adsabs/WIESP2022-NER huggingface dataset:
Paper: 2015ApJ...805...68P (acknowledgments)
We thank the XMM-Newton and HST teams, in particular Project Scientist N. Schartel and STScI director M. Mountain, for the approval and prompt scheduling of our DD requests. We are also grateful to James Guillochon and Ryan Chornock for valuable discussions. D.R.P. is grateful for valuable discussions with Sjoert van Velzen and Nick Stone. S.B.C. thanks the Aspen Center for Physics and NSF Grant #1066293 for hospitality during the preparation of this manuscript. K.L.P. acknowledges support from the UK Space Agency. Support for this work was provided by the National Aeronautics and Space Administration (NASA) through Chandra Award Number GO3–14107X issued by the Chandra X-ray Observatory Center, which is operated by the Smithsonian Astrophysical Observatory for and on behalf of NASA under contract NAS8-03060. D.R.P. and S.B.C. also acknowledge support from HST grant GO-13611-006 A. The work of A.V.F. was made possible by NSF grant AST-1211916, the TABASGO Foundation, and the Christopher R. Redlich Fund. A.V.F. and S.B.C. also acknowledge the support of Gary and Cynthia Bengier. Finally, we would like to thank the referee for his/her careful comments and suggestions. The scientific results reported in this article are based in part on observations made by the Chandra X-ray Observatory, NASA/ESA Hubble Space Telescope , obtained from the Data Archive at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555, and XMM-Newton , an ESA science mission with instruments and contributions directly funded by ESA Member States and NASA. Some of the data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and NASA; the observatory was made possible by the generous financial support of the W. M. Keck Foundation. Also, observations were obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (United States), the National Research Council (Canada), CONICYT (Chile), the Australian Research Council (Australia), Ministério da Ciência, Tecnologia e Inovação (Brazil), and Ministerio de Ciencia, Tecnología e Innovación Productiva (Argentina). Also, based on observations made with ESO Telescopes at the La Silla or Paranal Observatories. We acknowledge the use of public data from the Swift data archive. Facilities: Swift (XRT), XMM (EPIC), Chandra (ACIS), VLT (FORS2, HAWK-I, XSHOOTER), Keck (LRIS), Gemini:South (GMOS-S), HST (WFC3, ACS), VLBA
Paper: 2019ApJ...874...94W (acknowledgments)
This work was supported by the Chinese NSF through grants NSF 11673066, NSF 11673051, and NSF 11873019. B.Z. and Y.W.W. are supported by the 100 Talents Project of the Chinese Academy of Sciences (CAS). K. L. J. Rygl acknowledges financial support by the Italian Ministero dell’Istruzione Università e Ricerca through the grant Progetti Premiali 2012-iALMA (CUP C52I13000140001). Y.W.W. is supported in part by the West Light Foundation of the Chinese Academy of Sciences (XAB2016A06). Facility: VLBA.
