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

and mid-IR emission by Li Draine ( 2001b ). Figure 8. Schematic of allowable parameters for silicate nanoparticles for which the rotational emission and polarization do not violate observational constraints (white area). The orange shaded region represents the parameter space where the polarization violates the observed AME polarization, and the blue shaded area depicts the space where rotational emission violates the AME and the polarization by nanosilicate violates the UV polarization of starlight for the ISM. 6.4. Comparison with Previous Spinning Dust Studies Previous spinning dust models ( DL98 ; Ali-Haïmoud et al. 2009 ; Silsbee et al. 2011 ; HDL10 ; HLD11 ) dealt with spinning PAHs, because they are a well-established dust population in the ISM (see Tielens 2008 ). The last spinning dust model ( HDL10 ; HLD11 ) treats all known important physical effects, including grain wobbling due to thermal fluctuations within the grain, transient spin-up by single-ion collisions. In particular, the model can be applied to spinning dust grains of arbitrary shape and arbitrary temperature ( HLD11 ). Since the physics of spinning silicate (iron) is essentially analogous to that of spinning PAHs, it is natural to use our advanced spinning dust model for modeling emission from spinning non-PAHs. Finally, the spinning dust model developed in HDL 10 and HLD11 is the unique model that can predict self-consistently the polarization level of spinning dust emission (see also Hoang et al. 2013 , 2014 ); the spinning models from other groups only provide rotational emissivity. Therefore, our spinning dust model can be used to constrain the dipole moment and magnetic properties of nanoparticles using the AME polarization data. 7. SUMMARY In this paper, we have obtained the principal results as follows: 1. We have quantified rotational emission from spinning ultra-small silicate grains for different grain size distribution parameters, various fractions of total Si abundance contained in ultra-small grains , and a wide range of the dipole moment per atom β . 2. The polarization fraction of spinning silicate emission is found to increase with decreasing value of β . The polarization fraction is below for the dipole moments , but it can reach for assuming K. 3. We have identified that the presence of silicate nanoparticles with and the dipole moment does not violate the UV polarization of starlight and the observed polarization of the AME. With this realization (), rotational emission from spinning nanosilicate can adequately reproduce the observed AME from the ISM. 4. Our quantitative results suggest that rotational emission from spinning silicate nanoparticles may be an important source of AME. Future observations searching for signatures of nanosilicates from the regions with prominent AME would be valuable in understanding the carrier of AME. There are several outstanding questions on the problem of spinning nanosilicates, including the dipole moment and


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

the Small and Large Magellanic Clouds ( Crawford et al. 2001 ; Ridley et al. 2013 ); but also non-detections towards, for example, dwarf spheroidal galaxies ( Rubio-Herrera Maccarone 2013 ). In addition, several efforts have been made to capture periodic as well as single pulse signals from nearby galaxies, with different telescopes. Unfortunately none of these searches discovered new sources. For the deepest of such past surveys, we list the frequencies and sensitivities in Table 1 . These frequencies range from 328–1440 MHz. Based on the facts that at lower frequencies pulsar beams get wider and pulsar fluxes get higher ( Stappers et al. 2011 ), there is a possibility that deep, lower-frequency surveys could find pulsars that these past efforts have missed. Table 2 LOFAR Observations of nearby galaxies M 33, M 81, and M 82. Notes. For tied-array rings (TARs) only the coordinates of the central tied-array beam (TAB) are provided. The LOw Frequency Array (LOFAR, van Haarlem et al. 2013 ) is a radio telescope capable of tracking several nearby galaxies, at long wavelengths. The LOFAR high-band antenna’s (HBA, 120–240 MHz) frequency range approximately coincides with the peak of pulsar flux density distribution (100–200 MHz, Stappers et al. 2011 ), which is an advantage for a pulsar search. Compared to previous low-frequency pulsar searches, further improvements such as the much increased bandwidth (), the high core gain (), and the relatively low antenna temperature (, see Eq. (3) from van Leeuwen Stappers 2010 ) mean that LOFAR can, on the one hand, find many new interesting pulsars (see Coenen et al. 2014 ), and on the other hand, better investigate their fundamental emission peculiarities (see Stappers et al. 2011 ). In general, pulsar beams are thought to be wider at lower frequencies, giving LOFAR the advantage in capturing radio pulses over higher-frequency surveys. Finally, the LOFAR multi-beaming allows for efficient, deep integrations at a sensitivity and field of view unparalleled in the world. The main downside of searching for pulsars with LOFAR is that dispersion and scattering degrade the inherently sharp pulsar peaks. In this paper, we describe the searches we have performed with LOFAR for pulsars in spiral Triangulum Galaxy M 33 (distance ), Bode’s Galaxy M 81 (), and starburst Cigar Galaxy M 82 (). Given their northern positions (see Table 2 ), these three galaxies can be well targeted with LOFAR, as the projected effective area of LOFAR’s fixed dipoles, and thus the sensitivity, is the highest close to zenith (see van Leeuwen Stappers 2010 ). The origin and current environment of a galaxy inevitably affect its star-formation rate and mass-energy distribution. As a result, the pulsar population in nearby galaxies can be different from that of our Milky Way, and a comparison between this population and that of our Milky Way is interesting. Furthermore, measuring a dispersion measure (DM) toward an extragalactic pulsar


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This work was supported by NASA grant NNX10AD78G. This research has made use of the NASA/IPAC Extragalactic Database (NED), which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. We thank the referee, Tim Kallman, for his careful review of the paper and constructive comments. We thank A. Maeder, M. Catalan, and E. Behar for useful suggestions. We also thank G. Ferland and associates for their continuing maintenance of cloudy .


