adsabs/WIESP2022-NER huggingface dataset:
Paper: 2019A&A...622A..80C (acknowledgments)
Acknowledgements This work has been carried out within the frame of the National Centre for Competence in Research “PlanetS” supported by the Swiss National Science Foundation (SNSF). A.M. acknowledges the support of the DFG priority program SPP 1992 “Exploring the Diversity of Extrasolar Planets” (MU 4172/1-1). J.O. and N.G. acknowledge financial support from the ICM (Iniciativa Científica Milenio) via the Núcleo Milenio de Formación Planetaria grant. J.O. acknowledges financial support from the Universidad de Valparaíso, and from Fondecyt (grant 1180395). A.Z. acknowledges support from the CONICYT + PAI/ Convocatoria nacional subvención a la instalación en la academia, convocatoria 2017 + Folio PAI77170087. N.G. acknowledges support from project CONICYT-PFCHA/Doctorado Nacional/2017 folio 21170650. SPHERE is an instrument designed and built by a consortium consisting of IPAG (Grenoble, France), MPIA (Heidelberg, Germany), LAM (Marseille, France), LESIA (Paris, France), Laboratoire Lagrange (Nice, France), INAF – Osservatorio di Padova (Italy), Observatoire Astronomique de l’Université de Genève (Switzerland), ETH Zurich (Switzerland), NOVA (Netherlands), ONERA (France), and ASTRON (Netherlands) in collaboration with ESO. SPHERE was funded by ESO, with additional contributions from CNRS (France), MPIA (Germany), INAF (Italy), FINES (Switzerland), and NOVA (Netherlands). SPHERE also received funding from the European Commission Sixth and Seventh Framework Programmes as part of the Optical Infrared Coordination Network for Astronomy (OPTICON) under grant number RII3-Ct-2004-001566 for FP6 (2004-2008), grant number 226604 for FP7 (2009-2012), and grant number 312430 for FP7 (2013-2016). This work has made use of the SPHERE Data Centre, jointly operated by OSUG/IPAG (Grenoble), PYTHEAS/LAM/CeSAM (Marseille), OCA/Lagrange (Nice), and Observatoire de Paris/LESIA (Paris) and supported by a grant from Labex OSUG@2020 (Investissements d’avenir - ANR10 LABX56). This publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation. This research has benefitted from the SpeX Prism Spectral Libraries, maintained by Adam Burgasser at http://pono.ucsd.edu/~adam/browndwarfs/spexprism . This work has made use of data from the European Space Agency (ESA) mission Gaia ( https://www.cosmos.esa.int/gaia ), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://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.
Paper: 2016MNRAS.455L..21G (fulltext)
the same is not necessarily true for the standoff radius. In Fig. 3 we plot the standoff radius versus orbital radius. The standoff radius near the pericentre may not be resolvable, although at larger distances from Sgr A* the likelihood for resolving the source increases. It is also worth noting that we calculated the thermal free–free emission around Sgr A* and concluded that it is not detectable. Figure 3. Left: the standoff radius for S2 ( R o ) versus the orbital radius ( R ⋆ in units of 10 −3 pc). We see that the value is always less than unity, as expected. Right: angular diameter of the standoff radius (θ o ) versus the angular diameter of the orbital radius (θ ⋆ ). Around pericentre it may be difficult to resolve the finite size of the standoff radius. However, S2 should still be detectable via synchrotron emission. 4 CONCLUSIONS AND FUTURE OBSERVATIONS The innermost stars orbiting Sgr A* (such as the S-stars) produce a bow shock. Although this shock will likely not be detectable via thermal emission, we have shown that stars such as S2 may be detectable via synchrotron emission. Fig. 1 shows that the contrast of synchrotron flux relative to Sgr A* is maximized around the 1.4 GHz band. However, due to scattering we will need to use a higher frequency, around 10 GHz, if we are to resolve our star. If a star such as S2 emits strong synchrotron emission, the combined signal from the star and Sgr A* may exceed the quiescent radio emission from the black hole. As was the case with G2 (see next paragraph) it is not clear that any additional synchrotron emission will be observable. Arguably, it is best to resolve the synchrotron emission from any star orbiting Sgr A*, such as S2. At apoapse S2 is ∼0.23 arcsec from Sgr A* while at periapse it is only ∼0.015 arcsec away. Thus, to detect a star such as S2 requires both good sensitivity and resolution. VLBI can provide submilliarcsec observations of Sgr A* (e.g. Lu et al. 2011 ) and thus the required precision. S2 is an ideal test case since the star will reach periapse in 2017 or early 2018. Recently, gas cloud G2 was observed orbiting Sgr A*, and was approximately 3100 Schwarzschild radii from the black hole at