adsabs/WIESP2022-NER huggingface dataset:
Paper: 2017ApJ...835..212K (fulltext)
(UCD-C group; see Section 3.1.2 ) include two groups with v r > 400 km s −1 and v r 400 km s −1 . The mean radial velocity of the other UCDs with v r > 400 km s −1 ( = 977 km s −1 ) is lower than those of the dwarfs with v r > 400 km s −1 and the M87 UCDs. The mean radial velocity of the other UCDs with v r 400 km s −1 is −117 km s −1 . Figure 13. (a) Radial velocities of GCs and dwarfs as a function of galactocentric distance from M87. The filled circles, open circles, and crosses represent the IGCs, M87 GCs, and dwarfs in the survey region (Kim et al. 2014 ), respectively. The small and large open circles represent the M87 GCs in Strader et al. ( 2011 ) and in this study, respectively. The dashed horizontal line indicates v r = 400 km s −1 , where a dip in the radial velocity distribution can be seen (see Figure 12 ). (b) Mean radial velocity of GCs and dwarfs in each radial bin as a function of galactocentric distance from M87. The symbols are the same as in (a). We divided the IGCs and dwarfs into two groups according to their radial velocities: v r > 400 km s −1 and v r 400 km s −1 . The vertical error bars indicate the root mean square velocities of the objects in each bin. Figure 14. (a) Radial velocities of UCDs and dwarf galaxies as a function of galactocentric distance from M87. The open squares, filled squares, and crosses represent the UCDs in the M87 region, the UCDs not in the M87 region, and the dwarfs in the survey region, respectively. The small and large open squares represent the UCDs in Zhang et al. ( 2015 ) and in this study, respectively. (b) Mean radial velocity of UCDs and dwarfs in each radial bin as a function of galactocentric distance from M87. The symbols are the same as in (a). We divided the dwarfs into two groups according to their radial velocities: v r > 400 km s −1 and v r 400 km s −1 . The vertical error bars indicate the root mean square velocities of the objects in each bin. Figure 15 shows the radial velocity dispersion profiles of the GCs and UCDs. The radial velocity dispersion of the GCs, UCDs, and dwarfs in each radial bin as well as its error is calculated following the formula in Pryor Meylan ( 1993 ). We use the IGCs, UCDs, and dwarfs with v r > 400 km s −1 that are not probably affected by infalling populations to derive the velocity dispersion for each tracer. The radial velocity dispersion of the combined M87 GCs is almost constant at 333 km s −1 . The radial velocity dispersion of the IGCs is similar to that of the GCs in M87 ( σ = 314 km s −1 ). Both are much lower than the radial velocity dispersion of dwarfs in the same survey region ( σ = 608 km s −1 ) and that of ICPNe superposed on the M87 region ( σ = 881 km s −1 ; Longobardi et al. 2015 ). Strader et al. ( 2011 ) suggested that the stellar halo of M87 is not truncated at R GC ∼ 30′, which is different from the result from the planetary nebulae (PNe) of M87 (Doherty et al. 2009 ). Our results are consistent with Strader et al. ( 2011 );
Paper: 2018MNRAS.475..508M (fulltext)
IRTF spectral library and the present spectrum of V1534 Sco, and to the Fitzpatrick ( 1999 ) reddening law. Figure 2. Upper panel: expanded view from Fig. 1 around the far-red Ca ii triplet and head of the Paschen series. Lower panel: a plot of the residuals after subtracting the M6III spectrum from that of V1534 Sco. The strongest emission lines are identified. 3.2 The emission-line spectrum There are several emission lines visible in the IRTF spectrum of V1534 Sco, as illustrated in the zoomed views of Figs 2 – 4 . Fig. 2 focuses on the 0.84−0.94 μm region. The O i 0.8446 μm emission line is already evident in the direct spectrum of V1534 Sco of the top panel. Other lines like the Ca ii triplet and hydrogen Paschen series become more clearly visible once the template M6III spectrum is subtracted from that of V1534 Sco, as illustrated in the bottom panel of Fig. 2 . We have explored the large number of ∼200 spectra of symbiotic stars surveyed in the spectral atlas of Munari and Zwitter ( 2002 ), and found that Hen 3-1410 provides the closest match with V1534 Sco. Their observed spectra are compared in Fig. 3 . The strength of O i 0.8446 μm and the simultaneous absence of O i 0.7772 μm are direct evidence that a strong Lyman-β fluorescence (Bowen 1947 ) is at work in Hen 3-1410. This could also be the case for V1534 Sco, but the low signal-to-noise ratio (S/N) at the blue end of its spectrum does not allow us to judge about the presence and intensity of O i 0.7772 