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

pixels and 1's to the valid ones. This form of the 2PT function is the same as the unbiased measure described in Kleiner Dickman ( 1984 ), though we used the column density of each pixel without subtracting the mean column density. In this way, we are more sensitive to the correlation of the density field, rather than density fluctuations. We adopted a flat weighting, where all pixel pairs were assigned with an identical weight. This otherwise unbiased estimator may be biased when the scales of the lags (i.e., the spatial separation of two pixels in a pair) are comparable with the observational FOV (Kleiner Dickman 1984 ). Figure 14 shows the obtained 2PT correlation functions with the directional information averaged out. Figure 14. Normalized 2PT functions for all the sources, showing the correlation strengths as a function of spatial separation. For separations with pixel pairs of less than total pixel number, the correlation strengths are plotted with dashed lines. The gray filled region indicates approximately where the rapidly decreasing (RD) components end. The averaged 2PT correlation functions of W49A, G10.6-0.4, W33, W43-Main, and G10.2-0.3, have a common feature: a rapidly decreasing (RD) correlation strength at short lags, and a sudden transition to a shallower decrease at larger lags. The RD component corresponds to localized clumps/cores, while the shallower decreasing (SD) component comes from the broader molecular cloud. We note that all the derived 2PT correlation functions show a steep decrease in correlation strength at large lags because of the limited FOV. To avoid this bias in our analysis, we exclude the range of lags that have pixel pairs less than ∼90% of the number of total pixels. For sources like W43-south and G10.2-0.3, where the structures of column density are composed of widely scattered overdensities, the correlation strengths at shorter lags do not decrease as significantly as the correlation strengths of the more centrally condensed sources, like W49A, W33, and G10.6-0.4. They also do not show an obvious RD component at short lags. There are some bumps seen in the 2PT functions for several sources at larger lags, which may present the characteristic scales of some localized overdensities. We do not quantify these features in this paper. The average azimuthal profiles of our obtained 2PT functions are intended to capture the major similarities and differences between the target sources. We hypothesize that the steeply decreasing component and the shallower one represent structures that were created or supported with different physical mechanisms, and thereby have different characteristic spatial scales and spatial distributions. More discussion about the physical implications is deferred to Section 4.1 . For the sake of quantifying and archiving the observed 2PT functions for comparison with other observations, theories, and numerical simulations, we perform segmented linear fits of these 2PT functions in log


O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O B-CelestialObject I-CelestialObject B-CelestialObject O B-CelestialObject O O B-Telescope O O O B-Observatory I-Observatory I-Observatory I-Observatory O B-Observatory O O O O B-CelestialObjectRegion I-CelestialObjectRegion O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Observatory O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Telescope O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O B-Wavelength I-Wavelength O B-Wavelength O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O B-Wavelength O O O O O O O O O O O B-Model I-Model B-Citation I-Citation I-Citation I-Citation 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 B-CelestialObject I-CelestialObject O O O O B-Telescope O O B-Observatory O O O O O O O B-Observatory O O O O O O O O O O O B-Model I-Model O O B-Citation I-Citation I-Citation I-Citation O B-CelestialObject I-CelestialObject O O O O O O O O O O O B-Model I-Model 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 B-CelestialObject I-CelestialObject 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 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-CelestialObject I-CelestialObject B-CelestialObject O B-CelestialObject O O O O O O O O O O O B-CelestialObject I-CelestialObject O O O O

to three and four for C nTh + C Th and C nTh + C Th + ( C )PL, respectively. In this article we reanalyzed three famous bright long GRBs (namely, GRBs 941017, 970111, and 990123) observed with BATSE on board the Compton Gamma Ray Observatory ( CGRO )—which was operating in low-Earth orbit from 1991 to 2000—in the context of the new paradigm to verify its consistency with these archival data. This article does not aim to be a full validation of the new model and relation, but rather to show that the results obtained with Fermi also hold with the data of other instruments too. It is a crucial step since it reduces the risk that instrumental calibration/systematic effects may account for the results. A comprehensive study of the new model and relation using an extensive sample of GRBs detected with multiple instruments is in progress, but it is out of the scope of the current paper. In Sections 2 and 3 we discuss the data selection criteria and our analysis methodology. In Section 4 we present our results. We will see how the view we had of those GRBs—which attracted a lot of attention in the scientific community—may be completely refreshed in the framework of the new model. 2. DATA SELECTION We focus this first article of a series on a limited sample of three famous bright long GRBs detected with BATSE. These GRBs are of particular interest because they have often been and still are cited to support or discard theoretical interpretations for GRB prompt emission. GRB 990123 was the first GRB to be simultaneously detected during its prompt phase in the γ -ray and optical bands (Akerlof et al. 1999 ). The prompt emission spectra of this burst in the keV–MeV energy range was considered to be adequately fitted to a single Band function (Briggs et al. 1999 ). A redshift estimate for the burst of 1.61 was reported by Kelson et al. ( 1999 ) and Hjorth et al. ( 1999 ). GRB 941017—which was also observed with EGRET on board CGRO —was the first burst of the pre- Fermi era for which a strong deviation at high energy from the Band function was reported (González et al. 2003 ). GRB 941017 was considered to be adequately fitted to a combination of a Band function fading with time and an additional PL remaining constant and incompatible with the synchrotron models. Unfortunately no redshift was measured for this GRB. Finally, we also analyzed GRB 970111 which was thought to be adequately fitted to a Band function but with positive values of at early times. The photometric redshift of this burst was estimated to be 0.2 z 1.4 based on its probable association with host galaxies at this redshift range (Gorosabel et al. 1998 ). Unfortunately, many fainter galaxies may lie in the same region of the sky and the association with the detected objects is not secure, which jeopardizes the validity of this photometric redshift. The light curves of GRBs 941017, 970111, and 990123 are presented in Figures 1 – 3 , respectively. Figure 1. GRB 941017 count light curves as


O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O B-Instrument O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O B-CelestialObject I-CelestialObject O 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 B-CelestialObject O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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-Dataset I-Dataset 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

come back to this problem in Sect. 4.4 and discuss how our findings can describe the smallest diameter of a jet. 2.2. Geometric inversion of local sources As seen in our observations, jet-like features are detected in most images and rotate with the nucleus. Similar studies of other comets have shown that jets can often be associated with specific locations on the surface, presenting a different composition and/or morphology than other areas. For instance, some areas of comet 9P/Tempel 1 would remain active and produce jets even when far into the night, hinting at sublimation of material that is much more volatile than water ice ( Feaga et al. 2007 ; Vincent et al. 2010 ). The high resolution provided by OSIRIS allows an accurate determination of active sources in principle, although the process is not straightforward. Indeed, single images provide only two-dimensional information, and one needs to combine several observations to reconstruct the true three-dimensional structures we want to investigate. To achieve this we developed two independent techniques: blind and direct inversion, as explained in the following sections. These methods are very similar to those used by Sekanina et al. (2004) and Farnham et al. (2013) in their respective studies of the jets of comets 81P/Wild 2 and 9P/Tempel 1. Another aspect of jet studies is the detailed investigation of the physics taking place in the jet itself, as cometary material arises from the surface and possibly fragments or sublimates. We focus here on the use of our inversions to understand the sources themselves better and describe their morphology, evolution, and the associated surface physical processes. Readers interested in photometric properties of dust jets from 67P are referred to Lara et al. (2015) and Lin et al. (2015) or to Vincent et al. (2013) for a numerical modeling of these features on a larger scale. 2.2.1. Blind inversion This first algorithm considers each feature in the images as an isolated jet. Although it seems obvious that a jet can be tracked from one image to another, appearance can be deceiving, and we do not impose this condition for the inversion. For each collimated structure, it is safe to assume that the dust is emitted in a plane defined by the observer (Rosetta) and the central line of the jet. A single image does not allow us to determine whether the jet is inclined toward or away from the observer. In a second step, we calculate the intersection between the jet plane and a shape model of the nucleus, oriented beforehand to match the geometric conditions of our observations. We used a shape model reconstructed by photogrammetry ( Preusker et al. 2015 ). Spacecraft and comet attitudes and trajectories were retrieved with the SPICE library ( Acton 1996 ). Each jet-plane/comet intersection defines a line of possible sources on the surface of the nucleus. For the same jet observed at different times, this technique provides different sets of source lines, but


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

The simulation results were obtained on NASA’s Pleiades supercomputer at NASA Ames Research Center. This work was partially supported by NASA grants NNX10AC55G and NNH11ZDA001N-LWSCSW, and Oak Ridge Associated Universities.


