O B-CelestialObjectRegion I-CelestialObjectRegion I-CelestialObjectRegion 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 B-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 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 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 B-CelestialObject O O O O B-Telescope O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 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

for NOAA AR 11591. whereby t is in days and t ∈ N is at noon. X 0 is the value we are interested in and will be henceforth called offset. It is used instead of a time average ⟨ X ( t )⟩ t because it correctly accounts for missing data (most importantly the gap in the afternoon of Oct 17) and that t start and t end have a different time of day. Here we have |⟨ X ( t )⟩ t − X 0 | 0.5 G for all X ( t ) in G and 0.01° for . While X 1 and X 2 are used internally during the fitting process to guarantee numeric stability, the results are presented with parameters X 0 , X 3 , and X 4 in Table 2 . X 3 and X 4 are the amplitude and phase of the orbital artefacts. Also listed are the standard deviations of the residuals σ t = σ ( X ( t )− X fit ( t )) and the means of the standard deviations along the contours over the same range in time ⟨ σ ψ ⟩ t . Table 2. Results: fit parameters and time averages. Notes. ( a ) Excluding five snapshots due to faulty 180°-disambiguation: t = 10.22.{12 : 14, 12 : 36, 13 : 36, 14 : 00, 14 : 12}. Levels of magnetic contours. The offsets X 0 from the fits to , and for the 0.5(0.4) I qs contours are then used as contour level on the B ver , | B | and γ LRF maps, respectively. They are discussed in Sect. 3.2 and plotted in Figs. 3 and 5 and the videos. Distance between contours. To quantify how well two contours match we calculated the average distance between them ⟨ d ⟩ ψ , which we define as the area of symmetric difference divided by the length of the intensity contour, l( t ). The area of symmetric difference, Δ a ( t ), is the area surrounded by either of the contours but not both. When averaging in time we weighed by the contour length, giving These average distances between contours are listed in Table 2 in pixel. For ⟨ d ⟩ ψ ≪ 1pixel only the total ordering should be relied upon due to griding and other computational effects. Fit along each contour. For every point along a contour, a reference angle ψ = ∡(PCD) is calculated, whereby P is the point on the contour, C is the centroid of the I c = 0.5 I qs contour in the CCD frame and D is the centre of the solar disc as observed by SDO. The angles are calculated on the sphere. For every time step and every contour, is least square fitted against functions of the form Those fits are plotted in the right panels of the videos (cf. Sect. 3.2 and bottom panels of Figs. 3 and 5 ). Furthermore the time averages of the fit amplitudes are listed in Table 2 . Optimal height difference. Δ h = 465 km was chosen because it minimizes the average distance ⟨ d ⟩ ψ , t between the I c = 0.5 I qs contours after transformation with Eq. ( 1 ) and the B ver contours, whereby the contour level X 0 on the B ver map has been derived with the fit to ⟨ B ver ⟩ ψ ( t ) as described above (Eq. ( 2 )). An optimal height difference of Δ h = 465 km means that the intensity contour at the limb is shifted outwards by 465 km ⋅ r ⊙ / R ⊙ ≈ 0.65′′ ≈ 1.3 pixel. The difference of the formation heights for


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

in the closure phases across these spectral channels at 200 cycles/arcsec (cf. Sect. 4.3 , Fig. 6). However, we cannot currently exclude an uncertainty of the position of the dominant spot of this order in the imaging process. 4.5. Fundamental parameters of R Scl Table 5 Fundamental properties of R Scl used in this work. Notes. 1: Discussion in Sect. 2.1 ; 2: Whitelock et al. (2008) ; 3: integrated photometry, see Sect. 2.1 ; 4: this work, average of our three epochs, see Sect. 4 ; 5: calculated from 2 and 4; 6: calculated from 3 and 4; 7: calculated from 2 and 3; 8: 7 and 8 with evolutionary tracks by Lagarde et al. (2012) ; 9: 6 and 9. Fig. 11 Position of R Scl in the HR diagram together with evolutionary tracks by Lagarde et al. (2012) . The tracks are those without rotation and reach up to the start of the TP-AGB. Masses are ZAMS masses; values in parenthesis are masses at the start of the TP-AGB, that is, at the end of the shown tracks. Table 5 summarizes the fundamental parameters of R Scl that we used in this work, including our adopted values for the bolometric flux and distance, the measured Rosseland angular diameter, and the derived effective temperature and luminosity. We note that the distance to R Scl is quite uncertain, as discussed in Sect. 2.1 , which is reflected in its large adopted error. Figure 11 shows the position of R Scl in the Hertzsprung-Russell (HR) diagram based on the effective temperature and luminosity. This figure includes stellar evolutionary tracks by Lagarde et al. (2012) for zero age main sequence (ZAMS; initial) masses between 1 and 2.5 . These tracks reach up to the start of the thermally pulsing (TP) AGB, at which point the mass range is 0.7 to 2.5 . The position of R Scl is consistent with an evolutionary phase shortly beyond the start of the TP-AGB and with an initial mass interval between 1 and 2 . We also compared the position of R Scl to the tracks of the TP-AGB by Marigo et al. (2013) as shown by Klotz et al. (2013) . Here, R Scl is also consistent with masses at the start of the TP-AGB between about 1 and 2 , that is, not significantly below 1 and not significantly above 2 . These are evolutionary tracks for single stars, while a binary companion has been detected for R Scl. However, based on the estimates for the binary companion mass and separation ( Maercker et al. 2016 ), it is unlikely that the companion has affected the evolution of R Scl to the AGB. As a result, we estimate the initial mass of R Scl to be 1.5 0.5 and the current mass to be 1.3 0.6 . Together with our estimate of the radius, these values correspond to a surface gravity of –0.6 0.4. The mass of R Scl can also be estimated by the pulsation properties. We used the formula from Wood (1990) , where is the pulsation constant, and and are the mass and radius in solar units. We estimated a value of 0.093 0.005 for the given ranges of masses and pulsation periods based on Fox Wood (1982) and assuming fundamental pulsation


O O O O O O O O O O O O O O B-Survey O O O O O O O B-Telescope B-Proposal I-Proposal I-Proposal 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-Survey O O B-URL O O O O O O O O B-Wavelength O O O O O O O O O O O B-URL O O O O B-Person I-Person O O O O O O O O B-Person O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O O O O O O B-Fellowship I-Fellowship I-Fellowship I-Fellowship I-Fellowship B-Person O O B-Organization I-Organization I-Organization I-Organization B-Organization O B-Organization O O O O O B-Person O O B-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant B-Grant O O O B-Organization O O B-Grant B-Person O O O O O O O O O B-Fellowship I-Fellowship I-Fellowship O B-Location B-Person O O O O B-Organization O B-Grant I-Grant I-Grant O B-Organization O B-Grant I-Grant O O B-Organization B-Grant I-Grant I-Grant O O O O O O O O B-Instrument O O O O B-Telescope O B-Organization O O B-Telescope I-Telescope B-Telescope O O O O O B-Organization I-Organization I-Organization B-Organization O B-Location O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O B-Location O O B-Organization I-Organization I-Organization O O O O O O O O O O O B-Software O O O B-Organization I-Organization I-Organization I-Organization O O O O B-Survey I-Survey I-Survey I-Survey O O O O B-Organization O B-Organization

We would like to thank the anonymous referee for the useful comments and suggestions. XXL is an international project based around an XMM Very Large Programme surveying two 25 deg extragalactic fields at a depth of erg s cm in [0.5−2] keV at the 90% completeness level (see Paper I). The XXL website is http://irfu.cea.fr/xxl . Multiband information and spectroscopic follow-up of the X-ray sources are obtained through a number of survey programmes, summarised at http://xxlmultiwave.pbworks.com/ . The authors acknowledge L. Chiappetti for producing a format and catalog compliance report. EK acknowledges fellowship funding provided by the Greek General Secretariat of Research and Technology in the framework of the programme Support of Postdoctoral Researchers, PE-1145. E.K. acknowledges the Centre National d’Études Spatiales (CNES) and CNRS for support of post-doctoral research. Y.J. and the Marie Curie Actions of the European Commission (FP7-COFUND) acknowledges support by FONDECYT grant N. 3130476. O.M. is grateful for the financial support provided by the NEWFELPRO fellowship project in Croatia. F.P. acknowledges support from the BMBF/DLR grant 50 OR 1117, the DFG grant RE 1462-6 and the DFG Transregio Programme TR33. This work is based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/IRFU, at the Canada-France-Hawaii Telescope (CFHT) which is operated by the National Research Council (NRC) of Canada, the Institut National des Sciences de l’Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii. This work is based in part on data products produced at Terapix available at the Canadian Astronomy Data Centre as part of the Canada-France-Hawaii Telescope Legacy Survey, a collaborative project of NRC and CNRS.