O O O O O O O O O O O O B-Person O O O B-Organization O B-Fellowship I-Fellowship I-Fellowship I-Fellowship O O O B-Organization I-Organization I-Organization I-Organization O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O B-Organization O O B-Grant I-Grant B-Person B-Person O B-Person O O B-Organization I-Organization I-Organization I-Organization I-Organization O O O B-Event I-Event I-Event I-Event I-Event I-Event I-Event O O O O O O O O O O O O O B-Organization I-Organization I-Organization O O O B-Grant I-Grant O O O O O O O O O O B-Archive I-Archive I-Archive O O B-Dataset I-Dataset I-Dataset O O O O O B-Organization I-Organization I-Organization B-Organization O O O O B-Software B-Software O B-Software O O O O O O O O O B-Telescope I-Telescope I-Telescope I-Telescope 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 I-Organization I-Organization O O B-Organization O O O O O O O O O B-Telescope I-Telescope I-Telescope I-Telescope B-Telescope O O O B-Organization O O B-Organization I-Organization I-Organization I-Organization O B-Organization O B-Grant O O O O O O O B-Database I-Database I-Database B-Database O O O O O B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization O O O B-Organization O O O O B-Person I-Person O O O O O O B-Database I-Database O O O B-Database I-Database O O O O O B-Organization B-Grant I-Grant I-Grant I-Grant B-Grant O O B-Organization B-Grant

We thank the anonymous referee for helpful comments and suggestions. Support for A.E.R. was provided by NASA through Hubble Fellowship grant HST-HF2-51347.001-A awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA, under contract NAS 5-26555. A.E.R., J.E.G., and E.G. thank the Kavli Institute for Theoretical Physics for hosting the 2013 workshop “A Universe of Black Holes,” during which this project began. This research was supported in part by the National Science Foundation under Grant No. NSF PHY11-25915. This research has made use of data obtained from the Chandra Data Archive and the Chandra Source Catalog, and software provided by the Chandra X-Ray Center (CXC) in the application packages CIAO, ChIPS, and Sherpa. This publication makes use of data products from the Wide-field Infrared Survey Explorer, which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, funded by NASA. This work has also used observations made with the NASA Galaxy Evolution Explorer. GALEX is operated for NASA by the California Institute of Technology under NASA contract NAS5–98034. This study has made use of the NASA/IPAC Extragalactic Database (NED), which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA. We are grateful to Michael Blanton and all who helped create the NASA-Sloan Atlas. Funding for the NASA-Sloan Atlas has been provided by the NASA Astrophysics Data Analysis Program (08-ADP08-0072) and the NSF (AST-1211644).


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

of XMM - Newton and NuSTAR simultaneous data. As a first attempt, we simply adopted this absorbed PLCUT model as a pure phenomenological and statistically acceptable description of the continuum emission. The results from fitting the eight time-resolved 3–78 keV spectra in this way are reported in Table 2 . Table 2 Time-resolved Spectroscopy (3–78 keV), Fitting Only NuSTAR Data of the Flare Peaks Note. a Fluxes (corrected for the absorption) and luminosities are in the energy range 1–100 keV. In some of these spectra, negative residuals appeared at energies between 15 and 40 keV. To account for these absorption features, we modified the PLCUT continuum multiplying it with a cyclotron absorption model ( cyclabs in xspec package). At first, we calculated the line significance by increasing the Δ χ 2 value until the confidence region boundary of the depth (Depth cycl in Table 3 ) of the cyclotron line crosses 0. The significance of these lines was greater than 2 σ in five (of eight) spectra (flare numbers 1, 2, 3, 4, and 6), so we have reported absorption line parameters only for these spectra in Table 3 for clarity. The absorption lines were measured with a significance ranging from σ = 2.3 to σ = 4.4 (with cyclabs model), with the best value obtained during the first flare observed by NuSTAR . The centroid energy was different: in spectra 1, 4, and 6 the feature was in a narrow range around 17–18 keV, while during spectrum 3 it was at ∼33 keV. In spectrum 3, the line at ∼17 keV was undetected: we could place an upper limit (Depth cycl ≲ 0.18) to the depth of the cyclabs line with the centroid energy fixed at 17 keV (and line width of 2 keV). Table 3 Same as Table 2 ( NuSTAR Only), Considering Only Flare Peaks 1, 2, 3, 4, and 6, Where the Inclusion of an Absorption Feature Resulted in a Line Significance Larger than 2 σ Notes. a cyclabs model in xspec . b This line significance was calculated by increasing the Δ χ 2 value until the confidence region boundary of the depth (Depth cycl ) of the cyclotron line crosses 0. In order to test the significance of the absorption line, since the F-test could bring unreliable results (Protassov et al. 2002 ), we used Monte Carlo simulations to confirm the presence of the cyclotron line in spectrum 1 (our best case, Figure 6 ), following the approach described by several authors (Barrière et al. 2015 ; Bhalerao et al. 2015 ; Lotti et al. 2016 ). We used the simftest routine in xspec with 100,000 simulations, 6 6 simftest is a script that tests for the presence of an additional component simulating N fake spectra based on the model without such component. It then fits the spectra with both the models with and without the additional component registering the Δ χ 2 and comparing it with the Δ χ 2 obtained with the real data to obtain the probability of a false detection. fixing the N H to the values reported in Table 3 to speed up the process, and found that the probability of such a line to be required by


O O O O O B-Model O O O O O B-Model O O O O O O O O O O O O O O B-CelestialObject O O O B-Survey I-Survey 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 O O O O B-CelestialObject 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 O O O O O O O O O O O O B-Telescope O O B-Model O O O O O O O O O O O O O O O O O O B-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion O O B-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion O O O O O O B-Model 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 B-Model 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 B-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion O O B-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion O O O O O O B-Model 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 B-Model 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 B-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion O O B-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion O O O O O O B-Model 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 B-Model 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 B-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion O O B-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion I-CelestialRegion O O O O O O B-Model O O O O O O O O O O O B-Telescope O O O O O O

measurement. 4. We claim that VGT–PCA as a modification of the VGT is advantageous in studying the magnetic field morphology and predicting the contribution from the Galactic foreground. Appendix A GALFA-H <sc>i</sc> Data Selection In this work, the ensemble GALFA-H i data is separated into three data sets: East (A), North pole (B), and West (C). Each data set is divided into five individual subregions. The velocity range of each data set is selected, such that the majority of the Galactic neutral hydrogen gas is included. Table 1 gives the description of the GALFA-H i data set used in this work. The uncertainty on the AM is given by the standard error of the mean, i.e., the standard deviation divided by the square root of the sample size. Figures 11 – 16 show the morphology of the POS magnetic fields inferred from Planck polarization and VGT–PCA with resolution ≃1°. Figure 11. The morphology of the POS magnetic fields on the sky patch with (a): R.A. from 240 to 480 and decl. from −12 to 371, and (b): R.A. from 480 to 720 and decl. from −12 to 371. Left: the magnetic field predicted from VGT–PCA (red segments) with resolution ≃1°. Middle: the magnetic fields inferred from Planck polarization (blue segments). Right top: the histogram of the relative orientation between the magnetic field predicted by VGT–PCA and the one inferred from Planck polarization. Right bottom: the variation of the AM with respect to the polarization percentage. Figure 12. The morphology of the POS magnetic fields on the sky patch with (a): R.A. from 720 to 960 and decl. from −12 to 371, and (b): R.A. from 960 to 1200 and decl. from −12 to 371. Left: the magnetic field predicted from VGT–PCA (red segments) with resolution ≃1°. Middle: the magnetic fields inferred from Planck polarization (blue segments). Right top: the histogram of the relative orientation between the magnetic field predicted by VGT–PCA and the one inferred from Planck polarization. Right bottom: the variation of the AM with respect to the polarization percentage. Figure 13. The morphology of the POS magnetic fields on the sky patch with (a): R.A. from 2640 to 2880 and decl. from −12 to 371, and (b): R.A. from 2880 to 3120 and decl. from −12 to 371. Left: the magnetic field predicted from VGT–PCA (red segments) with resolution ≃1°. Middle: the magnetic fields inferred from Planck polarization (blue segments). Right top: the histogram of the relative orientation between the magnetic field predicted by VGT–PCA and the one inferred from Planck polarization. Right bottom: the variation of the AM with respect to the polarization percentage. Figure 14. The morphology of the POS magnetic fields on the sky patch with (a): R.A. from 3120 to 3360 and decl. from −12 to 371, and (b): R.A. from 3360 to 3600 and decl. from −12 to 371. Left: the magnetic field predicted from VGT–PCA (red segments) with resolution ≃1°. Middle: the magnetic fields inferred from Planck polarization (blue segments). Right top: the


