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

length. N J can be written as where n 3 is the number density of the gas in units of 1000 cm −3 , 5, t is the turbulent velocity (approximated here as the velocity dispersion of the cloud) in km s −1 , and μ is the mean molecular weight that we will assume to be 2.3 for a gas composed of H 2 and He. The cloud is gravitationally unstable to collapse if N ≥ N J . The volume density can be obtained from Table 2 by taking the average column density, multiplying by the inverse of the OH/H 2 abundance, and dividing by the path length through the cloud. If we assume the cloud extends in the radial direction, the same amount as in the plane of the sky, the path length would be ≈1–4 pc for distances ranging from 400 to 100 pc. In the most extreme low column density case (), n has a value of 34–140 cm −3 . All other values of T ex lead to higher average densities. For these estimates of n, N J ranges from 3.7 to 7.5 × 10 21 cm −2 . The highest column density derivable from the OH data in Table 2 is based on . Using this value and the OH/H 2 abundance leads to an average N (H 2 ) of 1.1 × 10 21 . Even comparing the highest cloud column densities with the lowest values of N J leads to the conclusion that the cloud is not gravitationally collapsing. In this respect, G211+63 resembles the bulk of high-latitude molecular clouds that are not bound by gravity and likely breaking up on the sound crossing time (). If this analysis is confirmed for other IVMCs then these objects may be transient structures formed as thermal instabilities in large-scale atomic flows (e.g. Shore et al. 2003 ; Shore et al. 2007 ; Barriault et al. 2010b ). 5.2 Linewdiths compared to CO Désert et al. ( 1990 ) observed only one position in the cloud (which we refer to as the ‘CO peak’) in the CO(1–0) line. They noted one component with a velocity full width at half-maximum (FWHM) of . They also reported other CO observations but of the (2–1) line from the IRAM 30 m radio telescope that showed two distinct velocity components like the ones we observe for positions 1–3. They give no line parameters but comment that the strength of the two peaks was highly variable within two beams (about 30 arcsec) of the central observation at (l, b ) = (210.927°, 63.280°). They do show a spectrum for the central CO(2-1) position where the two components are each only two channels wide. Their IRAM observations were made at resolution so the individual components have to be less than wide (FWHM). Our OH linewidths are clearly larger than the CO lines in four out of seven instances. The reason for this behaviour is difficult to ascertain because the CO and OH observations are at significantly different sensitivities and resolutions. The behaviour of molecular gas at cloud edges is not often discussed and there is little consensus on even the phenomenology of spectral lines at cloud edges. If the OH main lines are tracing the diffuse outer regions of the molecular cloud, then the broader profiles could be


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

Acknowledgements We acknowledge the help of Roberto Menezes, Rogério Riffel, and Rogemar Riffel in reducing a Gemini spectrum of NGC 3115, the continuum of which unfortunately was dominated by stellar emission and contained no information on the LLAGN. We acknowledge useful discussions with João Steiner, Alexander Tchekhovskoy, and Massimo Gaspari. This work was supported by FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo) under grants 2015/26831-1 and 2016/24857-6.


O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 B-Instrument O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject O O O O O B-Model O O O O O O O O O O O O O B-CelestialObject O O O B-Instrument O O B-Telescope O O B-Telescope O O O O O O O O B-Telescope 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 B-CelestialObject O O O O B-Instrument O B-Instrument 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-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 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 B-Citation I-Citation I-Citation

prior. Since we benefitted from transit observations that span more than three years, we did not use a prior on the period and time of inferior conjunction of the transiting planet. 3.4. Results We present in Table 3 the median and 1 limits of the marginalised posterior distributions after running five chains of 100 000 accepted steps (considering a 20% burn-in phase). The acceptance rate is 25% (40% for the burn-in phase). The convergence of the chains is validated by the test of Gelman Rubin (1992) (PSFR better than 1.01), and the autocorrelations are shorter than 2000 steps. Including the second planet in the model undoubtedly improves the fit. The rms of the CORALIE data after the two-planet fit is ten times smaller than after a one-planet fit. The best fit solution is plotted in Fig. 8 for the transit light curves and in Fig. 9 for the radial velocities. Again, the values provided in Table 3 are not the ones used in Figs. 9 and 8 . We checked that they represent a self-consistent set of parameters by comparing the BIC using both sets of values (best fit and median of the posterior distribution) and get compatible results. Table 3 Median and 1 limits of the posterior marginalised PDFs obtained for the WASP-41 system derived from our global MCMC analysis. Notes. (*) Assuming zero albedo and efficient redistribution of energy. Fig. 8 WASP-41b transit data (blue: FTS ; green: TRAPPIST ; red: Danish ) and best fit model (black line). The TRAPPIST light curve was obtained by binning the data from five transit observations, and the Danish one from one full and one partial transit observations. Each point corresponds to a 7.2 min bin. Fig. 9 WASP-41 radial velocity data (blue: CORALIE, green: HARPS; red: HARPS RM sequence) and best fit model (black line). Top : phase-folded on the period of the inner planet (outer planet subtracted). Middle : zoom on the Rossiter-McLaughlin effect. Bottom : phase-folded on the period of the outer planet (inner planet subtracted). The best-fitting model suggests a misaligned planet with a projected orbital obliquity of . However, the uncertainties are large (see Fig. 10 ), and the data do not allow an aligned orbit to be excluded (). The rotation velocity expected from the photometric rotation period of the star (2.44 km s) is compatible within the error bars with the spectroscopic (2.64 0.25 km s), suggesting that the star is equator-on. That reinforces the possibility of an aligned planet. 4. Discussion We have shown that finding long-period planets with instruments such as CORALIE is still possible around active stars. Recognising the periodic structure of activity-related signals is essential to avoiding false detections. While spots or plages induce signals at the rotation period of the star, the evolution of their coverage of the stellar surface is correlated with the magnetic cycle of the star. Such cycles have periods of several years and must be distinguished from long-period companions. Lovis et al.


B-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 B-Instrument B-Citation I-Citation I-Citation I-Citation O O O B-Telescope 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 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-Instrument O O B-CelestialObject I-CelestialObject O O O O O O O O O O O B-Wavelength I-Wavelength O O B-Wavelength I-Wavelength 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 B-Telescope O O B-CelestialObject I-CelestialObject O B-Instrument O O O B-Wavelength O O O O O B-Wavelength I-Wavelength O B-Wavelength O B-Telescope B-Citation I-Citation I-Citation I-Citation O O O O B-Instrument I-Instrument B-Instrument O B-Instrument O O O O O O O B-Instrument I-Instrument 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 B-Wavelength I-Wavelength O O O O O O O O O O O O O O B-Wavelength I-Wavelength B-Citation I-Citation I-Citation I-Citation O O O O O O B-Instrument I-Instrument O O O O O O B-Instrument I-Instrument B-Instrument O B-Instrument 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 B-Telescope O B-Wavelength 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 B-CelestialObject O O B-Wavelength O B-Wavelength O O O O O O B-Telescope O O O O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O B-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-URL O O O O O O O O O O O O O O O O O O O O B-CelestialObjectRegion I-CelestialObjectRegion I-CelestialObjectRegion O B-CelestialObject O O O O O B-CelestialObject O O O O O O O