O O O O O O O B-Observatory I-Observatory I-Observatory O O O O O O O O O B-Organization I-Organization I-Organization I-Organization O B-Organization I-Organization I-Organization O B-Organization O O O O O O O O O O O B-Organization I-Organization I-Organization O O O O B-Organization B-Grant I-Grant I-Grant B-Grant B-Grant O B-Grant B-Grant I-Grant I-Grant O O B-Organization O O B-Organization I-Organization I-Organization I-Organization O O B-Grant O O B-Organization B-Grant I-Grant O O O O B-Organization O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Grant O O B-Organization O O O O B-Collaboration I-Collaboration O O O O O O O O O B-Survey O O O O O O O O O O B-Location O O O O O O O O O O O O O O O O O O O O O O O O

ACKNOWLEDGEMENTS Based on data obtained at the W.M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and NASA, and was made possible by the generous financial support of the W.M. Keck Foundation. We acknowledge support from NSF AAG grants AST-1312780, 1312547, 1312764, and 1313171, archival grant AR-13907 provided by NASA through the Space Telescope Science Institute, and grant NNX16AF54G from the NASA ADAP program. We also acknowledge a NASA contract supporting the ‘WFIRST Extragalactic Potential Observations (EXPO) Science Investigation Team’ (15-WFIRST15-0004), administered by GSFC. We additionally acknowledge the 3D-HST collaboration for providing spectroscopic and photometric catalogues used in the MOSDEF survey. We wish to extend special thanks to those of Hawaiian ancestry on whose sacred mountain we are privileged to be guests. Without their generous hospitality, the work presented herein would not have been possible.


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

for non-degenerate companion stars to SNe Ia (Ruiz-Lapuente et al. 2018 ). Woods et al. ( 2017 , 2018 ) have searched for the extended, ionized nebulae around Galactic and LMC SN remnants that are expected for an SSS progenitor to SNe Ia, and similar to analysis of pre-explosion X-ray imaging, they rule out the most luminous and hottest of these sources. Also similar to our analysis of NGC 4696, analysis by Gilfanov Bogdán ( 2010 ) and Johansson et al. ( 2016 ) do not find a large population of SSS in elliptical galaxies that could produce SNe Ia at their observed rates, suggesting that the SSS phase is either very short-lived, occurs at low X-ray luminosities, is significantly obscured by circumstellar material, or does not precede a large fraction of SNe Ia in elliptical galaxies. Combined with the growing sample of optical and X-ray limits in the literature (Maoz Mannucci 2008 ; Nelemans et al. 2008 ; Li et al. 2011 ; Nielsen et al. 2013 , 2014 ; Kelly et al. 2014 ), our SN 2017ejb limits rule out interesting regions in WD temperature and luminosity for plausible progenitor systems. In particular, we can rule out most systems near the Chandrasekhar limit, assuming they were stably accreting for years before explosion. Combined with the limits from SNe 2011fe, 2012fr, and 2014J, we conclude at the 95 per cent confidence level that 47 per cent of SNe Ia explode from systems involving a stably accreting Chandrasekhar-mass SSS. With the growing body of evidence against typical SSS phases in particular and many single-degenerate scenarios in general as the progenitors of SNe Ia, theoretical and observational focus must shift towards the evolutionary pathways and detectable signatures of binary WD systems as the progenitors of SNe Ia (such high-velocity WD runaways from the dynamically driven double-degenerate double-detonation scenario; Shen et al. 2018 ). Future analysis of pre-explosion imaging for all SNe Ia can be used to verify or constrain expectations for the configuration of their progenitor systems and explosion scenarios. In light of the wide variety of SN Ia explosion models, this type of analysis provides one of the most promising lines of inquiry for resolving the SN Ia progenitor problem. 6 CONCLUSIONS We analyse post-explosion imaging and spectroscopy of SN 2017ejb and pre-explosion HST and Chandra imaging of its explosion site. In summary, we find: SN 2017ejb is a low-luminosity SN Ia with strong C ii absorption features in its pre-maximum spectra. Photometrically, it has a low peak luminosity, it declines quickly, and it lacks a secondary i -band maximum. Spectroscopically, it is similar to SN 1986G, but with relatively weak Ti ii bands. Overall, it is most similar to low-luminosity SNe Ia such as SNe 1986G and 1991bg. We do not detect any counterpart to SN 2017ejb in pre-explosion Chandra imaging. Assuming that any pre-explosion Chandra source resembles a blackbody obscured by Milky Way extinction, our limits correspond to 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 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 B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O B-Wavelength I-Wavelength O O O O B-Telescope I-Telescope I-Telescope I-Telescope B-Telescope B-Wavelength O B-Citation I-Citation I-Citation I-Citation 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-CelestialObject 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-CelestialObject 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 B-Citation I-Citation I-Citation I-Citation O B-Citation O B-CelestialObject O O O O O O O O O O O O O O B-Wavelength O O O O O O O O O O B-Wavelength O O B-Wavelength O O O O B-Wavelength O O O O O O O O O O B-Wavelength O O O O O O O O O O O O O O O O O O B-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O B-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-Survey O B-Survey I-Survey O B-Survey I-Survey I-Survey I-Survey I-Survey I-Survey B-Survey O O B-Wavelength O B-Wavelength B-Wavelength B-Wavelength O B-Wavelength I-Wavelength I-Wavelength O O B-CelestialObjectRegion I-CelestialObjectRegion O

The expanding H ii region may overrun and compress these nearby preexisting clumps/cores, causing them to collapse and form new stars/clusters. This is the so-called radiation-driven implosion model (Bisbas et al. 2009 ). As the ionization front “boiled off” the outer parts of those dense clumps/cores, the rest of the neutral gas is stretched out into a cometary globule, with a dense head surrounding the newly formed stars, a bright rim pointing toward the ionizing star, and a cometary tail pointing away from the ionizing star (Bisbas et al. 2011 ). Appearances of cometary globules and bright-rimmed clouds inside H ii region are thought to be the evidence of the radiation-driven implosion model (Bisbas et al. 2011 and references therein). Considering that expanding bubbles interact with surrounding materials and trigger star formation, it is reasonable to expect that bubbles of larger size will have much more time to sweep around the surrounding materials, and thus have more chances to trigger star formation and then show more evidence of triggered star formation (Yuan et al. 2014 ), and vice versa for bubbles with smaller size. Hence we plan to study the molecular cloud and star formation around bubbles with larger and smaller sizes separately in a large sample, compare them with each other, and get evidence of triggered star formation. We found a sample of 226 bubbles from the catalog of Simpson et al. ( 2012 ) in the region covered by the 12 CO(3–2) survey performed with the James Clerk Maxwell Telescope (JCMT) submillimeter telescope (Dempsey et al. 2013 ). The 12 CO(3–2) data makes it possible for us to study the molecular gas around these bubbles in a relatively high angular resolution. As a pilot study, we first investigate G15.684-0.29 as one example of the largest bubbles in our sample, and G13.899-0.011 as one example of the smallest bubbles in our sample in the next paper. G15.684-0.29, which has a diameter of 31.4 pc (Section 3 ), is an ideal bubble for studying triggered star formation. Similar to RCW 79 and RCW 120 (Zavagno et al. 2006 , 2007 ), G15.684-0.29 has a simple morphology (circular ionized regions surrounded by dust emission rings in the mid-IR) and hosts signposts of massive-star formation at their peripheries (luminous IR sources, ultracompact radio sources; Section 3 ). Near-IR imaging gives information about the stellar nature of the luminous IR point sources observed at the borders of the ionized regions. In this work, we study the large bubble G015.684-0.29, and see if it is easy for the large bubble to trigger star formation. We describe our data in Section 2 and give a simple introduction of G15.684-0.29 in Section 3 . We present the results and discussions in Section 4 and a summary in Section 5 . 2. Archival Data 2.1. The GLIMPSE and MIPS Survey The Galactic Legacy Infrared Mid-Plane Survey Extraordinaire (GLIMPSE) is a mid-infrared survey (3.6, 4.5, 5.8, and 8.0 μ m) of the Inner Galaxy performed