Paper: 2020ApJ...899....7B (fulltext)
that will be found by next-generation space-based grism surveys, such as those planned for Euclid and WFIRST (Maciaszek et al. 2014 ; Gong et al. 2016 ). Section 2 briefly describes our galaxy sample and the archival photometry and spectrophotometry available for analysis. Section 3 lists the parameters used for modeling the galaxies’ UV through near-IR SEDs and introduces our new SED fitting code, MCSED . Section 4 explores the basic properties of the Bowman et al. ( 2019 ) sample, the systematics of the data set, and the effect that various assumptions have on the results. Section 5 extends our analysis to the mid- and far-IR and tests the ability of MCSED to explore the balance between the sight-line attenuation of the UV stellar continua by dust and its isotropic reradiation at longer wavelengths. Finally, in Section 6 , our results are placed in the context of other work at these redshifts and within the framework of simulations. Throughout this paper, we assume a ΛCDM cosmology, with Ω Λ = 0.7, Ω M = 0.3, and H 0 = 70 km s −1 Mpc −1 (Bennett et al. 2013 ). 2. The Sample At present, the largest samples of z ≳ 2 galaxies have been constructed from broadband photometry and color selection via the use of photometric redshifts (e.g., Reddy et al. 2012 ; Bouwens et al. 2015 ; Ono et al. 2018 ). However, in the near future, space missions such as Euclid/NISP (Maciaszek et al. 2014 ) and WFIRST (Gong et al. 2016 ) will detect millions of emission-line galaxies via near-IR slitless grism spectroscopy. Since the selection criteria for these galaxies will differ substantially from those identified using broadband photometric techniques, we can expect the distribution of the galaxies’ physical properties to differ as well. To prepare for this era, we can study the objects found by the pathfinding 3D-HST survey, a 625 arcmin 2 set of two-orbit observations taken with the Wide Field Camera 3 (WFC3) and the G141 grism on the HST (GO programs 11600, 12177, and 12328; Momcheva et al. 2016 ; Weiner AGHAST Team 2014 ). This data set consists of R ∼ 130 near-IR (1.08 μ m λ 1.68 μ m) slitless spectroscopy within the deep CANDELS fields of AEGIS, COSMOS, UDS, GOODS-N, and GOODS-S (Giavalisco et al. 2004 ; Davis et al. 2007 ; Lawrence et al. 2007 ; Scoville et al. 2007 ). Tens of thousands of objects are detectable on these frames, but of special interest are galaxies in the redshift range 1.90 z 2.35. In this window, the emission lines of [O ii ] λ 3727, [Ne iii ] λ 3869, H β , and the distinctively shaped [O iii ] blended doublet λλ 4959, 5007 are simultaneously present in the bandpass. This set of observable emission lines, which includes two different ionization states of oxygen, not only enables the determination of unambiguous redshifts but also allows for the direct detection of galaxies over an extremely wide range of metallicities and ionization parameters. Bowman et al. ( 2019 ) recently created a sample of 1952 such oELGs by vetting the list of 1.90
Paper: 2018MNRAS.474.1277A (fulltext)
flows merely graze past each other appear qualitatively similar to the fits provided by Lombardi et al. to the N-PDFs deduced by them for clouds such as the Perseus, Pipe or the California. All of these latter clouds exhibit little star-forming activity. The potential star-forming ability of a cloud can also be quantitatively assessed by investigating into the fraction of gas cycled into the dense phase. The latter realization, realization 4, is most inefficient in transforming gas into the dense phase as is reflected by the relatively small dense-gas fraction in the plot on the upper panel of Fig. 6 . Similarly, the SFF shown on the lower panel of Fig. 6 , for this latter case declines rapidly to less than a percent while that for the remaining three realizations, can be seen to rise steadily. In fact, Orkisz et al. ( 2017 ) attribute the observed poor efficiency of star formation in the Orion B cloud to the impact of large-scale differential motion causing the gas within the cloud to shear. The next set of plots in Fig. 7 showing the cumulative distribution of gas mass as a function of visual extinction (actually calculation for the K -band extinction), is also quite revealing from the perspective of the star-forming ability of a cloud. Similar plots were deduced by Lada, Lombardi Alvés ( 2010 ) for an ensemble of MCs in the Solar neighbourhood. Clouds such as the Pipe, Perseus, California and the Lupus 1, 3 and 4 known for their poverty in forming