that the wing of the Ca II 854.2 nm line can be a very good proxy for the existence of EBs, with enhanced emission that is colocated and roughly cotemporal with bright H α wing enhancement. These observations in the blue wings of both the Ca II 854.2 nm and H α lines also show dark, presumably cool, surges that occasionally emanate from the site of EB emission. We find that the EB in this location shows brightening, starting at time t = 7500 s and lasting for at least 1200 s thereafter. This enhanced emission, 0.0735 nm in the blue wing of the Ca II 854.2 nm triplet line, is shown in Fig. 5 , which also shows emission in the line core and in the shape of the line profile. Similar as for H α , the cores of the Ca II H Kand the Ca II 854.2 nm triplet lines show the loops that emanate from the vicinity of the current sheet as narrow thin fibrils that stretch toward higher and lower y -values, approximately in the y -direction. The EB is visible as a narrow band of emission in the line wing, and it is also visible at the time of this image ( t = 8220 s) in the line core, although this emission is partially covered by overlying longer fibrils. Apparently rising from the EB location, about parallel with the positive y -axis, a small cool surge is seen to be accelerated along the field lines, or loops, that form the cool portion of the canopy. Signs of the


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

Convolutional neural networks take advantage of the typically high correlation of local groups (e.g., adjacent pixels in an image) and hierarchically extract features (edges → motifs → parts → objects; LeCun et al. 2015 ). With this, deep CNNs extract, by layer-wise transformations, the feature representation of an image that serves as a basis to, for example, classify images ( Armstrong Fletcher 2019 ), predict sequences ( Upendran et al. 2020 ), transform images to different domains ( Kim et al. 2019 ; Jarolim et al. 2020 ), or provide segmentation maps ( Long et al. 2015 ). From deep learning applications for semantic segmentation, the concept of multi-scale architectures has proven to be most successful ( Ronneberger et al. 2015 ; Chen et al. 2018 ; Badrinarayanan et al. 2017 ). Here the spatial dimensions are successively reduced, while the depth of the network (number of filters) is being increased. With this, the neural network can correlate features of different scales at each resolution level and can solve more complex tasks with the increased number of filters (greater number of parameters). In order to correlate features across the full image, a sufficient network depth is required. For semantic segmentation, the output is a pixel-wise classification of the input image (segmentation map). Therefore, the feature representation (low spatial resolution) needs to be matched to the size of the input image. The segmentation map can be directly obtained from the deepest layer of the neural network (e.g., Long et al. 2015 ), but with this approach the output typically lacks spatial detail. An alternative approach, which accounts for global relations and spatial resolution simultaneously, is the use of an encoder-decoder architecture ( Ronneberger et al. 2015 ; Chen et al. 2018 ; Badrinarayanan et al. 2017 ). Here, the image is first transferred into a feature representation over multiple scales by the encoder, and then upsampled to the original resolution over the same number of scales by the decoder. At each scale, skip connections are used to combine the upsampled features, which comprise the full context information, with the spatial details from the encoder. A common problem with deep networks is the vanishing gradient problem, where the parameter optimization of the neural network becomes inefficient with increasing network depth ( He et al. 2016 ; Szegedy et al. 2015 ). In addition, when dealing with high resolutions, the training time increases exponentially, which often results in long convergence times for model training. A possible solution to this problem was developed by Karras et al. (2017) for the application of image generation. Here the authors used an approach where the size of the network is progressively increased. The advantage of this method is that the training with low-resolution samples is computationally efficient and allows the deepest layers to be trained until full convergence is reached, before introducing


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Acknowledgements We thank the anonymous referee for useful comments that greatly improved the quality of this paper. This scientific work makes use of the Murchison Radio-astronomy Observatory, operated by CSIRO. We acknowledge the Wajarri Yamatji people as the traditional owners of the Observatory site. Support for the operation of the MWA is provided by the Australian Government (NCRIS), under a contract to Curtin University administered by Astronomy Australia Limited. We acknowledge the Pawsey Supercomputing Centre, which is supported by the Western Australian and Australian Governments. This work is part of the project 176005 “Emission nebulae: structure and evolution” supported by the Ministry of Education, Science, and Technological Development of the Republic of Serbia. T.G.P. would like to thank Dirk Grupe (Morehead State University), Aviv Brokman (University of Kentucky) and Eric Roemmele (University of Kentucky) for useful discussions about Cash statistics.