O O O O O O O B-Dataset I-Dataset I-Dataset I-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 O O O O O O O O O O O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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-CelestialObject I-CelestialObject O B-CelestialObject I-CelestialObject 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject 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 B-CelestialObject I-CelestialObject O B-CelestialObject I-CelestialObject O O O O O O O O O B-Telescope O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Telescope O O O O O O O O O B-CelestialObject I-CelestialObject B-CelestialObject I-CelestialObject B-CelestialObject I-CelestialObject O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O 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 B-Software O O O O O O O O O O O O O O O O O O O O

could hinder follow-up observations. 6 CONCLUSION The ASKAP Early Science data set presented in this paper verifies that the array and its associated processing pipeline askapsoft – both in moderately preliminary states – are successfully producing scientifically useful data. Overall, within the 12-beam image cube centred on the NGC 7232 group, we detect 17 H i sources. Six of these detections are well-known H i -rich galaxies including one fully interacting pair. Five of these detection are newly resolved H i galaxies with identifiable stellar counterparts. The remaining six H i detections are likely tidal debris associated with the NGC 7232/3 triplet. The triplet is a complex system. The H i components of NGC 7232 and NGC 7233 appear to be fully intertwined. NGC 7232B still retains most of its gas but shows evidence that it is beginning to interact with the other two galaxies. H i clouds C5 and C6 are likely tidal clumps that have been produced by the triplet system and possibly indicate the projected spatial location of two tidally formed tails of H i . If H i cloud C6 is moving away from its parent galaxies, it has sufficient mass to eventually decouple from the tidal tail and possibly develop into a long-lived TDG. H i clouds C1–C4 might have been produced by the triplet system, or these clouds could indicate an earlier interaction event involving another group member, such as IC 5181. A portion of the H i within this region, which was originally identified as belonging to HIPASS J2214−45 is likely diffusely distributed and lies below the detection threshold of our current ASKAP observations. Accordingly, it is difficult to ascertain the origins of the H i bridge that appears to be connecting NGC 7232/3 and IC 5181. Future work would include adding short-spacing/single-dish observations to the ASKAP data in order to recover more of the diffuse gas in and around the tidal features, in order to further understand the interaction processes that are taking place. The high-resolution capabilities of ASKAP produced moderately well-resolved moment maps of four galaxies (i.e. IC 5171, ESO 288−G049, ESO 298−G010, and ESO 289−G011) that can be used for further kinematic analysis. The newly detected H i counterparts of five stellar galaxies indicate their membership to the group. These nine galaxies provide a more complete picture of the group environment surrounding the NGC 7232/3 triplet. There are many areas where the data quality and processing procedure can be greatly improved for ASKAP. The addition of more antennas – to provide more complete sky coverage and achieve higher sensitivity with less integration time – along with the use of the on-dish calibration system and an overall improved observing method will show vast improvements to the data quality. With expanded computing systems and a more robust askapsoft pipeline, larger data sets can be processed more efficiently. The observations and results presented in this paper serve as one


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We acknowledge financial contribution from the agreement ASI-INAF I/037/12/0. NLP and LS acknowledge the grant from PRIN-INAF 2014 ‘Towards a unified picture of accretion in HMXRBs’.


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-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-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 O B-Citation I-Citation I-Citation I-Citation 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 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 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 B-Model I-Model 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 O O O O O O O O O O O O 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-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 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-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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 B-Software O O O O O O O O O O O

(Shu, Adams Susana 1987 ) do not also play a role in bringing ε SF down. We note, however, that if clouds form stars preferentially in one short burst with ε SF ≈ ε min , this presents a challenge to the survivability of these star clusters because star clusters with ε SF ≲ 10 per cent tend to dissolve after the natal gas has been removed (Baumgardt Kroupa 2007 ; Shukirgaliyev et al. 2017 ). We speculate that studies of star clusters with N -body simulations that include a centrally peaked star formation profile as in the model by Parmentier Pfalzner ( 2013 ) together with slow gas removal with velocities of approximately 10 km s −1 as predicted by our warpfield2 simulations will result in a higher survival rate even for low star formation efficiencies. 4.3.1 Giant clumps Giant clumps at redshift ∼ 1−3 with gas masses of have typical surface densities of pc −2 and are consistent with isothermal spheres, i.e. α = −2 (Ceverino et al. 2012 ). In this paper we probe the lower mass end of such clumps. Our results indicate that they are more resilient against destruction by stellar feedback than clouds with shallower density profiles. As noted above, this is due to the larger binding energy of the giant clump and in particular of the inner region when α = −2 (see equation 28 ). As more of the gas mass is accumulated in the inner regions, an expanding shell in a cloud with such a steep density profile decelerates faster, making it more susceptible to energy loss via leakage of hot gas after gravitational fragmentation and via strong cooling. Our results indicate that giant clumps at the low-mass end () can be destroyed by a single starburst with ε SF ≥ 4 per cent for pc −2 ( per cent for pc −2 ). Were the star formation spread out over the lifetime of the clump (∼30 Myr), this would correspond to ε ff = 0.5 per cent ( per cent for pc −2 ). This result is in line with simulations by Oklopčić et al. ( 2017 ) but puts analytic models by Krumholz Dekel ( 2010 ) into question who argue that star formation efficiencies per free-fall time of a few per cent are insufficient to disrupt a giant molecular clump (they focus on clumps with though). Our result does not yet take into account that the metallicity in galaxies at ∼ 2 is approximately a factor 2 lower than in present-day galaxies (Yuan, Kewley Richard 2012 ), which will affect the amount of radiative cooling, the strength of metal-line-driven winds of massive stars, and the coupling of radiation to the ISM. We plan to revisit giant clumps with warpfield in the future. 5 CONCLUSION In this paper we have presented improvements to the 1D stellar feedback code warpfield (Rahner et al. 2017 ). warpfield is a fast, publicly available code which models the formation of a shell around a massive cluster and how this shell is affected by stellar winds, radiation, and SNe, as well as gravity. The improvements which are part of a new code release, warpfield2 , include, but are not limited to, a better treatment of


O O O O O O O O O B-Telescope I-Telescope I-Telescope O O O O B-Grant I-Grant O B-Grant I-Grant O O B-Organization O O O O O O B-Observatory I-Observatory O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O O O O O O B-Organization O O O O B-Collaboration I-Collaboration O B-Organization I-Organization I-Organization B-Location I-Location O B-Organization I-Organization I-Organization B-Location B-Organization B-Location O B-Organization I-Organization I-Organization B-Location B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Location O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Location O O O O O O O O O O B-Observatory B-Telescope O O B-Observatory I-Observatory O O O B-Proposal O B-Person O O O O O O O O O O O O O O O O O O

This work is based in part on observations from Spitzer Space Telescope and was supported by RSA 1415602 and RSA 1346842, issued by JPL/Caltech. Based on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (United States), the National Research Council (Canada), CONICYT (Chile), the Australian Research Council (Australia), Ministério da Ciência, Tecnologia e Inovação (Brazil) and Ministerio de Ciencia, Tecnología e Innovación Productiva (Argentina). This work is also partially based on observations made with ESO-NTT Telescope at the La Silla under programme ID 184.D-1140 (PI Benetti). We would like to thank the anonymous referee for their insightful comments during the revision of this paper.