stars, showed mass distribution very similar to that for clouds assembled via collisions having a large impact parameter (realization 4 here), where there is very little mass at large extinction. By contrast, the mass distribution for the cloud assembled in realization 1, where the collision was almost head-on is similar to that for MCs such as the Orion or Ophiuchus that form stars more efficiently. It is of course true that stellar feedback in these latter clouds must also contribute to star formation in these latter clouds. We therefore restrict ourselves to the inference that a pristine cloud assembled via head-on or near head-on collision is likely to cycle a larger fraction of gas to higher extinctions ( A K > 1), which could then possibly become future birth-sites for stars. It is indeed interesting that a relatively simple self-gravitating, hydrodynamic model such as the one discussed here can possibly reconcile the observed variations in the distribution of gas mass as a function of visual extinction in nearby MCs. Finally, we examined the possible correlation between the fraction of gas cycled into the dense phase and the relative strength of compressional/solenoidal modes in the velocity field induced in the assembled cloud. The propensity of compressional modes towards assembling putative star-forming gas was demonstrated by Federrath, Klessen Schmidt ( 2008 ). They showed numerically that gas dominated by compressional turbulence, as indicated by the strength of the so-called driving
Paper: 2019MNRAS.489.5136G (fulltext)
during the first step and varied the abundances of the individual elements using the same masks. For a few elements, we extracted the lines of the particular element from the common masks and ran SME with these individual masks. The abundances of O, Sr, La, and Eu were derived from the spectral synthesis of individual lines not falling into the chosen SME spectral regions: the O i IR triplet λλ7771.94, 7774.16 and 7775.39 Å; Sr i λλ4607.33 and 7070.07 Å; La ii λλ5114.56, 5301.97, 5303.55, 5805.78 and 5808.32 Å; and Eu ii λλ6437.64 and 6645.11 Å. The carbon and nitrogen abundances were estimated by simultaneous fitting of the C 2 and CN molecular lines distributed in all regions covered by the SME analysis. The atomic parameters of the lines were extracted from the Vienna Atomic Line Database ( vald ; Kupka et al. 1999 ) using its 3rd release ( vald3 ; Ryabchikova et al. 2015 ). The atomic parameters for the C 2 and CN molecular lines were taken from Brooke et al. ( 2013 ) and the Kurucz's website (see below), respectively. The isotopic structure (IS) of Cu ii , Ba ii , and Eu ii was taken into account. For elements with odd isotopes the synthetic calculations included hyperfine splitting (hfs). Most of the data for isotopic and hyperfine splitting were obtained from the website of R. L. Kurucz, 2 who collected data and a bibliography for individual atomic species. In particular, the hyperfine structure constants for Na i were taken from Griffith et al. ( 1977 ), Tsekeris, Liao Gupta ( 1976 ), and Yei, Sieradzan Havey ( 1993 ); for Sc i and ii from Ertmer Hofer ( 1976 ) and Mansour et al. ( 1989 ); for V i from Childs et al. ( 1979 ), Palmeri et al. ( 1995 ), and Unkel et al. ( 1989 ); for Mn i, ii from Blackwell-Whitehead et al. ( 2005 ) and Holt, Scholl Rosner ( 1999 ); for Co i from Pickering ( 1996 ); for Cu i from Fischer, Hühnermann Kollath ( 1967 ) and Ney ( 1966 ); for Y i from Dinneen et al. ( 1991 ) and Villemoes et al. ( 1992 ); and for Ba i from Villemoes et al. ( 1993 ). All hfs data were collected in a new data base (Pakhomov et al. in preparation) and used by the internal vald programs for the hfs calculations. The average abundances for the final atmospheric model of TYC 8606-2025-1 are given in log (X/H) + 12 units in the second column of Table 3 . The third column of this table presents the current solar photospheric abundances (Asplund et al. 2009 ; Scott et al. 2015a , b ; Grevesse et al. 2015 ), while the fourth columns lists the elemental abundances derived for TYC 8606-2025-1 relative to the Sun. The last column of Table 3 provides information about different effects taken into account in the SME or spectral synthesis analyses. For clarity, the elemental abundances of TYC 8606-2025-1 relative to the Sun are shown in Fig. 2 , highlighting the overabundance of s-process elements, with the Ba abundance increased by a factor of ≈3 with respect to solar. Figure 2. Elemental abundances of TYC 8606-2025-1 relative to the Sun.