O O B-EntityOfFutureInterest O O O O O O O O O O B-EntityOfFutureInterest O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-EntityOfFutureInterest O O O O O O O O O O O O O B-EntityOfFutureInterest O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Telescope 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-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 B-Wavelength I-Wavelength I-Wavelength O O O B-Wavelength I-Wavelength I-Wavelength I-Wavelength 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-Telescope O O O O O O O O O B-Software I-Software I-Software B-Software O B-Identifier I-Identifier 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 B-Model I-Model O O O O B-Model I-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-EntityOfFutureInterest O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 solar-like stars for which rotational periods could not be determined exhibit near-solar photometric variability, R var . Here, we have provided one possible explanation for a decreased detection fraction for these stars. We investigated the compensation of the facular and spot contributions to the rotational signal in stellar photometric light curves. This compensation hampers the detection of stellar rotational periods, and contributes to a decreased detection rate for solar-like stars. Our results show that the detectability of rotational periods in stars with solar-like photometric variability crucially depends on metallicity. Hence, metallicity is one additional important parameter to consider when investigating solar-like stars, and more accurate measurements of metallicity are needed. Appendix A: Kepler rotation periods Fig. A.1. Period detection for the star KIC 10797342. Top panel : part of the full 4 yr light curve showing photometric variability. Middle panel : Lomb-Scargle periodogram showing several peaks above the 5 σ threshold (blue line). Bottom panel : auto-correlation function showing one pronounced peak indicated by the red asterisk. Table A.1. Stellar fundamental parameters and rotation periods of the 97 periodic stars in our sample. Notes. In the last two columns the apparent Kepler magnitude Kp and the absolute Gaia magnitude M G are given. We analysed stars from Table 2 in McQuillan et al. (2014) satisfying our selection criteria (i.e. the non-periodic sample) to search for potentially undetected rotation periods. The Kepler data used in this study were reduced with the Presearch Data Conditioning (PDC) pipeline (version 8.0-9.2). We appended all available Kepler quarters by dividing each light curve by its median and subtracting unity. Then we rebinned the data from 30-minute to 6-hour cadences, and analysed the full 4-year time series using Lomb-Scargle periodograms and auto-correlation functions. The Lomb-Scargle periodogram return peaks of different power on a period grid. The peak height is equivalent to the goodness of sine fit to the data, i.e. the more sinusoidal the signal, the higher the peak at this period. At the same time, the auto-correlation function (ACF) searches for self-similarity of the light curve signal, independently of the shape of the signal, and returns a peak at the best time lag (i.e. the ACF period). Since the time series of these slowly rotating solar-like stars are usually non-sinusoidal, we use the ACF period as initial period guess. For both the periodogram and the ACF, we searched for cases where both methods returned consistent peaks, with periods of up to 50 days. The term “consistent” covers different cases. In case a) the periodogram and the ACF both show a pronounced peak at roughly the same period (i.e. the periods may differ by up to five days). This case is considered the easiest one, and we do not show an example here. In case b) the ACF shows a pronounced peak and the


O O O O O O B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O O O B-Grant O O O O O O O B-Observatory I-Observatory I-Observatory O O B-Organization O O O B-Location I-Location O O O O O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O O O O O B-Organization I-Organization O O B-Organization I-Organization I-Organization I-Organization O O O B-Organization I-Organization I-Organization I-Organization I-Organization O O O O O O O O O O O O O O O O B-Software B-Citation I-Citation I-Citation I-Citation O O O O O O B-Person I-Person O O B-Software I-Software O O O B-Instrument O O O O O O O B-Person I-Person O O O O O O O O B-Observatory

This research was conducted by the Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO), through project number CE110001020. 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. The International Centre for Radio Astronomy Research (ICRAR) is a Joint Venture between Curtin University and the University of Western Australia, funded by the State Government of Western Australia and the Joint Venture partners. Some of the results in this paper have been derived using HEALPix (Górski et al. 2005 ). We would like to thank André Offringa for customizing AO-flagger software to work with BIGHORNS data. We would also like to thank Matthew Francis for generating and sharing STEC data for the MRO.


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 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 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 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 O O B-Wavelength I-Wavelength O O O B-Telescope O O O B-Wavelength I-Wavelength O O O O O O O O O B-Organization O O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O O B-Telescope O O O O O O B-Wavelength I-Wavelength O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation B-CelestialObject O O O B-Wavelength O O O O O O O O O O O O B-Wavelength O O O O O O O B-Wavelength O O O O O O O O O O B-Telescope O O O O O O B-Wavelength O O O O O O O B-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion 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 B-Wavelength O O B-Citation I-Citation I-Citation I-Citation O O O O O B-CelestialObject O O B-Wavelength O O O O O O O B-Wavelength I-Wavelength 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 O O O O B-CelestialObject I-CelestialObject O B-Wavelength I-Wavelength O O O O O O O O O O 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 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 B-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O O B-Tag O O O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O B-Wavelength O O O O O B-Observatory B-Wavelength O O O O O B-Wavelength I-Wavelength O O O B-Observatory B-Telescope O O O O O O O O O O O B-Software I-Software I-Software I-Software I-Software I-Software O O O O O O O O O B-Dataset I-Dataset I-Dataset O O O O O O O O O O