O O O O O O O O O O O O O O O O O O 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 B-Tag I-Tag I-Tag I-Tag I-Tag I-Tag 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 B-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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 O B-Person I-Person O O O O O O O O O O O O O O O O O B-Grant I-Grant B-Grant O O B-Organization I-Organization O O O O O O O O O O O O O O O B-Organization I-Organization I-Organization I-Organization O B-Organization I-Organization I-Organization I-Organization I-Organization O B-Organization I-Organization O O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization

ACKNOWLEDGEMENTS We thank Liantong Luo, Doron Kushnir, Subo Dong, Andrew Gould, Silvia Toonen, and Hagai Perets for useful discussions. We thank the anonymous referee for useful comments. This research was supported by the ICORE Program (1829/12) and the Beracha Foundation. The computations were performed with a high-performance computing facility which is partly supported by the Israel Atomic Energy Commission – The Council for Higher Education – Pazi Foundation and partly by a research grant from The Abramson Family Center for Young Scientists.


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Acknowledgements This work has been partially supported through financial contribution from PRIN INAF 2014. The results are based on observations obtained with XMM–Newton , an ESA science mission with instruments and contributions directly funded by ESA Member States and NASA, and on data obtained from the HEASARC archive. PE acknowledges funding in the framework of the NWO Vidi award A.2320.0076. EC acknowledges support from a VIDI grant from the Netherlands Organisation for Scientific Research (NWO). We thank Daniele Viganò who developed part of the software used in 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 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 B-Wavelength 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength O O B-Wavelength O O B-Wavelength O O O O O O O O O O O B-Citation I-Citation O O O O O O O O O O O O O O O O O O O B-Wavelength O O O O O B-Wavelength O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O B-Wavelength O O O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength O B-Wavelength O 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 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

of 18.5arcsec. This procedure was also applied to the E relic, but since the emission of the NAT is extended, it is impossible to properly separate the contribution of the tail from the relic. Hence, we decided not to subtract the radio galaxy. This choice allows us to study the spectral index behaviour from the core of the NAT to the lobes, and to investigate its connection with the diffuse source. We computed the average flux density and spectral index of the E relic (and of the NAT radio galaxy) and of the W relic and the radio halo emission (sources subtracted) between 1.5 and 3GHz. The values are reported in Table 3 . The uncertainties on the flux density measurements are computed as where is the calibration error, is the rms noise listed in Table 2 and n beam is the number of beams in the sampled region. These uncertainties were then propagated to the spectral index. Table 3. Flux density, spectral index between 1.5 and 3GHz and radio power of extended sources measured from the images used for the spectral index study. We separated the region of the W relic and the halo on the basis of the spectral index profile as described in Section 4.2.2 . The stands for point-like sources subtracted. We extrapolated the radio power at 1.4GHz from the 1.5GHz flux density measurement, considering a luminosity distance D L 1253.3 Mpc (Wright 2006 ) and using the spectral indices for the k -correction. The uncertainties on flux densities were propagated to the radio power. The sum of the radio power of the two relics (sources subtracted) is consistent with the relation found by de Gasperin etal. ( 2014 ) between the radio power of double radio relics and the cluster mass. Finally, we computed the spectral index for each pixel with value 3 in both frequency bands. We show the spectral index map of the E relic in Fig. 5 . We propagated the uncertainties on the flux densities pixel by pixel on the spectral index. The error map of the spectral index for the E relic is shown in the bottom panel of Fig. 5 , while the spectral index image of the western region and its error map are shown in Fig. 6 . Figure 5. Top panel: Spectral index image of the E relic region between 1.5 and 3GHz. The 1.5GHz total intensity contours (BCD configuration) are overlaid in black: the levels start at 3, with 0.04 mJy beam 1 , and are separated by a factor of 2. Bottom panel: Error map of the spectral index image with the same contours overlaid. The restoring beam of the two images is shown in the left-hand corner and its size is 18.5arcsec 18.5arcsec. Figure 6. Top panel: Spectral index image of the W relic and halo region computed between 1.5 and 3GHz. Point-like sources were subtracted. The two dashed red polygons mark the flux density extraction regions for the halo and the West relic. Bottom panel: Error map of the spectral index image. Contours and restoring beam are as in Fig. 5 . Spectral index images obtained from interferometric data should be treated with


