O O O O O O O O O B-Instrument O O O O O O O B-Instrument 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 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 B-Instrument O O O O O O O O O O O O O O O B-Wavelength I-Wavelength 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 B-CelestialRegion I-CelestialRegion O O O O B-CelestialRegion I-CelestialRegion O O O B-Instrument 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 B-CelestialRegion 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 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 B-Model I-Model O O O O O O O O O O O O O O B-Model I-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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-Wavelength I-Wavelength O B-Wavelength I-Wavelength O O O O O O O O O O B-Instrument O O O O O O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O B-Wavelength I-Wavelength O O B-Wavelength I-Wavelength O B-Wavelength I-Wavelength O O O O O O O O

the pre-event frame acquired at 16:04 UT from the LASCO-C2 frame containing the CME at 19:30 UT. LASCO images were also used to measure the plane-of-the-sky (POS) velocity of the prominence, ν POS ≃ 300 km s −1 , as well as its projected thickness, D ≃ 56 000 km, which was taken as an approximation of the prominence average LOS thickness, under the simple assumption of cylindrical geometry. Fig. 1. LASCO-C2 mass image acquired at 19:30 UT on August 2, 2000, and intensity distribution of the Ly α line along the UVCS slit (measured at the same time and represented with color gradient). The two points considered in this analysis (P1, located at a helio-latitude of ~57° N, and P2, located at ~37° N) are also indicated. UVCS recorded spectra of several UV coronal lines (see Table 1 of Paper I for a complete list) as the prominence crossed its field of view (FOV), a 40 arcmin long slit placed perpendicularly to the solar radius at a latitude of 40°NE and heliocentric distance of 2.3 R ⊙ (see Fig. 1 ). In particular, spectral profiles of the neutral hydrogen Lyman- α ( λ 12 = 1215.67 Å) and Lyman- β ( λ 13 = 1025.72 Å) lines were acquired with a spatial resolution of 21 arcsec (≈15 000 km) and an integration time of 120 s during the entire CME event. Both lines systematically appear to be the superposition of two components with different widths, the narrower one representing, in our interpretation, real prominence emission, while the broader one is more likely due to plasma in the PCTR or, alternatively, in the hot plasma shroud surrounding the prominence (see Habbal et al. 2010 ). Table 1. Observed quantities and modeling results. The two components were separated with a double Gaussian fit to the line profiles, and consistency of the fit was verified with a minimum chi-squared analysis (see Paper I). A mean pre-event spectrum, obtained by averaging over several exposures preceding the onset of the eruption, was subtracted from the line profiles in order to remove the contribution from the quiet corona surrounding the prominence from the observed emission. This correction may not be accurate because, as evidenced by the depleted (black) region around the prominence in Fig. 1 , much of the pre-event corona has been blown away by the CME during the eruption. However, prominences are generally very bright in the Lyman lines (e.g., Ciaravella et al. 2003 ), and the quiet-corona contribution can be assumed to be very small; therefore possible uncertainties related to the background subtraction can be considered negligible in this case. Figure 2 reports the total integrated intensities of the Ly α and Ly β narrow components as functions of time and position along the UVCS slit. The prominence exhibits a complex structure in both lines, with ramifications and apparently superimposed emission features. The intensity of the Ly α line is up to 250 times higher than that of the Ly β . The Ly α to Ly β intensity ratio is consistent with the value somewhat


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ACKNOWLEDGEMENTS MC thanks A. Mead for useful conversations in the early stages of this work. MC, JHD and CH acknowledge support from the European Research Council under grant number 647112. CH acknowledges support from the Max Planck Society and the Alexander von Humboldt Foundation in the framework of the Max Planck-Humboldt Research Award endowed by the Federal Ministry of Education and Research. Work at Argonne National Laboratory was supported under U.S. Department of Energy contract DE-AC02-06CH11357. The authors are grateful to Ue-Li Pen for his assistance with computing resources. Computations were performed on the BGQ and Niagara supercomputers at the SciNet HPC Consortium (Loken etal. 2010 ; Ponce etal. 2019 ). SciNet is funded by the Canada Foundation for Innovation; the Government of Ontario; Ontario Research Fund - Research Excellence; and the University of Toronto.


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The contribution of V.S.T., Z.M., T.T., and J.A.L. was supported by NASA's HSR, LWS, and HGI programs, NSF grants AGS-1156119 (SHINE program) and AGS-1560411, NSF (Frontiers in Earth System Dynamics program), and contracts from Lockheed-Martin and Stanford University to Predictive Science Inc. O.P. was supported by NASA Grant NNX15AB89G. Computational resources for the MHD computation were provided by NASA Advanced Supercomputing and the NSF-supported XSEDE program.


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Based on observations collected at the European Southern Observatory Very Large Telescope in programme 177.D-3023(C). VMK and JSV acknowledge funding from DCAL-NI and the UK Science and Technology Facilities Council. VMK thanks the anonymous referee, and Drs R. Oudmaijer and G. Ramsay for providing helpful and constructive comments.


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This work is supported by the Fundamental Research Funds for the Central Universities and from the National Science Foundation of China (NSFC, grant No. 11421303 and grant No. 11590782). Studies of interstellar chemistry at Leiden Observatory are supported through a grant by the Netherlands Organisation for Scientific Research (NWO) as part of the Dutch Astrochemistry Network and through the Spinoza premie.


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

polarized intensity (grayscale), and polarization position angle segments (red bars) in the GGD27 MM1 disk. Bottom panel: similar as before, but the color image showing the polarization fraction (here, the polarization position angle segments appear as black bars). In both panels, the contour levels are 3, 10, 50, 120, 200, and 400 K. The wedge shows the scale of the polarized intensity and polarization fraction. The synthesized beam is shown in the bottom-right corner of the panels. Note that the 120 K contour appears at the transition radius, with an almost null polarization ring, between two distinctive polarization patterns. The region inside the transition radius, R turn , (hereafter the inner disk) has a very low polarization level region. Thus, within this radius the polarization degree has a mean value of 0.56% and a standard deviation of 0.33%. In the left panel of Figure 4 , the histogram of the polarization position angles shows two main directions. Most of the angles are partially aligned with the minor axis (226), with an average direction of ∼36°. The other region arises from the northeast quadrant of the inner disk, and shows an average position angle of −38°. Figure 4. Left panel: histogram of the distribution of the polarization position angles for the disk’s inner region ( R 010). The dashed line indicates the position angle of the disk minor axis. Right panel: histogram of the differences between the polarization position angles and the disk azimuthal angles for the disk’s outer region ( R > 010). The outer disk (i.e., the region outside R turn ) has significantly higher polarization levels than the inner disk, with an average value of 4.0% and a standard deviation of 2.3%. 17 17 This has been measured in a region enclosed between R turn and the disk radius of R disk . The polarization position angles have a nearly azimuthal pattern (i.e., they follow a direction tangent to the iso-intensity contours of the Stokes I emission). At the position of each polarization position angle segment shown in Figure 3 , we have computed the expected tangent angle for an ellipse centered in the disk center that crosses this point. The right panel of Figure 4 shows the histogram of the difference between this tangent angle and the observed polarization angle. The average angle difference, 11°, is relatively small. This confirms the azimuthal pattern in the outer disk. 4. Discussion 4.1. The Optically Thick Disk around the Massive Protostar Powering the HH 80–81 Jet The brightness temperature of the disk dust emission reaches high values, up to ∼400 K, but it drops well below 10 K in the outskirts of the disk. This suggests that the inner part of the disk is optically thick and that the dust optical depth decreases with radius, becoming optically thin. A multi-line analysis of SO 2 , at scales of a few hundred au, indicates that the average kinetic temperature of the traced molecular gas is ∼120 K (Fernández-López et al. 2011b ).