either because the source istoo faint or, for example, because of non-ideal weather. The flux density scale is set by observations of DR 21. Sources NGC 7027, 3C 274, and 3C 84 are used as secondary calibrators. A detailed description of the data reduction and analysis is given in Teräsranta et al. (1998) . The error estimate in the flux density includes the contribution from the measurement rms and theuncertainty of the absolute calibration. Observation statistics are available in Table A.1 . Columns 1 – 3 give the name and the coordinates of the sources (in J2000). The number of detections and observations at 37 GHz isshown in Col. 4. and the detection percentage in Col. 5. Cols. 6 and 7 give the maximum flux density at 37 GHz and the 1.4 GHz flux density from FIRST. A table containing 37 GHz flux densities and their errors is available at the CDS. Table A.1 Basic data and statistics of the 37 GHz observations. Notes. ( a ) This source has been detected also by LOFAR at a very low frequency of 150 MHz with a flux density of 3.6 mJy. We also performed test observations of a source with a descrepancy in its classification. In Järvelä et al. (2015) J090113.23+465734.7 is listed as radio loud. A search radius of 1 arcmin was used to obtain the radio data, and while there is no detected radio source at the source coordinates (the mean epoch of the FIRST observations is 1997.2), there is a radio source in its close proximity at coordinates RA 09h01m09.225s, Dec +46d57m21.19s. This is MJV 09737, which has no listed redshift or observationsat other wavelengths. Their separation is 0.72 arcmin and it is therefore probable that the radio data in Järvelä et al. (2015) originate in this source, and J090113.23+465734.7 is apparently radio silent. The source has been detected at 37 GHz only once, and the detection raised concern about the possible contamination by MJV 09737 since it also lies within our antenna beam (2.4 arcmin at 37 GHz). The flux density of MJV 09373 at 1.4 GHz is 1.55 mJy and it has not been detected at higher radio frequencies; thus it is likely to be faint at 37 GHz. To ensure this we ran a set of simple tests to check how another radio source lying in the antenna beam might affect our observations, by observing the sources in pairs several times. All observations of MJV 09737 were non-detections so its contributionto 37 GHz observations seems negligible, but this test is not precise enough to certainly rule out possible contamination. Appendix B <italic>Fermi</italic>–LAT data reduction Since the 37 GHz detections suggest the presence of jets, it is possible that these sources are also gamma-ray emitters. Therefore we obtained their Fermi gamma-ray fluxes in the energy range 0.1–300 GeV by analysing the Fermi –LAT data from 2008 August 04 to 2017 August 10 using the Fermi Science Tools 1 version v10r0p5. We applied the data selection recommendation 2 for the Pass 8 data to select events in the source class, while excluding those


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We thank the referee for useful comments that improved the manuscript. We thank K. Schmidt, L.I. Mas-Ribas, and R. Amorin for useful discussion. E.V. and S.C. acknowledge financial support from PRIN-MIUR 201278X4FL, Evolution of Cosmic Baryons: Astrophysical Effects and Growth of Cosmic Structures. C.G. acknowledges support by VILLUM FONDEN Young Investigator Programme through grant no. 10123. K.C. acknowledges funding from the European Research Council through the award of the Consolidator Grant ID 681627-BUILDUP. L.C. is supported by Grant DFF 4090-00079. Based on observations collected at the European Southern Observatory for Astronomical research in the Southern Hemisphere under ESO programmes P095.A-0653, P094.A-0115 (B) and ID 094.A-0525(A). M.N., M.M., A.M., and P.R. acknowledge financial support from PRIN-INAF 2014 1.05.01.94.02.


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

measured Eu is likely due to the current detection limit for Eu (Ishimaru et al. 2004 ). Overall, the result for case 1 (a mean delay of 0.1 Gyr in the lognormal term for NSMs) appears in qualitative agreement with those in Ishimaru et al. ( 2015 ) and Ojima et al. ( 2018 ) with a fixed delay of 0.1 Gyr (see Appendix A for additional tests). The top-right panel of Fig. 5 shows the result for case 2, in which the delay-time distribution of NSMs is ∝ t −1 . We find a slower increase of [Eu/Fe] with [Fe/H] and a smaller [Eu/Fe] at high [Fe/H] than those for case 1. This is due to an absence of the early (lognormal) component in the delay-time distribution. As a whole, however, the evolution of [Eu/Fe] including its scatter is similar between cases 1 and 2. The bottom-left panel of Fig. 5 shows the result for case 3, in which a CCSN-like, little delay time for NSMs is assumed (Fig. 1 ). We find that the evolution of [Eu/Fe] with [Fe/H] appears incompatible with the measured stellar abundance. The model predicts stars with [Fe/H] −3.5, at which few stars with measured Eu have been found. Note this cannot be attributed to the detection limit for Eu, because the predicted stars have high [Eu/Fe] (>0.5). It should also be noted that the reason cannot be the rarity of stars with [Fe/H] −3.5. The building blocks more massive than M * = 10 6 (orange curve in the bottom-left panel of Fig. 5 ), which generate the bulk of stars in the halo (the right-hand panel of Fig. 3 ), have already experienced NSM events (〈 N NSM 〉 > 1) at [Fe/H] −3.5. Moreover, the model does not predict stars with [Eu/Fe] 0 at [Fe/H] ∼ −3, at which a large number of stars with measured Eu exist (see also Section 4.4 and Appendix A ). The result for case 4 is shown in the bottom-right panel of Fig. 5 . The smaller SFE ( K in Table 1 ) results in the appearance of Eu at too low metallicity ([Fe/H] ∼ −4) to be compatible with the observation. However, the lowest metallicity at which Eu starts increasing depends on t min in the delay-time distribution of NSMs (equation ( 13 ); see Appendix A ). Another problem is that the contribution of SNe Ia starting at low metallicity inhibits the increase of Eu above [Eu/Fe] ∼ 0. It should be noted, however, that the yield of Eu from NSMs and their event rate, the product of which determines the average [Eu/Fe], are somewhat uncertain. Overall, therefore, our model is (at least marginally) compatible with the observational trend of [Eu/Fe] in the MW halo, regardless of the explored variations in the delay-time distributions (except for case 3). Note that a reduction of the NSM (or rare CCSN-like) event rate (or B in Section 2.2 ), which also reduces 〈 N NSM 〉, will enhance [Eu/Fe] at low metallicity in the low-mass building blocks with 〈 N NSM 〉 1. However, this will not substantially change the probabilistic distribution of stars on the [Eu/Fe]–[Fe/H] plane (colour scale in Fig. 5 ) as presented in Appendix A (Fig. A4 ) because of the resulting


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We gratefully thank J. Zhao for providing his inversion results from HMI data, T. Hartlep for providing his meridional flow simulation data, and an anonymous referee for an excellent numerical suggestion. This material is based upon work supported by the National Science Foundation under Grant Number 1351311. A.S. acknowledges support from grant FA-F02-F028 of the Uzbek Academy of Sciences. S.K. was supported by NASA’s Heliophysics Grand Challenges Research grant 13-GCR1-2-0036. This work utilized data obtained by the Global Oscillation Network Group (GONG) program, managed by the National Solar Observatory, which is operated by AURA, Inc. under a cooperative agreement with the National Science Foundation.


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

temperatures and metallicities is fair, with our temperatures being an average of 161 K cooler (σ = 181 K), and our metallicities an average of 0.12 dex lower (σ = 0.15 dex). The surface gravities show a similar offset, ours being lower by 0.18 dex, and an rms scatter σ = 0.16 dex, but the discrepancies seem to be largest (by up to 0.5 dex) for the coolest and more metal rich stars in the sample. Figure 2. Upper panel: observed (solid black line) and best-fitting model (broken red line) for four representative stars in our sample of proposed flux standards. Bottom panel: ratio between model and observed fluxes. Table 1. Derived parameters and angular diameters (θ) for the proposed bright spectrophotometric A-type standards. The scatter given corresponds to the standard deviation in θ for the spectral data points in the 400–800 nm range. The uncertainty σ(θ) is derived by adding the scatter in quadrature with a 0.4 per cent error that corresponds to propagating the uncertainty in the zero-point of the flux scale (0.8 per cent or 0.008 mag). Both the atmospheric parameters from the NGSL library (Lindler Heap 2008 ) and those derived in this paper are provided. We estimate our uncertainties are about 120 K, 0.2 dex and 0.1 dex (random) and 150 K, 0.2 dex and 0.1 dex (systematic), for T eff , log g and [Fe/H], respectively (but see text for a caveats about log g for some stars). The V -band photometry derived from the NGSL spectra, and those measured from the ground and compiled by Mermilliod, Mermilliod Hauck ( 1997 ) are in the last two columns. Our conclusion about the systematics in our derived surface gravities is reinforced by comparing our results with Allende Prieto Lambert (1999), who compared the V -band absolute magnitudes, computed from Hipparcos ’ parallaxes, and B − V colours, with models of stellar interiors. Their surface gravities for eight stars in common are an average of 0.33 larger than ours (σ = 0.18 dex), and show a similar trend as we found with the NGSL values, with larger discrepancies for cooler more metal-rich stars. The comparison with metallicities from the PASTEL bibliographical catalogue (Soubiran et al. 2010 ), which compiles stellar atmospheric parameters determined from high resolution, high signal-to-noise spectra in the literature, shows, for eight stars in common, a mean offset of 0.02 dex, ours being lower, and significant scatter (σ = 0.48 dex). Our gravities are also lower than those in PASTEL by an average of 0.08 dex (σ = 0.21 dex). Lastly, our comparison with the parameters published by Koleva Vazdekis ( 2012 ) shows the largest spread, with standard deviations of 702 K in T eff , 0.5 dex in log g and 0.6 dex in metallicity. To evaluate the effect of neglecting reddening in our analysis, we have tested the consequences of adopting instead the reddening estimates provided by Lindler Heap (2008) as part of the NGSL, correcting the spectra for reddening using the mean Galactic extinction curve given by