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ACKNOWLEDGEMENTS We thank the anonymous referee for thoughtful comments. IM acknowledges support by the Deutsche Forschungsgemeinschaft under the grant MI 2009/1-1, as well as support by Observatoire de la Côte d’Azur and Université Côte d’Azur for a one-month visit in 2017, where this project was conceived. ARB and PdL acknowledge financial support from the ANR 14-CE33-014-01. CC acknowledges support from DFG Grant CH1188/2-1 and from the ChETEC COST Action (CA16117), supported by COST (European Cooperation in Science and Technology). VA acknowledges the supported by Fundação para a Ciência e Tecnologia (FCT) through national funds (ref. PTDC/FIS-AST/7073/2014 and ref. PTDC/FIS-AST/1526/2014) and by FEDER through COMPETE2020 (ref. POCI-01-0145-FEDER-016880 and ref. POCI-01-0145-FEDER-016886). VA also acknowledge the support from FCT through Investigador FCT contract of reference IF/00650/2015/CP1273/CT0001. GC acknowledges financial support from the European Union Horizon 2020 research and innovation programme under the Marie Marie Skłodowska-Curie grant agreement no. 664931.


O O O O O O O B-Grant O B-Grant O B-Organization I-Organization I-Organization I-Organization O B-Grant O B-Organization I-Organization O O O B-Organization I-Organization I-Organization I-Organization O O O O O B-Observatory I-Observatory I-Observatory O O O O O B-Organization O O B-Grant B-Organization B-Person O O O O 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 B-Organization O O O O O O O O B-Organization I-Organization I-Organization I-Organization O O O O O O O O O O B-Archive I-Archive I-Archive O O B-Dataset I-Dataset I-Dataset O O O O O B-Organization I-Organization I-Organization B-Organization O O O O B-Software O O O O O O O O O O O O B-Archive I-Archive I-Archive I-Archive I-Archive I-Archive I-Archive B-Archive O O O O O O B-Organization I-Organization I-Organization O B-Organization O O B-Organization I-Organization I-Organization I-Organization O O B-Observatory I-Observatory I-Observatory B-Person O O O O B-Fellowship I-Fellowship O B-Organization O O B-Fellowship I-Fellowship I-Fellowship B-Person O B-Person O O O O B-Location B-Organization O B-Grant I-Grant O O B-Organization O

This research was supported via award numbers GO1–12025A and GO3–14019A to Rochester Institute of Technology and GO3–14019B to Vanderbilt University issued by the Chandra X-ray Observatory Center, which is operated by the Smithsonian Astrophysical Observatory for and on behalf of NASA under contract NAS8-03060 (RIT). R.S.'s contribution to the research described here was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA, and supported via an award issued by the Chandra X-Ray Observatory Center. This research has made use of data obtained from the Chandra Data Archive and the Chandra Source Catalog, and software provided by the Chandra X-ray Center (CXC) in the application packages CIAO. This research has made use of data and/or software provided by the High Energy Astrophysics Science Archive Research Center (HEASARC), which is a service of the Astrophysics Science Division at NASA/GSFC and the High Energy Astrophysics Division of the Smithsonian Astrophysical Observatory. E.B. acknowledges support from an IBM-Einstein Fellowship at IAS, and a Simons Foundation Fellowship. J.A.T. and M.A.G. are supported by the Spanish MICINN grant AYA 2011-29754-C03-02 co-funded with FEDER funds.