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of the code used here is essentially identical to the one employed by Hartlep et al. ( 2013 ). The code has been used over many years to study wave propagation in the solar interior in the presence of both sound-speed perturbations as well as flows, and was used to help improve and validate various helioseismic measurement and inversion techniques. This includes the far-side imaging technique for detecting solar active regions on the side facing away from Earth using observations from the Earth-facing side (Zhao 2007 ; Hartlep et al. 2008 ; Ilonidis et al. 2009 ); measuring the solar meridional flow in the deep interior (e.g., Hartlep et al. 2013 ; Roth et al. 2016 ); detecting sound-speed variation using time–distance helioseismology (Parchevsky et al. 2014 ) and the acoustic holography technique (Braun 2014 ; Díaz Alfaro et al. 2016 ); and studies related to magnetic flux emergence (e.g., Hartlep et al. 2011 ; Ilonidis et al. 2013 ). The code models solar acoustic oscillations in a spherical domain using the Euler equations linearized around a stationary background state, which is characterized by a background density, sound speed and acceleration due to gravity, all taken from a standard solar model. The code also takes into account the effect of mass flows on the propagation of waves. For the governing equations and more details on the code, we refer to Hartlep et al. ( 2013 ). A significant difference between how the code is used in the current study and previous works is the excitation of acoustic waves. In the Sun, turbulent flows near the photosphere act as sources for acoustic perturbations driving waves in a stochastic fashion. However, since this driving mechanism is a nonlinear process, it is lost by linearizing the governing equations. Therefore, for most previous studies, a stochastic term was added in the equations to mimic this excitation. This is not used here, however. Instead, each simulation excites and follows individual waves as described in the next section. 2.1.2. Simulation Setup In order to measure helioseismic travel times accurately, one usually needs many hours of data, for either actual solar observations or numerical simulations that are stochastically driven to mimic solar-like wave excitation. Such numerical simulations are feasible when only one or few sets of them are needed, as for instance in Hartlep et al. ( 2008 , 2013 ). However, for deriving sensitivity kernels, we need to probe many perturbations at many different depths and locations while keeping them spatially separated to avoid travel times to be shifted by multiple perturbations simultaneously. This requires many individual simulations, with only few perturbations in each, which quickly becomes infeasible. The alternative we have chosen here is to simulate not a stochastic Sun-like wavefield but excite individual waves and measure their travel times from their source location to other points on the surface. There is no stochastic noise in this


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I thank Dr. Miho Janvier for a critical review of the manuscript and several helpful suggestions. I also gratefully acknowledge the stimulating discussions on related topics from the team on magnetic waves in solar flares led by Alexander Russell and hosted and organized by the International Space Science Institute ISSI.


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ACKNOWLEDGEMENTS We would like to thank to Dr. G.B. Rusu from the USAMV, Iasi, Romania for its help during the electron microscopy imaging. Our thanks also go to Dr. R. Jijie, for her contribution during the preliminary phases of the study, and to our colleagues, Dr. G. Borcia, Dr. A. Chiper and Prof. G. Popa, for careful reading of the manuscript and helpful suggestions. This work was supported by the Romanian Space Agency (ROSA) under the project STAR CDI ID 486/2017–2018. The authors also acknowledge the support from the COST action CM1401 (Our Astro-Chemical History).


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The authors thank the anonymous referee for constructive comments that helped to improve the manuscript and presentation of the results. The research work was funded by the Austrian Science Fund (FWF): P27765 and P23618. The model calculations have been carried out at VSC (project P70068, H. Muthsam). We thank Luis Bellot Rubio from the Instituto de Astrofisica de Andalucia (CSIC) supplying the inverted SUNRISE IMaX data used in this paper.


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ACKNOWLEDGEMENTS We are grateful to an anonymous referee whose suggestions helped improve the manuscript. PH acknowledges financial support from the Natural Sciences and Engineering Research Council of Canada and thanks NAOC for hospitality during a sabbatical visit made possible by support from the Chinese Academy of Sciences (CAS President’s International Fellowship Initiative, 2017VMA0013). We also acknowledge support from the National Natural Science Foundation of China under grant numbers 11733007 and 11673037.