pericentre. It was predicted that the bow shock from this encounter would displace the quiescent radio emission of Sgr A* by ∼33 mas (Narayan, Özel Sironi 2012 ; Sadowski et al. 2013 ). However, observations across the spectrum showed no apparent variability during the periastron passage of G2 (Bower et al. 2015 ; Valencia-S et al. 2015 ). It is unclear why a bow shock was not detected. One possibility is that at the centre of G2 is low-mass star with wind velocity ∼100 km s −1 (Crumley Kumar 2013 ; Scoville Burkert 2013 ). Synchrotron emission from such a small v w would be extremely difficult to detect. Star S2 is massive, and thus the winds are likely an order of magnitude larger. If synchrotron emission is not detected for S2 it may be that our value for ε nt is too large. It
Paper: 2017ApJ...847...29O (acknowledgments)
The authors are grateful to the referee for comments which improved the manuscript. We thank Nikhil Mahajan for performing some of the early explorations. We are grateful to B.J. Fulton for permission to reproduce his figure and useful discussions. We acknowledge Tim Morton, Lauren Weiss, and Josh Winn for helpful insights. J.E.O. acknowledges support by NASA through Hubble Fellowship grant HST -HF2-51346.001-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. Y.W. acknowledges support from NSERC.
Paper: 2021MNRAS.501.1520C (fulltext)
reduced χ 2 values determined from GRB data alone are around unity for all models (being between 1.03 and 1.06), while those values determined from the H ( z ) + BAO data combination range from 0.48 to 0.53, with the lower reduced χ 2 here being due to the H ( z ) data (that probably have overestimated error bars). As discussed in Ryan et al. ( 2019 ) and Cao et al. ( 2020 ), the cases that involve H ii G and QSO-AS data have a larger reduced χ 2 (between 2.11 and 3.02), which is probably due to underestimated systematic uncertainties in both cases. Based on the AIC and the BIC (see Table 1 ), the flat ΛCDM model remains the most favoured model, across all data combinations, among the six models we study. 14 From ΔAIC and ΔBIC, we find mostly weak or positive evidence against the models we considered, and only in a few cases do we find strong evidence against them. According to ΔBIC, the evidence against non-flat XCDM is strong for the H ii G, QSO-AS, and GRB only cases, and very strong for the HQASG and HzBHQASG cases. Similarly, the evidence against flat φCDM is strong for the HQASG and HzBHQASG cases, and the evidence against non-flat φCDM is strong for the H ii G, QSO-AS, and GRB only cases, and very strong for the HQASG and HzBHQASG cases. Among these six models, a comparison of the ΔBIC values from Table 1 shows that the most disfavoured model is non-flat φCDM, and that the second most disfavoured model is non-flat XCDM. This is especially true when these models are fitted to the HQASG and HzBHQASG data combinations, in which cases non-flat φCDM and non-flat XCDM are very strongly disfavoured. These models are not as strongly disfavoured by the AIC, however; from a comparison of the ΔAIC values in Table 1 , we see that the evidence against the most disfavoured model (non-flat φCDM) is only positive. 6 CONCLUSION We find that cosmological constraints determined from higher z GRB, H ii G, and QSO-AS data are mutually consistent. It is both reassuring and noteworthy that these higher z data jointly favour currently accelerating cosmological expansion, and that their constraints are consistent with the constraints imposed by more widely used and more restrictive H ( z ) and BAO data. Using a data set consisting of 31 H ( z ), 11 BAO, 120 QSO-AS, 153 H ii G, and 119 GRB measurements, we jointly constrain the parameters of the GRB Amati relation and of six cosmological models. The GRB measurements are of special interest because they reach to z ∼ 8.2 (far beyond the highest z ∼ 2.3 reached by BAO data) and into a much less studied area of redshift space. Current GRB data do not provide very restrictive constraints on cosmological model parameters, but in the near future we expect there to be more GRB observations (Shirokov et al. 2020 ) that should improve the GRB data and provide more restrictive cosmological constraints. Some of our conclusions do not differ significantly between models and so are model independent. In particular, for the
Paper: 2020MNRAS.491..580T (acknowledgments)
ACKNOWLEDGEMENTS DT acknowledges support of a studentship funded by the Perren Fund of the University of London. This research was supported by the UK Science and Technology Facilities Council (STFC) grant ST/P000622/1. This research utilized Queen Mary’s Apocrita HPC facility, supported by QMUL Research-IT, http://doi.org/10.5281/zenodo.438045 .