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We thank Roger Griffin for radial-velocity monitoring and calculation of the orbital elements for HIP 99725. We acknowledge support from the Research Council of the Lithuania under grant No. MIP-85/2012, from the Latvian Council of Science under grant No. 09.6190, and from the Universidad Nacional Autónoma de México by way of project IN103014 of the PAPIIT/DGAPA. This research has made use of the Simbad database operated at CDS, Strasbourg, France. We greatly thank the referee for his constructive and valuable discussions and comments which have improved this paper.


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

smaller than the symbols. Right: Similar to the left panel, but showing the distribution of . All spectra were visually inspected for the presence of Ca ii triplet emission. The spread in EW values is extremely large at low S/N values due to noise (compare the left and right panels of Fig. 3 ), but rapidly tightens as the S/N increases, making it trivial to identify genuine emission features such as SDSS J1228+1040. Closer to the bulk EW distribution, it becomes difficult to detect Ca ii triplet emission such as that of SDSS J0738+1835 and SDSS J1043+0855 (see Fig. A1 for the EW values). We therefore chose to limit the sample used for the following statistical analysis to spectra with S/N ≥ 5, wherein if there were any additional emission features with an EW similar to the gaseous debris discs in our sample we should have detected them. Assuming that we can only detect gaseous emission in the spectra of systems above S/N = 5, the number of white dwarfs in our sample reduces to 7705, which we use for the calculations in the next section. 2.1 The occurrence rate of gaseous discs at white dwarfs We find no new gaseous discs in our magnitude and S/N limited Gaia /SDSS sample, resulting in a total of five detected gaseous components to debris discs out of 7705 systems. Using Bayes’ theorem we calculate the probability distribution, p ( f | n, t ), of an occurrence rate, f , of a gaseous debris disc at a white dwarf, given n detections out of t systems as where p ( n | f, t ) = f n (1 − f ) t − n is the binomial distribution, p ( f ) is the prior distribution of f , and p ( n, t ) is the probability distribution of detecting n gaseous disc hosts out of t systems which is a constant. We assume an uninformative prior distribution known as the Jeffreys prior (Jeffreys 1946 ), which for the binomial distribution is where B is the beta function. Substituting this prior into equation ( 1 ) results in Taking the median and 1σ intervals of this probability distribution (which is independent of the proportionality constant) with n = 5, and t = 7705, we find that 0.067 ± per cent of white dwarfs host a debris disc with a detectable gaseous component (Fig. 4A ). This is significantly lower than the occurrence rate of detectable dust discs around white dwarfs, which has been estimated by various studies to be 1–3 per cent (Farihi et al. 2009 ; Girven et al. 2011 ; Rocchetto et al. 2015 ; Rebassa-Mansergas et al. 2019 ; Wilson et al. 2019 ). For further discussion, we adopt the estimate of Wilson et al. ( 2019 ), 1.5 ± per cent, calculated using an unbiased sample of 195 white dwarfs observed with Spitzer containing three dusty debris discs. We note, however, that using equation ( 3 ) with n = 3 and t = 195, we obtain a slightly different occurrence rate of 1.6 ± per cent, and the probability distribution of this occurrence rate is shown in Fig. 4(B) . These two occurrence rates of dusty debris discs at white dwarfs are in agreement, and the difference results


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

of any model for distributions of the properties of the clouds in the BLR. In fact, in the current analysis, our only constraint is to suppose that all the hydrogen lines are emitted from the same clouds with certain density and excitation conditions, which is a reasonable assumption considering the similarity of the profile of the various H i lines we analysed for each object. Additionally, if more than one grid point is a good match to the data, we adopt a simple weighting scheme where we calculate median Φ H , n H and line ratios from these point. A detailed description of our photoionization modelling scheme is given in Section 3.3 . 3.3 Extinction measurements The extinction affecting a set of line ratios may be determined by comparing the measured ratios with their theoretically predicted intrinsic values. In the case of the He ii lines, considering the He ii λ4686/He ii λ10 126.4 line ratio is expected to be similar to the case B prediction even in the BLR spectrum (Bottorff et al. 2002 ), we estimate the extinction to both the NLR and BLR assuming an intrinsic He ii λ4686/He ii λ10 126.4 line ratio of 3.77, corresponding to the case B prediction for a temperature of 10 000 K and a density of 10 6 cm −3 . If broad He ii λ4686 Å is not observed, we estimate a lower limit to A V (BLR) based on the broad He ii λ10 126.4 Å flux. This was done decreasing the observed broad He ii λ4686/He ii λ10 126.4 ratio in steps of 0.1, starting from the intrinsic value of 3.77, until the broad He ii λ4686 Å line becomes indistinguishable from the continuum. The lower limit to the extinction is then derived from this ratio. In Table 2 , we list A V (NLR) and A V (BLR) as estimated from the He ii lines for each object. The errors in these estimates were derived assuming an uncertainty of 20 per cent in the observed line ratios. Table 2. Extinction to the narrow-line region, A V (NLR), and extinction to the broad-line region, A V (BLR), derived from Balmer and Paschen H i line ratios and the He ii λ4686/He ii λ10 126.4 line ratio as described in Section 3.3 . In objects where broad He ii λ4686 is not detected, a lower limit to A V (BLR) was determined from broad He ii λ10 126.4 Å. These lower limits are marked with an asterisk. Abbreviated name: MCG–05-14-012, MCG–05-23-16 and MCG–06-30-015. In the case of the H i lines, determining A V (NLR), is a straightforward process since, as outlined in Section 3.1.3 , a fixed set of intrinsic line ratios can be assumed. Deriving the extinction A V ( NLR ) to the NLR was done during the step of fitting and subtracting the narrow lines as described in that section. In Table 2 , we list A V (NLR) as estimated from the H i lines for each object. The errors in A V estimates were derived assuming an uncertainty of 20 per cent in the observed line ratios. The extinction to the BLR is derived in a different way, since the H i intrinsic line ratios are not known. To do so, we followed these steps. We compared the


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

TT is grateful to K. Nitadori and J. Makino for the tuning of our code. The computations in this research were performed on the K computer of the RIKEN AICS through the HPCI System Research project (Project ID:hp120304) together with XC30 of CfCA in NAOJ. YS was supported by JSPS postdoctoral fellowships for research abroad. This study was supported in part by the Grants-in-Aid for the Scientific Research from the Ministry of Education, Science and Culture of Japan (Nos. 24103006, 24244036, 26104001, 26707013, 26870823, 15H01039 and 15H00789) and by HPCI Strategic Program of Japanese MEXT.


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 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 O O B-Person 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 O O O O B-Collaboration I-Collaboration I-Collaboration I-Collaboration I-Collaboration I-Collaboration I-Collaboration I-Collaboration O O B-Organization I-Organization O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O B-Organization I-Organization I-Organization B-Person O O O B-Organization O O B-Grant O O O O O O O B-Software I-Software O B-Citation I-Citation O B-Software I-Software O B-Citation I-Citation O O B-Software I-Software O B-Citation I-Citation I-Citation I-Citation O

CV thanks Andreas Floers, Stefan Lietzau and Markus Kromer for stimulating discussions during various stages of this project. The authors gratefully acknowledge Stefan Taubenberger for sharing his enormous expertise in the field of supernovae and for being a key member of the supernova cosmology project that motivated this work. CV would also like to thank Michael Klauser for providing help and guidance during the start of this project. The authors thank the anonymous reviewer for valuable comments. This work has been supported by the Transregional Collaborative Research Center TRR33 “The Dark Universe” of the Deutsche Forschungsgemeinschaft and by the Cluster of Excellence “Origin and Structure of the Universe” at Munich Technical University. SAS acknowledges support from STFC through grant, ST/P000312/1. Data analysis and visualization was performed using M ATPLOTLIB ( Hunter 2007 ), N UMPY ( Oliphant 2006 ) and S CIPY ( Jones et al. 2001 ).