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

Virial equilibrium (PVE), instead of the usual SVE. The implication, being a single magnitude of the external pressure, P ext , may be insufficient to explain the variations reported by Heyer etal. ( 2009 ). Instead, their data could be reconciled only if different clouds in the sample experienced different magnitudes of pressure in the range 10 4 10 7 K cm 3 . Equivalently, it meant that the sizelinewidth relation would be modified by the magnitude of external pressure, P ext , experienced by a GMC. In an earlier work, Ballesteros-Paredes ( 2006 ) strongly argued against GMCs obeying the SVE because: (i) clouds being the consequence of turbulent fragmentation in the interstellar medium (ISM), the fragmentation process must necessarily induce a flux of mass, momentum and energy between clouds and the ISM, and (ii) clouds often exhibit asymmetries in their respective line-profiles, which is inconsistent with clouds obeying the SVE. Instead, the Larsons scaling relations should, at best, be viewed as evidence for energy-equipartition. The possibility of bound, turbulence-supported clouds as suggested by Krumholz McKee ( 2005 ) is difficult to reconcile, for it is unlikely that there will be no redistribution of mass within such clouds over their lifetime (Ballesteros-Paredes 2006 ). Gas dynamics within a typical GMC is likely governed by collisions between smaller clumps within them (e.g. Anathpindika 2009a , b and references therein), and/or feedback from existing stellar populations (see e.g. Mac Low Klessen 2004 and references therein). In a more recent work, Ballesteros-Paredes etal. ( 2011 ) argued that the variations in the sizelinewidth relation reported by Heyer etal. ( 2009 ) is actually consistent with the scenario of hierarchical fragmentation in which a cloud does not collapse as a whole, but only isolated pockets in it collapse to form stars. In this paradigm, although turbulence in the ISM possibly plays a role in assembling the cloud, post its formation, when the contribution due to self-gravity becomes significant, the cloud no longer needs to be in equilibrium with the external medium. It is therefore unnecessary to resort to mechanisms that can actually hold clouds with complex geometries and density distributions in approximate equilibrium (see also Burkert Hartmann 2004 ). Simulations of unbound clouds leading to inefficient star formation were discussed by e.g. Clark etal. ( 2005 ) and Clark, Bonnell Klessen ( 2008 ). The virial state of GMCs has also been interrogated numerically. Dobbs etal. ( 2008 ) and Tasker Tan ( 2009 ), for instance, reported that clouds forming in a galactic disc typically have a virial coefficient between 0.2 and 10. Furthermore, Dobbs etal. ( 2011 ) argued that intercloud collisions in the disc of a galaxy was a viable mechanism to render clouds unbound. Alternatively, several other authors examined the formation of clouds out of collisions between large-scale flows (e.g. Vzquez-Semadeni, Passot


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at a distance of 1 arcsec (140 au) from the star. 5.6 Orientation in space The envelope thickness at y = 0, measured by an FWHM of ∼0.55 in λ (Fig. 10 , left) meaning ∼0.7 arcsec, is consistent with the value quoted in Section 3.1 from which an upper limit of ∼22° was placed on a possible tilt θ 2 between the disc plane and the ( y , z ) plane about the y -axis. The observed ∼10° tilt θ 1 about the z -axis of the map of 〈 V z 〉 that was mentioned in Section 3.2 and illustrated in Fig. 4 deserves some comments. As remarked then, such a tilt is also seen in the integrated flux for distances from the star exceeding ∼3 arcsec, not only in the present data (Figs 1 and 3 , left), but also in infrared observations (Tobin et al. 2008 ). The difference of inclination of the central part of the envelope, as measured from the integrated flux, and of the outer part, including the outflow, is not due to some trivial geometric effect but is real. Many factors may play a role in this context, such as magnetic field (see for example the review of Li et al. 2014 ) or binarity (Loinard et al. 2002 ). 6 SUMMARY In summary, the main original contribution of the present analysis to our understanding of the formation process of L1527 is the presentation of a simple 3D parametrization of the morphology and kinematics of the gas envelope based solely on the observation of the C 18 O (2–1) line emission from regions that are not dominated by absorption. In the explored range, the model, which uses eight relevant parameters, reproduces observations significantly better than earlier attempts. This was made possible by assuming central symmetry and axisymmetry about the x (west–east) axis and by excluding from the analysis Doppler velocities between 0 and 0.32 km s −1 and a band of the sky map of ±0.675 arcsec about the x -axis. Moreover we have reduced the radial dependences of the temperature and density to a single quantity, the effective emissivity. We have presented arguments showing that such assumptions are indeed reasonable. The main conclusions of the analysis are as follows. Rotation : the model uses successfully trajectories spiralling down towards the disc on paraboloids coaxial with it. We give evidence for the dominance of rotation over the explored range and confirm that the rotation curve is as expected from a transition from an inverse distance law to a Keplerian regime. The rotation velocity decreases from ∼1.66 to ∼0.34 km s −1 when r increases from 1 to 5 arcsec. However, the range explored is too distant from the star to allow direct observation of the disc. In-fall velocity : we measure a mean in-fall velocity of 0.43 ± 0.10 km s −1 over the explored range, smaller than free-fall velocity, with no evidence for a significant r -dependence, in particular no evidence for the sudden jump to ∼1.5 km s −1 required by Ohashi et al. ( 2014 ) to describe the absorption-dominated central region. Central mass : using simple arguments of energy conservation, we


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Acknowledgements This work was supported by CONICYT through its grants CATA Basal PFB06, QUIMAL project 140002, ALMA 31150012 and Fondecyt 11140428, ESO-Chile Joint Committee for Development of Astronomy, and NL NOVA ALMA RD project. We thank Xilinx Inc. for the donation of FPGA chips and software licenses.


