adsabs/WIESP2022-NER huggingface dataset:
Paper: 2016ApJ...823...30B (acknowledgments)
It is a pleasure to thank the anonymous referee, Brett Andrews, Bob Benjamin, and Chris McKee for helpful comments and discussions. Some of the results in this paper have been derived using the HEALPix (Górski et al. 2005 ) and healpy packages. J.B. received support from a John N. Bahcall Fellowship and the W.M. Keck Foundation. H.W.R. received funding for this research from the European Research Council under the European Union’s Seventh Framework Programme (FP 7) ERC grant Agreement No. [321035]. T.C.B. acknowledges partial support for this work from grants PHY 08-22648; Physics Frontier Center/Joint Institute or Nuclear Astrophysics (JINA), and PHY 14-30152; Physics Frontier Center/JINA Center for the Evolution of the Elements (JINA-CEE), awarded by the US National Science Foundation. J.B. and H.W.R. acknowledge the generous support and hospitality of the Kavli Institute for Theoretical Physics in Santa Barbara during the “Galactic Archaeology and Precision Stellar Astrophysics” program, where some of this research was performed. Funding for SDSS-III has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, and the U.S. Department of Energy Office of Science. The SDSS-III web site is http://www.sdss3.org/ . SDSS-III is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS-III Collaboration including the University of Arizona, the Brazilian Participation Group, Brookhaven National Laboratory, Carnegie Mellon University, University of Florida, the French Participation Group, the German Participation Group, Harvard University, the Instituto de Astrofisica de Canarias, the Michigan State/Notre Dame/JINA Participation Group, Johns Hopkins University, Lawrence Berkeley National Laboratory, Max Planck Institute for Astrophysics, Max Planck Institute for Extraterrestrial Physics, New Mexico State University, New York University, Ohio State University, Pennsylvania State University, University of Portsmouth, Princeton University, the Spanish Participation Group, University of Tokyo, University of Utah, Vanderbilt University, University of Virginia, University of Washington, and Yale University.
Paper: 2018MNRAS.479.2630D (fulltext)
of the model with the expected scaling relations described in Section 3.1 using km s −1 from Bernardi et al. ( 2003 ). The expected value is , which is in agreement with the model values in Table B4 , mostly the one of the most complete cluster model. The two other results are closer to the upper limit value because those models do not take in account the impact of the cluster convergence boosting the lensing power of the galaxy, therefore leading to an overestimation of the velocity dispersion of the lens. However the value of of the complete cluster model is ∼40 per cent higher than the one optimized in the cluster model. This could indicate that the standard galaxy is not constrained well enough, as the cluster model not including the GGL constraints provides different values. We find a similar problem in the cluster model of RX J2129 where . If the GGL lens follows the scaling relation as we assumed it, the velocity dispersion of the lens would be , which is far too low according to Fig. 12 to produce multiple images as we observe them even for a source with s = 10. Even with the boost of the cluster, a complete model constraining the GGL parameters with a source with s = 10 leads to a σ 0 = 166.8 . There is a ∼30 per cent variation with this value and the one derived from the scaled standard galaxies in the models presented in Table B2 . Either the standard galaxy parameters are not well constrained or our assumption about the GGL lens is wrong. Having a spectroscopic redshift for the GGL source would provide a way to constrain σ 0 independently of the scaling relation and would allow us to test the consistency of the results. Then, assuming that the galaxy follows this relation, we could constrain better the standard galaxy parameters directly using the locations of multiple images in the GGLs. For this reason, a spectroscopic follow-up of the 24 GGLs presented in Fig. A1 and Table A1 would improve greatly the model constraints for all those clusters. 5 SUMMARY AND CONCLUSIONS We visually inspect the full Hubble field of view of the 25 observed clusters from the CLASH survey in order to locate GGL events in the outskirts of those clusters. We find a selection of 24 candidate GGLs (some already known), and study in detail three of them presenting the following characteristics: a single lens, at least four distinct multiple images, and a separation from the BCG larger than 80 arcsec. For each of those GGLs and their associated cluster, we produce four parametric models of the DM distribution to study the influence of the cluster on the GGL modelling and the influence on the GGL on the cluster models. Through those models, we show that the modelling of the GGLs cannot be done properly without taking into account its environment. This can be achieved through a complete model of the neighbour structures or even with a simple parametrization of their effects like an external shear. A photometric redshift is accurate enough to properly