Paper: 2019A&A...627A..30L (fulltext)
velocity. A transient current system is generated during a time corresponding to at least the travel time at the Alfvén velocity between the interaction site (e.g., the equator in the case of a satellite–magnetosphere interaction) and the planetary ionosphere. Because of the large size of the current system (several planetary radii in this example), this transient phase can last for a long time and may even be longer than the interaction time itself (see e.g. Neubauer 1980 ; Gurnett Goertz 1981 ; Saur et al. 2004 , for the Io-Jupiter case). In this case, electron acceleration is due to the parallel electric field associated to kinetic Alfvén waves above the ionosphere of the planet. This electric field is modulated at the Alfvén wave frequency and does not form electric potential drops, and hence does not directly form auroral cavities either (although cavities may slowly build up due to the excitation of ion acoustic waves, Hess et al. 2010a ; Matsuda et al. 2012 ). Thus, the electron density in the current system is the same as outside of it, with the cold component of the plasma remaining present, and the electron distribution is either a ring or a Kappa-like distribution ( Swift 2007 ; Hess et al. 2007b , 2010b ). 3.3. Unstable electron distributions Wave-particle resonance is reached when the Doppler-shifted angular frequency of the wave ω = 2 πf in the frame of the electron ( ω − k ∥ v r ∥ ) is equal to that of the gyration motion of resonant electrons (). Components k ∥ and v r ∥ are the parallel components (to the magnetic field lines) of the wave vector and of the velocity of the resonant particle, respectively. The electron cyclotron angular frequency is ω c = 2 πf c = eB / m e , with B being the magnetic field amplitude and e and m e the charge and mass of the electron. Finally, Γ r is the Lorentz factor associated with the resonant electron motion. The resonance condition therefore writes with In the weakly relativistic case ( v r c ), the resonance equation can be rewritten as: The resonance equation therefore forms a circle in the [ v ∥ , v ⊥ ] velocity space, whose centre v 0 , located on the v ∥ axis, is given by: which can be rewritten as where θ is the direction of the emission ( k cos θ = k ⋅ b = k ∥ ) and N = ck / ω is the refractive index value (which must be taken into account to reproduce the observations, as shown by Ray Hess 2008 ). The resonance condition can therefore be rewritten as Therefore, the resonance condition does not only define the angular frequency of the amplified wave ω = 2 πf , but also the direction of the emission θ . The resonance equation is under-constrained as there are two variables ( ω and θ ) to determine for a single equation. To solve it, one must consider another constraint brought by the CMI amplification equation, which states that the amplification occurs for positive gradients of the electron perpendicular velocity distribution around the resonant velocities v r ( Wu 1985 ). Given an
Paper: 2018A&A...612A.104F (fulltext)
was derived as the distance between the two radii, where the normalized intensity profile becomes lower than (1 − 0.66 × (1 − Ī min )) ( Rosotti et al. 2016 ), where the outer of these two radii is defined as the CO wall ( R CO ). We defined the gap radius ( R gap ) as the midpoint between these two radii. Finally, the radius of the sub-mm ring ( R mm ) was defined as the radius of maximum intensity in the radial continuum intensity profile outside the gap radius. The distance of this ring from the gap is R mm − R gap . A visualization of these three radial parameters can be found in Fig. 6 . 4.2.1 Distance of the sub-mm ring from the gap radius The distance of the sub-mm ring from the gap radius (normalized to the gap radius itself) as a function of planet mass is presented in Fig. 11 . The plot shows a clear trend in which the distance of the ring increases with planet mass. The plot contains quantities derived for all eight simulations, and where the analyzed images were produced with three different beam sizes, specifically 0.03 ′′ , 0.08 ′′ , and 0.15 ′′ . The plot shows planet radii as derived from 13 CO. The same result holds for planet radii obtained from 12 CO or C 18 O, since for these three CO isotopologs, and for the beam sizes considered here (up to 0.15 ′′ ), the gap radius is always recovered with an accuracy 1.5 AU. The very small scatter of the ring distance for a given planet mass shows that this diagnostic does not depend on the disk viscosity, at least for the range of viscosities and planet masses analyzed here. Moreover, this diagnostic does not require the gap to be radially resolved; the only requirement is that for a given gap width and depth, the angular resolution is high enough to pick the presence of a