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

possible powering source could be the spin-down of a magnetar (Kasen Bildsten 2010 ; Inserra et al. 2013 ; Nicholl et al. 2013 ). Another possibility is the interaction between the ejecta and an H-poor CSM (Chatzopoulos, Wheeler Vinko 2012 ; Sorokina et al. 2016 ; Vreeswijk et al. 2017 ). A third scenario could be a pulsational pair-instability SN (Woosley, Blinnikov Heger 2007 ; Woosley 2017 ), or pair-instability explosion of a very massive star (with a core of ≥50 M ⊙ , e.g. Gal-Yam et al. 2009 ; Dessart et al. 2013 ). The latter is perhaps limited only to slowly declining H-poor SLSNe, SLSNe-R, with a declining rate consistent with the radioactive decay of 56 Ni and 56 Co. Until recently, models predicted a long rise in contradiction to observations (Chen et al. 2015b ), but Kozyreva et al. ( 2017 ) showed that they can also be fast rising. The long rise times predicted by pair-instability supernova models have been seen in at least one SLSN (Lunnan et al. 2016 ). However, spectroscopic models predict spectra that are different from observations (Jerkstrand, Smartt Heger 2016 ). SLSNe-R are a potential subclass of SLSNe-I. The existence and characterization of this class is discussed in Gal-Yam ( 2012 ) and De Cia et al. (in preparation). While the debate on the powering source of SLSN-I is ongoing, the general agreement is that these explosions are associated with the death of massive stars, given their total radiated energies ( E > 10 51 erg, Gal-Yam 2012 ). The study of their host galaxies has revealed that SLSN-I require extreme hosts, e.g. with low-metallicity ( Z ≤ 0.5 Z ⊙ ) and a high rate of star formation (SFR) for their low mass (Neill et al. 2011 ; Lunnan et al. 2014 ; Thöne et al. 2015 ; Chen et al. 2016 ; Perley et al. 2016 ; Schulze et al. 2016 ), and strong emission lines (Leloudas et al. 2015 ). However, Perley et al. ( 2016 ) argue that a high rate of star formation is not required, since there are many counterexamples of SLSNe with low SFRs, based on slit spectroscopy. High-resolution observations with Hubble Space Telescope (HST) showed that the host galaxies of hydrogen-poor SLSNe are usually irregular dwarf galaxies with asymmetric morphology or multiple peaks (Lunnan et al. 2015 ; Angus et al. 2016 ). Gamma-ray bursts (GRBs) are another energetic phenomenon likely associated with deaths of massive stars (Hjorth et al. 2003 ). Their host galaxies show similarities to the hosts of SLSNe (Lunnan et al. 2014 ), although the latter are more extreme (Vreeswijk et al. 2014 ; Leloudas et al. 2015 ; Perley et al. 2016 ; Schulze et al. 2016 ). Fruchter et al. ( 2006 ) and Blanchard, Berger Fong ( 2016 ) showed that GRBs are more concentrated in the brightest regions of their host galaxies. Similarly, if SLSNe are indeed associated with very massive stars, and their hosts are unusual for the young stellar content (Leloudas et al. 2015 ; Thöne et al. 2015 ), one natural expectation is that they may explode in blue, UV bright,


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

non-thermal electrons with energy 30 keV are depositing their energy and the plasma densities are sufficient to make 0.4 THz emission optically thick. The observation of ribbon-like HXR emission ( Liu et al. 2007 ) is often viewed as an additional indication that UV emission is caused by the energy deposition of HXR producing electrons. 4.3. Time variability of sub-THz emission Relatively dense plasma n > 10 11 cm −3 heated by energetic electrons to temperatures 0.1–1 MK leads to enhanced radiation ( Raymond et al. 1976 ; Johnson et al. 2011 ; Scullion et al. 2016 ), so that the radiation losses would lead to effective cooling. The radiative cooling time is ( Cox Tucker 1969 ; Raymond et al. 1976 ; Bian et al. 2016 ) where the radiative loss function is calculated using the CHIANTI ( Dere et al. 1997 ) function rad_loss.pro 2 . The radiative loss can be estimated using the approximation Λ( T )≃1.2 × 10 −19 T −1/2 , where T is in units of kelvin and Λ( T ) in units of [erg cm 3 s −1 ], giving Λ( T )≃4 × 10 −22 for T = 10 5 K. The radiative loss time for plasma temperatures between T = 10 4 − 10 6 K is shown in Fig. 3 . The results suggest that the plasma can quickly cool if the heating time is greater than the radiation loss time. The observations by Kaufmann et al. (2009a) show that the flux changes with a characteristic time of 0.1 − 1 s. This suggests that the interplay between non-thermal electron heating and the radiative cooling of dense plasma can explain the observed variability of sub-THz emission. Quasi-synchronised broadband solar flare rapid pulsations at sub-second timescales are observed at HXR and centimetre-millimetre wavelengths ( Takakura et al. 1983 ; Cornell et al. 1984 ; Kaufmann et al. 2000 ). These short-timescale features are often called “elementary bursts” following de Jager de Jonge (1978) . In particular, efforts to search for small-scale structures have also been made in optical wavelengths, typically H α observations ( Wang et al. 2000 ; Trottet et al. 2000 ; Kurt et al. 2000 ; Altyntsev et al. 2008 ; Fleishman et al. 2016 ) For example, Wang et al. (2000) reported fine temporal structures of the order of 0.3 − 0.7 s in H α off-band emission, and it is found that these fine structures only occur at flare kernels whose light curves are closely correlated with HXR emission. This close correlation suggests that the sub-THz pulsations are caused by fast electron energy deposition or by thermal conduction in the transition region and heated chromosphere. In such a scenario, the finite temperature of the ambient plasma plays an important role in determining the energy deposition ( Kontar et al. 2015 ; Jeffrey et al. 2015 ). An alternative way proposes heating by fast electrons accelerated in situ in the chromosphere due to the magnetic Rayleigh-Taylor instability ( Zaitsev Stepanov 2015 , 2017 ). 5. The sub-THz emission model During solar flares the transition region defined as the plasma between the chromosphere and


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Acknowledgements We thank the anonymous referee for insightful comments and suggestions. We thank Vincent van Eylen and Subo Dong for useful discussions. This work was supported by the Netherlands Research Council NWO [grant #621.016.701 (LGM2)] and by the Netherlands Research School for Astronomy (NOVA). This research was supported by the Interuniversity Attraction Poles Programme (initiated by the Belgian Science Policy Office, IAP P7/08 CHARM) and by the European Union's Horizon 2020 research and innovation programme under grant agreement no. 671564 (COMPAT project).


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Acknowledgments We thank the anonymous referee for their comments, which helped us to improve the manuscript. We thank Alessandro Bressan for his invaluable suggestions and useful discussions. MM and MS acknowledge financial support from the Italian Ministry of Education, University and Research (MIUR) through grant FIRB 2012 RBFR12PM1F and from INAF through grant PRIN-2014-14. MM acknowledges support from the MERAC Foundation. Part of the Numerical calculations have been made possible through a CINECA-INFN agreement, providing access to resources on GALILEO and MARCONI at CINECA.