μm. Figure 3. Comparing the blue end of the IRTF spectrum with that of the M6III symbiotic star Hen 3-1410 taken from the spectral atlas of symbiotic stars by Munari Zwitter ( 2002 ). The spectral region explored in more detail in Fig. 4 is that of He i 1.0830, Paschen-γ 1.0938, and O i 1.1287 μm which are clearly present in emission in the spectrum of V1534 Sco. They well match what is normally seen in symbiotic binaries, as proved by the comparison with T CrB in the bottom panel of Fig. 4 (this IRTF spectrum of T CrB – itself a NwSS – was taken on the same night and with the same instrumental set-up of V1534 Sco.). The only significant difference between T CrB and V1534 Sco is the deep P-Cyg absorption that the latter displays for He i 1.0830 μm. It is not an observational artefact and there is no photospheric line at this position that could mimic such a P-Cyg profile, as proved by the over-plotted spectrum for the M6III template. P-Cyg profiles are sometimes observed for He i lines in symbiotic stars (e.g. Smith 1981 ), their presence and intensity being usually a function of orbital phase (e.g. Munari 1993 ). Figure 4. Similar to Fig. 2 , the upper panel shows an expanded view from Fig. 1 , this time around the He i 1.0830 μm line, while the central panel presents the result of the subtraction of the M6III spectrum from that of V1534 Sco. Note the presence of a deep P-Cyg absorption component for the strong He i line. For comparison a spectrum of T CrB, an M3III symbiotic star
Paper: 2018ApJ...861..126R (acknowledgments)
We are grateful to the entire Gaia collaboration for providing data and assistance which made this project possible. We congratulate them on their tremendous achievement to date. Support for this work was provided by the National Aeronautics and Space Administration (NASA) through programs GO-12879, 13334, 13335, 13344, 13571, 13678, 13686, 13928, 13929, 14062, 14394, 14648, 14868 from the Space Telescope Science Institute (STScI), which is operated by AURA, Inc., under NASA contract NAS 5-26555. B.B. and M.G.L. are indebted to the Italian Space Agency (ASI) for their continuing support through contract 2014-025-R.1.2015 to INAF, and to R. Morbidelli (INAF) and R. Messineo (ALTEC S.p.A, Torino) of the Italian Data Processing Center (DPCT) for their help with the Gaia data. A.V.F.’s group at UC Berkeley is also grateful for financial assistance from the TABASGO Foundation, the Christopher R. Redlich Fund, and the Miller Institute for Basic Research in Science (UC Berkeley). S.C. and A.G.R. 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 NAS 5-26555. This publication makes use of data products from the Wide-field Infrared Survey Explorer (WISE) , which is a joint project of the University of California (Los Angeles) and the Jet Propulsion Laboratory/California Institute of Technology, funded by NASA. It has also made use of the SIMBAD database, operated at CDS, Strasbourg, France. Research at Lick Observatory is partially supported by a generous gift from Google. The HST data used in this paper are available at the MAST archive doi: 10.17909/T9G40B .
Paper: 2015MNRAS.449.3543W (acknowledgments)
We wish to thank Sourav Chatterjee for carefully reading the manuscript and providing useful comments that helped to improve this paper. We wish to thank Rainer Spurzem and Sverre Aarseth for their advice regarding the adjustment of the nbody6 software package for our study. LW and XCZ were supported by the Department of Astronomy at Peking University and the Kavli Institute for Astronomy and Astrophysics. MBNK was supported by the Peter and Patricia Gruber Foundation through the PPGF fellowship, by the Peking University One Hundred Talent Fund (985), and by the National Natural Science Foundation of China (grants 11010237, 11050110414, 11173004). This publication was made possible through the support of a grant from the John Templeton Foundation and National Astronomical Observatories of Chinese Academy of Sciences. The opinions expressed in this publication are those of the author(s) do not necessarily reflect the views of the John Templeton Foundation or National Astronomical Observatories of Chinese Academy of Sciences. The funds from John Templeton Foundation were awarded in a grant to The University of Chicago which also managed the programme in conjunction with National Astronomical Observatories, Chinese Academy of Sciences. RPC was supported by the Swedish Research Council (grants 2012-2254 and 2012-5807). MBD was supported by the Swedish Research Council (grants 2008-4089 and 2011-3991).