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

fit the absorption trough. In Fig. 8 , it is clear that the P Cygni model profile matches the observed spectrum in this region. The model profile is unable to reproduce the emission region of the observed spectrum. This is a result of the feature not being produced purely by scattering; clearly the feature is in net emission, and as a result we underestimate the amount of flux in this region. However, this is not important, as we are only interested in obtaining velocity ranges for the line-forming region. We obtained a minimum ejecta velocity, v phot ∼ 20 000 , and a maximum ejecta velocity, v max ∼ 26 000 . These velocity values are, surprisingly, ∼2 times higher than those obtained from our tardis models. This is quite strong evidence that there is an additional high-velocity component of the ejecta that is not observed in the early, photospheric spectra. The computation for the P Cygni Ca ii line produces a velocity from the absorption trough that is fairly robust, as is the velocity estimates from our tardis models. Therefore, we believe the difference to be a real physical effect, and is an indication of additional high-velocity material, likely of low mass, which has been ejected beyond the emitting photospheric region (which is travelling at ∼12 000–14 500 ). We note that the level of the observed continuum to the red of the P Cygni peak falls significantly below that on the blue side. We attribute this to some oversubtraction of the host galaxy flux model as described in Appendix A , and do not attach any line forming significance to the discrepancy. Our best-fitting model required a Sobolev optical depth, τ ∼ 1.3, which tells us that the P Cygni feature originates from a moderately optically thick region. Even though the +7 d spectrum appears to be nebular, the region forming the P Cygni feature is optically thick, at least for the wavelengths of the Ca ii triplet. The optical depth for these lines in all three of our tardis models is 1. Hence, the envelope is optically thin at these wavelengths in our tardis models. However, the optical depth in the tardis models becomes progressively larger with time. Since a P Cygni line requires an optically thick transition, we have a consistent picture of the Ca ii triplet line being optically thin at early epochs (probably due to high temperature), after which the material develops an optical depth around τ ∼ 1.3, providing the opacity for the absorption trough to form. We will see the next spectrum is consistent with the idea that the opacity in this line has dropped further, due to expansion, and a pure emission component has formed. 4.2 Interpreting the +14 d spectrum In the +14 d spectrum, we observe the Ca ii feature to be purely in emission. We fit a Gaussian profile to the emission feature, to further estimate the velocity of the ejecta material. By assuming the feature is solely produced by the three transitions of the Ca ii triplet, we can estimate the ejecta velocity, and the


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Authors thank the Centre National d’Études Spatiales for its financial support. We thank Laura Portinari for very useful discussions. We thank the referee for his helpful report and his comments.


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

object. This is because we need it for the de-blending process, but it is excluded from the rest of the analysis. For the rest of the region, we had to use a different tracer. Good examples are either 24 m (e.g. Marsden et al. 2009 ; Pascale et al. 2009 ; Elbaz et al. 2010 ; Béthermin et al. 2012 ) or radio (e.g. Ivison et al. 2010 ; Magnelli et al. 2010 ; Basu et al. 2015 ; Rujopakarn et al. 2016 ; Delhaize et al. 2017 ). Even though an MIPS 24 m map was available, the beam size is still large (∼6 arcsec) and galaxies will still be blended. Instead we used the 10 cm (3 GHz) JVLA map as our tracer, as it has resolution comparable to that of our ALMA map. We identified 319 significant sources in the radio map (within the same area of the SCUBA-2 maps), and combine these with the 12 ALMA sources. These sources were then passed through XID+ to obtain fluxes for both the PACS and SPIRE maps. A specially modified version of XID+ was used to work with the SCUBA-2 maps, so we also have de-blended fluxes for both 450 and 850 m. 3.3 Association with radio sources We then went about associating each of our SCUBA-2 sources with at least one radio source (and therefore can associate with optical and NIR sources). To determine the most likely radio source we use the standard Poissonian probability of positional match similar to the method outlined in Downes et al. ( 1986 ). This value P gives us the probability of a source not being associated with the SCUBA-2 source and is given by where n is the number density of sources in the radio map, and θ is the separation between the SCUBA-2 source and the radio source. We found all radio sources within 15 arcsec of the SCUBA-2 source, and calculated the P value for all of them. For galaxies that had similar P values we picked the source that was reddest in the IRAC bands, as it has been shown that sub-mm galaxies tend to be redder at these wavelengths (e.g. Ashby et al. 2006 ; Yun et al. 2008 ; Hainline et al. 2009 ). We did not worry about the central source (source 850_1) as we use the ALMA sources from C18 , which have been shown to have association with optical and NIR sources. Using the prescriptions laid out in Ivison et al. ( 2002 ), Chapin et al. ( 2009 ), and Chen et al. ( 2016 ), we considered a reliable match to have a P ≤ 0.05 and a tentative match to have 0.05 ≤ P ≤ 0.1. Anything with a P > 0.1 is considered an untrustworthy match and removed. We found that all but two sources had either reliable or tentative matches, with 850_12 and 850_19 having sources too far to be considered significant. Even though 850_18 and 850_28 had low P values, in the optical and NIR images they were obscured by nearby stars and hence removed from the sample. Finally 850_30 was removed because there was no radio source within 15 arcsec. Applying these cuts we ended up with 37 sources that we can calculate redshifts for, and determine if they are likely to be within the cluster or not. 4 REDSHIFT DETERMINATION To