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

is particularly the case when considering stars with (quasi)periodic amplitude/phase change, commonly known as the Blazhko phenomenon ( Blazhko 1907 , see also Shapley 1916 ). Most of the progress made on this issue comes from observations, largely attributed to the space missions CoRoT and Kepler (e.g., Benkő et al. 2014 ; Szabó et al. 2014 ). Nevertheless, even these highly accurate data have been unable to provide the grounds for a physically sound (and working) scenario 1 . There are also contradictory figures on the mere occurrence rates of the Blazhko (hereafter BL) stars. These rates (for fundamental mode stars) range from ~ 12% to ~ 50% (see Kovacs 2016 and Smolec 2016 and references therein). Interestingly, analyses of the high-precision space observations yield apparently quite similar rates to those derived from classical ground-based data ( Benkő et al. 2014 ; Jurcsik et al. 2009 ). This, and the apparent lack of application of modern methods of time series analysis in this field, has prompted us to examine the occurrence rates of the BL stars from a subset of the available space data. Even without knowing the underlying physical cause of the BL phenomenon, it is clear that this single number may help to distinguish between various ideas. For example, models based on the resonance between radial modes will likely face difficulties if amplitude/phase modulation is indeed as common as the present study shows. 2. Datasets and the method of analysis In establishing a solid, but not too extensive dataset for this introductory work, we opted for the Kepler two-wheel (K2) survey. Unfortunately, there are not many well-documented (star-by-star) RR Lyrae surveys available for this mission. However, the variability survey on Campaigns 0–4 by Armstrong et al. (2016) has proven to be extensive enough, suitable for the purpose of this work. We have chosen not to include C0 due to the short observational time span devoted to this campaign in the early phase of K2. A few basic parameters of the datasets used are listed in Table 1 . As this table shows, there are several miss-classifications in the original list 2 . Nevertheless, the number of the remaining stars is large enough to use them as a statistically significant sample in assessing the occurrence rate of the BL phenomenon. There are some four or five stars belonging to the globular cluster M4 in C02; otherwise the rest are apparently Galactic field/halo stars (many of them are rather faraway objects); see Fig. 1 for the distribution of the 237 targets analyzed in this paper over the Kepler field of view during the four campaigns. Fig. 1. Distribution of the stars analyzed in this letter (see Table 1 ) in the field of view of Kepler . Table 1. Summary of the datasets used in this paper. Notes. N tot stands for the total number of stars classified as RRab stars by Armstrong et al. 2016 . N RR is for the actual number of RRab stars. The time series data were downloaded for C01 and C02 from


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 O O O O B-Person O B-Person O O O O O O O O O B-Organization I-Organization I-Organization O B-Organization B-Grant I-Grant I-Grant I-Grant B-Grant B-Person O O O B-Organization O B-Location O O O B-Grant B-Grant I-Grant I-Grant O O O 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 B-Organization I-Organization I-Organization I-Organization I-Organization O O O O O B-Software O O O B-Software I-Software I-Software O O O O B-Location B-Organization O O B-Grant O O O O O O O B-Database O O O B-Organization B-Location I-Location O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O B-Software O O O O O O B-Software O B-Citation I-Citation I-Citation I-Citation O B-Software O B-Citation I-Citation O B-Software O B-Citation I-Citation O B-Software O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O B-Software O B-Citation I-Citation I-Citation I-Citation O B-Software O B-Citation I-Citation I-Citation I-Citation O O B-Software O B-Citation I-Citation I-Citation O B-Citation O O

Acknowledgement We thank C. Dominik for his extremely valuable input on infrared excesses of circumstellar disks and the anonymous referee for providing useful feedback that helped to improve the quality of this article. The research of A.J.B. and F.S. leading to these results has received funding from the European Research Council under ERC Starting Grant agreement 678194 (FALCONER). M.B. acknowledges funding from ANR of France under contract number ANR-16-CE31-0013 (Planet Forming disks). Part of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. This publication makes use of VOSA, developed under the Spanish Virtual Observatory project supported from the Spanish MINECO through grant AyA2017-84089. This research has made use of the SIMBAD database, operated at CDS, Strasbourg, France ( Wenger et al. 2000 ). To achieve the scientific results presented in this article we made use of the Python programming language 4 , especially the SciPy ( Jones et al. 2001 –), NumPy ( Oliphant 2006 ), Matplotlib ( Hunter 2007 ), scikit-image ( Van der Walt et al. 2014 ), scikit-learn ( Pedregosa et al. 2012 ), photutils ( Bradley et al. 2016 ), and astropy ( Astropy Collaboration 2013 , 2018 ) packages.


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b ) and Nardiello etal. ( 2015 ). To look for signatures of SP stars along M4 AGB stars in the V C UBI plane, we follow a standard procedure similar to the one outlined in Monelli etal. ( 2013 ). We first cleaned the CMD from foreground/background contamination, i.e. cluster membership has been assigned on the basis of the source position in the ( B I ) versus ( U V ) plane (see fig. 2 in Monelli etal. 2013 ). As a first step, we defined AGBs as shown in the top-left panel of Fig. 2 . Then, we plotted the selected stars in other CMDs that provide the cleanest separation of the evolved sequences to help verify the identification (see Fig. 2 ). To this aim, we cross-correlated our UBVI photometry with the 2MASS catalogue 3 to carefully inspect the position of selected AGB stars in CMDs including near-infrared colours. All selected stars are compatible with being AGBs in all diagrams displayed in Fig. 2 . This demonstrates that they cannot be RGBs migrated to the AGB sequence due to photometric errors. Indeed, no random errors can explain that the selected stars are always located in a well-defined sequence bluer of the main body of the RGB in different CMDs obtained from independent measurements/data sets. From all the above, we conclude that the selected stars are indeed AGBs. We finally note that the observed AGB/RGB ratio ( R AGB/RGB 0.44 0.23) agrees within the errors with the theoretical one ( R AGB/RGB 0.37). This by itself is obviously not a proof that all candidate AGBs are indeed AGB stars, but just a consistency check for our empirically derived value of R AGB/RGB . Figure 2. Selection of AGB star candidates in different CMDs. From top-to-bottom: V , B V ; V , B I ; and U , U I . Empty cyan symbols are AGB stars. Magenta asterisks mark candidate AGB stars in common with Marino etal. ( 2008 ). To assess whether some significant residual contamination may still be present in our AGB sample after the field-star subtraction, we used the code TRILEGAL (Girardi etal. 2005 ). We determined the fraction of Galactic field stars within a box 3030arcmin 2 (i.e. comparable to the FoV of our photometric catalogue) centred on the cluster centre that survive our cluster AGB selection. We found one star with colours and magnitudes consistent with being on the cluster AGB, to be compared with the two AGB objects rejected with our field-subtraction procedure. This implies that any residual field contamination is very likely negligible. Fig. 3 shows the V C UBI diagram, with AGB stars highlighted. As already shown by Monelli etal. ( 2013 ), the RGB shows a large C UBI spread at fixed V , that exceeds the spread due to photometric errors, and a hint of bimodality can also be observed. Figure 3. V C UBI diagram is shown. AGB stars and stars in common with the Marino etal. ( 2008 ) study are marked with the same symbols as in Fig. 2 . We display also a fiducial reference line (dashdotted line) employed to quantify the broadening of the RGB and AGB sequences