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

Acknowledgements One of the authors (KH) is indebted to Dr. T. Y. Saito for valuable discussion on the CTA sensitivity. This work is supported by the Theoretical Institute for Advanced Research in Astrophysics (TIARA) operated under Academia Sinica, and by the Ministry of Science and Technology of the Republic of China (Taiwan) through grants 103-2628-M-007-003-MY3, 105-2112-M-007-033-MY2, 105-2112-M-007-002, 103-2112-M-001-032-MY3.


O O O O O B-Person I-Person O O O O O O O O O B-Telescope O O O O O O B-Person O O O O B-Grant I-Grant I-Grant I-Grant O O B-Organization I-Organization I-Organization I-Organization O O O O O O O B-Telescope O O O O O O O O B-Organization I-Organization I-Organization I-Organization O O O O O O O O O O B-Observatory I-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 O B-Organization I-Organization I-Organization O O O O O O O B-Archive I-Archive I-Archive O O O O O B-Organization I-Organization I-Organization I-Organization O O O O B-Organization I-Organization I-Organization I-Organization I-Organization O O B-Grant I-Grant I-Grant O O O O O O O O B-Database I-Database I-Database O O B-Database O O O O O O B-Organization B-Observatory I-Observatory O B-Location O O B-Telescope O B-Telescope O B-Telescope O

The authors are indebted to Jeff Coughlin for his expert review and suggestion to use the Kepler FFIs to evaluate false positive scenarios. E.G. was supported by the International Short Visit program of the Swiss National Science Foundation. This paper includes data collected by the Kepler mission, funding for which is provided by the NASA Science Mission directorate. 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 NASA. The Observatory was made possible by the generous financial support of the W.M. Keck Foundation. This research has made use of the NASA Exoplanet Archive, which is operated by the California Institute of Technology, under contract with the National Aeronautics and Space Administration under the Exoplanet Exploration Program. This research has also made use of the Aladin Sky Atlas and the SIMBAD database, developed and operated at the CDS, Strasbourg Observatory in France. Facilities : IRTF:SpeX , UH2.2m:SNIFS , Keck2:ESI/NIRC-2 .


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

next section, we describe the framework developed and its features, followed by a description of the various methods implemented within it to tackle this problem. After this, we describe the data set provided for the challenge, and what additional techniques were utilized to ‘expand’ on this data set. We then go on to describe what metrics are presented by our framework, and how methods are evaluated, and compare the performances achieved with those achieved in other works. We conclude the work by describing further improvements that can be implemented in order to make gravitational lensing detection methods more efficient and more accurate. 1.1 LEXACTUM The framework developed in this work has been named Lens EXtrActor CaTania University of Malta (LEXACTUM). The first of its main features are the image augmentation techniques described in Section 2.2 which can be toggled on or off to train for a greater number of epochs without overfitting. Another feature is the modularity of the code, allowing for the rather easy development of new models, with very easy integration of new models into the pipeline. Other features include the ability to set parameters from the command line. Examples of such parameters are the data set path, whether to train a model or load one from disk, the name of the model (to train or load), the number of epochs to train for, the batch size, and whether to use image augmentation during training or not. LEXACTUM also uses a custom ‘Data Generator’, which loads and pre-processes images in batches with the CPU, while the GPU can train on the last batch of images. Apart from image augmentation during training, all images are normalized using ZScale (NOAO 1997 ). Like other components, the normalization method can be easily swapped out for other techniques. Furthermore, LEXACTUM comes with a ‘results’ package, which scores the trained models and calculates several metrics, described in detail in Section 3 . Moreover, LEXACTUM saves trained models to disk, and also provides functionality for loading trained models. Finally, the ‘visualize features’ component was created, which allows for the viewing of the feature maps at every convolutional layer that a trained model is ‘looking at’ during execution. All of the architectures described in Section 1.2.5 were implemented in LEXACTUM. All of these models were then trained from scratch, on both the Space and Ground data sets, using ZScale normalization and image augmentation, for a varying number of epochs. As a starting point, all models were trained for 5 or 10, 25 or 50, 100, and 250 epochs. After that, if, say, a particular model obtained promising results, and did not seem to be overfitting (judging by the loss and accuracy of the validation set) after 250 epochs, it would then be further trained for 500, or even 1000 epochs. 1.2 Literature review 1.2.1 Conventional methods The methods described in this subsection are not implemented in LEXACTUM, and are only presented to give


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

UV O vi measurements. It is thus highly unlikely that the poorer data quality of X-ray spectra contribute much to the O vi problem. XMM-Newton detection of the z = 0 O vi absorption line toward Mrk 421 is robust, with a sigma detection ( mÅ, error; Rasmussen et al. 2007 ). Moreover, the line was also independently detected by Chandra with similar strength ( mÅ; Williams et al. 2005 ), a detection, increasing the combined significance to . Thus, we cannot just dismiss this robust detection as a statistical accident. 2. Saturation. If UV O vi lines are saturated, the column density might be underestimated (Arav et al. 2003 ). For the unresolved lines, the observed equivalent width (EW) is related both to the column density and the velocity dispersion parameter (or the Doppler parameter b ). The column density and the b -parameter can be disentangled by using different transitions of the same ion, as we did in Williams et al. ( 2005 ) for the z = 0 absorption along the Mrk 421 sightline. Using the UV O vi absorption line doublet, we constrained the b- parameter tightly and found that for this value of b , the X-ray O vi line has a column density about 0.5 dex higher than the UV line. If the X-ray O vi line is saturated, the column density would be even higher. Thus the O vi discrepancy cannot be attributed to simple phenomena such as saturation in the z = 0 systems, so the solution has to lie elsewhere, and may be different for different systems. 3. Variability. Another possibility is variability, discussed by Arav et al. ( 2003 ). AGN absorption lines are known to vary, so if UV and X-ray measurements are not obtained at the same time, the measured column densities may be different. However, variability cannot be the cause of the O vi discrepancy in CGM/IGM systems that do not vary. 4. Size of the emission region. In AGNs, the size of the X-ray emission region is known to be smaller than the UV continuum size. Therefore, if part of the O vi X-ray absorption happens inside the UV continuum region, and both X-ray and UV O vi absorption takes place outside the UV emitting region, there might be a discrepancy, with X-ray O vi absorption probing a larger column density. Once again, this cannot be the cause of the O vi discrepancy in CGM/ISM systems that are far from the background quasars. 5. Excitation. In a high-temperature plasma, electron impact excitation and recombination may suppress absorption from the ground level and contribute to emission. However, the Einstein A 21 coefficient for the 2 p –2 s decay is extremely large (), which means any excited O vi atom decays immediately to the ground state. Even in a plasma with an unrealistically high collision/photoexcitation rate (), the standard Boltzmann equation only allows for the ground state to be depleted by a factor of one-half, and the observed discrepancy is much larger than this. 6. Atomic physics. The wavelengths, oscillator strengths, photoionization cross-sections of the UV O vi λλ