Paper: 2016A&A...586A..38M (fulltext)
BH (), but in this case the BH shadow at millimeter wavelengths is also illuminated by the counter-jet, which is geometrically more extended compared to our GRMHD numerical models. Broderick Loeb (2009) did not restrict the orientation of appropriate baselines to E-W direction in their analysis because their counter-jet emission is more uniform and extended compared to ours. At 7 mm, the size of the jet emission in their model is sensitive to the jet collimation parameter, . It is quite possible that our model will also be sensitive to the exact value of the BH spin or the disk size that may control the jet collimation. We leave this issue for a future study. 4.6. Matter content of the jet funnel Unlike those by Broderick Loeb (2009) and Dexter et al. (2012) , our model does not make any assumption about the jet matter content. At the jet wall (sheath), the plasma is baryonic, and it is constantly supplied from the accretion disk. Inside of the jet funnel, electron-positron pairs are produced in collisions. We calculate the pair production rate directly from the RT model following Mościbrodzka et al. (2011) . In model RH100, the pair production rate near the SMBH horizon is (based on Eq. (26) in Mościbrodzka et al. 2011 , assuming that the luminosity of the source around the electron rest-mass energies is ). This gives an estimate for the pair plasma density near the event horizon . Using Eq. 45 in Mościbrodzka et al. (2011) , we can calculate the Goldreich–Julian density , i.e. the pair density required to enforce the ideal MHD condition () in the rest frame of the plasma ( Goldreich Julian 1969 ). We find that in model RH100; i.e., the pairs cannot be produced in cascades and multiply themselves. In summary, the pair density in the jet funnel (spine) remains low. 4.7. Emission from the jet sheath in radio Finally, we briefly discuss the effect of the jet vertical stratification (jet spine and sheath) on the observational properties of jets in general. A recent work by Boccardi et al. (2015) reports the detection of the edge-brightened jet in Cyg A. The jet in Cyg A jet is not resolved by radio observations as well as is the M 87 jet. Therefore we should keep in mind that their scales are different and their inclination angles are also probably different. The authors report that the counter-jet is narrower than the approaching jet. To clarify what our models predict we plot our 43 GHz images of the M 87 jet at various inclination angles in Fig. 11 . Here we do not notice any evident difference in the opening angle of the jet and counter-jet owing to the geometrical effects of light propagation. However, we find that the jet edge-brightening depends on inclination, and it becomes more notable for . In the images presented in Sect. 3 , the signal-to-noise ratio is greatly improved thanks to the time-averaging of many frames. However, we notice that single images of the jet at longer wavelengths exhibit some numerical artifacts. These are most
Paper: 2020MNRAS.497.3896A (fulltext)
LMXBs. The disc temperature of GX 339–4 ranged from ∼0.6 to ∼0.9 keV (Plant et al. 2014 ) and the temperature of Cyg X–1 ranged between 0.5 and 0.6 keV (Shaposhnikov Titarchuk 2006 ). The temperature of 4U 1636–53 ranged from ∼0.3 to ∼0.8 keV in the best-fitting results (Zhang et al. 2017 ) and the disc temperature of MXB 1658–298 ranged from ∼0.6 to ∼0.9 keV (Sharma et al. 2018 ). The disc temperature of MAXI J1727–203 was lower than these four systems. A potential explanation for a lower temperature in MAXI J1727–203 than in other sources could be related to the mass of the compact object. Assuming that the accretion disc is at the innermost stable circular orbit (ISCO), the temperature at the inner disc radius is proportional to , where is the mass accretion rate and M is the mass of the compact object (Frank, King Raine 2002 ). According to Muñoz-Darias, Casares Martínez-Pais ( 2008 ), M 6 M ⊙ for GX 339–4. We take the temperature of GX 339–4 in the soft state (0.79 keV) from Plant et al. ( 2014 ) and we also take the disc temperature of the softest observation in the HID of MAXI J1727–203 (0.45 keV). From that, if we assume that is the same for two sources in the same spectral state, we estimate a lower limit for the mass of MAXI J1727–203 of ∼19 M ⊙ . Therefore, the high mass of the compact object can