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

6 are heavily driven by the differential abundances of the most volatile species, such as C, CH, O, and N (i.e., T Cond 200 K). In fact, the number of volatiles is much smaller than the number of refractory elements, as is visible in Figure 1 . In addition, the chemical abundances of volatile elements are often more uncertain than those of refractories. In the case of HIP 34407/HIP 34426, the chemical anomaly is extremely large compared to all the other pairs. The elements with an intermediate condensation temperature, such as Na, S, and Zn (i.e., 500 T Cond 1000 K) are well aligned by the Δ[X/H]– T Cond relation plotted in Figure 1 . This neat linear relation between elemental abundances and condensation temperature for this system may suggest that the anomaly was caused by a planetary engulfment event. Similar results were independently obtained by Ramirez et al. ( 2019 ). Interestingly, the HIP 34407/HIP 34426 system was determined to be the most chemically inhomogeneous system found to date among other pairs in binary systems or clusters, that show similar trends between abundances and condensation temperature (Tucci Maia et al. 2014 , 2019 ; Biazzo et al. 2015 ; Spina et al. 2015 , 2018 ; Teske et al. 2015 , 2016 ; Saffe et al. 2016 , 2017 ; Oh et al. 2018 ). Its median differential abundance in the refractory elements is 0.19 dex. In addition, we note that the results from the HIP 34407/HIP 34426 system involve similar but not identical volatile elemental abundances. Out of the four most volatile species measured (i.e., ), only one is consistent with zero, leading to the hypothesis that the slope is due to the engulfment of a gas giant. This is because such planets are capable of causing abundance changes in both volatiles (due to their gaseous outer layers) and refractories (due to their rocky cores and metallic inner layers). This hypothesis has been also proposed to explain a similar anomaly observed in the chemical composition of the 16 Cyg binary system (Tucci Maia et al. 2014 , 2019 ). 4. Conclusions The occurrence of chemically anomalous stars at the 0.01 dex precision level can be deduced from line-by-line differential analysis of twin stars in binary systems. Out of the 14 systems measured using UVES and HDS, 6 were found to exhibit chemical inhomogeneities (i.e., σ χ ), rendering chemical tagging on these systems inaccurate. However, only two pairs were chemically inhomogeneous at the precision level typical of large spectroscopic surveys (i.e., 0.05 dex). Of special note is that the HIP 34407/HIP 34426 system was determined to be the most chemically inhomogeneous system found to date. For this pair, the trend between differential abundances and condensation temperature is neat, and it may suggest that rocky material has polluted the atmosphere of HIP 34407. We speculated that the planet engulfed by the star was a giant gaseous planet, as HIP 34426 is also anomalously rich in the volatiles. The planet population around the


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ACKNOWLEDGEMENTS We thank the referee for constructive and valuable comments, which increased the scope of our work significantly and improve the overall quality even in some details of our paper. We thank Artem Tuntsov, Oleg Yu. Tsupko, and Shude Mao for interesting discussions. XE is supported by National Nature Science Foundation of China Grant No. 11473032 and No. 11873006. AR wishes to acknowledge the contribution of the Brandon University Research Committee.


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We thank the referee for the interesting comments. We are grateful to Emmanuel Bertin for many enlightening discussions. F.D. acknowledges long-term support from CNES. I.M. acknowledges financial support from the Spanish Ministry of Economy and Competitiveness through the grant AYA2013-42227P.


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This work was carried out through the National Solar Observatory Research Experiences for Undergraduate (REU) site program, which is co-funded by the Department of Defense in partnership with the NSF REU Program. The National Solar Observatory is operated by the Association of Universities for Research in Astronomy, Inc. (AURA) under cooperative agreement with the National Science Foundation. S.C. is grateful to Dr. Peter Foukal for reading the paper and providing useful comments, and to Dr. Odele Coddington for interesting discussions about the NRL reconstructions.


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

JS thanks Rob Simcoe, Kate Rubin, Laura Sales, Vicente Rodriguez-Gomez, and Dylan Nelson for their helpful comments. VS acknowledges support by the European Research Council under ERC-StG EXAGAL-308037. LH acknowledges support from NASA grant NNX12AC67G and NSF grant AST-1312095.


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

of 3.6 . The adopted width variation at each step corresponds to considering one more point at each side of the line profile, i.e. the minimal possible difference when the profile width is varied symmetrically around the centre. For each considered profile width, we performed a linear regression over the 50 synthetic spectra to obtain the optimal value of that gives the best results to determine H eff through equation ( 3 ). Note that it is not possible to obtain separately the values λ 0 and g 0 , but only their product. The results are shown in Fig. 2 . In the upper panel, we show the mean absolute percental error (MAPE) obtained by comparing the original values of H eff and the ones derived by the regressions, 1 while the lower panel shows the respective fitted values of , both as a function of the integration limits (width profiles). Figure 2. Mean absolute per centual error (upper panel) and normalization values (lower panel) as a function of the profiles width. In the right Y -axis of the lower panel, the values are normalized to the case when the profile width is 39.6 . The results were obtained analysing a sample of 50 synthetic spectra. The first remark of this test is that for all considered profile widths, it is always possible to fit a value of that allows us to infer very accurately H eff : the MAPE remains inferior to 1.0 per cent in the big majority of the cases. This result is quite unexpected since even underestimating the width of the profiles up to the extreme case in which the profiles consist of only five central points (from −3.6 to 3.6 ), one can obtain very precise estimations of H eff . Analogously, the same behaviour is obtained when the profiles are highly overestimated, with very small MAPE values. The fact that it is possible to consider deliberately only a part of the profiles to infer H eff can be useful in some practical applications, as, for example, in binary systems or in stars surrounded by circumstellar envelopes with strong stellar winds that can generate shocks visible as bumps. The bump produced by the shock is in turn blended with the intensity profile of the star (e.g. Sabin, Wade Lèbre 2015 ), so to consider only a fraction of the intensity profile of the star could be of interest. Another important result of this test is that it shows that the value of is very sensitive to the integration range, see lower panel of Fig. 2 . The fitted values of start at 329 nm (profile width of 7.2 ) and they increase very quickly to reach a maximum of 918 nm (profile width of 21.6 ), to then decrease following a likely exponential-type curve, finishing at 286 nm for the broadest profile width of 97.2 . Additionally, to illustrate the relative changes in the values of , we take as reference a width of 39.6 (from −19.8 to 19.8 ), which seems a plausible selection by visual inspection of the profiles in Fig. 1 . In the right Y -axis of the lower panel in Fig. 2 are shown the percentage variations of : as example, if