O O O O O O O O O O O O O O B-Person B-Person O B-Person O O O O B-Organization I-Organization I-Organization O B-Grant O B-Grant B-Person O O O O O B-Organization I-Organization I-Organization I-Organization B-Person O O O O B-Fellowship I-Fellowship I-Fellowship I-Fellowship I-Fellowship I-Fellowship I-Fellowship B-Person O O O O O O O O O B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization I-Organization O O O B-Grant O O O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O O B-Organization B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O O O O O O O O O B-Survey I-Survey I-Survey I-Survey I-Survey O O O O O O O B-Organization I-Organization I-Organization O O B-Organization I-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization O O O B-Organization I-Organization I-Organization I-Organization I-Organization O O B-Organization I-Organization I-Organization O B-Survey I-Survey O O O O O O O B-Observatory I-Observatory I-Observatory O O B-Grant B-Grant B-Grant B-Grant O O O O O O O O O O O B-Telescope O O B-Location I-Location O O O O O O O O O

ACKNOWLEDGEMENTS We thank the anonymous referee for comments that helped to improve this manuscript. LD, MA, and KCF acknowledge funding from the Australian Research Council (projects FL110100012 and DP160103747). LD gratefully acknowledges a scholarship from Zonta International District 24. DMN was supported by the Allan C. and Dorothy H. Davis Fellowship. MA’s work was conducted as part of the research by Australian Research Council Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), through project number CE170100013. Part of this research was conducted at the Munich Institute for Astro- and Particle Physics (MIAPP) of the DFG cluster of excellence ‘Origin and Structure of the Universe’. This publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation. The GALAH survey is based on observations made at the Australian Astronomical Observatory, under programmes A/2013B/13, A/2014A/25, A/2015A/19, A/2017A/18. We acknowledge the traditional owners of the land on which the AAT stands, the Gamilaraay people, and pay our respects to elders past and present.


O O O O O O O O O O O B-Organization O O O O O O O O O O O O O O O O O B-Person I-Person I-Person O B-Person I-Person O O O O O B-Person I-Person B-Person I-Person B-Person I-Person B-Person I-Person B-Person I-Person O B-Person I-Person O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O B-Software O O O O O O O B-Database O O B-Database O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O B-Citation I-Citation I-Citation I-Citation O O O O O B-Survey I-Survey I-Survey I-Survey I-Survey O B-Survey O B-Citation I-Citation I-Citation I-Citation O O O O O O O O B-Organization I-Organization I-Organization O O B-Organization I-Organization I-Organization I-Organization I-Organization B-Organization B-Organization I-Organization I-Organization B-Organization O O O B-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O O B-Organization I-Organization I-Organization B-Citation I-Citation I-Citation I-Citation O O O O O B-Telescope I-Telescope I-Telescope I-Telescope O B-Telescope O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization O O B-Organization I-Organization I-Organization B-Organization O O B-Organization O O O O O O O O B-Event I-Event I-Event I-Event O O O B-Organization I-Organization I-Organization I-Organization O O O O O O O O O B-Organization I-Organization I-Organization B-Organization O B-Mission O B-URL O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization B-URL O O O O B-Organization O O O O O O O O O O O O O B-Collaboration I-Collaboration I-Collaboration O O O O O O O O O B-Organization I-Organization I-Organization I-Organization O O O O B-Organization B-Model I-Model O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O O O B-Organization I-Organization I-Organization O B-Organization I-Organization I-Organization I-Organization I-Organization B-Organization B-Person O B-Software I-Software O O O O O O O B-Software O O O O O O O O O O B-Person O O O O O O O O O O O O O O O O O B-Person O O O B-Software O O B-Software I-Software B-Person B-Person O B-Person O O B-Software I-Software B-Software O O O O O O O O O O O B-Person O O O O O O O O O B-Person O B-Person O O O O B-Person O O O O O O O O B-Model I-Model I-Model B-Person O O B-Model I-Model I-Model O O O O O O O O O O B-Person O O O O B-Person O B-Software I-Software O O B-Software B-Citation I-Citation I-Citation I-Citation O B-Software I-Software B-Citation I-Citation I-Citation I-Citation O B-Software I-Software B-Citation I-Citation I-Citation I-Citation O O O O O B-Citation I-Citation I-Citation I-Citation O B-Software O B-Organization I-Organization B-Software I-Software


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

The authors are grateful to the IRAM staff, especially Tessel van der Laan, Arancha Castro-Carrizo, Chin-Shin Chang, and Sabine König, for their help with the calibration of the data. This research was supported by a Junior Group Leader Fellowship from the Lundbeck Foundation (to J.K.J.). Centre for Star and Planet Formation is funded by the Danish National Research Foundation. M.V.P. acknowledges EU FP7 grant 291141 CHEMPLAN. The research leading to these results has received funding from the European Commission Seventh Framework Programme (FP/2007-2013) under grant agreement No. 283393 (RadioNet3).


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

LAZ, AP, RG, and LFR acknowledge the financial support from DGAPA, UNAM, and CONACyT, México. This paper makes use of ALMA data: ADS/JAO.ALMA#2011.0.00419.S. ALMA is a partnership of ESO (representing its member states), NSF (USA), and NINS (Japan), together with NRC (Canada), and NSC and ASIAA (Taiwan), in cooperation with the Republic of Chile. The Joint ALMA Observatory is operated by ESO, AUI/NRAO, and NAOJ. GG acknowledges support from CONICYT project PFB-06.


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

ACKNOWLEDGEMENTS We thank the referee for a prompt and constructive report, and Matt Auger, Vasily Belokurov, Sergey Koposov, Xianzhong Zheng, and Cameron Lemon for helpful discussions. YS has been supported by the National Natural Science Foundation of China (No. 11603032 and 11333008), the 973 program (No. 2015CB857003), and the Royal Society – K.C. Wong International Fellowship (NF170995). RMC and IPF have been supported by the Spanish research grants ESP2015-65597-C4-4-R and ESP2017-86852-C4-2-R.


B-Person O O O O O O O O B-Person I-Person B-Person I-Person O B-Person I-Person O O O O O O O O O O O O O O B-Survey I-Survey I-Survey I-Survey I-Survey O O O O O B-Organization I-Organization I-Organization I-Organization O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O O O O B-Survey O O O O O O B-ComputingFacility I-ComputingFacility I-ComputingFacility I-ComputingFacility O O B-Organization I-Organization I-Organization O B-Survey O O B-URL O B-Survey O O O O B-Collaboration I-Collaboration I-Collaboration O O O O O O B-Collaboration I-Collaboration O O B-Collaboration I-Collaboration I-Collaboration O B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization O B-Collaboration I-Collaboration I-Collaboration O B-Collaboration I-Collaboration I-Collaboration B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization I-Organization B-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 I-Organization B-Organization B-Organization I-Organization O B-Collaboration I-Collaboration I-Collaboration B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization I-Organization B-Organization B-Organization I-Organization I-Organization B-Organization B-Location B-Organization I-Organization I-Organization B-Organization B-Location B-Organization I-Organization I-Organization I-Organization B-Organization B-Observatory I-Observatory I-Observatory I-Observatory I-Observatory B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization B-Observatory I-Observatory B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Observatory I-Observatory I-Observatory B-Collaboration I-Collaboration I-Collaboration I-Collaboration B-Organization I-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization O B-Organization I-Organization

H.C.H. would like to acknowledge the helpful discussion with Christy Tremonti, Michael Dopita, and Frédéric Vogt. The authors are grateful to the anonymous referee for constructive suggestions. Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS website is www.sdss.org . SDSS-IV is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration including the Brazilian Participation Group, the Carnegie Institution for Science, Carnegie Mellon University, the Chilean Participation Group, the French Participation Group, Harvard-Smithsonian Center for Astrophysics, Instituto de Astrofísica de Canarias, The Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe (IPMU)/University of Tokyo, the Korean Participation Group, Lawrence Berkeley National Laboratory, Leibniz Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie (MPIA Heidelberg), Max-Planck-Institut für Astrophysik (MPA Garching), Max-Planck-Institut für Extraterrestrische Physik (MPE), National Astronomical Observatories of China, New Mexico State University, New York University, University of Notre Dame, Observatário Nacional/MCTI, The Ohio State University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, Universidad Nacional Autónoma de México, University of Arizona, University of Colorado Boulder, University of Oxford, University of Portsmouth, University of Utah, University of Virginia, University of Washington, University of Wisconsin, Vanderbilt University, and Yale University.