The author wishes to thank the anonymous reviewer for useful comments that lead to significant improvement of the paper.


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ACKNOWLEDGEMENTS The authors express thanks to Aniruddha Kembhavi for a careful reading of the manuscript and comments. S.A. acknowledge the use of IUCAA cluster Sarathi for the computational work. A.K.A. would like to thank the Square Kilometre Array South Africa (SKA SA) for funding the research project. This research has been conducted using resources provided by the Science and Technology Facilities Council (STFC) through the Newton Fund and the SKA Africa. Funding for the SDSS 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, 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.


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LL would like to thank Robert Beswick for fruitful discussion and helpful comments. We thank an anonymous referee for constructive comments, which helped improve the manuscript. KKK acknowledges support from the Swedish Research Council.


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J.V. would like to acknowledge the availability of computing resources on the Occigen super computer at CINES (France) to perform the computations required for modeling the theoretical meteoroid streams. Special acknowledgement also goes to all members of the Croatian Meteor Network for their devoted work on this project.


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assumption that BBHs trace the location of their parent star particles. The prospects for detecting BHs without stellar companions remain limited. Still, with a refined model of the star formation history in the MW, non-detections with X-ray, radio and microlensing surveys will put constraints on binary evolution models. Conversely, a much higher number of detected systems will be equally constraining, and may inform us of additional BBH formation channels (Rodriguez et al. 2015 ; Marchant et al. 2016 ). Our understanding of massive binary evolution is still very uncertain, especially the modelling of stellar mass-loss through different evolutionary phases, the properties of common-envelope mass transfer, and supernova kicks. Specifically, we have assumed that common envelope interactions during the Hertzprung gap result in stellar mergers, which may underestimate the BBH production rate. Conversely, we assume the BH natal kicks are reduced with respect to NS natal kicks, which may overestimate the number of systems surviving both supernova explosions. As our work highlights the importance of improved galactic models, we do not explore the wide parameter space of current binary models. The different BBH merger rates predicted by Mapelli et al. ( 2017 ) show how different binary evolution models will eventually be ruled in or out by observational data, provided appropriate models are used for the star formation. Based on our assumptions for binary evolution, we predict that LISA will detect about 25 BBHs within the MW halo. The frequency of these systems will not vary over the duration of the LISA mission, which means that the measured chirp mass will be degenerate with the distance of the system (see equation 4 ) and discerning it from a closer NS binary may not be possible. While certain aspects of binary evolution are likely to be revised, we emphasize that the BBH predictions of our model are somewhat on the high end (see a discussion in Lamberts et al. 2016 ) and that fine-tunning it in order to produce more galactic BBHs may overproduce the observed BH merger rate (Abbott et al. 2017c ). Unless a mechanism allows for the formation of BBHs at close to solar metallicity, BBHs are strongly biased towards the galactic halo, which strongly reduces their GW signal on Earth relative to disc populations. Even a single detection with accurate localization will provide information on the binary evolution mechanism and the conditions of its formation. We find that less than a million BBHs have merged in the MW by the present day. Focusing on the mergers within the last 2 Gyr, we find a merger rate of ≃10 −5 yr −1 . Our model, which assumes a binary fraction of unity, is on the higher end of the measured rate. We find the mean mass of the systems to be 29, which is in line with the announced detections (Abbott et al. 2016a ; 2017a , b , c ). We find that sources with represent 8 per cent of the merged systems, meaning there could be roughly 40 000


O O O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Tag 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 B-Telescope O O O B-Location I-Location I-Location I-Location O O B-Location I-Location 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 B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-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 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 B-Collaboration I-Collaboration O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O B-Telescope O O O O O O O O O O O O B-Telescope O B-Telescope O O O O O O O O O O O O O O O O O O O O O O O B-Telescope 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

sets with each set obtained from weighted average over 100 voxels. This yields an RMS of for clean modes in the range k ≃ 0.02–1 h Mpc −1 . The RMS estimate can be further improved by averaging over all the data for a fixed τ (this leaves the mean unchanged for reasons outlined in the foregoing) and then computing the RMS using bootstrapping (e.g. Kolopanis et al. 2019 ). We plot the power spectra for both the XX and YY polarizations in all the figures to emphasize the long-term system stability in a drift scan. Our calibration does not involve a polarized source so both the polarizations are assigned equal weight in the beginning of the scan. Our results show that no significant deviation emerges at the end of the scan. As the H i signal is unpolarized, the power spectra for the two polarizations can be added in quadrature to yield a further improvement in RMS by nearly a factor of . 5.5.1 Comparison with other H <sc>i</sc> power spectrum measurements Our results can be directly compared to PAPER H i power spectra upper limits as it was also a drift scan experiment. PAPER was located in Karoo desert, South Africa at geo-coordinates 30°43′17′′S, 21°25′42′′E. Its 2-m antenna had a primary beam (FWHM) of nearly 50°. PAPER’s 64 antennas were placed in a 8 × 8 pattern. For the final results presented in Kolopanis et al. ( 2019 ), six of the antennas were flagged and only a subset of baselines were used for the power spectrum estimations. This subset consisted of 30-m East–West baselines between adjacent columns and those staggered by one row (see fig. 2 of Kolopanis et al. 2019 ). The system temperature for the observational runs varied between 400 and 800 K in the frequency range. These data sets had a total bandwidth of 10 MHz with a channel width of 493 kHz, centred around six frequencies in the range 120–167 MHz. The power spectrum estimate was based on 135 d of observations, but only the data from 124 d was used for LST binning. The LST spanned the range 00 h 30 m 00 s to 08 h 36 m 00 s . The data sets were initially binned with a time resolution 43 s. After the LST binning, they were further averaged with a top-hat filter in time which yielded a resolution of 938 s. With these instrumental parameters, the PAPER collaboration recently published the analysis of its final data products. Their upper limits on the H i power spectra at z ≃ 8.13 are: Δ 2 ( k ) ≃ (1000 mK) 2 at k = 0.2 h Mpc −1 and (380 mK) 2 at k ≃ 0.32 h Mpc −1 (Kolopanis et al. 2019 ). Our upper limit at a comparable wavenumber and redshift is ≃(1000 mK) 2 , based on nearly 35 h of MWA drift scan data. While a more direct comparison between the performance of MWA and PAPER is harder, this allows us to note the following salient differences between the two interferometers and analysis pipelines: (i) the collecting area of MWA is nearly five times large, (ii) PAPER baselines have a higher level of redundancy (Section 3 ), (iii) the time over which the visibilities are averaged is