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Lind ( 2017 ) predict for Al a correction for dwarf and giant stars of ∼−0.1 dex at solar metallicity for the line at 669.6 nm. For Mg, we do not expect NLTE effects to have a strong influence on the abundances. Zhang et al. ( 2017 ) calculate corrections of the order of ±0.01 dex for stellar parameters similar to our NGC 6633 sample. For the same stars, Zhang et al. ( 2016 ) predict corrections of the order of −0.03 (RGB) and 0.00 dex (MS) for Si. The latter, however, has , i.e. the offset is relatively large and cannot be explained by NLTE effects. Since also in the case of M67, we found that the offset in Si between the upper MS and RGB is larger than predicted by the models, this could mean that indeed for Si there is a bias in the analysis of dwarf and giant stars. 5.4 APOGEE DR14 The recent fourteenth data release of the Apache Point Observatory Galactic Evolution Experiment (hereafter APOGEE DR14; see Abolfathi et al. 2017 ; Majewski et al. 2017 ) contains very important results concerning the abundances of M67 stars. In APOGEE DR14, stars in every evolutionary stage of M67 have been observed and analysed, from the MS to the RC. We decided to be as conservative as possible in the choice of the stars to be taken into consideration and we selected only those with STARFLAG, ASPCAPFLAG, and the ELEMFLAG of the element under study equal to zero. By doing so, we aim at excluding as many possible biases due to unreliable results as possible. APOGEE DR14 contains the abundances determined by the APOGEE Stellar Parameters and Chemical Abundances Pipeline (ASPCAP) (see Holtzman et al. 2015 ; García Pérez et al. 2016 ) as well as calibrated abundances. These are calculated under the assumption that abundances of open cluster members should be homogeneous and that therefore any trend with temperature must be corrected for. Since for our purposes it is important to take into consideration any trend of the chemical abundances as a function of temperature, we decided to use the uncalibrated abundances. We present the results in the form [X/H]. For the elements that were calculated as [X/M], we add the uncalibrated [M/H] of the star. The error bars only represent the errors on the fit of the uncalibrated abundances presented in the APOGEE DR14 catalogue (for the uncalibrated [M/H] no errors are given). These are very small and are not to be considered realistic errors. Fig. 5 shows the CMD of the sample (not corrected for reddening) selected after a membership analysis based on radial velocity, PM, photometry and metallicity, and after all stars with the flags listed above not equal to zero were excluded. The stars are colour coded based on their iron abundance. It is already clear from this plot that [Fe/H] on the TO is lower than on the RGB and on the RC. Since no calibrated log g is available for dwarf stars in APOGEE DR14, we plotted in Fig. 6 the abundances of several species as a function of the effective temperature together with the models


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This research was supported by NSF Grant AST-0708079, the Louisiana Space Consortium and NASA through Grant NNX10AI40H, as well as the Kathryn W. Davis Postdoctoral Scholar program, which is supported in part by the New York State Education Department and by the National Science Foundation under grant numbers DRL-1119444 and DUE-1340006. A.U.L. acknowledges support from NSF Grant AST-0803158. K.L.P. and J.P.O. acknowledge support from the UK Space Agency. G.H. acknowledges partial financial support from the Austrian FWF grant P20526-N16 and encouragement from Patrick Woudt. We heartily thank all members of the USCO2010 collaboration, whose observations were critical to our successful campaign. We acknowledge with many thanks the variable star observations from the AAVSO International Database contributed by observers worldwide and used in this research, as well as the observers of the Center for Backyard Astrophysics. This publication makes use of data products from the Wide-field Infrared Survey Explorer , which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration. This research has made use of the NASA/IPAC Infrared Science Archive, which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.


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The authors acknowledge research funding by the Deutsche Forschungsgemeinschaft (DFG) under the grant SFB 963/1 project A18. L.G. acknowledges support from EU FP7 Collaborative Project Exploitation of Space Data for Innovative Helio- and Asteroseismology (SPACEINN). S.H. acknowledges a collaboration with the Max Planck Institute for Solar System Research through a Max Planck Partner Group established at the Tata Institute of Fundamental Research, Mumbai. We thank Robert Cameron for useful discussions and Jesper Schou and Hannah Schunker for useful comments.


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

dispersion relation for the slow mode gives for quasi-perpendicular and perpendicular propagations. The weak perpendicular magnetic power can be associated with the Alfvén mode. In this discussion, it is assumed that the plasma temperature is isotropic. However, the presence of temperature anisotropy can modify the dispersion relation of the MHD eigenmodes and/or excite other wave modes, such as the mirror mode, kink mode and sausage mode (e.g., Hasegawa 1975 ; Huang et al. 1988 ; Wang Hau 2003 ; Schoeffler et al. 2011 ). The modification of eigenmodes and the excitation of other modes can also affect the turbulence and hence alter the observed power relation. 7. Summary This paper presents the turbulence spectra of magnetic and electron density fluctuations in situ measured by Voyager 1 in the local ISM. The results can be summarized as follows: 1. The present magnetic spectra obtained by Lomb–Scargle periodogram show a good agreement with the results by Burlaga et al. ( 2015 , 2018 ). At m k ≤ 10 −8.8 , the magnetic spectrum is close to a Kolmogorov power law with a one-dimensional power-law index −5/3. The magnetic SDFs show a bulge of enhanced magnetic power at m k = 10 −8.8 –10 −8.2 . 2. We extend our previous study of the electron density turbulence spectrum (Lee Lee 2019 ) and spans the data coverage to 2019 June. The composite spectrum of both the present in situ measurements and the earlier remote observations shows the Kolmogorov power law in the inertial range (10 6 –10 18 m) and an enhanced power in the kinetic range (50–10 6 m). 3. The electron density turbulence measured by Voyager 1 in the local ISM shows higher intensity than that of the remote observations in the distant ISM by a factor of 10 1.96 ≈ 91. Such an enhanced turbulent power can be resulted from a combination of the energy sources from both the turbulent interstellar plasma and the turbulent solar wind. 4. The relationship between the outer scale L 0 , and the rms values of magnetic and electron density fluctuations are obtained. In the calculation with only in situ measured data of electron density and magnetic field, we obtain and for L 0 = 3 × 10 14 m. Burlaga et al. ( 2018 ) obtained the same outer scale and interpreted this outer scale as the spatial range of the disturbed local ISM, which is separated by the bow wave or bow shock from the undisturbed local ISM. 5. For the typical interstellar cloud size L 0 = 10 18 m, we obtain from the in situ measured magnetic data and obtain by including both the in situ measurements and remote observations in the calculation of electron density SDFs. These rms values of magnetic and electron density fluctuations are much higher than the in situ measured mean values because the turbulence amplitude becomes larger at a longer wavelength. Chepurnov Lazarian ( 2010 ) measured a high electron density fluctuation power at the scale of an interstellar cloud. A high magnetic strength of tens of nanotesla has been observed at the


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The research of JRM is supported through a Royal Society University Research Fellowship. The authors thank Daniel Mortlock for reviewing a draft of the paper and the referee Nancy Elias-Rosa. The authors are grateful to Jason Kalirai, Paul Crowther and Simon Goodwin for their useful discussions during the preparation of this manuscript.