explain the low temperature of the inner disc. Alternatively, as suggested by Gou et al. ( 2011 ), the low temperature at the inner disc radius can be a consequence of a low inclination of the accretion disc with respect to the line of sight. We can repeat this analysis to estimate the mass of MAXI J1727–203 with the NS Aql X–1. For this, we took the temperature of Aql X–1 in the soft state of its 2007 outburst (∼0.66 keV, Raichur, Misra Dewangan 2011 ). Considering a mass of ∼1.4 M ⊙ for the NS in Aql X–1, we obtained a mass of ∼2 M ⊙ for the compact object in MAXI J1727–203. If we consider a higher mass for Aql X–1, the mass of MAXI J1727–203 also increases. Considering the latter, this mass estimates suggest that the compact object in MAXI J1727–203 is massive NS or a low-mass BH. Based on all the above comparisons, although we cannot unambiguously identify the nature of the compact object in MAXI J1727–203, the evolution in the HID, RID, and RHD, and the temperature at the inner radius of the accretion disc during the softest observations suggest that it is a BH. 4.2 Anticorrelation between the fractional rms amplitude and the flux of the disc component Fig. 9 shows that the relation between the fractional rms amplitude and the disc flux is continuous and that both quantities are anticorrelated during phases A and C (orange diamonds and black circles) of the outburst. While in phases B and D (blue triangles and red crosses), the rms amplitude is consistent with being independent of the disc flux, those measurements extend the relation seen in phases A and C to low (phase D) and high (phase B) values of the disc flux. The simplest
Paper: 2018MNRAS.478.3756C (acknowledgments)
ACKNOWLEDGEMENTS We thank A. Babul, S. Clesse, J. Garcia-Bellido, S. Khochfar, I. Musco, T. Nakama, and M. Volonteri for useful discussions. We are also grateful to Y. Sendouda for help in drawing one of the figures. BC thanks Institut d’Astrophysique in Paris for hospitality received during this work. JS acknowledges the support of the European Research Council via grant 267117.
Paper: 2016MNRAS.459.3505P (acknowledgments)
TGS would like to acknowledge the Department of Science and Technology (DST), Government of India for providing financial support through the project SR/FTP/PS-172/2012.
Paper: 2016ApJ...817...60T (fulltext)
( 2013 , 2014 ), and further details on the strong lensing modeling of MACSJ1149.5+2223 are provided in a dedicated paper (Grillo et al. 2015a ). 4.2.1. Definition of the Mass Model Different mass models have been explored for this galaxy cluster, but only the best-fitting one is discussed here. The projected dimensionless total surface mass density of 300 cluster members within the WFC3 field of view of the CLASH observations is modeled as a dual pseudoisothermal elliptical mass distribution (dPIE; Elíasdóttir et al. 2007 ) with vanishing ellipticity and core radius. The zero-core dPIE profile corresponds to the three-dimensional mass density profile:The galaxy luminosity values in the F160W band are used to assign the relative weights to their total mass profile. The galaxy total M / L ratio is scaled with luminosity as , thus mimicking the so-called “tilt” of the Fundamental Plane. The values of axis ratio, PA, effective velocity dispersion, and truncation radius of the two cluster members closest in projection to the central and southern images of the SN Refsdal host are left free. To complete the total mass distribution of the galaxy cluster, three additional mass components are added to describe the cluster dark matter halo on physical scales larger than those typical of the individual cluster members. These cluster halo components are parametrized as two-dimensional pseudo-isothermal elliptical mass profiles (PIEMD as defined by Kassiola Kovner 1993 ; see also Grillo et al. 2015a ). No external shear or higher-order perturbations are included in the model. The number of free parameters associated with the model of the cluster total mass distribution is 28. 4.2.2. Definition of the Inputs The positions of the multiple images belonging to the 10 systems of the gold sample and to 18 knots of the SN Refsdal host are the observables over which the values of the model parameters are optimized. The adopted positional uncertainty of each image is 0065. The redshift values of the 7 spectroscopically confirmed gold systems are fixed, while the remaining 3 systems are included with a uniform prior on the value of , where D ds and D s are the deflector-source and observer-source angular diameter distances, respectively. In total, 88 observed image positions are used to reconstruct the cluster total mass distribution. 