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

The present work is supported by the Xinjiang Natural Science Foundation grant No. 2014211A069. This work is also funded by the CAS Key Laboratory of Solar Activity, National Astronomical Observatories, the Key Laboratory of Modern Astronomy and Astrophysics (Nanjing University), Ministry of Education, China Scholarship Council (CSC), XAO Director Foundation, and NSFC (No.11673056 and 11403087). The authors also thank the support from the Supercomputer Center of University of Arizona. In addition, the authors appreciate Prof. J. R. Jokipii and his group in the University of Arizona, Profs. Hongbo Hu and Hong Lu at IHEP, Prof. Xueshang Feng and his group at NSSC, Profs. W. Gan and Haisheng Ji at PMO, Prof Jun Lin at YNAO, Profs. Quanming Lu and Chenglong Shen at USTC of CAS, and Prof. Liuguan Ding at Nanjing University of Information Science and Technology for their many helpful discussions.


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

We are grateful for all of the referee’s suggestions and comments, which greatly improved the scientific quality and information flow of this work. K.C. would like to recognize and thank the Royal Thai Government Scholarship in the section of the Ministry of Sciences Technologies for the National Astronomical Research Institute of Thailand (NARIT) and the University of Florida’s Graduate School Doctoral Dissertation Award for guidance and financial support during the phase of completing this work and his thesis. E.S.S. acknowledges funding and support from the Spanish MINECO under the projects MDM-2014-0369 of ICCUB (Unidad de Excelencia “María de Maeztu”), AYA2015-70498-C02-2-R and AYA2017-88085-R (both cofunded with FEDER funds), and the Catalan DEC grant 2017SGR643. R.C. and J.M.R.E. acknowledge support from the Spanish Ministry of Science under grant AYA2015-70498-C2-1. J.M.R.E. also acknowledges support from the Spanish Ministry of Science through grant AYA2017-84061-P. R.C., J.M.R.E., and A.H. acknowledge the Spanish Ministry of Science’s support through the Severo Ochoa grant SEV2015-0548. A.H. acknowledges support by the Spanish Ministry of Science through grant AYA2015-68012-C2-1 and by the Gobierno de Canarias through grant ProID2017010115. J.G. acknowledges support by the Spanish Ministry of Science through grant AYA2016-75808-R. J.M.M.H. is partially funded by Spanish State Research Agency grants ESP2017-87676-C5-1-R and MDM-2017-0737 (Unidad de Excelencia ‘María de Maeztu’ CAB).


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

We are grateful to the referee for the constructive comments and substantial improvements to this work. We thank Dr. Chang Liu for providing ideas to explain the observation, and Dr. Xin Chen for providing the tracing method. The observations presented in this paper were mainly obtained with NST at the Big Bear Solar Observatory, which is operated by New Jersey Institute of Technology. The data are courtesy of the BBSO and NASA/ SDO teams. This work was partially supported by NASA grants NNX13AF76G, NNX16AF72G, NNX13AG13G, and NNX14AC12G, and by NSF grants AGS 1348513, 1408703 and 1620875. BBSO operation is supported by NJIT, US NSF AGS-1250818 and NASA NNX13AG14G, and NST operation is partly supported by the Korea Astronomy and Space Science Institute and Seoul National University, and by strategic priority research program of CAS with grant No. XDB09000000.


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

consequence of the release of the S-species from the icy grain mantles because of thermal and nonthermal desorption and sputtering. Contrary to dark clouds and prestellar cores, in B1b the S depletion is comparable to that of C and O, which explains the high abundances of S-bearing species in this core. Table 4 Elemental abundances relative to H. Notes. (a) From the compilation by Agúndez Wakelam (2013) ; (b) this work; (c) elemental abundance in the gas phase; (d) depletion factor = (X/H)/(X/H). The abundance of sulfur in grains is very uncertain. Thus far, the only S-bearing molecule unambiguously detected in ice mantles is OCS, because of its large band strength in the infrared ( Geballe et al. 1985 ; Palumbo et al. 1995 ), and maybe SO ( Boogert et al. 1997 ), but there are only upper limits of the solid HS abundance ( Jiménez-Escobar Muñoz Caro 2011 ), which is thought to be the main sulfur reservoir in the ice. Measurements of the sulfur depletion are derived by comparing the predictions of gas-phase chemical models with the observed abundances of the main S-bearing species. As reported above, chemical models are limited by the uncertainty in the reaction rates and the poorly known [O]/[O] ratio and the exact value of the sulfur depletion is uncertain. Our results suggest, however, that the sulfur depletion in Barnard 1b is not as extreme as in dark clouds where the abundance of S-bearing species is lower. This moderate sulfur depletion could be the consequence of the star formation activity in the region. B1b is irradiated on its eastern side by UV photons from the nearby Herbig Ae stars LkH 327 and LkH 328 ( Walawender et al. 2009 ; Young et al. 2015 ). On its western side, B1b is impacted by the outflows associated with B1a and B1d ( Hatchell et al. 2007 ). Not unrelated, the level of turbulence in B1 (0.4 km s) is higher than in cold cores such as L1544, TMC-1 or L134N (0.1 km s). Sputtering induced by collisions may be efficient in this turbulent environment to erode the icy mantles and release the sulfuretted species to the gas phase. Sputtering could also explain the high abundances of complex molecules observed in this core ( Marcelino et al. 2009 ; Cernicharo et al. 2012 ). The main drawback of this interpretation is that it would also imply a low depletion of CO that is not observed. Another possibility is that the moderate sulfur depletion is a consequence of the rapid collapse of B1b. Aikawa et al. (2005) investigated the impact of different collapse timescales on the gas chemistry. The initial conditions of their first model lie close to the critical Bonnor-Ebert sphere with a central density of 10 cm. When the central density of the core reaches 10 cm, the S-bearing species were totally depleted at AU. In the second case, internal gravity overwhelms pressure and the collapse is much faster (about 0.1 Myr). When the central density of the core reaches 10 cm, molecules such as CS, SO, and CS have abundances of 10 in the