O O O O O O B-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant O O O O O O O O O O O O O O O B-Organization I-Organization O O B-Observatory I-Observatory I-Observatory 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 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-Organization I-Organization I-Organization I-Organization O O O O O O O O O O O O O O O O O O O O

This work was supported by the cluster of excellence “Origin and Structure of the Universe.” Thanks to the referee for valuable comments that substantially improved the paper. I thank my CAST group at the University Observatory, Munich for inspiring discussions and suggestions. Special thanks also go to Edvige Corbelli, Avishai Dekel, Ken Freeman, Pavel Kroupa, Go Ogiya, Jerry Ostriker, Paolo Salucci, and David Spergel for interesting discussions and a careful reading of the manuscript. Finally, I would like to thank the Harvard Center for Astrophysics for support, lively discussions, and an infinite supply of coffee that was essential and the driver for finishing this paper.


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 O B-Person I-Person O O O 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-Observatory O O O B-Observatory I-Observatory I-Observatory I-Observatory O B-Proposal I-Proposal I-Proposal O O O O O O O B-Location I-Location B-Grant I-Grant O B-Organization B-Grant I-Grant I-Grant

It is a pleasure to thank Seppo Mattila, Rubina Kotak, Nancy Elias-Rosa, Stephen Smartt, Anders Jerkstrand, John Eldridge and Justyn Maund for useful discussions and comments on this work, and Gerry Gilmore for ongoing support. We thank the anonymous referee for a careful reading of the Letter. This Letter is based on observations made with ESO Telescopes at the La Silla Paranal Observatory under programme ID 094.D-0351. This work was partly supported by the European Union FP7 programme through ERC grant number 320360.


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

midplane values n e0 and n CR0 for the electron densities. For (corresponding to ), , and , we have . This is large compared to the typical Galactic magnetic field strength of a few , so Faraday rotation effects are weak. We perform the line-of-sight integration by computing on a ( θ , φ ) mesh with 36 × 72 meshpoints for distances s from the observer going up to in steps of . 4.2.3. Results from the Mean-field Model In Figure 3 we show the results for Model B of Brandenburg Furuya ( 2020 ). In spite of the parameters being unrealistic for the Galaxy, there are characteristic features that are similar to what is seen in Figure 1 for the Galaxy: positive Q at φ = 0 and 180°, along with negative E at φ = 90° and 270°. The results for U and B are not immediately obvious because there are two nearly equally big patches of opposite sign in each hemisphere. Only after φ -averaging do we recognize a latitudinal dependence that is similar to that of the Galaxy; see Figure 4 . The observed sign of emerges only when we place the observer at a distance sufficiently far away from the Galactic center ( μ = A), while for smaller distances ( μ = B), the sign changes and the profile becomes similar to that shown in the top right panel of Figure 1 of Brandenburg ( 2019 ). Faraday rotation is weak, but it contributes a profile that is symmetric about the equator. This is because the global magnetic field has quadrupolar symmetry; see Brandenburg ( 2019 ) for a corresponding result for a dipolar field. Changing the sign of α 0 results in a qualitatively different (oscillatory) dynamo, but, to our surprise, it does not change the sign of . The sign only changes when the differential rotation changes and thereby the global Galactic spiral. Changing the signs of α 0 and Ω 0 simultaneously has the advantage of leaving the dynamo properties unchanged. Figure 3. Polarization results for the mean-field model with the Faraday rotation term in Equation ( 6 ) included. Top: and . Bottom: and . Figure 4. Azimuthally averaged polarization results for the mean-field model with Faraday rotation using (solid lines) and without Faraday rotation (dashed lines). Top: and . Bottom: and . The statistical error of the mean and the standard deviation are indicated by dark and light shades, respectively, except for panels (b) and (d), where only the former is shown. An important difference between model and observation is the fact that in our model, the amplitude of is several hundred times smaller than that of , while for the Galaxy, it is only about 10 times smaller; see Table 1 . We recall that the quadratic EE correlation for dust polarization was found to be about twice that of the BB correlation (Planck Collaboration 2016 ). This came as a major surprise (Kandel et al. 2017 ) and triggered numerous investigations trying to explain this (Kritsuk et al. 2018 ). In the present Letter, however, we have not studied quadratic correlations, but the signed functions E and B themselves.


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

sets in some specific cases – in particular in the second outermost shell when using projct . We speculate that these discrepancies may be due to a combination of remaining calibration issues and artifacts propagated when projct is used. Nevertheless, in both cases the deprojected EPIC spectra clearly reveal the presence of central drops for the Fe, Si, S, Mg and Ca abundances. Despite the formal consistency reported above, we note that the uncertainties of the XMM-Newton abundances of Ar and Ca are much larger than the uncertainties of the Chandra measurements. This point is discussed in more detail in Sect. 3.5 . 3.5. Broad-band versus narrow-band fits Whereas fitting the spectra using the full energy band (i.e., typically ∼0.5–7 keV for Chandra ACIS) is the standard procedure for deriving the best-fit parameters, this approach may bias the metal abundance measurements. In fact, since the abundance of a given element is directly proportional to the equivalent width of its line (namely, the ratio between the total line flux and the continuum flux at the centroid energy of the line), incorrect determination of the continuum in the vicinity of the line would lead to incorrect measurement of the corresponding elemental abundance. Because no instrument is calibrated with infinite precision, some slight imperfections of the effective area may produce these local over- or underestimates of the continuum. In the case of very deep observations, that is, when statistical uncertainties become smaller than the above systematic effect, such a bias may become highly significant (e.g., Mernier et al. 2015 ; Simionescu et al. 2019 ). A good way to minimize such biases is to refit the spectra between several local energy bands, each of them including the K-shell emission line(s) used to derive the abundance of a given element as well as part of the surrounding continuum. In these “narrow-band” fits (by contrast to the above “broad-band” approach), the only parameters that were kept free were the (local) normalization and the abundance of the considered element. All the other parameters were fixed to the best-fit value of the broad-band fit. A comparison of the resulting narrow-band fit profiles with the ones obtained using broad-band fits (assuming a vgadem model and using dsdeproj ) is shown in Table 2 and Fig. 4 . We used the 1.5–2.8 keV energy range for Si and S, 2.9–3.5 keV for Ar, 3.3–4.3 keV for Ca, and 5.0–7.0 keV for Fe. Fig. 4. Deprojected profiles of Fe, Si, S, Ca, and Ar abundances, and the Ar/Fe (Fe taken from the broad-band fits) ratio, using broad- (red) and narrow-band (blue) fits, obtained using the vgadem model and the dsdeproj deprojection method. All errors are quoted at the 68.27% (1 σ ) confidence level based on . The blue data points have been shifted slightly on the X-axis for clarity. The narrow-band Fe profile in Fig. 4 is consistent with the broad-band profile and also shows a drop in the innermost two bins (at r ≲10 kpc). 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 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 B-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O B-Observatory B-Instrument 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 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 B-Citation I-Citation I-Citation 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 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 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 B-Instrument 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 B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O B-Instrument O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 B-Instrument O O O O B-Instrument O O O O O O O O