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

by cutting the first 10 multipoles. Figure 6. We plot the SNR for the optimistic Euclid cluster survey (Eu_cl_opt) as a function of l min (top left), the maximum redshift probed by the survey (top right), the area of the sky survey (bottom left), and the minimum observed mass as over the redshift range 0.2 ≤ ≤ 2 (bottom right). Dashed line represents the expected SNR for the Eu_cl_opt specifications. All the SNR take into account of the contribution from CMB E-mode polarization according to equation ( 21 ). Bottom left-hand panel of Fig. 6 shows the SNR as a function of the observed sky fraction, which does not affect just equation ( 21 ) as SNR, but it changes also the amount of total clusters observed, i.e. the shot-noise error. The SNR is sufficiently robust to a reduction of max ; the forecast SNR remains above a detection for max ≳ 1.4 for the optimistic Euclid cluster survey when the CMB polarization is added. We finally study the dependence of the SNR when changing M min . We vertically shift a redshift independent selection function around 8 × 10 13 M ⊙ , as representative of the selection function from (Sartoris et al. 2016 ) for the photometric Euclid cluster survey. The results in Fig. 6 (bottom left-hand panel) show that the expected selection function for Euclid would be optimal in terms of SNR. We can conclude that for the ISW detection is more important to have wide surveys, covering a large fraction of the sky, than deeper ones, since the surveys analysed are already signal dominated on the scales relevant for the ISW. We now briefly discuss the dependence of the SNR on the underlying cosmology. The cross-correlation power spectrum is sensitive to the total matter density Ω m and to the dark energy equation of state 0 . They both change the amplitude of (since for a flat universe an increased amount of matter density corresponds to have a smaller amount of dark energy density). Moreover, the peak of is shifted according to a different matter-dark energy equivalence. We show the dependence of the SNR on these two parameters in Fig. 7 by keeping fixed all the other cosmological parameters (note that we change σ 8 according to the variation of Ω m and 0 ). The SNR varies less than when we change Ω m up to away from the Planck best fit (Aghanim et al. 2016 ). We find a stronger effect on the dark energy parameter of state 0 . Even a small shift of Δ 0 ≃ 0.2 would lead to a difference larger than on the SNR. In particular, by assuming a fiducial cosmology with a smaller value of 0 leads to a higher SNR. Figure 7. Top panel: dependence on Ω m of the SNR for the ISW detection with clusters (optimistic Euclid cluster survey, blue line) and with galaxies (photometric Euclid galaxy survey, grey line). Bottom panel: dependence on the dark energy equation of state 0 of the SNR for the ISW detection. 5.2 Combining clusters with galaxies Different LSS surveys can be combined to increase the significance of the ISW detection. The


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ACKNOWLEDGEMENTS The authors thank the reviewer for a thorough review and highly appreciate the comments and suggestions, which significantly contributed to improving the content. RK is thankful to the Council of Scientific and Industrial Research, New Delhi, for a Senior Research Fellowship (SRF). RK would also like to thank Miss Alessia Garofalo for helping her with the Gaia data during VOSS 2018. DM gratefully acknowledges support provided by the BASAL Center for Astrophysics and Associated Technologies (CATA) through grant PFB-06, and the Ministry for the Economy, Development and Tourism, Programa Iniciativa Científica Milenio grant IC120009, awarded to the Millennium Institute of Astrophysics (MAS), and from project Fondecyt No. 1170121. HPS and RK thank the Indo-US Science and Technology Forum for funding the Indo-US virtual joint network centre on ‘Theoretical analyses of variable star light curves in the era of large surveys’. RK and DM are also very grateful for the hospitality of the Vatican Observatory, where this work was started.


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We thank the referee for helpful comments that have helped us to improve the presentation of the paper. This work was supported by the National Basic Research Program (973 Program) of China (grant No. 2014CB845800), the National Key Research and Development Program of China (grant No. 2017YFA0402600), the National Natural Science Foundation of China (under grant Nos. 11722324, 11725314, 11603003, 11633001, 11690024, and 11573014), and the Strategic Priority Research Program of the Chinese Academy of Sciences (grant No. XDB23040100).


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

the ion density in the “strong gradient” simulation at , the LHDI fluctuations are highlighted in the unstable plane (yellow) and in a cut that is perpendicular to the ambient magnetic field. The initialization of the simulations ensures pressure balance by means of the Vlasov equilibrium proposed in Alpers (1969) , Pu et al. (1981) , which shapes a plasma boundary with density and magnetic field asymmetries, uniform temperature, with no electric field and no velocity nor magnetic field shear. Hereafter, we refer to the side I (resp. side II ) of this boundary as the high (resp. low) density side. The expressions for the initialization profiles are: Here, T = T i + T e is the uniform temperature, PBC is the constant of pressure balance (set to have the plasma beta β I = 10/3 and β II = 1/12), and w is a constant that defines the width of the layer – set to 0.98 (resp. 0.5) in the “strong” (resp. “weak”) gradient case. We use a density and magnetic field asymmetry of n I / n II = 10 and B I / B II = 0.5. The shape of these initialization profiles is shown in the left panel of Fig. 1 . In the following, all quantities are normalized to ion quantities in side I : the ion gyrofrequency, ; the ion skin depth, ; and the Alfvén speed . The numerical box dimensions are: L x = L y = 2 π and L z = 20 π , with a number of cells, namely, N x = N y = 288 and N z = 1472. The box is elongated (by a factor of in the magnetic field direction in order to reliably include the narrow cone angle over which unstable LHDI modes grow. The timestep used in the simulations is d t = 3.4 × 10 −4 to satisfy the CFL stability condition. The simulations are ran for several tens of the ion gyroperiods until electron acceleration saturates. We use 100 macro-particles per cell and a second order spline interpolation for the macro-particles. We use a reduced ion-to-electron mass ratio m i / m e = 100 to make simulations computationally feasible while maintaining a sufficient scale separation between ions and electrons. The implications of using such a reduced mass ratio are discussed in Sect. 4 . We use an ion-to-electron temperature ratio T i / T e = 1, and a plasma-to-cyclotron frequency ratio of . The magnitude of the density asymmetry used in these simulations encompasses the typical parameters observed in small planetary magnetospheres such as Mercury ( Gershman et al. 2015 ). Two different simulations are investigated using two different layer widths: (i) a steeper boundary case (with the inverse gradient scale length ε n = 1, defined in Eq. ( 7 )), hereafter called a “strong gradient” simulation; and (ii) a smoother boundary case (with ε n = 0.5), hereafter called the “weak gradient” simulation. These parameters are chosen to ensure that the amplitude of the LHDI fluctuations is well above the PIC noise level and also to saturate through the two different mechanisms introduced in Sect. 2.1 : ion trapping or current relaxation. 3. Evolution of LHDI and associated


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ACKNOWLEDGEMENTS The authors thank the referee for her/his useful comments and suggestions, which helped improving the quality of the paper. The authors acknowledge financial support from the Italian Space Agency (ASI) under the contracts ASI-INAF I/037/12/0 and ASI-INAF n.2017-14-H.0.