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

provide the best overall fits in terms of visual inspection of the residuals and through comparison of likelihood ratios between models. Thus, we adopt the BaSTI models for this Letter. We adopt a metallicity grid that ranges from −2.3 ≤ [M/H] ≤ −0.5 with a resolution of 0.1 dex and an age grid that ranges from with a resolution of dex. We find that including ages younger than did not change the SFHs (as these galaxies have no young populations) but increased the computational time. Thus, we simply exclude ages with from our CMD modeling. Finally, given that our CMDs do not reach the oldest MSTO, we follow Weisz et al. ( 2011 , 2014 ) and adopt a prior on the age–metallicity relationship that requires the metallicity to increase monotonically with time, with a modest dispersion allowed at each age. This choice helps to mitigate some of the age–metallicity degeneracy on the RGB and RC. We compute random (which accounts for the finite number of stars on the CMD) and systematic uncertainties (which are a proxy for uncertainties in the physics of the underlying stellar models) as described in Weisz et al. ( 2014 ). Finally, as detailed in Section 3.6 and Figure 6 of Weisz et al. ( 2014 ), SFHs measured from CMDs that include the HB but do not include the oldest MSTO have larger systematic uncertainties, but are consistent with SFHs measured from the oldest MSTO-depth CMDs. Figure 1 illustrates the CMD modeling process. Panel (a) shows the observed Hess diagram of And XXI, and panel (b) shows the best-fit model for the BaSTI stellar library. A visual comparison of the model and data indicates good overall agreement. Panel (c) is a residual significance diagram, i.e., (model–data)/model, which quantifies the level of (dis)agreement. The majority of populated pixels are consistent within ∼1 σ , while only a handful of pixels are highly discrepant (i.e., 3 σ ). There are no signs of poorly fit regions of the CMD (e.g., large swaths of only black or white pixels), which indicates that the model is a good fit to the data. Panel (d) shows the cumulative SFH of And XXI, i.e., the fraction of total stellar mass formed prior to a given epoch. The solid black line is the best-fit BaSTI solution, and the gray-shaded band reflects the 68% confidence interval of the total (i.e., random plus systematic) uncertainties. The random uncertainties are negligibly small compared to the systematic uncertainties. The thin colored lines in panel (d) are the best-fit SFHs from the other four stellar libraries. These SFHs are similar in shape to the BaSTI solution, though particular features can be shifted by up to ∼2 Gyr, which is due to differences in the underlying stellar physics (e.g., Gallart et al. 2005 ). As intended, the scatter in the SFHs from different models is well captured by the gray-shaded error envelope. The small amount of apparent star formation ∼1–3 Gyr ago is likely due to a handful of blue stragglers that occupy similar portions of the CMD as


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The authors thank Catherine Espaillat and Lynne Hillenbrand for providing the optical spectra and physical parameters of a few objects, and John Kwan for providing the mid-IR hydrogen line ratios. E.R. is supported by the NASA's Astrophysics Data Analysis Program research grant to I.P. (ID: NNX11AG60G).


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

to be around 2.5 throughout the whole envelope in good agreement with previous measures. All these conclusions lead us to think that Y CVn is a quite active star that could have developed structure in its envelope. Due to the physical mechanisms that are producing the suggested asymmetries close to the star, the high temperatures, gas densities below ~ 10 8 –10 10 cm −3 , the influence of the Galactic UV radiation field in the chemistry at different distances from the star, and its proximity, Y CVn is a good candidate to better understand the physical and chemical evolution of the envelopes of low mass-loss rate C-rich stars. Appendix A Brief description of HCN Hydrogen cyanide is a linear triatomic molecule that belongs to the C ∞ group and displays a permanent dipole moment of 2.985 D ( Ebenstein Muenter 1984 ). The vibration of its atoms can be described with the aid of four normal modes, two of which are degenerate and are combined into the bending mode ν 2 ( π ). These two degenerate normal modes involve atomic oscillations out of the molecular axis that allow the molecule to spin around it. This results in the creation of a vibrational angular momentum that splits the rotational levels in sublevels with different e − f parity ( Brown et al. 1975 ). The other two normal modes, ν 1 ( σ + ) and ν 3 ( σ + ), are stretching modes that can be essentially described as the HC–N and H–C vibrations along the molecular axis, respectively (e.g., Herzberg 1956 ). Fig. A.1 Vibrational energy diagram of HCN below 5000 K. The lines that connect the vibrational states represent the strongest allowed vibrational transitions. The transitions in blue lie around 13.5 μm, in red around 7.5 μm, and in orange at other wavelengths (3.0, 3.6, 4.8, and 8.2 μm, depending on the transition). Those plotted with ticker lines are detected in the spectra presented in the current work ( Figs. 1 and 2 ). In the current work, we adopted two different notations commonly used in Molecular Spectroscopy and Astrophysics to label a vibrational state: v 1 ν 1 + v 2 ν 2 + v 3 ν 3 ( l ± ) and , where i = 1, 2, 3. The v i is the vibrational quantum number related to the i -th normal mode, l the quantum number for the vibrational angular momentum, which can be expressed with the Greek letters σ , π , δ , φ , γ , ... for l = 0, 1, 2, 3, 4, ..., ± is the total parity of the molecule in this vibrational state (usually given only for the σ states), and p is the e − f parity. The v = 0 means the vibrational ground state (G.S.). The change of the rotational number in a transition is given by B p ( J l ) for the ro-vibrational lines, where J u and J l are the upper and lower rotational levels, respectively, B is the branch (P: Δ J = J u − J l = −1, Q: Δ J = 0, and R: Δ J = +1), and J = J u − J l for the pure rotational ones. More information about the selection rules and the line intensities of linear molecules can be found, for example, in Fonfría et al. (2008) . Figure A.1


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WASP-South is hosted by the South African Astronomical Observatory and we are grateful for their ongoing support and assistance. Funding for WASP comes from consortium universities and from the UK’s Science and Technology Facilities Council. J.A.K.-K. and D.F.E are also funded by the UK’s Science and Technology Facilities Council. A.M.S. acknowledges support from grants SGR1458 (Generalitat de Catalunya), ESP2014-56003-R and ESP2015-66134-R (MINECO). This research has made use of “Aladin sky atlas” developed at CDS, Strasbourg Observatory, France and NASA’s Astrophysics Data System.


