adsabs/WIESP2022-NER huggingface dataset:
Paper: 2018ApJ...856...23G (acknowledgments)
The authors would like to thank the anonymous referee and the AAS statistics consultant for valuable and detailed comments that significantly improved the quality of this paper. We thank Bruno S. Alessi and Eric Bubar for sharing data. We thank Noé Aubin-Cadot, Joel Kastner, Thierry Bazier-Matte, Simon Gélinas, Jean-François Désilets and Brendan Bowler for useful comments, as well as the anonymous referee of Gagné et al. ( 2015b ), who suggested the inclusion of a parallax motion correction in the BANYAN tools. This research made use of: the SIMBAD database and VizieR catalog access tool, operated at the Centre de Données astronomiques de Strasbourg, France (Ochsenbein et al. 2000 ); data products from the Two Micron All Sky Survey ( 2MASS ; Skrutskie et al. 2006 ), which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center (IPAC)/California Institute of Technology (Caltech), funded by the National Aeronautics and Space Administration (NASA) and the National Science Foundation (Skrutskie et al. 2006 ); data products from the Wide-field Infrared Survey Explorer ( WISE ; and Wright et al. 2010 ), which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory (JPL)/Caltech, funded by NASA. This project was developed in part at the 2017 Heidelberg Gaia Sprint, hosted by the Max-Planck-Institut für Astronomie, Heidelberg. This work has made use of data from the European Space Agency (ESA) mission Gaia ( http://www.cosmos.esa.int/gaia ), processed by the Gaia Data Processing and Analysis Consortium (DPAC, http://www.cosmos.esa.int/web/gaia/dpac/consortium ). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. Part of this research was carried out at the Jet Propulsion Laboratory, Caltech, under a contract with NASA. BGM simulations were executed on computers from the Utinam Institute of the Université de Franche-Comté supported by the Région de Franche-Comté and Institut des Sciences de l’Univers (INSU). J.G. designed BANYAN Σ, compiled the bona fide members, wrote the IDL codes, wrote the manuscript, generated figures and led all analyses; E.E.M. shared parts of the young association literature data, characteristics and bona fide members, and provided general comments; O.R.L. wrote the initial Python translation of BANYAN Σ; L.M., A.R., and D.R. performed the BANYAN I, LACEwING and convergent point tool calculations used in Section 8 , respectively; A.R. also provided help with the bona fide members compilation; D.L. and J.K.F. shared ideas and comments; L.P. shared ideas and provided comments especially for the ROC curves analysis; A.R. performed custom Besançon Galactic simulations and wrote the second pagraph of Section 6 ; and R.D. shared comments and supervized O.R.L. Software: BANYAN Σ (this paper), LACEwING (Riedel et al. 2017b ), BANYAN II (Gagné et al. 2014 ), BANYAN I (Malo et al. 2013 ), the convergent point tool (Rodriguez et al. 2011 ), Notability by Ginger Labs, Sublime Text.
Paper: 2015A&A...576A...5C (acknowledgments)
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).
Paper: 2015MNRAS.447.1826Z (acknowledgments)
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.
Paper: 2018MNRAS.481L.136S (acknowledgments)
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.
Paper: 2019ApJ...872..144H (acknowledgments)
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.
Paper: 2019ApJ...876...85R (acknowledgments)
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/ .
Paper: 2019ApJ...874..174P (fulltext)
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
Paper: 2018ApJ...862...10M (fulltext)
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
Paper: 2020ApJ...889..179G (acknowledgments)
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.
Paper: 2019A&A...625A..79H (fulltext)
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
Paper: 2019MNRAS.489.5398W (fulltext)
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,
Paper: 2018MNRAS.475.5570H (acknowledgments)
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.
Paper: 2019MNRAS.482..184A (fulltext)
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
Paper: 2016MNRAS.458.2667S (acknowledgments)
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.