4.2.3. Description of the Inference Process and Error Estimation The best-fitting, minimum- model is obtained by minimizing the distance between the observed and model-predicted positions of the multiple images in the lens plane. A minimum value of 1441, corresponding to an rms offset between the image observed and reconstructed positions of 026, is found. To sample the posterior probability distribution function of the model parameters, the image positional uncertainty is increased until the value of the is comparable to the number of the degrees of freedom (89), and standard Markov chain Monte Carlo (MCMC) methods are used. The
Paper: 2019MNRAS.490.2050K (fulltext)
). Thus, a subsurface strengthened layer has to be very large and thick to avoid lifting by gas released beneath it. If we consider a disc of strengthened material with a 50-m radius and a 10-m thickness, then for a density of 531 kg m −3 and g = 2 × 10 −4 m s −2 , the gravity force exerted on the material underneath (e.g. gas cavity, pristine material) is F grav ∼ 8340 N. If the pressure is enhanced under a small fraction of the disc (i.e. 1 per cent), then the condition F gas > F grav can be met when p ∼ 0.1 kPa. When the edges of the strengthened layer are under elevated surrounding terrain, then the critical gas pressure is higher. In any case, the tensile strength of the strengthened material is important. 3.2 Tensile strength Fig. 3 plots the profiles of σ T versus depth, calculated when the initial tensile strength σ T0 = 1 kPa. The curves are drawn for selected locations for the times when the gas pressure in given locations satisfies conditions: p 0.1 kPa (upper panel), p > p crit,1 = 1 kPa (middle panel) and p > p crit,2 = 10 kPa (lower panel). Profiles shown in the middle panel are taken 113 h (nine rotation periods) after the profiles presented in the upper panel. During this period, the thickness of the strengthened layer increased by at least 0.5 m. In one location, a secondary strengthened layer formed above the crystallization front of the amorphous water ice. The thickness of the main strengthened layer is ∼1 m when the gas pressure approaches 0.1 kPa, 0.8–1.8 m when p > p crit,1 and 0.8–3.3 m when p > p crit,2 . A strengthened layer about 1 m thick will probably be broken or lifted. Thus, in locations marked with white triangles, the presence of uncovered ice-rich material should be expected. Increased emission of more volatile components (such as carbon monoxide) is also likely. Figure 3. Tensile strength versus depth, when the CO pressure p beneath the strengthened layer is p 0.1 kPa (upper panel), p > p crit,1 = 1 kPa (middle panel) and p > p crit,2 = 10 kPa (lower panel). The initial tensile strength is 1 kPa. The remaining parameters of the model parameters are given in the legends. It is interesting that when σ T0 = 1 kPa the ejection of material is possible in all considered locations, while the uncovered ice was found only in the pit. This difference can be explained by the non-uniform concentration of highly volatile CO, but other options should also be considered, such as the non-uniform granulation or porosity of the material. Fig. 4 is similar to the upper and lower panels of Fig. 3 . The profiles shown in Fig. 4 are calculated for σ T0 = 0.1 kPa instead of σ T0 = 1 kPa. It can be seen that the strengthening of the loosely bonded mixture of grains is slower than with moderate initial strength. The thickness of the strengthened layer at the moment when the CO gas pressure reaches the threshold value p crit,1 is ∼1 m for σ T0 = 0.1 kPa and 1.1–1.9 m for σ T0 = 1 kPa. The next threshold p crit,2 is exceeded when the
Paper: 2018ApJ...861...82W (acknowledgments)
We would like to thank Jo Dunkley from Princeton University, Johannes Hubmayr from NIST, and Jeff McMahon from the University of Michigan for useful comments and discussions. David Alonso acknowledges support from the Science and Technology Facilities Council (STFC) and the Beecroft Trust and Jonathan Ward acknowledges support from the NASA Space Technology Research Fellowship Program.