between observed and calculated intensities expressed as a percentage of the observed intensity for all the spectral lines used in the emission measure analysis, except the those beyond 1000 Å. The data are plotted at the wavelength of the relevant line. We show the full line-list with wavelengths for cross-checking in Table 1 . Results are shown for all daily spectra analyzed (1103 observations). 3.2. Comments on the Accuracy of the Li-like Spectral Lines There is a caveat to our threshold condition. While the atomic structure of Li-like ions is very simple (three electrons only) and lines emitted from these ions are therefore expected to be spectroscopically accurate, they are well known to sometimes show anomalously large intensities (Dupree 1972 ; Judge et al. 1995 ). Based on off-limb observations from Hinode /EIS, where the solar corona is close to isothermal and so atomic data discrepancies are readily apparent, Warren et al. ( 2016 ) found that the contribution functions for some O vi lines need to be adjusted upward by a factor of 3.4 to bring them into agreement with other lines. Other work has found that these discrepancies are wavelength dependent (Muglach et al. 2010 ), and several studies have successfully used the longer wavelength O vi lines we use here for composition studies (Feldman et al. 1998 ; Landi Testa 2015 ). In our analysis, we also found that the Li-like O vi 1031.93 Å, O vi 1037.64 Å, Ne viii 770.42 Å, and Ne viii 780.38 Å observed line intensities were several factors brighter than the intensities calculated from the EM distribution. Excluding the Ne viii lines and adjusting the G ( T , n ) functions for O vi 1031.93 Å and O vi 1037.64 Å upward by the factor of 3.4 determined from EIS off-limb spectra by Warren et al. ( 2016 ) improves the minimization of the EM solution, and helps to anchor the distribution around their formation temperatures. We therefore make the adjustment solely for the purpose of determining the best EM solution. We make no adjustment for the subsequent abundance ratio correction since Ne viii is also Li-like and it is necessary to treat them consistently. Note also that the Warren et al. ( 2016 ) adjustment factor was computed using off-limb EIS spectra taken near solar minimum in 2007, November. Our analysis suggests that this factor is also representative of the rest of the solar cycle, since the computed O vi line intensities are maintained within 25% of the observed intensities in all the daily spectra. If there was a cycle dependent variation greater than 25% in this adjustment factor, perhaps due to the presence or absence of the high temperature component in the emission measure found by Morgan Taroyan ( 2017 ), then it would be detected in our analysis as a discrepancy between the calculated and observed intensities. It is interesting that the same adjustment factor works well for both our EVE analysis and the independent EIS off-limb spectral analysis. For a further cross-check of


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

synchrotron emission. The XMM–Newton upper limit (black arrow) and the Fermi -LAT data (red squares) are from this work. The other data are taken from Aliu et al. ( 2014 ) (VERITAS – green diamonds) and Abdo et al. ( 2007 ) (MILAGRO – pink hexagons). The blue and grey butterflies are the HAWC models from Abeysekara et al. ( 2020 ) and from Abeysekara et al. ( 2017 ), plotted for comparison, but not used in the fit. We performed a binned analysis with five bins per energy decade and spatial pixel size of . In the maximum likelihood fitting, the normalization parameter of all the sources within 3° of the ROI centre, as well as the diffuse emission components, was left free to vary. Instead the parameters of all the other sources at more than 3° were fixed to the values given in the 4FGL catalogue (Abdollahi et al. 2020 ). To describe the spatial morphology of MGRO J1908+06, we used the VERITAS emission region at 3σ level (i.e. the outermost contour in Fig. 1 ), while for the spectral model we assumed a power law with photon index Γ = 1.6. This leads to a detection significance in the energy band considered. The γ-ray flux was obtained by binning the γ-ray data in the range from 10 to 1000 GeV into four energy intervals, and performing a binned likelihood analysis in each energy bin. The resulting Fermi -LAT SED is plotted in Fig. 4 . 3.3 X-ray analysis To study the X-ray emission in the vicinity of PSR J1907+0602, we used a 52 ks long observation carried out on 2010 April 26 with the XMM–Newton satellite. We analysed the data of the European Photon Imaging Camera (EPIC)-Metal Oxide Semiconductor (MOS) instrument that was operated in full frame imaging mode and with the medium thickness optical filter. We excluded time intervals with high background, resulting in net exposure times of 36 and 38 ks for the two MOS cameras. Using the Extended Source Analysis Software ( esas 3 ), we extracted the spectra from a circular region of 5 arcmin radius centred at the position of PSR J1907+0602 (excluding a circle of 30 arcsec radius around the source) and from a concentric annular region with radii 5 and 12.5 arcmin. The latter was used to estimate the X-ray background (which in this sky region is dominated by the Galactic ridge diffuse emission). Comparison of the two spectra showed no evidence for diffuse emission associated with PSR J1907+0602, with an upper limit (at 95 per cent confidence level) of 1.2 × 10 −15 erg cm −2 s −1 arcmin −2 on the surface brightness in the 1–10 keV energy range. 4 ORIGIN OF THE γ-RAY EMISSION Emission at TeV energies indicates the presence of ultrarelativistic particles that, in principle, can produce it through inverse Compton (IC) scattering of the cosmic microwave background (CMB), infrared (IR), and/or starlight seed photons by electrons, or through the decay of neutral pions resulting from proton–proton (and/or other nuclei) interactions. In this section, we first explore the possibility that a single mechanism is


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We thank the anonymous referee for constructive comments that helped to improve the paper. This work is partially supported by the Bundesministerium für Wirtschaft und Technologie through the Deutsches Zentrum für Luft und Raumfahrt (grant FKZ 50 OG 1301). V.D. and A.S. thank the Deutsches Zentrum für Luft- und Raumfahrt (DLR) and Deutsche Forschungsgemeinschaft (DFG) for financial support (grant DLR 50 OR 0702). Partial support comes from NewCompStar, COST Action MP1304. Part of this work is based on the publicly available “GBM Accreting Pulsar Histories” provided by the Fermi team.