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

can lead to an almost infinite amount of parameter space to consider (Bate, Clarke McCaughrean 1998 ; Parker Meyer 2012 ; Jaffa, Whitworth Lomax 2017 ). We therefore restrict our comparison to either box fractals as defined by Goodwin Whitworth ( 2004 ); Cartwright Whitworth ( 2004 ) or centrally concentrated clusters with different radial density profiles (Cartwright Whitworth 2004 ; Cartwright 2009 ). 3.2 The mass segregation ratio, ΛMSR MSTs are often used to quantify the relative spatial distribution of the most massive stars in a star-forming region (Allison et al. 2009 ; Parker Goodwin 2015 ), but the method can be applied to any distribution of points with assigned masses (or indeed any other scalar property), and we will apply it to the dense cores in Orion B. For the data set we use in this paper, the ‘mass segregation ratio’ (Λ MSR ) is defined as the ratio between the average MST pathlength of 10 randomly chosen cores in a star-forming region and that of the 10 most massive cores: As described in Allison et al. ( 2009 ) and Parker et al. ( 2011a ), we define the lower (upper) uncertainty as the MST length, which lies 1/6 (5/6) of the way through an ordered list of all the random lengths (corresponding to a 66 per cent deviation from the median value, 〈 l average 〉). This determination prevents a single outlying object from heavily influencing the uncertainty, which could be an issue if using the Gaussian dispersion as the uncertainty estimator. If Λ MSR > 1, then the most massive cores are more spatially concentrated than the average cores, and we designate this as significant if the lower error bar also exceeds unity (see also Alfaro González 2016 ; González Alfaro 2017 ). Parker Goodwin ( 2015 ) show that Λ MSR can sometimes be too sensitive in that it sometimes finds that random fluctuations in low-number distributions lead to mass segregation according to our definition. Therefore, if Λ MSR is calculated to be less than 2, then we also do not consider this to be a significant deviation from a random distribution. 3.3 The local surface density ratio, ΣLDR We calculate the relative local surface density of the most massive cores compared to lower mass cores using the local surface density ratio, Σ LDR (Maschberger Clarke 2011 ; Küpper et al. 2011 ; Parker et al. 2014 ). We first determine the local surface density around each core, Σ, as where r N is the distance to the N th nearest neighbour, N (Casertano Hut 1985 ). We adopt N = 10 throughout this work. We divide the median Σ for the 10 most massive cores, , by the median value for all the cores to define a ‘local density ratio’, Σ LDR (Parker et al. 2014 ): If Σ LDR > 1, then the most massive cores are in areas of higher local surface density than the average core, the significance of which is quantified by a Kolmogorov–Smirnov (KS) test on the cumulative distribution of the cores, ranked by their local surface densities Σ. We reject the hypothesis that


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ACKNOWLEDGEMENTS We would like to thank R. Ekers for useful comments and discussion. Parts of this research were conducted by the Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO), through project number CE110001020. The Australia Telescope Compact Array is part of the Australia Telescope, which is funded by the Commonwealth of Australia for operation as a National Facility managed by CSIRO. The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc. The figures in this work made use of astropy , a community-developed core python package for astronomy (Astropy Collaboration 2013 ). SPO acknowledges financial support from the Deutsche Forschungsgemeinschaft (DFG) under grant BR2026/23.


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Acknowledgements We acknowledge support from the STFC consolidated grant 173869-01. Support from a Marie Curie International Research Staff Exchange Scheme Radiosun PEOPLE-2011-IRSES-295272 RadioSun project is greatly appreciated. This work benefited from the Royal Society grant RG130642. This paper is based (in part) on data obtained with the International LOFAR Telescope (ILT) under project code LC3-012 and LC4-016. LOFAR ( van Haarlem et al. 2013 ) is the Low Frequency Array designed and constructed by ASTRON. It has observing, data processing, and data storage facilities in several countries, that are owned by various parties (each with their own funding sources), and that are collectively operated by the ILT foundation under a joint scientific policy. The ILT resources have benefitted from the following recent major funding sources: CNRS-INSU, Observatoire de Paris and Université d’Orléans, France; BMBF, MIWF-NRW, MPG, Germany; Science Foundation Ireland (SFI), Department of Business, Enterprise and Innovation (DBEI), Ireland; NWO, The Netherlands; The Science and Technology Facilities Council, UK. We thank the staff of ASTRON, in particular Richard Fallows, for assistance in the set-up and testing for the solar LOFAR observations used.


O B-Collaboration I-Collaboration I-Collaboration O O O O O O O O O O O O O O O B-Collaboration I-Collaboration I-Collaboration O O O B-Organization I-Organization I-Organization I-Organization I-Organization O O B-Organization I-Organization I-Organization O O B-Location I-Location O B-Organization I-Organization I-Organization I-Organization O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O B-Location O B-Organization I-Organization I-Organization O O B-Organization I-Organization I-Organization I-Organization I-Organization O B-Location O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization B-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O B-Organization I-Organization I-Organization I-Organization B-Organization O B-Location O O B-Organization I-Organization I-Organization I-Organization O B-Organization I-Organization I-Organization O O B-Organization I-Organization I-Organization I-Organization O B-Location O O O O O O O O O B-Telescope I-Telescope I-Telescope I-Telescope B-Telescope O O O O O O O B-Organization B-Telescope B-Telescope B-Telescope B-Telescope O O B-Telescope O O O O O O O O O B-Organization O B-Location I-Location O B-Telescope O O O O O B-Observatory I-Observatory I-Observatory I-Observatory 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 B-Wavelength I-Wavelength B-Telescope O O O B-Survey I-Survey I-Survey I-Survey B-Survey B-URL O O O B-Organization O O B-Grant I-Grant I-Grant I-Grant O B-Telescope O O O O O B-Observatory I-Observatory I-Observatory I-Observatory O B-Observatory I-Observatory I-Observatory I-Observatory O O O O O B-Organization I-Organization I-Organization O O B-Organization I-Organization I-Organization O B-Telescope I-Telescope O O O O O O B-Observatory I-Observatory I-Observatory O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O O O O O B-Organization I-Organization O O B-Organization I-Organization B-Person O O O B-Person I-Person B-Person I-Person B-Person I-Person O B-Person I-Person O O O O O O O O O O O O O O O


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