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J.R.A.D. is supported by an NSF Astronomy and Astrophysics Postdoctoral Fellowship under award AST-1501418. C.B. acknowledges support from the Alfred P. Sloan Foundation. This paper includes data collected by the Kepler mission. Funding for the Kepler mission is provided by the NASA Science Mission directorate. Some/all of the data presented in this paper were obtained from the Mikulski Archive for Space Telescopes (MAST). STScI is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555. Support for MAST for non- HST data is provided by the NASA Office of Space Science via grant NNX09AF08G and by other grants and contracts. Some of the data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation. The authors wish to recognize and acknowledge the very significant cultural role and reverence that the summit of Maunakea has always had within the indigenous Hawaiian community. We are most fortunate to have the opportunity to conduct observations from this mountain. Facilities: Kepler , Keck:II (NIRC2).


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

inhomogeneities provide a number of testable predictions, such as photometric or radial-velocity flickering of integrated starlight. Stellar brightness varies in a somewhat random fashion, as differently bright granular structures develop across the surface ( Cranmer et al. 2014 ; Ludwig 2006 ). The effects are greater for giant stars, where the small-number statistics of fewer granules across the star induces a greater variability, as observed ( Bastien et al. 2013 , 2016 ; Mathur et al. 2011 ) and as modeled ( Samadi et al. 2013a , b ). For the Sun, with 10 granules across its surface, each with a 20 intensity contrast, the amplitude of variability in integrated sunlight (assuming random variability among the granules) can be expected to be on the order of this contrast divided by the square root of the number of granules, i.e., , measurable with photometric instruments in space. Since the contrast is greater at short optical wavelengths (as expected for a given temperature contrast in the photosphere), also the amplitude of flickering is greater in the blue than in the red. In specific wavelength regions comprising numerous temperature-sensitive spectral lines, such as the -band, the photometric flickering may be expected to be greater but does not yet appear to have been either computed nor observed. An analogous variability in the disk-averaged radial velocity on a level of some m s is a concern in radial-velocity searches for low-mass exoplanets and for the confirmation of exoplanet candidates found from transits ( Cegla et al. 2013 , 2014 ; Dumusque et al. 2011a ). Again, the amplitude of flickering can be expected to increase at shorter wavelengths, where the granular contrast is greater. Further, the astrometric location of the stellar photocenter may wander and is detectable with space astrometry ( Chiavassa et al. 2011a ; Pasquato et al. 2011 ). Other effects include interpretation of stellar p-mode oscillations, where 3D models have to be applied for any more precise representation of stellar near-surface layers, detecting inconsistencies that may indicate which modeling parameters need adjustment ( Baldner Schou 2012 ; Kallinger et al. 2014 ; Piau et al. 2014 ; Schou 2015 ). Fig. 2 Top : build-up of synthetic Fe I lines at stellar disk center ( = cos.0) from a CO BOLD model of a dwarf star with approximate spectral type F7 V (250 K, log [cgs] = 4.5). Thin colored lines are spatial averages over the simulation area for each of 20 temporal snapshots; bold curves are the total averages. All five different line strengths are for 20 nm, eV. The convection patterns especially cause the weaker lines to become asymmetric and wavelength-shifted. Bottom : evolution of the continuum intensity during the simulation sequence for four different center-to-limb positions , 0.87, 0.59, 0.21. For off-center positions, slight differences exist among the four different azimuth angles (, /2, , 3/2 rad). Fig. 3 Spectral line changes across a


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

with the predictions of Reiners et al. (2010) and Barnes et al. (2011) . Their simulations suggest that the large scatter around the std(RV)– v sin i correlation seen in the left panel of Fig. 3 could be caused by the spot characteristics of the active stars, such as their spot coverage fraction, and their spot-to-photosphere temperature contrast. We also recall that an additional source of scatter could be true orbital motions of these stars due to their as yet undiscovered planetary systems. 5.2 Correlations of RVs with spectral activity indicators After searching for correlations between std(RV) and activity-related stellar parameters of the active RV-loud sample as a whole, we moved on to investigate individual stars of the sample for correlations between their stellar activity indicators and their measured RVs. Finding a parametric function that could translate measurable spectral activity indicators into RV deviations is a great challenge, but at the same time, it holds the promise to enable the modeling of RV time series with a combined model of planetary- and activity-induced signals. Moreover, such a function would obviate simultaneous auxiliary measurements to quantify activity-induced RVs, such as multi-band photometric observations. Unfortunately, no such a function has been proposed so far for M dwarfs. Lacking a physical model to guide our spectral data exploration, we searched our active RV-loud stars for linear correlations between their varying RVs and three ofthe spectral activity indicators that we have chosen to investigate in this paper: CRX, dLW, and log L H α ∕ L bol . To best illustrate the process, we show here a few representative plots for one of the most frequently observed stars in our sample: J22468+443 (EV Lac). In order to demonstrate the CRX definition, we show in the top panel of Fig. 4 the order-by-order RVs from four representative observations of EV Lac: three observations with close-to-median H α emission but different CRX values, and one observation with extremely high H α emission. The latter observation was taken during a strong flare event ( Fuhrmeister et al. 2018 ). The slopes of the best-fit lines to these RV–order scatter plots are related to the CRX values of these four observations ( Zechmeister et al. 2018 ). The locations of activity-induced emission lines are marked at the top panel of Fig. 4 . The bottom panel of Fig. 4 shows the corresponding CARMENES spectra from these four observations, centered on the H α line. Fig. 4 CARMENES VIS measurements of J22468+443 (EV Lac). Top : Order-by-order RVs from four representative observations. Red, green, and blue show three observations with close-to-median H α emission. Black plots an observation with extremely high H α emission, taken during a strong flare event ( Fuhrmeister et al. 2018 ). The corresponding log L H α ∕ L bol values are given in the inset. Dashed lines show the best-fit straight lines to the RV–order scatter plots of each