O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O B-Survey I-Survey I-Survey I-Survey I-Survey B-Survey O B-Citation I-Citation I-Citation I-Citation O O O O O O O B-Survey 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 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 B-CelestialObject 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-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject O 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 B-Wavelength I-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 B-Telescope I-Telescope I-Telescope I-Telescope I-Telescope I-Telescope I-Telescope I-Telescope B-Telescope O O O O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O B-Formula I-Formula I-Formula I-Formula O B-Citation I-Citation I-Citation I-Citation O O O O O O B-Model I-Model I-Model I-Model B-Model B-Citation I-Citation 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 B-Citation I-Citation O O B-Citation I-Citation B-Model O O O O O O O B-Wavelength B-Wavelength B-ObservationalTechniques I-ObservationalTechniques O B-CelestialObject O O O O B-Instrument I-Instrument I-Instrument B-Instrument O O O B-Telescope I-Telescope I-Telescope I-Telescope I-Telescope B-Telescope O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Telescope O B-Proposal O B-Person I-Person 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 B-Wavelength I-Wavelength O O O O O O O O B-Wavelength O O O O O O O B-Survey

) but in the range of the H α -excess galaxies at redshifts ∼4−5 that were recently identified in the Spitzer UltraVISTA ultra-deep stripes survey (SMUVS survey; Caputi et al. 2017 ). An important fraction (15%) of the SMUVS galaxies in the 9.4 ≤ log( M stellar [ M ⊙ ]) ≤ 11.0 mass range appear to be in a starburst phase with SFR of hundreds to thousands M ⊙ yr −1 and sSFR well above 24 Gyr −1 , and up to 120 Gyr −1 . The SMUVS galaxies in the starburst phase account for more than 50% of the cosmic SFR density at redshifts ∼3.9−4.9. Therefore, extreme UV luminous galaxies such as BOSS-EUVLG1 could represent the short lived phase of this class of H α -excess galaxies, and could be important contributors to the SFR density at intermediate and high redshifts. BOSS-EUVLG1, therefore, brings on the opportunity to investigate the presence and properties of ionized gas outflows for the first time in this class of extreme star-forming galaxies. In this article, we report the detection of the ionized phase of the outflow in BOSS-EUVLG1 using the H α emission line. Section 2 describes the observations and calibrations of the H α spectrum. Section 3 presents the analysis of H α emission and rest-frame UV absorption lines. The results of the analysis and interpretation as outflowing material are presented in Sect. 4 , including the overall kinematic and mass (Sect. 4.1 ), the outflowing mass rate and mass-loading factor (Sect. 4.2 ), the nature of the energy source (Sect. 4.3 ), and the mass escape fraction into the intergalactic medium (Sect. 4.4 ). The results are discussed in Sect. 5 , focusing in the comparison with low- and high- z SFGs (Sect. 5.1 ), the multi-phase nature of the outflows (Sect. 5.2 ), and the possibility of detecting these outflows with the future X-ray observatory Advanced Telescope for High ENergy Astrophysics (ATHENA; Sect. 5.3 ). Finally, Sect. 6 present the summary and outlook. We adopted H 0 = 67.7 km s −1 Mpc −1 and Ω m = 0.307 ( Planck Collaboration XIII 2016 ) as cosmological parameters and the Salpeter initial mass function (IMF; Salpeter 1955 ) throughout this paper. A factor of 1.66 ( Newman et al. 2012 ) is used to convert the SFRs and stellar masses ( M stellar ) from a Chabrier (2003) to a Salpeter (1955) IMF when using some published data. 2. Observations Near-infrared (Near-IR) long-slit spectroscopy of BOSS-EUVLG1 was obtained with the Espectrógrafo Multiobjeto Infra-Rojo (EMIR) instrument on the 10.4 m Gran Telescopio Canarias (GTC). Observations were taken in two service mode nights – 2020 February 10 and May 8 – in bright Moon and subarcsec seeing (≃0.8′′ full width half maximum) conditions, as part of the GTC program GTCMULTIPLE2E-19A (PI: R. Marques-Chaves). The observations used the K g r i s m with a dispersion of 1.71 Å pix −1 and a 0.8′′-wide long-slit, providing a spectral resolution of 82 km s −1 at ∼2.25 μm. The slit was centered on a bright ( K = 17.43 ± 0.02, AB) reference star (SDSS


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

, and replace the bulge with a rotating bar using the analytic model from Long Murali ( 1992 ). For the bar parameters, we take a mass of 5 × 10 9 M ⊙ , a length of a = 3 kpc, a width of b = 1 kpc, and a present-day orientation of θ 0 = −30° (as in Hattori et al. 2016 ; Erkal et al. 2017 ). We vary the pattern speed between 0 and −100 km s −1 kpc −1 in steps of 0.1 km s −1 kpc −1 (where negative pattern speeds are prograde with the MW disc), more than encompassing the observed constraints on the pattern speed (e.g. Bland-Hawthorn Gerhard 2016 ). We find that the bar has a small effect on the stream, giving slightly different stream tracks depending on the pattern speed of the bar. Thus, the properties of the bar will also need to be marginalized over in order to measure the LMC mass from the misaligned proper motions. 5.4 Effect of LMC on other streams in the Milky Way The predicted misalignment between the stream track and proper motions should also be seen in any streams which receive a large tidal force from the LMC. Given the orbit of the LMC, we expect that the most affected streams will likely be in the southern Galactic hemisphere, e.g. the 11 streams newly discovered in Shipp et al. ( 2018 ), the Phoenix stream (Balbinot et al. 2016 ), the Jet stream (Jethwa et al. 2017 ), or the atlas stream (Koposov et al. 2014 ). In order to determine which are the most affected, each stream will need to be evolved in the presence of the LMC. Interestingly, some works have proposed assuming that stream tracks are aligned with their proper motions to measure the Sun’s proper motion (Majewski et al. 2006 ; Malhan Ibata 2017 ). If the significant misalignment predicted for the Tuc III stream is verified, this means that these methods must account for the perturbation of the LMC or only use streams which have received a negligible perturbation (possibly those in the northern Galactic hemisphere). 5.5 Effect of Tuc III on the Milky Way disc Our analysis in Section 3 found that Tuc III is on a very eccentric orbit with a pericentre of ∼1.8 kpc. This close passage of Tuc III with the MW could induce perturbations in the inner disc of our Galaxy (Feldmann Spolyar 2015 ). For these perturbations to be significant, Tuc III would have needed a substantial mass of ∼10 8 −10 9 M ⊙ and hence would have to be a dwarf galaxy. Given the current data, it is difficult to determine whether Tuc III is a globular cluster or a dwarf (see Li et al. in preparation). However, assuming that Tuc III is a dwarf, if Tuc III’s recent pericentre was its first approach to the MW (and thus Tuc III still retained the bulk of its dark matter halo) there could be detectable perturbations in the MW centre. We note that although we have assumed a disruption age of 3 Gyr, during which our best-fitting orbits have experienced multiple pericentric passages (e.g. Fig. 3 ), our model is not designed to determine when Tuc III began disrupting. Instead, it is designed to match the observed


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Based on observations made with ESO Telescopes at the La Silla Paranal Observatory under program 87.C-0040. We thank the anonymous reviewer for helpful comments and suggestions that helped us to improve our manuscript.