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

from the SDSS DR11 quasars at z = 2.34, we reconstruct the evolution of the dark energy EoS using the polynomial expansion, PCA, and the correlated prior method, respectively. In this paper, we pay attention to the high-redshift BAO measurement of BOSS DR11 quasars, the Ly α FB data, which have been widely used to constrain cosmological parameters (Lee et al. 2015 ; Delabrouille et al. 2015 ), especially the EoS of dark energy. However, we note that this measurement slightly prefers a negative dark energy density, so the second main purpose of this paper is to study the possible influence of this Ly α FB data on the constraints of the EoS of dark energy. In the next section, we show the numerical method and measurements used in this paper. Then, we use different reconstruction methods to explore the evolution of the dark energy EoS. In particular, we carefully check the impact of Ly α FB data on the results. The final section presents our conclusions and a discussion. 2. Method and Data We perform a global fitting analysis of cosmological parameters, using the CosmoMC package, 3 3 http://cosmologist.info/cosmomc/ a Markov Chain Monte Carlo (MCMC) code. We assume purely adiabatic initial conditions and a flat universe. Our parameterization is thus:the and are the baryon and cold dark matter physical densities, Θ s is the angular size of the sound horizon at decoupling, τ is the optical depth, n s and A s are the spectral index and the primordial power spectrum, and P w will be the parameters that describe dark energy. In order to understand the nature of dark energy well, we consider the following data sets. 2.1. SN As standard candles, the SN measurements provide a luminosity distance as a function of redshift z , making them a powerful probe for cosmology, particularly for the EoS of dark energy. In this paper, we use 740 samples from JLA (Betoule et al. 2014 ), in which the redshift spans 0 z 1.299, and there are only eight high-redshift samples ( z > 1). The absolute magnitude comes from the logarithm of the luminosity of an astronomical object seen from a 10 parsec distance, which can also be used to give its brightness. We use the distance modulus μ th to relate the expansion history of the universe to the apparent magnitude of an SN at a given redshift. It is defined as the difference between the apparent magnitude m and the absolute magnitude M of the SN and relates to the distance throughwith μ 0 = 42.38 and dimensionless D L = H 0 d L . The luminosity distance is given by d L = (1 + z ) r ( z ), with r ( z ) standing for the comoving distance: The observation of distance modulus μ obs is given by an empirical linear relation:where α and β are set to nuisance parameters in our numerical calculations, , x 1 , and are parameters describing the SN, and M B is related to the host stellar mass M stellar by a simple step function (Betoule et al. 2014 ):so we can calculate the χ 2 of SN following:where σ i is the error of i th SN sample.


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

ACKNOWLEDGEMENTS This publication was made possible by grants NPRP-X-019-1-006 and NPRP-09-476-1-78 from the Qatar National Research Fund (a member of Qatar Foundation). GD acknowledges Regione Campania for support from POR-FSE Campania 2014-2020. MPGH acknowledges support from the Villum Foundation. Work by C.H. was supported by the grant (2017R1A4A1015178) of National Research Foundation of Korea. This work makes use of observations from the LCOGT network, which includes three ‘SUPAscopes’ owned by the University of St Andrews. The RoboNet programme is an LCOGT Key Project using time allocations from the University of St Andrews, LCOGT and the University of Heidelberg together with time on the Liverpool Telescope through the Science and Technology Facilities Council (STFC), UK. This research has made use of the LCOGT Archive, which is operated by the California Institute of Technology, under contract with the LCO. OGLE Team thanks Profs. M. Kubiak and G. Pietrzyński, former members of the OGLE team, for their contribution to the collection of the OGLE photometric data over the past years. The OGLE project has received funding from the National Science Centre, Poland, grant MAESTRO 2014/14/A/ST9/00121 to AU. LM acknowledges support from the Italian Ministry of Instruction, University and Research (MIUR) through FFABR 2017 fund. LM acknowledges support from the University of Rome Tor Vergata through ‘Mission: Sustainability 2016’ fund. KH acknowledges support from STFC grant ST/R000824/1.


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

We are grateful to Ewine van Dishoeck for suggesting this study and we thank her, Simon Bruderer, and François Lique for valuable discussions. We thank the computer and communication department (CCZ) of the Faculty of Science of the Radboud University for computer resources and technical support. The work is supported by The Netherlands Organisation for Scientific Research, NWO, through the Dutch Astrochemistry Network, and in part by the National Science Foundation under grant No. NSF PHY11-25915. N.B. is supported in part by NSF grant PHY-1505557. K.M.W. and P.C.S. acknowledge support from NASA grants NNX12AF42G and NNX13AF42G. I.K. and W.F.T. acknowledge funding from the European Union Seventh Framework Programme FP7-2011 under grant agreement no. 284405.


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

in an unbroken sequence lasting for 9.45 h which is slightly longer than Ceres rotational period of 9.074 h. On August 26, we took a second sequence of 29 exposures of 900 s each. The observations started on August 26 at 23:36 ut at the beginning of the night and ended at the set of Ceres on August 27 at 06:49 UT ut (MJD 2457260.9878–2457261.2840) in an uninterrupted sequence lasting 7.25 h, i.e. a bit shorter than a complete rotation. Five exposures were also taken at the end of the night on August 27, when we could shortly open the dome during a pause of bad weather. The journal of the observations together with the relevant quantities are given in Table 1 which is available online. Table 1. Journal of July observations. 1 st column is the time of the start of the exposure in UT. 2 nd column is the time in MJD. 3 rd column is the radial velocity computed by the HARPS pipeline. 4 th column is the radial velocity corrected from the instrumental drift. 5 th column is the BERV of the HARPS pipeline. 6 th column is the exposure time in seconds. 7 th column is the flux weighted mid exposure fraction. 8 th column is the effective mid exposure time. 9 th column is the radial velocity of Ceres with respect to the Sun. 10 th is the radial velocity of the observer relative to Ceres. The full table is available online. Ceres had an APmag of ≈7.5 mag, an angular dimension of 0.69 arcsec and was observable during most of the night. The observations were performed at phase angles of 4.4 and 12.3 in July and August, respectively. At opposition, Ceres becomes slightly brighter due to the Opposition Surge effect, but no radial velocity variations are expected within a single rotational period (Molaro et al. 2015 ). Inspection of the solar activity through the Solar Dynamic Observatory revealed no significant change in the solar activity to induce an important radial velocity change. The solar activity measured from the total sunspot area changed slightly from ≈500 to ≈1250 millionths of solar hemisphere between July 31 July and August 27. However, note that these will introduce a radial velocity offset between the two nights but not a change within one epoch. We used HARPS pipeline to obtain the radial velocities from sunlight spectra which are reported in the third column of online Table 1 . In the HARPS spectrograph, a second fibre supplies simultaneous ThAr spectra that are used to correct for instrumental radial velocity drifts occurring over the night due to residual temperature, pressure or mechanical changes. The radial velocity differences with respect to the previous calibration provide the instrumental drifts of the spectrograph. We are considering the values RV c corrected for instrumental drift and reported in the column 4 of online Table 1 but note that corrections are always below 0.5 m s −1 and do not affect the results. Single observations have S/N ≥ 100 and the error in the radial velocity measurement is lower than 1 m s −1 .