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also that, if we assume that is roughly proportional to as suggested by observations (Thompson 2008 ; Grenier Harding 2015 ), then . A final comment is in order here before we move on to the next section. As we saw in the calculation below equation ( 5 ), near the surface of the star the separatrix electric charge fails to account for the separatrix return current by a factor ( r pc / r lc ) 2 ≪ 1. The same calculation near the Y-point yields the separatrix surface charge density σ lc near the light cylinder R → r lc , (see Uzdensky 2003 ; Timokhin 2006 , for details). Here, B lc ≡ B * ( r * / r lc ) 3 /2 is the value of the dipole magnetic field at the light cylinder. In the above estimate, ‘IN’ and ‘OUT’ at the Y-point refers to the region just outside and inside the light cylinder, respectively. Obviously, the separatrix electric charge is sufficient to support the separatrix return current. The only way to reconcile this result with the inefficiency of the separatrix electric charge to carry the same electric current near the surface of the star is the following: The separatrix must contain an extra amount of distributed corotating positive electric charge with surface charge density σ + ( R ) > 0 such that, at all distances, from the polar cap at r pc to the light cylinder. Here, σ − ( R ) ∼ − I pc /2π Rc is the negative charge density carried by the electrons that inflow from the dissipation zone. Clearly, which is in absolute terms much greater than σ pc . Consequently, σ + pc ≈ |σ − pc |. It is conceivable that these corotating positrons are the result of pair formation by the inflowing separatrix electrons. Note that the concept of one particle population of the ‘right’ type flowing through another stationary (corotating) population of the ‘wrong’ type needed to support both the electric charge and electric current distributions in the pulsar magnetosphere was first proposed in section 4 of Contopoulos ( 2016 ). 3 HIGH-ENERGY RADIATION If we know the accelerating electric field and the trajectory of particles in the equatorial dissipation region, it is straightforward to calculate the asymptotic particle Lorentz factor Γ in the curvature radiation reaction limit, Here, E acc is the accelerating electric field in the dissipation region. We have assumed here that the radius of curvature around the Y-point is equal to r lc . We can estimate E acc if we make the simplifying assumption that the magnetic flux that crosses the equatorial dissipation zone does so in a dipole-like configuration. In that case, the width Δ of that region is equal to and hence, the accelerating electric field in that region is equal to We have thus shown that the accelerating electric field is approximately equal to the value of the magnetic field near the light cylinder. One can easily check that, with this accelerating electric field, where, P is the pulsar period. This will be reached within an acceleration distance on the order of Obviously, the


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Acknowledgements GAMA is a joint European-Australasian project based around a spectroscopic campaign using the Anglo-Australian Telescope. The GAMA input catalogue is based on data taken from the Sloan Digital Sky Survey and the UKIRT Infrared Deep Sky Survey. Complementary imaging of the GAMA regions is being obtained by a number of independent survey programmes including GALEX MIS, VST KiDS, VISTA VIKING, WISE, Herschel -ATLAS, GMRT, and ASKAP providing UV to radio coverage. GAMA is funded by the STFC (UK), the ARC (Australia), the AAO, and the participating institutions. The GAMA website is http://www.gama-survey.org/ . Based on observations made with ESO Telescopes at the La Silla Paranal Observatory under programme ID 179.A-2004. The G10-COSMOS redshift catalogue, photometric catalogue, and cutout tool uses data acquired as part of the Cosmic Evolution Survey (COSMOS) project and spectra from observations made with ESO Telescopes at the La Silla or Paranal Observatories under programme ID 175.A-0839. The G10-COSMOS cutout tool is hosted and maintained by funding from the International Centre for Radio Astronomy Research (ICRAR) at the University of Western Australia. Full details of the data, observation, and catalogues can be found in Davies et al. ( 2015 ) and Andrews et al. ( 2017a ), or on the G10-COSMOS website: cutout.icrar.org/G10/dataRelease.php This work is based on observations by the 3D-HST Treasury Program (GO 12177 and 12328) with the NASA/ESA HST , which is operated by the Association of Universities for Research in Astronomy, Inc. under NASA contract NAS5-26555. This work was supported by resources provided by the Pawsey Supercomputing Centre with funding from the Australian Government and the Government of Western Australia. SKA is supported by an Australian Postgraduate Award. LJD and SJM acknowledge support from European Research Council (ERC) in the form of Advanced Investigator grant COSMICISM and Consolidator grant Cosmic Dust.


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

s) the high ionization region. Figure 5. Same as Figure 4 , but for and . 3.4. Parameter Study In Figure 6 , we show the dependence of the Balmer- α line energy flux on (a) the preshock velocity v 0 and (b) the total number density of hydrogen nuclei n H,0 , respectively. In the Appendix , we also show the dependences regarding other lines such as Balmer- β , Paschen- α , and Paschen- β . 5 5 Those profiles would be similar even at infinity except for Ly α , because hydrogen is in the form of H 2 and excited H rarely exists above the shock front. As for Ly α , absorption in the interstellar medium modifies the profiles. As seen in panel (a), for v 0 30 km s −1 , the Balmer- α line flux is quite low. This is because almost all the energy of shock heating is consumed for dissociation of hydrogen molecules. For v 0 ≥ 30 km s −1 , the energy flux is found to be nearly proportional to in panel (a) and to n H,0 in panel (b). Intuitively, however, the energy flux is proportional to , because the kinetic energy that the flowing gas has before shock is . This holds true for Ly α , but for other lines, we have to take into account the effect of absorption of radiation propagated from downstream, as described below. Figure 6. Energy flux of the Balmer- α line (H α ) radiation at the shock front (i.e., the surface of the circumplanetary disk) against the preshock velocity v 0 (panels (a) and (c)) and the total number density of atomic hydrogen (including all the hydrogen nuclei) n H,0 (panels (b) and (d)). The upper two panels are the same as the lower two, respectively, but the latter shows the energy flux relative to the total incoming energy flux at the shock front (i.e., where is the total number of particles and μ is the mean molecular weight). In the left two panels, each color shows each choice of 10 15 m −3 (black), 10 16 m −3 (red), 10 17 m −3 (blue), 10 18 m −3 (orange), 10 19 m −3 (purple), and 10 20 m −3 (brown). Also in the right two panels, each color shows each choice of v 0 ; (black), (red), (blue), (orange), (purple), (brown), and (green). Figure 7 shows the profiles of the spectral energy density of the Ly α and Balmer- α lines at the shock front. In the upper row of panels, those for different choices of n H,0 are presented for v 0 = 40 km s −1 , while in the lower panels, those for different choices of v 0 are presented for . The Gauss profile caused by the Doppler broadening is seen near the line center, while the Lorenz profile mainly caused by the natural broadening is seen far from the line center. The borders between them are at ∼121.48 nm and ∼121.53 nm for Ly α (in panel (a)) and ∼656.00 nm and ∼656.26 nm for Balmer- α (in panel (b)), respectively. In panel (b), for to , the energy density is found to be nearly proportional to n H,0 as a whole. Figure 7. Spectral energy density profile of hydrogen Ly α line (left panels) and Balmer- α line (right panels) emitted upward at the shock front. In panels (a) and (b), the preshock