Paper: 2017MNRAS.469.3881S (fulltext)
we adopt the relation M star = M core /2, to ensure that the total mass of stars in our Class 0 binaries does not exceed that of their host cores. We may then rewrite equation ( 5 ) as After dividing equation ( 6 ) by equation ( 3 ), we find The numerical value for this ratio is actually an upper bound. First, Class 0 stars may have masses that are less than M core /2. Second, we have ignored the fact that the density distribution in the core is centrally peaked (see e.g. Jørgensen et al. 2007 ). Both corrections act to lower the ratio, but not by a lot. For example, if M star / M core is correct, but the interior density is 10 times the mean (an extreme assumption), then r star / r 0 falls to just 0.23. The lesson, in any case, is that the widest Class 0 binaries, which are presumably the youngest, are bound to their host core and not to each other. Nevertheless, the net force pulling on each star is inwards 4 towards the companion star, causing the two stars to drift together even as they are gathering mass from the core. The stars initially share the rotational motion of the core, but their transverse speed subsequently increases by conservation of angular momentum. Once their separation falls below the critical value, the stars attract each other and enter a true binary orbit. Inward drift continues and accelerates as angular momentum is transferred to the background gas via dynamical friction. Stahler ( 2010 ) has provided an analytic treatment for this orbital decay. Simulations of orbital shrinking indicate the process primarily occurs at early times. Offner et al. ( 2016 ) explored binary formation and evolution in magnetohydrodynamical simulations, and found that binaries with separations of few 10 3 au could shrink to separations of 100 au in only 0.1 Myr. Similarly, Bate, Bonnell Bromm ( 2002 ) found that wide binaries could produce very close binaries through accretion processes or via dynamical interactions while the stars are embedded in a gas-rich core. The optimal w_sb model gives a shrinking time-scale of t s / t 0 = 1.39, which becomes t s ≈ 0.28 Myr for t 0 = 0.2 Myr. (Note that the ejection models explored in Appendix A yield a similar shrinking rate for the optimal w_sb* model.) This shrinking rate is about three times longer than what was obtained by Offner et al. ( 2016 ) for a 4 M ⊙ core. Most of the cores in Perseus have masses of ∼1 M ⊙ (Sadavoy et al. 2010 ), so an average t s ≈ 0.3 Myr may still be in rough agreement with the simulations. Both the w_sb and w_sb* models predict that binary shrinking occurs primarily during the embedded phase, as is also found by simulations. Thus, our simple evolutionary models broadly agree with the theoretical studies currently available. Finally, our observations show that relatively tight binaries have random orientations with respect to their host cores, a situation that does not hold for the predominantly aligned wide binaries (recall Fig. 5 ). Thus, the processes
Paper: 2017MNRAS.471.4256V (acknowledgments)
Acknowledgements We thank Thomas Tauris for his very useful comments. This work was supported in part by the National Science Foundation under Grant No. NSF PHY11-25915. This research has partially been funded by the Interuniversity Attraction Poles Programme initiated by the Belgian Science Policy Office (IAP P7/08 CHARM). It further was supported by the Netherlands Research Council NWO (NWO grant \#621.016.701 for LGM-II) and by the Netherlands Research School for Astronomy (NOVA). SdM acknowledges support by a Marie Sklodowska-Curie Action (H2020 MSCA-IF-2014, project id 661502). Part of the numerical computations were carried out on the Little Green Machine at Leiden University (612.071.305 and 621.016.701).