O O O O B-Person I-Person I-Person I-Person O O O O O O O B-CelestialObject O O O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O O B-Grant I-Grant B-Grant O O B-Organization I-Organization I-Organization I-Organization B-Organization O O O O B-Organization I-Organization O B-Grant I-Grant I-Grant I-Grant I-Grant B-Person B-Person O B-Person O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O O B-Organization B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O O O O O O O O O B-Telescope I-Telescope I-Telescope I-Telescope O O O B-Organization O O O O B-Organization I-Organization O B-Grant I-Grant I-Grant I-Grant I-Grant O B-Telescope O O O O O O O O B-Identifier O O O O B-Archive O O O O O O B-URL O

We are grateful to Roeland van der Marel for assistance with the geometry of the LMC. Support for this work was provided by the National Aeronautics and Space Administration (NASA) through programs Nos. GO-14648, 15146 from the Space Telescope Science Institute (STScI), which is operated by AURA, Inc., under NASA contract No. NAS 5-26555. A.G.R., S.C., and L.M.M. gratefully acknowledge support by the Munich Institute for Astro- and Particle Physics (MIAPP) of the DFG cluster of excellence “Origin and Structure of the Universe.” This research is based primarily on observations with the NASA/ESA Hubble Space Telescope , obtained at STScI, which is operated by AURA, Inc., under NASA contract No. NAS 5-26555. The HST data used in this paper are available at 10.17909/t9-my41-h234 as part of the MAST archive which can be accessed at http://archive.stsci.edu/hst/ .


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

Fourier transform of a Gaussian function is also Gaussian, and leads tohowever, they comment that this expression breaks down at large FoVs and diverges at w = 0. By choosing to fix the sky to a parabola, rather than the sphere, we arrive at the same approximation above. First, we choosethen by integrating over n in Equation ( 14 ), we arrive at the same small FoV approximation. 3.2. <italic>w</italic>-projection with Exact Spherical Correction We choose to replace the horizon with a window function, where the expression for the full sphere isAny scaling from this window function can be corrected in the upper hemisphere of the measurement equation 3.2.1. No Horizon When h ( n ) = 1 there is no horizon and the w -projection kernel is calculated fromThe Fourier transform of this equation has an analytic solution that can be simply expressed as a real valued functionas shown in Vembu ( 1961 ), which is solved in spherical coordinates due to symmetry. This solution dates back as far as Poisson ( 1820 ), and similar problems have been solved in two-dimensions in Parseval ( 1805 ). The units of ( u , v , w ) are implicitly chosen to depend on the directional cosines ( l , m , n ), meaning corresponds to the largest spatial scales. The Sinc function above represents limits on the resolution in ( u , v , w ) due to the FoV being bounded to the sphere. The uncertainty principle states that restricting the FoV is equivalent to enforcing a resolution limit on C ( u , v , w ). At a small FoV, this kernel is effectively a delta function of small support. However, as the FoV increases, the kernel becomes a radial Sinc function with extended support and rapid oscillations. When mosaicking multiple FoVs, the resolution in ( u , v , w ) is increased (as discussed in Ekers Rots 1979 and Thompson 1999 ); however, the total FoV will be limited to the sphere, as represented by this radial Sinc function. Since x ( l , m ) is independent of n it will project both onto the sphere for n and − n . While C ( u , v , w ) models the curvature of the sphere, it allows a reflection of x ( l , m ) for −1 ≤ n 0. This is why a horizon window function needs to be included in the analysis. 3.2.2. Projecting above the Horizon If we let H ( w ) be the Fourier transform of h ( n ), we find that the horizon effect can be understood through the convolution theorem:We can get an expression for the horizon-limited w -projection kernel in the ( u , v , w ) domain in terms of the w -projection kernel for the full sphere. Choosing h ( n ) = Θ( n ) with , we find an expression equivalent to Equation ( 17 ) in the ( u , v , w ) domainwhere the second term is a Hilbert transform of the sphere along the w -axis. Another equivalent expression can be found by choosing a box function for the horizon window, by setting ,We are not aware of an analytic solution to this convolution, which could improve understanding of the behavior of wide-field effects. 3.3. Convolution with a Gridding Kernel To


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

as stars #4 and #6 (late-O-type dwarfs, = 0.8 and 0.9 mag, M K = −4.2 and −3.9 mag). In box3, star #5 has similar properties; it is an O9-B type ( = 1.1, M K = −4.1 mag). Star #3 is the main ionizing star since it is a massive O4-6 ( = 1.3 mag) of about 40 M ⊙ and an age of 5–7 Myr (Ekström et al. 2012 ). Figure 8. The gray scale shows a GLIMPSE 8.0 μ m image of GRS G331.31–00.34. Red long-dashed circles mark the candidate clusters projected into this H ii region. The H ii region is shown with a dot-dashed black circle. The three dotted boxes indicate regions plotted in the CMDs of Figure 9 (see text). Observed stars are marked with blue squares (blue stars) and with red triangles (late-type stars). The blue trees are the results of an MST search with a cutoff distance of 40′′ (0.8 pc). Figure 9. J – K s vs. K s diagrams of the three dotted-square regions marked in Figure 8 (see text). Squares mark detected early stars, and asterisks mark detected late-type stars. As in Figure 5 , diamonds indicate the locations of O4, O8, B2, and B5 dwarfs for a distance of 3.9 kpc at = 0.0 and 1.0 mag. Dashed lines connect the values at = 0 and those at = 1.0 mag. In conclusion, naked OB stars are not concentrated, as one would expect for a mass-segregated population, but are detected inside the bubble in two groups, while condensing molecular clumps are currently located on the shell surrounding the bubble. In the direction of Cl63 (AGALG331.3873−0.360), which is on the shell, we detected another early type, star #7, which is likely to be contributing to the heating of the protostar AGALG331.3873−0.360. These findings are in line with the current literature. Indeed, bound stellar clusters are a rarity, and in more than 90% of the cases (infant mortality and cluster dissolution), we expect associations of massive stars. For example, the massive association Cygnus OB2 (about 7 pc in diameter) is at least 5–7 Myr old, is not associated with gas, and is made of discrete clumps of stars (1–2 pc in size, Wright et al. 2014 , 2016 ). The authors conclude that Cygnus OB2 originated with discrete clumps, and there is no trace of dynamical evolution (e.g., mass segregation). Similar evidence is provided for the younger W33 complex by Messineo et al. ( 2015 ), 5 pc in diameter, which is made up of several condensing molecular clumps and has sparsely distributed exciting stars (2–4 Myr). 6. Summary We performed a spectroscopic survey of bright infrared stars in the direction of GRS G331.34−00.36 (S62), GRS G337.92−00.48 (S36), and MCM2005b77, and for the first time we detected massive members in these regions: a. A total number of 27 early-type and 32 late-type stars were detected. b. We confirm one O4-6 star and one B0-5 star as the main sources of ionizing radiation of GRS G331.34−00.36 (S62), at a kinematic distance of 3.9 ± 0.3 kpc. The stars have of 1.3 mag and 1.0 mag. With N lyc = 49 photons s −1 , the massive O4-6 star can alone account for most of the energy