gap. This is enforced by the rather small scatter with beam sizes. A linear fitting formula in log-log space can easily be retrieved, using all the points shown in Fig. 11 , leading to the simple relation Fig. 11 Distance of the sub-mm ring R mm from the gapradius R gap as a function of planet mass for all the simulations. The gap radius is estimated from the 13 CO J = 3-2 emission, whereas the ring radius is obtained from the maximum in sub-mm (850 μ m) continuum emission outside the gap radius. The ring distance is defined as the ring radius minus the gap radius. Circles, squares, and diamonds indicate quantities retrieved from images convolved with a 0.03 ′′ , 0.08 ′′ , and 0.15 ′′ beam, respectively, for sources located at a distance of 150 pc. The dashed green line shows a linear fit obtained for this relation in log–log space. The blue dashed-dotted line and brown dashed line indicate the fitting formula by Rosotti et al. (2016) obtained from hydro-simulations with 400 and 3000 planet orbits, respectively, where the gap location was inferred from synthetic scattered light maps. where A = −0.324 and B = 0.428. Interestingly, the relation between ring distance and planet mass is also well resembled by the
Paper: 2021A&A...649A..58L (fulltext)
(blue) are different, but the deviations are smaller than the uncertainty, and therefore they are consistent enough to reveal the expansion rate of the ejecta. Fig. 8. Dimensionless expansion rate ( ζ ) vs. heliocentric distance ( D ) for the northern part (−5° λ 5°), middle part (−20° λ −5°), and southern part (−35° λ −20°) of the CME ejecta, respectively, between 18:09 UT and 22:49 UT on 3 April 2010, where λ is the latitude in the HEE coordinates. The red and blue crosses with the horizontal and vertical error bars correspond to STEREO-A/B, while the thick solid black line is the linear fitting of the data points. The dashed line shows the value of ζ equal to 1. For the northern and middle part of the CME, ζ keeps a high value of 0.87 ± 0.11 and 0.81 ± 0.09, respectively, at a distance between 25 R ⊙ and 55 R ⊙ (see Figs. 8 a and b). This suggests that the northern and middle parts of this CME maintained a nearly self-similar expansion but were still slowly pancaked. For the southern part of the CME, ζ is in the range of 0.39 ± 0.09 (see Fig. 8 c), which means a higher degree of flattening than in other parts. This is because the ambient solar wind was much slower than the CME, as shown in Fig. 6 b, which acted as an obstacle and prevented the CME from expanding. A similarly low expansion rate (0.48 ± 0.79) was reported by Gulisano et al. (2010) , but the difference is that the low expansion rate in their work is due to the compression by the faster background solar wind from the back. The question now is why the CME different latitudinal parts show different dimensionless expansion rates, or in broad terms, different dynamics. The CME on 3 April 2010 is not the only one with such diverse properties. Savani et al. (2010) have previously found a similar differentiated radial distortion event on 2007 November 14 in which an initially circular CME was observed to be distorted into an increasingly concave structure in STEREO-HI1 images due to the latitudinally varied solar wind velocity ahead. In many magnetohydrodynamic simulations, the fast and slow solar wind ahead of a fast CME could also lead to a similar highly distorted concave shape of the CME at a heliocentric distance larger than 20 R ⊙ (e.g., Manchester et al. 2004 ; Lugaz et al. 2005 ). Owens et al. (2017) further pointed out that CMEs with constant angular width cease to be coherent magnetohydrodynamic structures within 0.3 AU from the Sun because beyond a certain heliocentric distance, the information spreading speed (i.e., the Alfvén wave speed V A ) in magnetized plasma decreases less than the geometric separation speed of two points on the ejecta leading edge. Owens et al. (2017) suggested that different parts of a CME may be isolated from each other and the CME interacting with the background solar wind may be similar to dust cloud rather than a billiard ball as a whole. In their work, B , the magnetic field intensity within the CME, A , the CME cross-sectional area, and n
Paper: 2018ApJ...864...62G (acknowledgments)
The authors thank the European Research Council (ERC CoG No. 682275) for support of their work. D.G. thanks J.R. and J.J. for the hospitality and the outstanding cooperation.
Paper: 2018ApJ...864..132B (acknowledgments)
Support for this work was provided to R.B. by NASA through Hubble Fellowship grant #51354. The COS-Halos and COS-Dwarfs data sets were collected under program IDs 11598 and 12248, respectively (PI Tumlinson). The fellowship and observing programs were all 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.