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

Acknowledgments The SILCC project details are available at http://www.astro.uni-koeln.de/silcc . All simulations have been performed on the Odin and Hydra clusters hosted by the Max Planck Computing Data Facility ( http://www.mpcdf.mpg.de/ ). We thank M. Anderson, C. Federrath, J. Mackey, M. M. Mac Low, E. Pellegrini, and X. Shi for useful discussions and Leroy etal. ( 2008 ) and Ekstrm etal. ( 2012 ) for making their data publicly available. AG, SW, TN, PG, SCOG, RSK, and TP acknowledge the Deutsche Forschungsgemeinschaft (DFG) for funding through the SPP 1573 The Physics of the Interstellar Medium. SW acknowledges funding by the Bonn-Cologne-Graduate School, by SFB 956 The conditions and impact of star formation, and from the European Research Council under the European Communitys Framework Programme FP8 via the ERC Starting Grant RADFEEDBACK (project number 679852). TN acknowledges support by the DFG cluster of excellence Origin and Structure of the Universe. RW acknowledges support by the Czech Science Foundation project 15-06012S and by the institutional project RVO: 67985815. RSK and SCOG acknowledge support from the DFG via SFB 881 The Milky Way System (sub-projects B1, B2, and B8). RSK acknowledges support from the European Research Council under the European Communitys Seventh Framework Programme (FP7/2007-2013) via the ERC Advanced Grant STARLIGHT (project number 339177). The software used in this work was in part developed by the DOE NNSA-ASC OASCR Flash Center at the University of Chicago. We thank C. Karch for the program package fy and M. Turk and the yt community for the yt project (Turk etal. 2011 ).


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

agrees well with the assumption. In addition to the reactions presented above, the following unimolecular hydrogen molecule elimination (UHME) process may occur during the photolysis of methanol at low temperatures (Gerakines et al. 1996 ; Hama et al. 2009 ): The reaction products of UHME process may be incorporated into AAs. If these reactions occur in a statistical manner, the frequencies of reactions ( 4 b ) and ( 5 a ) are twice as large as those of their counterparts (reactions ( 4 a ) and ( 5 b ), respectively) because the number of C–H bonds in CH 2 DOH is larger than that of the C–D bond, which may affect the D/H ratio of the reaction products. The production of C–H bonds is also possible from other pathways that do not use methanol as a reactant. Briggs et al. ( 1992 ) reported the formation of various COMs such as glycolic acid (HOCH 2 COOH), glycerol (HOCH 2 CH(OH)CH 2 OH), and Gly after the photolysis of solid mixtures (CO:H 2 O:NH 3 = 5:5:1) at 10 K. Although their gas composition is different from that in our study, similar products can be produced in the present experiment, which has the potential to decrease the deuteration level of Gly. Although the formation of other AAs was not reported by Briggs et al., others reported the formation of various AAs upon the hydrolysis of the organic residues even in the absence of methanol (Muñoz Caro et al. 2002 ), which should have the potential to drastically decrease their deuteration levels. 4.2. Effect of Hydrolysis on Deuteration Levels of Amino Acids We demonstrated that the acid hydrolysis of the organic residues generally results in significant increases in AA abundances, which is consistent with that demonstrated in previous studies (Nuevo et al. 2008 ; Evans et al. 2012 ). On the other hand, there has been no report on the variation in the deuteration levels of AAs after the acid hydrolysis of the organic residues. The present result suggests that the five AAs can be divided into two groups depending on whether the deuteration level decreases upon hydrolysis: those whose D/H is significantly decreased ( α -Ala and β -Ala; referred to as the Ala group) and those whose D/H did not change (Gly, Sar, and Ser; referred to as the Gly group). This indicates that the two groups have different formation mechanisms upon hydrolysis. We propose one possible scenario to explain the observed D/H ratio: we assume that these five AAs are produced by reactions of small radicals during warming of the irradiated ice and that most AAs formed are incorporated into macromolecules via relatively weak bonds such as peptide bonds. Upon hydrolysis, these weak bonds are broken and the unit AAs are released. If this is the only pathway for the formation of AAs, the deuteration levels of the AAs would not vary between the free and bound samples, as is the case for Gly-group AAs. On the other hand, for Ala-group AAs, if there are other formation pathways that do not use deuterated radicals and/or molecules


O O O O O O O B-ComputingFacility I-ComputingFacility I-ComputingFacility I-ComputingFacility I-ComputingFacility I-ComputingFacility B-ComputingFacility O O O O O O O O O O O O B-Software O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization B-Person O O O O O O O B-Fellowship I-Fellowship I-Fellowship I-Fellowship O O B-Organization I-Organization I-Organization B-Person O O O O O B-Organization I-Organization I-Organization B-Grant I-Grant I-Grant B-Person O O O O O B-Organization I-Organization I-Organization B-Organization B-Organization I-Organization I-Organization B-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant O B-Organization B-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant B-Grant I-Grant O O B-Person I-Person O B-Person I-Person O O O O O O O O O O O O O O O O O O B-Person I-Person I-Person O O O O O O O O B-Software B-Citation I-Citation I-Citation I-Citation O B-Software B-Citation I-Citation I-Citation O B-Software B-Citation I-Citation I-Citation I-Citation O B-Software B-Citation I-Citation O O B-Software O B-Software B-Citation I-Citation I-Citation I-Citation O

ACKNOWLEDGEMENTS The authors wish to acknowledge the DJEI/DES/SFI/HEA Irish Centre for High-End Computing (ICHEC) for the provision of computational facilities and support. This work used the BATS-R-US tools developed at the University of Michigan Center for Space Environment Modeling and made available through the NASA Community Coordinated Modeling Center. DÓF wishes to acknowledge funding received from the Trinity College Postgraduate Award through the School of Physics. AAV acknowledges funding received from the Irish Research Council Laureate Awards 2017/2018. SJ acknowledges the support of the German Science Foundation (DFG) Research Unit FOR2544 ‘Blue Planets around Red Stars’, project JE 701/3-1 and DFG priority program SPP 1992 ‘Exploring the Diversity of Extrasolar Planets’ (RE 1664/18). We thank Jackie Villadsen and Joe Llama for their useful discussion on topics of stellar radio emission. The authors would like to thank our referee, Dr Jorge Zuluaga, for his valuable input on this work. Software: bats-r-us (Powell et al. 1999 ), radiowinds (Ó Fionnagáin 2018 ), scipy (Jones et al. 2001 ), matplotlib (Hunter 2007 ), and tecplot and seaborn (Waskom et al. 2018 ).


O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-TextGarbage O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 next shock after one pulsation period. Any dust formed at 1 may thus not accumulate and grow over several pulsation periods in the shocked photosphere. The situation is different at larger radii, where the post-shock gas temperature drastically decreases. 3.2.1. Alumina The alumina clusters chiefly form in the post-shock gas at 1 , and their abundances in the first oscillation are illustrated in Fig. 6 . The formation of AlO involves the dimerisation of AlO through termolecular recombination while AlO forms from the reaction of Al with OH in the first place. The dimerisation of AlO is also described by termolecular recombination to form the AlO dimer, (AlO), which has a binding energy of eV ( Li Cheng 2012 ), and can thus withstand the high temperatures of the post-shock gas. This dimer is considered as the seed that will further condense into alumina grains. Over one oscillation resulting from the first shock at 1 , only a small quantity of alumina dimers forms, reaching an abundance of at . A large fraction of Al stays in the form of molecular rings (e.g., AlO and AlO). Because the dimerisation of AlO and AlO is termolecular and thus dependent on the background pressure, cluster formation occurs over a reduced range of radii in the inner wind and the formation of AlO cluster ceases after 2 . The grain size distributions for alumina in one oscillation at 1 is presented in Fig. 7 as a function of pulsation phase. Because of the high post-shock gas temperatures after the shock passage and the extremely low abundance of alumina dimers, no grains form at . Very small grains start forming after , but coagulation starts to be efficient for dust growth in the phase range , for which gas temperatures span the range K and the alumina cluster abundance reaches a maximum. The distribution peaks at grains in the size range Å, despite the small fraction of AlO clusters available. However, the post-shock gas densities are very high at 1 , as seen from Table 2 , and the clusters coagulate and condense with high efficiency and lead to the formation of AlO grains of small size over one oscillation and pulsation period. Under the assumption that small alumina grains may not survive the passage of periodic shocks, the results show that there exists a steady population of small size (m) alumina grains located in the shocked photosphere at 1 . If we consider that grain growth may also proceed through surface deposition when the grain radius has reached several tens of Å (at and after), the grain size will increase, but the growth will be time-limited and proceed only between . We now consider the extreme case where alumina grains survive the periodic shocks at each shock passage, while molecules are destroyed and reform. We may then investigate grain growth over several pulsation periods. For a gas drift velocity of 0.5 km s, the gas layer at 1 takes 12 pulsations to reach 2 . We thus consider the build-up of dust grains over a number of 12 pulsations for