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

The research leading to these results has received funding from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation program (grant agreement No. 695099). We (W.G., G.P., D.G., and W.N.) also very gratefully acknowledge financial support for this work from the BASAL Centro de Astrofisica y Tecnologias Afines (CATA) AFB-170002. We also acknowledge support from the IdP II 2015 0002 64 grant of the Polish Ministry of Science and Higher Education. M.T. acknowledges financial support from the Polish National Science Center grant PRELUDIUM 2016/21/N/ST9/03310. M.G. gratefully acknowledges support from FONDECYT POSTDOCTORADO grant 3130361.


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 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 B-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O B-Database I-Database I-Database I-Database 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 B-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength O B-Database 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 B-Software O O O B-Organization I-Organization I-Organization O O O O O O O B-Software I-Software I-Software O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject 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 B-Citation I-Citation I-Citation I-Citation 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 O O B-Formula I-Formula I-Formula 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-Formula I-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 O O O 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 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

2 ), are shown in Appendix A . Table 2. Adopted stellar parameters for HD 199178. Notes. (a) In case of no reference, a new parameter value was derived/adopted for this study. In general, a minimum number of ∼10 evenly distributed rotational phases is considered optimal for a fully reliable Doppler image. However, Hackman et al. (2011) demonstrated, that some useful information can be retrieved with a much more limited phase coverage. Therefore, we calculated Doppler images for all sets with n φ ≥ 4. 3. Spectral and stellar parameters The spectral parameters were obtained from the Vienna Atomic Line Database ( Piskunov et al. 1995 ; Ryabchikova et al. 2015 ). Some adjustments were made in the g f -values in order to get a satisfactory fit for all spectral regions. This is a standard procedure in Doppler imaging since the spectra of real stars always show some deviations from calculations based on LTE-models. As we did not intend to derive exact element abundances, it is safe to correct for all discrepancies between the model and the real star by adjusting the g f -values. Furthermore, to the first order all photospheric absorption lines will follow the same behaviour (i.e. a cool spot will cause a “bump” in the spectral line). The adopted parameters for the strongest lines are listed in Table 3 . The largest adjustment was for the line Ca I 6439.075 Å, were VALD listed lg( g f )=0.370 and we adopted the value 0.450. A total number of 917 lines were included in the line synthesis of the seven wavelength regions. Most of these were molecular lines. For the unspotted surface a smaller number, i.e. only the atomic lines, would have been sufficient. For the cool spots molecular lines, in particular TiO-bands, are important. The local line profiles were calculated using the code LOCPRF7 developed at the University of Uppsala. Recent changes in the code include a molecular equilibrium solver ( Piskunov Valenti 2017 ). Table 3. Wavelengths, lower excitation potentials, and adopted lg( g f )-values for the strongest lines. HD 199178 is a rapidly rotating late-type star, which was classified as G 5 III – IV by Herbig (1958) . Strassmeier et al. (1999) calculated its luminosity and mass to be 11 L ⊙ and 1.65 M ⊙ . Hackman et al. (2001) estimated its radius to be ∼5 R ⊙ and adopted the rotation velocity v sin i = 72 km s −1 , inclination angle i = 60°, and gravity lg( g )=3.5. With such a high rotation velocity, the macroturbulence is hard to determine, but in any case should not strongly influence Doppler imaging. In this study we used a radial-tangential macroturbulence of ζ RT = 5.0 km s −1 . We adopted an effective temperature T eff = 5300 K for the unspotted surface as a starting point. The microturbulence was determined by comparing the synthetic spectrum of an unspotted surface to the observations. This yielded ξ = 1.7 km s −1 . Jetsu et al. (1999) and Panov Dimitrov (2007) concluded, that the photometric light curve cannot be modelled using a


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

expected from the measured absorption. A soft excess produced by soft Comptonization in a secondary, warm corona was proposed in previous works (Marshall et al. 2003 ; Guainazzi et al. 2004 ). However, similarly to the partial covering interpretation, the variations in this model fail to reproduce the observed PCA. This is likely due to the fact that the soft and hard Comptonization components are almost independently responsible for the variability at low and high energies, which is contrary to the changes in normalization of a single component suggested by the variability analysis and shape of the PCA. As seen in Section 4.3 , the model is also unable to explain the high fluxes observed in the UV band, even when testing different black hole spins. The Δα ox values suggest an X-ray normal state for Mrk 478 at all epochs, so it is unlikely that the UV data are intrinsically extreme. One crucial disagreement between models is on the shape of the primary continuum. In the partial covering model, the power law slope is extremely steep, with Γ = 2.99 ± 0.02 for all epochs. Although NLS1 galaxies typically feature steeper spectra than other AGNs (e.g. Boller, Brandt Fink 1996 ; Brandt, Mathur Elvis 1997 ; Grupe, Thomas Beuermann 2001 ), this value is high. In the soft Comptonization model, the spectrum is much flatter, with the index ranging from 2.0 to 2.2 between epochs. These values are average among NLS1 AGNs. The blurred reflection models require intermediate slopes, steeper than those of typical NLS1 galaxies, but not so extreme as the partial covering model. reflionx suggests slopes in the 2.6–2.8 range, and relxill measures this to be lower, with slopes of around 2.4–2.6. Although the variations in slopes between models are all able to explain the spectra, they differ at . The partial covering and blurred reflection models predict fluxes below the BAT survey limit. Owing to the very shallow power law measured in the optxagnf model, the predicted flux for this model is the highest (∼2 × 10 −12 ) and just at the threshold limit of the BAT survey (Oh et al. 2018 ). All spectra are consistent with null detections using Suzaku PIN. One of the most curious features revealed by the spectral analysis is the unique iron line profile of Mrk 478. AGNs typically show evidence of both narrow and broad lines, with the broad line likely produced by reflection of the primary emission off of neutral material (e.g. the torus). However, no evidence for such a feature is detected in any of the presented models. There are some plausible explanations for this – the spectrum is very steep, meaning that a narrow line may be buried below the continuum at these high energies if the reflection off of neutral material was sufficiently weak. Additionally, only XMM5 has high signal-to-noise ratio at these high energies; the other data sets suffer from short exposure and high background making it difficult to model narrow features at high energies. The emission line,


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 B-Person I-Person O O O O

Acknowledgements We thank Walter Dehnen for stimulating discussions and detailed comments on the manuscript, the anonymous referee for comments that strengthened the paper, and Ernst Hairer for a helpful discussion.