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

data. Results from this joint analysis are listed in Tables 1 , 2 , and 6 . The QSO + H ( z ) + BAO 1D likelihoods and 2D confidence contours for all free parameters are shown in blue in Figs 4 – 15 . The updated QSO data don’t significantly tighten the BAO + H ( z ) data contours except in the cases of the non-flat XCDM parametrization and the non-flat φCDM model (Figs 10 , 11 , 14 , and 15 ). Another noticeable result is that adding the QSO data to the BAO + H ( z ) data results in the shifting of 1D likelihood distribution of the matter density parameter towards higher values in most cosmological models studied here. Table 5. Marginalized 1D best-fitting parameters with 1σ confidence intervals for all models using BAO and H ( z ) data (from Khadka Ratra 2020 ). a . From joint analyses of the QSO + H ( z ) + BAO data, from Table 6 , the matter density parameter lies in the range Ω m 0 = 0.30 ± 0.02 to 0.31 ± 0.01 (Ω m 0 = 0.30 ± 0.01 to 0.33 ± 0.02) for flat (non-flat) models and the H 0 = 68 ± 2.8 prior and lies in the range Ω m 0 = to 0.31 ± 0.01 (Ω m 0 = 0.31 ± 0.01 to 0.33 ± 0.02) for flat (non-flat) models and the H 0 = 73.24 ± 1.74 prior. In a few cases these results slightly differ from the BAO + H ( z ) data results in Table 5 , being shifted to slightly larger values. These results are consistent with those results determined from other cosmological data. Table 6. Marginalized 1D best-fitting parameters with 1σ confidence intervals for all models using QSO + H ( z ) + BAO data. a . The Hubble constant lies in the range H 0 = to ( H 0 = to ) for flat (non-flat) models and the H 0 = 68 ± 2.8 prior and lies in the range H 0 = to ( H 0 = to ) for flat (non-flat) models and the H 0 = 73.24 ± 1.74 prior. Not unexpectedly, for the H 0 = 73.24 ± 1.74 prior case the measured value of H 0 is reduced below the prior value because the BAO and H ( z ) observations prefer a lower H 0 . In most cases the H 0 error bars have increased in comparison to those derived using the 2015 QSO + BAO + H ( z ) data in Khadka Ratra ( 2020 ). In all models, except for non-flat ΛCDM with the H 0 = 68 ± 2.8 prior, closed spatial hypersurfaces are favoured at about 2σ. For the non-flat ΛCDM model the curvature energy density parameter is Ω k 0 = and −0.09 ± 0.05 for the H 0 = 68 ± 2.8 and 73.24 ± 1.74 priors, respectively. Values of curvature energy density parameter obtained for non-flat dynamical dark energy cosmological models are significantly higher than those obtained in the non-flat ΛCDM model. The curvature energy density parameter is Ω k 0 = −0.34 ± 0.18 and −0.32 ± 0.16 for the non-flat XCDM and non-flat φCDM models for the H 0 = 68 ± 2.8 prior and Ω k 0 = and −0.35 ± 0.15 for the non-flat XCDM and non-flat φCDM models for the H 0 = 73.24 ± 1.74 prior. This preference for closed spatial geometries is largely driven by the BAO + H ( z ) data (Park Ratra 2018c ; Ryan et al. 2019 ). From Table 6 , for the flat (non-flat) ΛCDM model the dark energy density


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The authors thank the anonymous referee for very valuable comments. R.S. acknowledges the support from grant AYA2014-54485-P (AEI/FEDER, UE) and from the Ministerio de Economía, Industria y Competitividad, and the Conselleria d’Innovació Recerca i Turisme del Govern Balear (Pla de ciència, tecnologia, innovació i emprenedoria 2013-2017) for the Ramón y Cajal grant RYC-2014-14970.


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We thank the anonymous referee for the careful and constructive reading of the paper and for his/her useful suggestions. We would like to thank Marta Volonteri and Lorenzo Lovisari for helpful feedback during the draft of the paper and Volker Springel for making the GADGET-3 code available to us. This project has received funding from: ExaNeSt and Euro Exa projects, funded by the European Union’s Horizon 2020 research and innovation program under grant agreement No 671553 and No 754337, the agreement ASI-INAF n.2017-14-H.0, the Agencia Nacional de Promoción Científica y Tecnológica de la República Argentina under the PICT2417-2013 grant; the Consejo Nacional de Investigaciones Científicas y Técnicas de la República Argentina (CONICET); the Secretaría de Ciencia y Técnica de la Universidad Nacional de Córdoba – Argentina (SeCyT); the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie grant agreement No 734374, PRIN-MIUR 2015W7KAWC, the INFN INDARK grant, NASA Chandra GO7-18121X and GO8-19104X. Simulations have been carried out using MENDIETA Cluster from CCAD-UNC, which is part of SNCAD-MinCyT (Argentina) and MARCONI at CINECA (Italy), with CPU time assigned through grants ISCRA C, and through INAF-CINECA and University of Trieste – CINECA agreements. The post-processing has been performed using the PICO HPC cluster at CINECA through our expression of interest.


O O O O O O O O O O O O O O O O O B-Person O B-Person O B-Person I-Person O B-Person I-Person O O O O O O O O O O B-Observatory O B-Identifier I-Identifier B-Identifier B-Identifier O B-Identifier O B-Observatory 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 I-Citation B-Observatory O O O O B-Observatory O O O O B-Organization B-Location O B-Organization B-Location O O B-Organization B-Location B-Organization O B-Organization B-Location O B-Organization B-Location I-Location I-Location O O O O B-Location I-Location I-Location O B-Observatory I-Observatory I-Observatory O O O B-Observatory B-Organization O B-Observatory O B-Observatory I-Observatory I-Observatory I-Observatory O O O O O B-Organization I-Organization I-Organization O O O O O B-Organization I-Organization I-Organization O O O O O O O O O B-Survey I-Survey O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O B-Survey I-Survey I-Survey I-Survey B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O B-Survey I-Survey I-Survey I-Survey B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O B-Telescope I-Telescope I-Telescope O O B-Telescope O O O B-Observatory O O O O B-Organization B-Location B-Organization B-Location O B-Organization B-Location O O O O O O B-Database I-Database I-Database O O B-URL B-Citation I-Citation I-Citation I-Citation O O B-Database I-Database O O B-URL B-Citation I-Citation I-Citation I-Citation O O B-Database I-Database I-Database O O B-URL O O B-Archive I-Archive I-Archive I-Archive O O B-URL B-Person B-Person O B-Person O O O O B-Organization I-Organization I-Organization O O B-Grant I-Grant B-Grant O B-Grant B-Person O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O O O B-Grant B-Person O O O O B-Organization I-Organization I-Organization I-Organization B-Organization B-Person O B-Person O O O O O B-Organization I-Organization I-Organization B-Organization O O O O O B-Fellowship I-Fellowship I-Fellowship I-Fellowship O O B-Grant O B-Person B-Person O O O O O B-Organization I-Organization I-Organization B-Organization O O B-Grant I-Grant I-Grant I-Grant O O O O O O B-Grant I-Grant I-Grant I-Grant O O O B-Grant O B-Person B-Person O O O O B-Organization I-Organization I-Organization B-Organization O O B-Grant I-Grant I-Grant I-Grant O O O O O O B-Grant I-Grant B-Person O O O B-Organization B-Grant I-Grant I-Grant I-Grant I-Grant B-Person O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization B-Person O O O O B-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant B-Grant O B-Organization O B-Organization O O B-Organization O B-Organization B-Person O O O B-Location B-Organization O B-Grant O B-Grant O B-Observatory O B-Telescope O B-Telescope O B-Telescope O O B-Software B-Citation I-Citation I-Citation O B-Software B-Citation I-Citation O B-Software B-Citation I-Citation O B-Software B-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 I-Citation I-Citation O