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engine half-opening angle θ 0 = 0.2 (denoted as SJ0.2-EH). The jet engine parameter values for these three models are listed in Table 3 . Table 3 Jet Engine Parameters Note. L 0 and τ 0 represent jet engine power and average jet engine duration, respectively. The energy-to-mass ratio η 0 and injected Lorentz factor γ 0 are set to the same value for all of the jet engine models. θ 0 is the half-opening angle of the injected jet engines. To better interpret the role of each fluid component, we use three passive scalars X i to track the mass fraction of each individual component filling the cells. The subscript i labels each individual component: 1 for a stellar progenitor, 2 for ISM material, and 3 for jet engine material. Initially, X 1 ( X 2 ) is set to 1(0) inside the progenitor and 0(1) in the ISM. Three auxiliary equations are solved accordingly (Duffell MacFadyen 2013 ):The conserved mass for each component () is updated based on the density flux through the cell boundary and the addition of source term (for the injection of jet engine material). Dividing the individual conserved mass M i by the total conserved mass () gives us the new primitive passive scalar X i . 4.2. Dynamical Details of the FTD Jet Simulation 4.2.1. Launch of the Jet Engine Figure 6 shows the early evolution of the jet engine flow upon injection. The ram pressure generates a bow shock. Dense stellar material gets pushed to the side, forming a cocoon that confines the engine outflow. A high-density wedge of stellar material develops at the head of the jet. It shreds jet engine materials from the head. These engine materials curl back, forming vortexes. These vortexes then detach from the jet and get swept backward relative to jet propagation. This vortex shedding phenomena is, generally speaking, similar to that found in previous simulations (Scheck et al. 2002 ; Mizuta et al. 2004 ; Morsony et al. 2007 ). The speed of the jet head keeps increasing and soon exceeds the local sound speed (at the time t = 1.5s, the Lorentz factor of the head of the jet is ∼2, as shown in Figure 6 ). The backflow becomes quasi-straight to the main jet (Mizuta et al. 2010 ). At early times, the bow shock has a narrow head and a wide tail. When it approaches the surface, the jet head expands in the low-density envelope, as shown in the next subsection (see also, e.g., Zhang et al. 2003 , 2004b ). We use spherical coordinate to conduct simulations. As jets propagate outward, the width of the cell increases. The features of the inner part of the jet (close to pole) may not be fully resolved. We resolve the relativistic shell in the radial direction via the previously described AMR scheme. As the ultra-relativistic jet shell penetrates the progenitor, the stellar material that lies on top of the jet easily gets pushed aside. No strong “plug” instability has been seen (Lazzati et al. 2010 ; Mizuta Ioka 2013 ; Gottlieb et al. 2018a ; Xie et al. 2018 ). Figure 6. Early time snapshots of jet