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

that cosmic rays and high-energy neutrinos may be produced by the interaction of an energetic outflow ejected by the newly born compact object with the surrounding pulsar nebula or supernova remnant at a distance . An FRB could also be produced during this interaction or directly inside the ejected outflow. The resulting neutrino flux may be low, because at such a distance from the progenitor the density of the target medium for the photo-hadronic interaction is quite small. However, the delay between the production of the radio and the neutrino signal is not clear yet. For all the hadronic models considered in this discussion, it seems that detecting a neutrino signal from single FRB sources may be difficult, as most of the FRB hadronic model predictions remain orders of magnitude below the ANTARES neutrino detection threshold. However, the expected large number of FRBs over the entire sky may contribute to a diffuse flux that can be tested by a large-scale neutrino telescope. This possibility is discussed in the following section. 4.4 Contribution to the neutrino diffuse flux In 2013, the IceCube Collaboration reported the significant detection of a cosmic diffuse neutrino flux (Aartsen et al. 2013 ). To date, the sources responsible for this cosmic isotropic signal have not been clearly identified. Even though the first compelling evidence of a cosmic high-energy neutrino signal from the blazar TXS 0506 + 056 has been claimed by Aartsen et al. ( 2018a , b ), it is still not clear how important the contribution of the blazars is to the neutrino diffuse flux. In contrast, the GRB contribution to this diffuse flux has already been constrained to be less than 1 per cent (Aartsen et al. 2015d ). The population of FRBs may also contribute significantly, because their expected rate is high, (Champion et al. 2016 ). This hypothesis is tested here by computing the 90 per cent CL upper limit on the diffuse neutrino flux associated with FRBs. As before, the neutrino flux associated with FRB sources is assumed to have a power-law energy distribution with spectral indexes γ = 1.0, 2.0, 2.5. The derived diffuse upper limits depend on the assumed neutrino spectrum. Hence, where N FRB is the number of FRBs considered in this analysis and is the characteristic neutrino fluence normalized to 100 TeV, as defined in equation ( 2 ) of the combined neutrino spectrum from the 12 FRBs. The neutrino fluence limit has been computed at the 90 per cent confidence level by estimating the average ANTARES effective area over the 12 FRB events for the different spectral models: According to the ANTARES upper limit on the individual neutrino fluxes from the 12 selected FRBs (see Table 2 ), and assuming the last updated estimate on the all-sky FRB rate (Bhandari et al. 2018 ), one can obtain the upper limits on the quasi-diffuse flux normalized to E 0 = 100 TeV, , 2.0 and 0.7 for E −1.0 , E −2.0 and E −2.5 neutrino spectra respectively. The neutrino diffuse flux observed by


B-Person O O O O B-Organization I-Organization I-Organization I-Organization O O O O B-Person I-Person O O O O O O O O O O O O O B-Collaboration I-Collaboration O O O O O O O B-Software O O O O O B-ComputingFacility I-ComputingFacility O B-Location O O O B-Organization O O B-ComputingFacility I-ComputingFacility I-ComputingFacility O O B-Location O B-Organization I-Organization B-Location O O B-Person I-Person O O O O B-Model O

JS acknowledges support from the Alexander von Humboldt Foundation. We thank the referee, Stacy McGaugh, for his comments, which helped to improve the manuscript substantially. We acknowledge the Virgo Consortium for making their simulation data available. The eagle simulations were performed using the DiRAC-2 facility at Durham, managed by the ICC, and the PRACE facility Curie based in France at TGCC, CEA, Bruyères-le-Châtel. We thank Dennis Zaritsky for providing us with BTFR values.


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

have the same peak value as the sample shown in the same panel. Based on the periodicity of these brightenings, we inquire whether or not they are standing mode MHD waves. They could be standing sausage waves because they can produce spectral profiles with enhancements at both red and blue wings (see, e.g., Tian et al. 2016b ; Shi et al. 2019a , 2019b ). For a loop with a cross section less than 1′′, the period of the sausage mode should be less than 10 s (Nakariakov et al. 2003 ; Nakariakov Verwichte 2005 ), thus the period of the observed phenomena is too large to be a sausage wave. One possibility is a combination of sausage and kink modes, which can occur concurrently in the solar atmosphere (Morton et al. 2012 ). The sausage mode can produce the observed spectral profiles, while the kink mode allows the bright loops to move transversely and thus can provide the observed periodicity. The periodicity of the sausage mode cannot be resolved in the current observations due to the temporal resolution. This leads to the question of whether a flux tube consisting of sausage motions with speeds more than 50 km s −1 is stable. This should be investigated in the future numerical studies. Another explanation is that shocks can be frequently seen in sunspots with periods of about 3 minutes (see Tian et al. 2014 ; Hou et al. 2018 , and references therein). Because shocks could be the result of leakage of p-modes, they can drive quasi-periodic brightenings in the transition region (Yang et al. 2015 ; Hou et al. 2016 , 2018 ). While shocks are propagating along loops, they might drive transverse motions (i.e., kink motions) and lead to repetitive appearances and disappearances of bright loops in the field of view of the spectrograph slit. The observed quasi-periodic brightenings can be the responses of shocks interacting with fine structures in the loop apex. Further theoretical study is required to understand whether and how shocks can produce such phenomena. Another scenario is that they are produced by repetitive magnetic reconnection. Such reconnection can result from magnetic braidings due to the plasma motions of the footpoints of the loops in the photosphere (Parker 1983a , 1983b ). The multiple loop threads seen in the field of view satisfy the basic requirement of this magnetic braiding scenario. Such magnetic reconnection can produce the observed non-Gaussian profiles of Si iv 1394 Å (see e.g., Huang et al. 2017 , 2018b ). Because the driven processes of the magnetic braiding can be modulated by the omnipresent 3 minute oscillations in sunspots, the braiding-induced magnetic reconnection then occurs with a periodicity. It has been demonstrated by numerical simulations that magnetic reconnection modulated by p-mode waves can produce quasi-periodic transition-region explosive events (Chen Priest 2006 ; Heggland et al. 2009 ). Moreover, the periods of the brightenings also agree with standing torsional (Alfvén) modes in a flux tube with lengths


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

a non-zero slope for either half. Similarly, if we split the sample into smaller ranges of group mass, as in Section 4.2 , we are not able to distinguish the slope from zero slope for either half. For our sample, the halfway point at r = 2.06 is at or beyond R 200 (up to almost seven times beyond; see Table 1 ). Therefore, it is not surprising that the gradient in galaxy properties is primarily within this radius. Ideally, with a larger sample, one could find a specific (not necessarily linear) function to describe the change in H i content within R 200 as function of group-centric distance. So far, this has proven to be a challenge; for example, Yoon Rosenberg ( 2015 ) do not detect a radial gradient in H i mass ratio within R 200 at all, using a slightly larger sample (but not including upper limits for galaxies not detected in H i ). 5. CONCLUSIONS AND DISCUSSION In this paper, we take the approach of comparing the H i content at fixed galaxy type and stellar mass in the centers of groups and clusters over a wide range of masses with the H i content in galaxies in control regions out to 4 Mpc surrounding each group or cluster. This process allows us to statistically test for pre-processing in the central systems themselves, including in isolated groups, an approach that complements environmental tests based on local density. Our H i data is from the new catalog, and we use statistical tests from survival analysis in order to include information on upper limits for galaxies not detected in H i . Our primary results are the following. (1) Late-type galaxies in groups lack H i at fixed stellar mass relative to galaxies in a control region extending to 4.0 Mpc surrounding each group. Most of the gradient in galaxy properties out to 4.0 Mpc occurs in the inner 2.0 Mpc. Although this effect is stronger in clusters and large groups (), it is also detectable in groups with . This shows pre-processing of H i gas, not simply at intermediate densities, but in intermediate-density isolated groups. (2) The gradient in H i content for fixed stellar mass is stronger in larger groups, but the gradient in stellar mass and color does not follow this trend; stellar masses increase and galaxies become bluer with r at similar rates across our four bins of group mass. These difference between H i and optical properties might reflect an additional, rapid mechanism for the removal of gas in the inner regions of larger groups and clusters. Our statistics are insufficient to address whether this is truly a threshold effect, or a gradual change with group mass. (3) Comparing six different environment variables, we find that local density is the best predictor of galaxy properties (including H i content at fixed stellar mass), followed by group-centric radius r and . Considering all combinations of two variables together, we find that fits are improved (higher adjusted R 2 ) only for the addition of group mass M 200 to local density, r , or . We note that