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

Acknowledgments The work of A.F. Seleznev and the science leave of G. Carraro in Ekaterinburg was supported by Act 211 Government of the Russian Federation, contract No. 02.A03.21.0006 and by the ESO DGDF programme. G. Baume acknowledges support from CONICET (PIP 112-201101-00301) and financial support from the ESO visitor programme that allowed a visit to ESO premises in Chile, where part of this work was done. This publication also made use of data 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. We thank the Centre de Donnes Astronomiques de Strasbourg (CDS), the US Naval Observatory and NASA for the use of their electronic facilities, especially SIMBAD, ViZier and ADS, and the WEBDA data base. This work was based on observations obtained at the Cerro Tololo Inter-American Observatory, Chile, and at ESO Paranal Observatory under programme 292.D-5043.


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 B-CelestialObject O B-Instrument I-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-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 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 B-ObservationalTechniques I-ObservationalTechniques I-ObservationalTechniques 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-CelestialObject 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-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject O O O B-CelestialObject O O O B-Citation I-Citation I-Citation I-Citation O O O 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 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-CelestialObject O O O O O O O O O O B-CelestialObject O O O O O O B-Citation I-Citation I-Citation I-Citation 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

period for the outermost planet of 192 d, i.e. one third of the period found by Burke et al. (2014) . They reported planetary masses for the two giant objects of and . We secured five observations of KOI-1574 with SOPHIE HE. The data have a rms of 12 m s which is compatible with the uncertainties. The bisector and FWHM have rms of 44 m s and 38 m s, respectively. We fitted four circular orbits to the data fixing the orbital ephemeris to the transit ones. For KOI-1574.02, we choose the period of 572 days. We detect a hint of variation for the EGP at 114 days, with an amplitude of m s, and an upper limit of m s within the 99% confidence interval. For the other planets, we find upper limits at the 99% level on their amplitudes of m s, m s, and m s. Assuming a stellar host mass of ( Ofir et al. 2014 ), it gives a mass constraint for the EGP in our sample of ( at the 99% level). This value is fully compatible with the one derived by the transit timing analysis of Ofir et al. (2014) . For the other planet candidates, we find upper limits on the mass at the 99% level of , , and . Assuming that KOI-1574.02 orbits with a period of 192 d, as stated by Ofir et al. (2014) , does not change significantly our constraints on the mass of KOI-1574.01. For the other planets, the upper limits at 99% change to , , and . We conclude that none of these transiting candidates is an eclipsing brown dwarf or low-mass star eclipsing the target star. We confirm they have a mass within the planetary range. Appendix A.35: KOI-1645.01 The giant-planet candidate KOI-1645.01 was found by Burke et al. (2014) with an orbital period of 41 days. We observed it twice with SOPHIE HE and find a clear SB2. We fitted the cross-correlation function with a two-Gaussian profile to derive the RV of both stars. We call star A the one with the deepest line profile and star B the one with the shallowest line profile. The variation of both stars is anti-correlated, which gives a mass ratio of 87.6%. The star A exhibits a RV variation in anti-phase with the Kepler ephemeris, revealing that the secondary eclipse was detected in the light-curve. This candidate is not a transiting planet but a secondary-only EB. Appendix A.36: KOI-1783.01 A giant-planet candidate was found to transit the host star KOI-1783 with a period of 134d by Batalha et al. (2013) . We observed it twice with SOPHIE HE and find no significant RV variation. The bisector and FWHM variation are also compatible with their photon noise. By fitting a circular orbit with no drift at the transit ephemeris, we find an upper limit at the 99% level on the RV amplitude of m s. We derived the stellar atmospheric parameters that are reported in Table B.2 . We find a host mass of , a radius of , and an age of Gyr. Combining the two analyses, we derive an upper limit on the mass of this candidate of , within the 99% confidence interval. We can therefore exclude a star or brown dwarf eclipsing the target star, but we can not firmly


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

(2013) and Jiménez-Serra et al. (2010) have introduced the possibility of low-velocity shocks, which are most likely an effect of large converging flows, such as cloud collision or interaction between two filaments. Jiménez-Serra et al. (2010) consider this possibility for emissions apart from the high-density structures. This could also be a valid possibility for our region, since the spectra from W43 ( Nguyen-Lu’o’ng et al. 2013 ) are, in view of line width and the velocity shift of the SiO line, comparable to those from IRAS 19410 2336. Additionally, the shift in the line peak in the present data lies with a maximum of 6.1 km s (see Table B.1 ) far below the predicted shock velocity for high-velocity shocks ( km s, Gusdorf et al. 2008a , b ). This could be a hint of low-velocity shocks, but it could, as mentioned, also be an effect of the projection in the observed plane and the acceleration of environmental gas. The main reason for Nguyen-Lu’o’ng et al. (2013) considering low-velocity shocks due to large colliding flows was the fact that they observed large SiO structures with relatively uniform emission over the whole area. Again, this is in contrast to our observation that the whole southern part of IRAS 19410 and 2336 lacks SiO emission. Therefore, a collision of flows could again explain the SiO emission in the middle of the region. Still, it cannot explain the only partially present SiO emission in the south or the differences between SiO and CO data. Furthermore, the detection of H emission as a jet shock indicator in the south without any SiO counterpart could not be explained by this. 5. Conclusion After combining the different results, we found that the SiO emission is most likely caused by high-velocity C-type or CJ-type shocks probably from protostellar jets. This explains the emission in the northern part, as well as the observed line widths. The emission in the middle of the region could be a result of decelerated postshock gas due to two or more colliding outflows. The only part of the observation that does not fit this explanation is the missing SiO emission in the southern region. The observed H emission clearly shows shock activity, and the CO data exhibit several bipolar structures. The most valid explanation for us is that there is ongoing jet and outflow activity in the southern part, which is not visible in the SiO data. The missing SiO emission could be a result of the different excitation properties of the molecules and the shock geometry. When the shocks break out of the densest area, as the H data suggest, the density could be too low for SiO to get excited. However, the opposite explanation that SiO is also not visible owing to densities that are too high in the core has to be considered here. Our final conclusion from this observation is that SiO emission has to be used with some caution, because a lot of effects can have an influence on the emission. This is nicely shown by the observed region, since it can be


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