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

detail. As mentioned before, we identified two mild-Am stars, HD 33204 and HD 46304. We show abundance distributions of these stars in Fig. 10 . A typical Am star exhibits overabundances of iron-peak elements and some heavy elements (Zn, Sr, Zr and Ba), but Ca and Sc abundances of these stars are underabundant (Gray Corbally 2009 ). As can be seen in Fig. 10 , the mild-Am stars in our study have nearly solar abundances of Ca and Sc elements. Only HD 33204 shows overabundances in some heavy elements typical for Am star. In the case of HD 46304, most of lines are blended due to high rotation velocity of the star. These blended lines cause difficulties in abundance calculations. The abundance differences between HD 46304 and a typical Am star can be caused by this effect. In the spectral classification process some stars were defined as metal-poor, mostly taking into account Mg, Mn and Fe lines (see Table 2 ). For these stars, the average abundance of Mg (7.57 dex) was found to be close to the solar abundance. However, the average abundances of Mn (5.13 dex) and Fe (7.27 dex) are slightly lower than the solar abundances. For some of our targets (HD 26298, HD 33204, HD 106103, HD 110379, and HD 126516) chemical abundances were already obtained before the present study. We compared our atmospheric parameters and abundance results with the literature values. Abundances of HD 33204 and HD 10613 were derived by Varenne Monier ( 1999 ) and Fossati et al. ( 2008 ), respectively. In their work, similar methods for abundance analysis were used but different atomic data bases were adopted. For HD 33204 higher abundances of Sc, Mg and Y were obtained in the present study. Our result is consistent with the Am: type peculiarity of this star. For HD 106103 only the Y abundance is different. Abundances of HD 26298, HD 110379 and HD 126516 were derived by Bruntt et al. ( 2008 ) using the equivalent width method and the different atomic data base. In the case of these three stars, the marked differences were detected only for V and Ba abundances. Figure 10. Chemical abundances of Am: stars compared with the solar values (Asplund et al. 2009 ). HD 33204 is represented by stars and HD 46304 by triangles. Additionally, we checked the possible correlations of the element abundances with atmospheric parameters, i.e. T eff , log g and ξ. Similar as in Niemczura et al. ( 2015 ), no correlations were found. Moreover, the element abundances do not depend on v sin i . The same result was found by Fossati et al. ( 2008 ). However, Takeda et al. ( 2008 ) reported negative correlations between v sin i and C, O and Ca elements. Finally, we checked the relations between abundances of iron and other elements. Strong positive correlations were found for Mg, Si, Ca, Sc, Ti Cr, Ni, Y and Ba. Similar correlations between Fe abundances and iron-peak elements were found by Niemczura et al. ( 2015 ). On the other hand, a negative correlation was obtained between Fe and O abundances. 6


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NA and SV thank Denis Erkal for stimulating discussions. We thank the referee, Ray Carlberg, for a constructive report.


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ACKNOWLEDGEMENTS This work was supported by the Science Technology Facilities Council (STFC) (Research Grants ST/L000628/1 and ST/M503599/1). We thank S. Falle for the use of the mg hydrodynamics code used to calculate the simulations in this work and S. van Loo for adding SILO output to it. The calculations used in this paper were performed on the DiRAC1 Facility at Leeds, which is jointly funded by STFC, the Large Facilities Capital Fund of the Department of Business, Innovation and Skills, and the University of Leeds. The 3D volumetric renderings were created using the VisIt visualisation and data analysation software (Childs et al. 2012 ). The data associated with this paper are available from the University of Leeds data repository ( https://doi.org/10.5518/573 ).


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; Tiwari et al. 2019 ), and the hottest loops can live up to multiple hours (López Fuentes et al. 2007 ; Klimchuk et al. 2010 ). Most of the longest lived loops are probably a result of interaction of multiple loop strands, which sequentially heat making the loop bundle live much longer than a loop strand (e.g., Warren et al. 2002 ). Loop 23 in Table 1 shows this behavior of sequential heating (see the animation of Figure 1 ). The coordinates of the center of the box outlining the two footpoints for each loop are also given in Table 1 . For easy identification, the coordinates in bold font indicate that the surrounding box has unipolar magnetic flux; all others have mixed-polarity magnetic flux. We quantified the distribution of magnetic field strength and polarity at each foot of each loop via histograms of LOS magnetograms within the selected footpoint region, in the way presented in Figure 5 for three examples. We use a 6′′ × 6′′ boxed area centered at each foot to obtain LOS magnetogram histograms at each foot. The 6′′ × 6′′ size of the box ensures that the loop foot is completely covered within the box. We have three categories of loops: (1) loops with unipolar magnetic flux in both feet, (2) loops with mixed-polarity magnetic flux in both feet, and (3) loops having one foot in mixed-polarity flux and the other foot in unipolar magnetic flux. Of the 23 loops that we examined, ∼40% (9/23) have both feet in unipolar magnetic flux, ∼4% of loops (1/23) have both feet in mixed-polarity flux, and ∼56% (13/23) have one foot in unipolar and one in mixed-polarity flux. We have considered the presence of mixed-polarity only when the LOS magnetogram at the loop foot contains values ≥20 G of positive or negative minority polarity flux. The random noise level in the LOS magnetograms is about 7 G (Couvidat et al. 2016 ), fairly well below our selected lower limit. We would have counted footpoint 2 of our only category 2 loop as unipolar if there was no minority-polarity pixel with a negative B z value larger than 20 G, i.e., if there were no pixel in the second bin (in 20–40 G range, bin size is 20 G) on the negative/minority polarity side of the zero line in this footpoint box’s histogram in Figure 5 . This case is the most marginal one in our sample—in all other mixed-polarity cases there are several to many minority-polarity pixels with the magnitude of B z larger than 20 G. Because there is only one loop in the category of both loop-feet having mixed-polarity flux, in our discussions we often count it in the category of loops having at least one foot in mixed-polarity flux region. In Figure 2 we show three example loops, one from each of the three categories. In the top row of Figure 2 , we show an example loop that has both feet in unipolar magnetic flux (category 1); the peak time in the hot 94 image comes at 05:02:59 and the associated LOS HMI magnetogram is obtained at 05:02:52. The light curve for this loop in Figure 3 (a) also shows another