Paper: 2020A&A...633A.165H (acknowledgments)
We are grateful to Dietrich Baade, Danny Lennon and Christophe Martayan for discussions and for pointing out the recent TESS result to us. We also thank our anonymous referee for useful comments on an earlier version of this manuscript.
Paper: 2021A&A...649A..61B (fulltext)
1.6%, subdominant in regard to time-delay measurements, the angular lens model component, and the line-of-sight convergence of the TDCOSMO sample of seven lenses. Similar considerations apply to the future scenarios illustrated in Figs. 3 and 4 , except for the precision that reaches 1.2–1.5% by virtue of the larger samples. A significant component of the error budget at the 1% level arises from the uncertainty in the relative expansion history of the Universe (in our case the prior on Ω m ). It is encouraging that, thanks to the external datasets, we can reach a similar precision to that forecasted by Shajib et al. (2018) . These latter authors broke the MST by assuming the mass profile is a power law. We break it with spatially resolved kinematics and external datasets. Fig. 3. Forecast precision on H 0 , the MST parameter λ , and the anisotropy parameter a ani for different spectroscopic scenarios of a future sample of 40 TDCOSMO lenses (future scenario) as specified in Table 1 in the row of TDCOSMO-5% ( https://github.com/sibirrer/TDCOSMO_forecast/blob/master/forecast.ipynb ). Fig. 4. Forecast precision on H 0 , the MST parameter λ , and the anisotropy parameter a ani for different spectroscopic scenarios of a future sample of 40 TDCOSMO lenses (future scenario) observed with aperture spectroscopy of 5% precision and additional external data sets specified in Table 1 in the row of TDCOSMO-5% ( https://github.com/sibirrer/TDCOSMO_forecast/blob/master/forecast.ipynb ). 5. Conclusions We describe two strategies to measure H 0 with 2.5–3.5% precision with gravitational time delays while accounting for the uncertainty introduced by the mass-sheet transformation. The first is based on current samples of 7 time-delay lenses and existing technology and the second is based on adding 50 nontime-delay lenses. The same strategies, applied to a future sample of 40 time-delay and 200 nontime-delay lenses can achieve 1.2–1.5% precision. The keys to achieving this precision are spatially resolved kinematics and the inclusion of datasets of nontime-delay lenses in a hierarchical framework. These two strategies are not mutually exclusive and both should be pursued. The TDCOSMO-only approach has the advantage of not relying on the assumption that the time-delay and nontime-delay galaxies are drawn from the same parent population. With this additional assumption, the TDCOSMO+external approach allows for further improvement in precision. The precision of each approach is sufficient to test the mutual consistency among different samples while simultaneously fitting for H 0 . If verified, potentially with the extension of the hierarchical framework, the consistency will enable the cosmological exploitation of larger samples of nontime-delay lenses that are expected to be discovered by future surveys ( Oguri Marshall 2010 ). Following our proposed strategies, time-delay cosmography will, in the near future, have sufficient precision to distinguish the current
Paper: 2019A&A...629A..35C (acknowledgments)
We thank the European Research Council for funding support under Synergy Grant ERC-2013-SyG, G.A. 610256 (NANOCOSMOS). CB would like to thank the Ministerio de Ciencia, Innovación y Universidades for a Juan de la Cierva postdoctoral fellowship (FJCI-2016-27983). IT, VJH, and JLD acknowledge additional partial support from the Spanish State Research Agency (AEI) through grant FIS2016-77726-C3-1-P. We would also like to thank Rosa Lebrón, Jesús Quintanilla, and Cristina Soria for providing us with the sample of succinonitrile and Prof. Yasuki Endo for logistic support with the quantum chemical calculations. This work was also based on observations carried out with the IRAM 30-meter telescope. IRAM is supported by INSU/CNRS (France), MPG (Germany), and IGN (Spain).