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

faint as 30. They predict for every galaxy a value of L X concordant with the scaling relation with the SFR (approximated by the infrared luminosity) of Basu-Zych et al. ( 2013 ). Without going into details, they estimate L 8–1000μm using photo- z , star-formation rate, UVJ rest-frame colors, and (observed or extrapolated) UV luminosity (). Using their mock catalog, we applied a selection as similar as possible to that of Laigle et al. ( 2016 ) from which we derived our mask. As a result, we find that these galaxies produce a [0.5–2] keV CXB surface brightness of the order of 3.3 × 10 −14 erg cm 2 s −1 deg −2 , which explains about 5% of the nsCXB. By assuming a typical X/O = 0 for AGNs as determined by Civano et al. ( 2012 ) and the i -limiting magnitudes in COSMOS (Scoville et al. 2007b ), we estimate that the undetected AGN [0.5–2] flux is 10 −17 erg cm 2 s −1 . At these low fluxes, star-forming galaxies vastly outnumber AGNs, so we can assume that ordinary AGNs cannot contribute more than galaxies to the soft nsCXB (5%). Being so faint, the sources producing the remaining CXB can be local ( z ∼ 1–3) and of low luminosity. Low-luminosity AGNs are preferentially highly absorbed (Barger et al. 2005 ; Hasinger 2008 ), and therefore we could argue that the hard portion of the nsCXB could be explained by these sources. However, at z ∼ 36, the number density of absorbed sources is still unknown, and we cannot exclude an unpredicted large number of such sources at that redshift. We propose that a large fraction of the remaining emission could arise from still undetected, rapidly accreting black holes at z > 6–7. Assuming the Direct Collapse black hole (DCBH) scenario for the formation of early black hole seeds, Pacucci et al. ( 2015 ) showed that these sources are likely undetected in current deep X-ray/NIR surveys. They compared the emission of DCBHs for two accretion models: radiatively efficient (Standard) and radiatively inefficient (Slim Disk; super-Eddington), in which photon trapping is significant and the outgoing radiation is diminished. In the latter case, the luminosity emitted by these sources is low. These short-lived and fainter black holes are more difficult to detect compared to brighter objects accreting at the Eddington limit (two tentative detections were proposed by Pacucci et al. 2016 ). Indeed, Comastri et al. ( 2015 ) revised the estimate of the local accreted mass density by taking into account that a significant fraction of the local black holes may have grown by radiatively inefficient accretion. From our measurements, the maximum flux produced by accretion onto early black holes is ∼10% of the CXB (see Table 3 ). To place limits on the amount of accretion occurring at , we follow the formalism of Salvaterra et al. ( 2012 ), assuming that the comoving specific emissivity of AGNs can be factorized aswhere is the normalization, , with , is the redshift evolution, and g ( E ) is a (normalized) template spectrum. For these


O O O O O O B-Fellowship I-Fellowship I-Fellowship O O B-Organization O B-Grant O B-Grant O O B-Person I-Person O O O O O O O O B-Instrument O O O O O O O O O B-Person I-Person O O B-Dataset I-Dataset I-Dataset I-Dataset I-Dataset I-Dataset O O O O O B-Person I-Person O O O O O O O B-Telescope O O B-Person I-Person I-Person O O O O O O B-Person I-Person O O O O O O B-Software I-Software O O O O O O O O O O O O O O O B-Organization B-Person O O O O O B-Organization I-Organization I-Organization I-Organization B-Grant O O B-Organization I-Organization O B-Grant B-Grant O O B-Organization O B-Grant I-Grant O B-Instrument O B-Person O O O O B-Grant I-Grant I-Grant O O B-Organization O O B-Grant O O O B-Grant O O O O B-Grant O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization

This work was supported by a Marie Curie Fellowship and the NASA grants NNX13AI63G / NNX14AQ31G. We thank J.P. Wuelser for providing us with the absolute calibration of IRIS and its temporal evolution. We are very grateful to S. Couvidat for creating hmi.Ic _ 45s _ nrt data for this flare and to P. Scherrer for his explanations of the details of HMI. We thank A. Sainz Dalda for comments on the manuscript and J. Kašparová for her help with adapting the MALI code to account for non-thermal hydrogen collisional rates. We acknowledge helpful discussions that took place at ISSI. S.K. acknowledges the support by the Swiss National Science Foundation (200021-140308), by the European Commission through HESPE (FP7-SPACE-2010-263086), and through NASA contract NAS 5-98033 for RHESSI . P.H. was supported by the FP7 project F-CHROMA under the EC contract no. 606862, by the project RVO:67985815, and by the grant P209/12/1652 of the Grant agency of the Czech Republic.


O O B-Person I-Person 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 B-Person O B-Person O O O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O B-Location B-Person O O O O O O B-Fellowship I-Fellowship I-Fellowship I-Fellowship B-Person O B-Person O O O O B-Organization B-Grant I-Grant I-Grant O B-Model O O O O O O O B-Software B-Citation I-Citation I-Citation I-Citation O

We thank Naomi McClure-Griffiths for providing the new H i terminal-velocity measurements from McClure-Griffiths Dickey ( 2016 ) in electronic form and the anonymous referee for a constructive report. J.B. and A.B. received financial support for this project from the Natural Sciences and Engineering Research Council of Canada. J.B. also received partial support from an Alfred P. Sloan Fellowship. T.F. and N.K. are supported by the NSF CAREER award 1455260. The MCMC analyses in this work were run using emcee (Foreman-Mackey et al. 2013 ).


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

large sample of AGNs and obtain some different results. (1) A few sources exhibit a hint of saturation at high flux levels, but about half of the sources do not show a clear evidence of saturation in our data (e.g. Ark120, Mrk110, Figs A5 and B3 ). (2) Different sources follow different tracks (i.e. different slopes of the correlation) in the L X / L Edd diagram rather than a common relation (i.e. a single slope of the correlation). (3) Using the sample of AGNs instead of individual source, we can explore the spectral evolution in a much larger X-ray Eddington ratio range (4 orders of magnitude, Fig. 1 ). (4) We introduce the slope of the correlation to parametrize the increase speed of as a function of flux, and find for an anticorrelation between and the X-ray Eddington ratio. Globally, the increasing tendency of with increasing X-ray luminosity becomes slower, but there is no saturation effect observed even when the X-ray Eddington ratio increases by four orders of magnitude (Fig. 1 ). 4 DISCUSSION It is well known that the observed is governed by the absorption, the reflection effects, and the Comptonization process itself. The X-ray flux can change significantly within a time-scale as short as 10 3 10 4 s; however, neither the column density nor the covering factor is expected to vary so fast. On the other hand, the variation of X-ray flux can affect the ionization state and the opacity of absorber, resulting in variable absorption. In this way, the observed increases with increasing the X-ray flux, but the derived relation is much shallower than the data of most sources (Sobolewska Papadakis 2009 ). Moreover, such absorption effect should be prominent at high luminosity, that is in conflict with the anticorrelation between and the X-ray Eddington ratio shown in Fig. 2 . The reflection component could offer a significant fraction of X-ray emissions, and tend to flatten the spectrum below 10keV, reducing the observed . However, the reflection is unimportant in the power-law fitting with the RXTE /PCA data due to their low energy resolution. Investigating the RXTE data of 10 AGNs (all in our sample), Sobolewska Papadakis ( 2009 ) argued that a constant reflection component plus a power-law component, which is variable in flux but constant in profile, failed to account for the spectral evolution. It is unclear whether the spectral softening behaviour can be interpreted as the decreasing of the relative contribution of the reflection component with increasing the X-ray flux. Recently, observations with XMMNewton and NuSTAR have been made on several objects in our sample (e.g. MCG-6-30-15 and Ark120; Parker etal. 2014 ; Porquet etal. 2018 ), and these data have sufficient statistics and spectral resolution to separate out the intrinsic power-law and reflection components. A quantitative estimation on the influence of the reflection effect at different flux levels could be accomplished with next generation of X-ray missions in the future (e.g.