We would like to thank the anonymous referee for valuable comments that helped us improve the manuscript. J.S. and A.K.L. thank Eve Ostriker and David Weinberg for useful discussions. This paper makes use of the following ALMA data: ADS/JAO.ALMA# 2011.0.00876.S, 2012.1.00650.S, 2015.1.00925.S, and 2015.1.00956.S. These ALMA programs are described in Whitmore et al. ( 2014 ) and A. K. Leroy et al. (in preparation). ALMA is a partnership of ESO (representing its member states), NSF (USA), and NINS (Japan), together with NRC (Canada), NSC and ASIAA (Taiwan), and KASI (Republic of Korea), in cooperation with the Republic of Chile. The Joint ALMA Observatory is operated by ESO, AUI/NRAO, and NAOJ. The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc. This work also makes use of data from the CARMA M31 survey (A. Schruba et al., in preparation), the IRAM M33 large program (Gratier et al. 2010 ; Druard et al. 2014 ), and the PdBI Arcsecond Whirlpool Survey (Pety et al. 2013 ; Schinnerer et al. 2013 ). Both the IRAM 30 m telescope and PdBI are run by IRAM, which is supported by INSU/CNRS (France), MPG (Germany), and IGN (Spain). We acknowledge the usage of the Extragalactic Distance Database 23 23 http://edd.ifa.hawaii.edu/index.html (Tully et al. 2009 ), the HyperLeda database 24 24 http://leda.univ-lyon1.fr (Makarov et al. 2014 ), the NASA/IPAC Extragalactic Database, 25 25 http://ned.ipac.caltech.edu and the SAO/NASA Astrophysics Data System. 26 26 http://www.adsabs.harvard.edu J.S., A.K.L., and D.U. are supported by the National Science Foundation under grants No. 1615105, 1615109, and 1653300. E.R. acknowledges the support of the Natural Sciences and Engineering Research Council of Canada (NSERC), funding reference number RGPIN-2017-03987. A.H. acknowledges support from the Centre National d’Etudes Spatiales (CNES). J.M.D.K. and M.C. gratefully acknowledge funding from the German Research Foundation (DFG) in the form of an Emmy Noether Research Group (grant number KR4801/1-1, PI Kruijssen). J.M.D.K. gratefully acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program via the ERC Starting Grant MUSTANG (grant agreement number 714907, PI Kruijssen). E.S. acknowledges funding from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation program (grant agreement No. 694343). G.B. is supported by CONICYT/FONDECYT, Programa de Iniciación, Folio 11150220. A.P.S.H. is a fellow of the International Max Planck Research School for Astronomy and Cosmic Physics at the University of Heidelberg (IMPRS-HD). J.P. acknowledges support from the Programme National “Physique et Chimie du Milieu Interstellaire” (PCMI) of CNRS/INSU with INC/INP co-funded by CEA and CNES. A.U. acknowledges support from Spanish MINECO grants ESP2015-68964 and AYA2016-79006. Facilities: ALMA , IRAM:30m , IRAM:Interferometer , CARMA . Software: IPython (Perez Granger 2007 ), NumPy (Oliphant 2007 ), SciPy (Oliphant 2007 ), Matplotlib (Hunter 2007 ), Astropy (Astropy Collaboration 2013 ), emcee (Foreman-Mackey et al. 2013 ), CASA (McMullin et al. 2007 ).


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

indicated by the green cross-hairs. The dotted line connects the feature with the core feature and is plotted with the mean position angle. The position at the image epoch is shown by a filled blue circle while other epochs are plotted with unfilled blue circles. The red solid line indicates the vector fit (or accelerating fit, if there is significant acceleration) to the feature positions. The gray dashed circles / ellipses indicate the fitted FWHM sizes of the feature at the measured epochs. Figure 2.1057. 1345+125 Component 01 Positions are relative to the core position. The left-hand panel shows a 15 GHz VLBA total intensity contour image of the jet at the epoch closest to the middle reference epoch. The green box delimits the zoomed region that is displayed in the middle panel. The feature's position at the image epoch is indicated by the green cross-hairs. The dotted line connects the feature with the core feature and is plotted with the mean position angle. The position at the image epoch is shown by a filled blue circle while other epochs are plotted with unfilled blue circles. The red solid line indicates the vector fit (or accelerating fit, if there is significant acceleration) to the feature positions. The gray dashed circles / ellipses indicate the fitted FWHM sizes of the feature at the measured epochs. Figure 2.1058. 1345+125 Component 02 Positions are relative to the core position. The left-hand panel shows a 15 GHz VLBA total intensity contour image of the jet at the epoch closest to the middle reference epoch. The green box delimits the zoomed region that is displayed in the middle panel. The feature's position at the image epoch is indicated by the green cross-hairs. The dotted line connects the feature with the core feature and is plotted with the mean position angle. The position at the image epoch is shown by a filled blue circle while other epochs are plotted with unfilled blue circles. The red solid line indicates the vector fit (or accelerating fit, if there is significant acceleration) to the feature positions. The gray dashed circles / ellipses indicate the fitted FWHM sizes of the feature at the measured epochs. Figure 2.1059. 1345+125 Component 03 Positions are relative to the core position. The left-hand panel shows a 15 GHz VLBA total intensity contour image of the jet at the epoch closest to the middle reference epoch. The green box delimits the zoomed region that is displayed in the middle panel. The feature's position at the image epoch is indicated by the green cross-hairs. The dotted line connects the feature with the core feature and is plotted with the mean position angle. The position at the image epoch is shown by a filled blue circle while other epochs are plotted with unfilled blue circles. The red solid line indicates the vector fit (or accelerating fit, if there is significant acceleration) to the feature positions. The gray dashed circles / ellipses indicate the fitted FWHM sizes of the feature at the


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W.T.B. was provided travel support to the Coronal Loops Workshop VII held in Cambridge, UK, at which a preliminary version of this work was presented, by NSF award number 1536094. This work was supported in part by the Big-Data Private-Cloud Research Cyberinfrastructure MRI-award funded by NSF under grant CNS-1338099 and by Rice University. Software: astroML (VanderPlas et al. 2012 ), IPython/Jupyter (Pérez Granger 2007 ), matplotlib (Hunter 2007 ), NumPy/scipy (van der Walt et al. 2011 ), seaborn (Waskom et al. 2016 ).


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May 2 (chosen arbitrarily) and are integrated using a Bulirsch–Stoer integrator, considering the gravitational perturbations from the eight major planets (with the Earth–Moon system represented by a single point mass at the barycenter of the two bodies), relativistic effects, and β = 0.001 particles, radiation pressure, and Poynting–Robertson drag. The particle representing Phaethon and all other dust particles are considered to be massless and do not interact with each other. We find that it only takes about 250 years (∼200 orbits) for particles to spread to the entire orbit of Phaethon (Figure 1 , left panel). The timescale is much shorter (∼30 years) for β = 0.001 particles under cometary ejection. The definition adopted here is the “encircling limit” described in Ye et al. ( 2016 , Section 3): meteoroids have spread to most of the orbit of the parent when the standard deviation of their mean anomalies σ ( M ) has reached 60°. The mathematical consideration is that 99.7% of the meteoroids have spread to half-orbit, or 180° in mean anomaly, assuming a Gaussian distribution along the orbit. (One may wonder why we do not choose 360° in mean anomaly instead of 180°. The reason is that σ ( M ) becomes highly sensitive to regional overdensities when meteoroids are quasi-evenly distributed along the orbit or , as reflected in the figure, and is no longer a good indicator of the dispersion of meteoroids along the orbit.) Figure 1. Evolution of particles ejected under different ejection mechanisms, cometary or gravitational escape. Left panel: standard deviation of mean anomalies of simulated particles, σ ( M ); the encircling limit at σ ( M ) = 60° follows the definition in Ye et al. ( 2016 ) (described in the main text). Right panel: along-orbit distance of the center of the particles (represented by the mean of the mean anomaly, ) to Phaethon. Regardless of the driving mechanism and size ( β ) of the particle, it only takes a small number of orbits for the bulk of the ejecta to spread to significant distances from Phaethon (∼0.1 au). This means that if any materials larger than typical meteor sizes (see below for more on meteor-sized particles) were recently ejected, they could be closer to the Earth than Phaethon itself during their late 2017 approach to the Earth and are potentially detectable using existing facilities. Examination of the existence of such ejecta will therefore provide a useful diagnosis as to recent activity of Phaethon that is otherwise irretrievable. This will also provide useful information for the design of any Phaethon-bound spacecraft like DESTINY + . We find that β = 0.001 particles quickly drift away from Phaethon (Figure 1 , right panel). This radiation-driven process is very fast due to the extreme orbit of Phaethon, with the along-orbit recession rate being approximately 0.1 au yr −1 . This means that it takes less than an orbit for small particles to drift to different locations of the orbit and effectively


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ACKNOWLEDGEMENTS AP is grateful for research support from the Gates Cambridge Trust. NM, SG, and RM acknowledge support from the Science and Technology Facilities Council (STFC), UK. We thank the reviewer for useful comments that have helped improve the manuscript. This research has made use of the SVO Filter Profile Service supported from the Spanish MINECO through grant AyA2014-55216. We thank the contributors of the Python Software Foundation, the Open Science Framework, and NASA’s Astrophysics Data System.