Paper: 2020MNRAS.tmp..241S (acknowledgments)
ACKNOWLEDGEMENTS We thank the anonymous reviewer for the careful reading of our manuscript. The work was supported by the RFBR grant 18-32-00194. Funding for the SDSS has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, the US Department of Energy, the National Aeronautics and Space Administration, the Japanese Monbukagakusho, the Max Planck Society, and the Higher Education Funding Council for England. The SDSS website is http://www.sdss.org/ . This research makes 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, and the LEDA data base ( http://leda.univ-lyon1.fr ). This research made use of Astropy, 10 a community-developed core python package for Astronomy (Astropy Collaboration 2013 ; Price-Whelan et al. 2018 ).
Paper: 2018ApJ...855...43M (fulltext)
stripped from the progenitor within the last ∼5 Gyr (i.e., are part of the most recent leading debris tail). The model predicts that only the northeastern corner of the HiTS footprint should contain any Sgr debris. The mean distance of these model debris points is , with a spread of σ d ∼ 6 kpc. There are nine HiTS RRLs between 31 d H 49 kpc, of which four are in the region occupied by Sgr model debris (i.e., 170° 7R.A. 175°, −3° decl. 3°). Interestingly, these four stars are tightly clumped in distance, with a mean of and standard deviation of σ d ∼ 0.7 kpc. Nonetheless, given that these four stars are ∼165–20° from the center of the Sgr stream (using the Sgr-aligned coordinate system of Majewski et al. 2003 ), we consider their association with Sgr tentative at best. In conclusion, while there are likely stars from previously identified substructures in our sample of HiTS RRLs, it is unlikely that they have significantly biased our density profile fits, as each of the substructures would contribute only a small number of stars in our field of view. 7. Discussion and Summary We present the detection of 173 RRLs using observations from the 2014 campaign of the HiTS survey. The data cover ∼120 square degrees of the sky and include from 20 to 37 epochs in the g -band. The photometric depth of the HiTS data enables us to build a catalog that includes a significant number of stars that do not appear in previous public surveys overlapping the same sky region (such as the CRTS). Most of the additional RRLs we contribute have , corresponding to d H ≳ 60 kpc. The surveyed region overlaps with the position of currently known satellite galaxies of the Milky Way. We detect 65 RRLs members of the Sextans dSph, 46 of them being new discoveries. This number includes seven stars that were not classified as RRLs by other works, but were already considered as members of the dwarf. Two additional dwarf galaxies, Leo IV and Leo V, were found within our RRLs catalog. A more detailed analysis of the RRLs in Leo V has been presented in a companion paper (Medina et al. 2017 ). Regarding distant RRLs in our sample, we find 18 candidates with d H > 90 kpc, 11 of which are classified as ab -type, while seven are c -type. To understand the connection of this subsample with previously known/unknown systems, the period-amplitudes of the individual stars could play a major role. RRLs that are members of globular clusters are separated in the distincted Oosterhoff groups (Oo I and Oo II; Oosterhoff 1939 ). On the other hand, RRLs in ultra-faint dwarf galaxies are mostly Oo II (Clementini 2014 ), while the halo general population (within a radius of ∼80 kpc) presents stars in both locus, but the majority of them follow the locus of the Oo I group. This has been shown multiple times in the literature (e.g., Zinn et al. 2014 ; Catelan Smith 2015 ), and it is also clearly seen in Figure 4 . The distant sample of RRLs, however, does not follow the main trend of nearby field
Paper: 2019MNRAS.489.4589A (acknowledgments)
ACKNOWLEDGEMENTS We appreciate the ATNF and CSIRO Data Access Portal for making such high-quality data publicly available. We thank the XMM–Newton help desk for important clarifications regarding the XMM–Newton data analysis. We also thank Bettina Posselt, Oleg Kargaltsev, George G. Pavlov, and Joanna Rankin for the useful discussions. We greatly appreciate Dr. Sebastien Guillot for carefully reviewing our manuscript and suggesting essential improvements. DM acknowledges funding from the grant ‘Indo-French Centre for the Promotion of Advanced Research – CEFIPRA’.
Paper: 2015A&A...575A.109B (acknowledgments)
V.B.-R. acknowledges support by the Spanish Ministerio de Economía y Competitividad (MINECO) under grant AYA2013-47447-C3-1-P. This research has been supported by the Marie Curie Career Integration Grant 321520. V.B-R. also acknowledges financial support from MINECO and European Social Funds through a Ramón y Cajal fellowship.