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

are denoted by black vertical lines. In all cases of Figure 1 a spectral break is observed at the largest of the three scales, i.e., the scale corresponding to the lowest ion frequency . This result is consistent with the observations in the solar wind (Chen et al. 2014 ). However, in the range , where is the frequency corresponding to the smallest ion scale, the power spectra are modified by ion instabilities: while a power law seems to develop after the break in the case of very high beta (Figure 1 , top panel), the onset of the cascade is shifted toward higher frequencies (Figure 1 , middle and bottom panels) by the formation of a broader “knee” and develops at . For example, in the bottom panel, we observe a local bump at the break, which has been identified in this particular event (see Alexandrova et al. 2006 ) as the signature of Alfvén vortices, controlled by . Each case presents a different slope α in this range, as shown by the compensated spectra depicted by red lines in each panel (the spectral index α is indicated in each panel on the right). Kinetic instabilities can modify the power spectrum at ion scales and affect the fluctuations in the small-scale range. Therefore, the identification of kinetic instabilities is important and it is the subject of investigation in the following section. 3. SMALL-SCALE TURBULENCE ANISOTROPY AND SPECTRAL INDEX In this section we study in detail the effects of mirror modes and AIC waves, which are observed to dominate in the magnetosheath (Schwartz et al. 1996 ), on the spectral index and anisotropy of fluctuations in the small-scale range, i.e., f ∈ [0.2–10] Hz in our case. To do so, we choose four time intervals of about 3–5 minutes each (i.e., PSDs at frequencies 0.025 Hz are not reliable) and we sort them out depending on the nature of the present waves. The selected cases are chosen as follows: (1) no waves are dominating the spectrum (2008 March 17, 12:30–12:35 UTC); (2) only strong mirror modes are observed (2008 March 25, 07:01–07:05 UTC); (3) strong AIC waves dominate (2008 March 30, 01:35–01:39 UTC); and (4) a mixture of the mirror and AIC waves is observed (2008 March 25, 06:51–06:56 UTC). These intervals are selected during periods of low v ( v ≈ 50 km s −1 ) so that the effects of the Doppler shift due to the plasma flow past the spacecraft (i.e., increase of δB y ) are minimized (Sahraoui et al. 2006 ; Alexandrova et al. 2008b ). Because of the low bulk velocity Taylor's hypothesis could be violated (see, e.g., Klein et al. 2014 ), thus we performed three tests to ensure that this hypothesis holds in the selected cases. First, we determined the turbulence intensity ( v 0 being the mean bulk velocity and v rms the root mean square of v fluctuations) to be in the range [0.04–0.09] (i.e., I ≪ 1); then, we found that the relation is fulfilled (for a detailed description of the test, see Sahraoui et al. 2012 ); and finally, we found good agreement between the probability density


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

be considered constant between all the observations. A simple light-travel argument can then put constraints on the distance between the central source and the reflector. For an edge-on view of the system, , and yr, depending on when the source switched on (between the beginning of 1996 and the beginning of 2001). In this case, the distance between the source and the reflector is pc. First a fading, and then an increase in reflection is then expected to occur in the future, and monitoring of the source is the only way to keep track of its changes. Monitoring could also shed new light on the role of the X-ray absorber, which varies on much shorter temporal scales and seems to be associated with broad line region (BLR) clouds (see Risaliti et al. 2010) . If this is the case, the physical interpretation of our result applying the decoupled MYTorus model is straightforward: the l.o.s. is intercepting the variable (and presumably compact) Compton-thin absorber, while the reflector is located on larger scales and the photons reflecting back to our l.o.s. are “seeing” a Compton-thick column of gas. Risaliti et al. (2010) suggest that the absorber is a BLR cloud, assuming a central black hole (BH) mass of . In this picture, a second “screen” is required to obscure the broad lines in the optical spectrum, which is instead likely showing an outflow, resulting in the classification of Mrk 1210 as a Seyfert 2 (Mazzalay Rodríguez-Ardila 2007) . However, if the reflection component comes from photons reflecting off the far inner wall of the torus, delayed with respect to the intrinsic emission, a rather distant torus edge is needed with respect to the dust sublimation radius , which is usually thought to mark the inner wall of the torus, and in this case is 0.2 pc ( Gandhi et al. 2009 , and references therein, and adopting a bolometric correction of 20; Lusso et al. 2012 ). Table 3 ASCA best fit parameters compared with NuSTAR pexrav+zgauss only model. Notes. The NuSTAR line equivalent width is calculated with respect to the reflection continuum. Fig. 9 Observed 1040 keV flux ( top panel ) and iron line flux ( bottom panel ) of Mrk 1210, as a function of time. 4.2. Eclipsing event The ASCA data cannot distinguish between a Compton-thick eclipsing event and an intrinsic low-flux state of the central engine. A random pass of a Compton-thick cloud (or an alignment of clouds along the l.o.s.) during the ASCA observation is consistent with the known clumpiness of the gas surrounding obscured AGN. During the two observations by ASCA in 1995, separated by 25 days, Mrk 1210 was in a low-flux state. In an eclipsing scenario, this means that the putative eclipsing event lasted for at least 25 days. Assuming Keplerian motion of the clump, the linear size eclipsed by a moving Compton-thick cloud in a given time interval can be written as cm, where is the distance from the center in parsecs, and is the eclipse time interval in units of 25 days. This implies that the


O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O O O B-Grant B-Grant B-Grant B-Grant O B-Grant O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O B-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant O O O O B-Grant O B-Grant I-Grant I-Grant I-Grant I-Grant I-Grant O O O O B-Grant O B-Organization I-Organization I-Organization I-Organization O O O O B-Grant O O B-Grant I-Grant I-Grant O B-Observatory I-Observatory I-Observatory B-Organization I-Organization I-Organization I-Organization B-Person O O O O B-Observatory O O O B-Fellowship O O B-Organization B-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant O B-URL O O O O O O O O O O B-Observatory I-Observatory I-Observatory I-Observatory I-Observatory I-Observatory O O O O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization O B-Organization I-Organization I-Organization I-Organization O O O O O O O O O

This work is supported by the National Natural Science Foundation of China through grants of 11503035, 11573036, 11373009, 11433008, and 11403040, the China Ministry of Science and Technology under State Key Development Program for Basic Research through the grant of 2012CB821800, the International ST Cooperation Program of China through the grant of 2010DFA02710, the Beijing Natural Science Foundation through the grant of 1144015, and the Young Researcher Grant of National Astronomical Observatories, Chinese Academy of Sciences. K.W. acknowledges support from the ESO fellowship and grant WA3628-1/1 through the DFG priority programme 1573 “Physics of the Interstellar Medium” ( http://www.ism-spp.de ). We give our thanks to the staff at the Qinghai Station of Purple Mountain Observatory for their hospitable assistance during the observations and the Key Laboratory for Radio Astronomy of Chinese Academy of Sciences for partial support in the operation of the telescope.