Paper: 2016ApJ...823..147C (acknowledgments)
We thank the anonymous referee for very useful comments and suggestions that substantially improved the manuscript. We are also grateful to M. Kromer for useful discussions about theoretic progenitor scenarios and to A. De Cia, O. Yaron, D. Tal, D. Perley, K. Tinyanont, A. Waszczak, I. Arcavi, and S. Tang for performing observation and data reduction. This research is partly supported by the Swift Guest Investigator program and by the National Science Foundation. Y.C. and M.M.K. acknowledge support from the National Science Foundation PIRE program grant 1545949. A.G. and R.A. acknowledge support from the Swedish Research Council and the Swedish Space Board. E.Y.H. acknowledges the support provided by the Danish Agency for Science and Technology and Innovation through a Sapere Aude Level 2 grant. Some observations were obtained with the SuperNova Integral Field Spectrograph on the University of Hawaii 2.2 m telescope as part of the Nearby Supernova Factory II project, a scientific collaboration between the Centre de Recherche Astronomique de Lyon, Institut de Physique Nucl’eaire de Lyon, Laboratoire de Physique Nucl’eaire et des Hautes Energies, Lawrence Berkeley National Laboratory, Yale University, University of Bonn, Max Planck Institute for Astrophysics, Tsinghua Center for Astrophysics, and Centre de Physique des Particules de Marseille. Some data in this paper were obtained with ALFOSC, which is provided by the Instituto de Astrofisica de Andalucia (IAA) under a joint agreement with the University of Copenhagen and NOTSA. We also thank the RATIR project team and the staff of the Observatorio Astronómico Nacional on Sierra San Pedro Mártir. RATIR is a collaboration between the University of California, the Universidad Nacional Autónoma de México, NASA Goddard Space Flight Center, and Arizona State University, benefiting from the loan of an H2RG detector and hardware and software support from Teledyne Scientific and Imaging. RATIR, the automation of the Harold L. Johnson Telescope of the Observatorio Astronómico Nacional on Sierra San Pedro Mártir and the operation of both is funded through NASA grants NNX09AH71G, NNX09AT02G, NNX10AI27G, and NNX12AE66G, CONACyT grants LN 260369, and UNAM PAPIIT grant IG100414. A portion of this work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. Copyright 2016 California Institute of Technology. All Rights Reserved. US Government Support Acknowledged.
Paper: 2017ApJ...851....6P (fulltext)
brackets refer to the inverted mass hierarchy. Different columns give the numbers for different detection channels: the superscripts CC and el refer, respectively, to the dominant charged current process (inverse beta decay or absorption on the Ar nucleus) and to neutrino-electron scattering. The subscript β indicates the contribution of the β processes to those two channels. The total number of events is given in the last column. The results for Betelgeuse ( D = 0.2 kpc) can be obtained by rescaling by a factor of 25. Table 4 Same as Table 3 , but for the Progenitor The tables confirm that a large LS like JUNO has the best potential, due to its sensitivity at low energy, with events (depending on the type of progenitor) recorded from a star at D = 1 kpc. For these events, the contribution of the β p is at the level of 10%–30%, and is larger for the inverted mass hierarchy, for which the flux is larger; see Section 4.1 . For Betelgeuse, a spectacular signal of more than 200 events in two hours could be seen. One can define (optimistically) the horizon of the detector, D h , as the distance for which one signal event is expected. We find that JUNO has a horizon . Although it is disadvantaged by the higher energy threshold, SuperKamiokande and DUNE can observe presupernova neutrinos for the closest stars. For the most massive progenitor, SuperKamiokande could reach a horizon and record events for D = 0.2 pc. Of these, ∼10%–20% would be from β p. Looking further into the future, the larger water Cherenkov detector HyperKamiokande (Abe et al. 2011a )—with a mass 20 times the mass of SuperKamiokande—might become a reality. Assuming an identical performance as SuperKamiokande, HyperKamiokande will have a statistics of up to thousands of events, and a horizon of . 10 10 Due to its mass, HyperKamiokande will have a level of background that is ∼20 times higher than that of SuperKamiokande, and probably a higher energy threshold as well. Therefore, its performance will be worse, and the figures given here have to be taken as best case scenarios. At DUNE, a detection is possible only for the closest stars; the number of events varies between and , depending on the parameters, for . For the most optimistic scenario (the more massive progenitor and the inverted mass hierarchy), the horizon can reach . DUNE will observe a strong component due to β p, at the level of of the total signal. Therefore, in principle LAr has the best capability to probe the isotopic evolution of supernova progenitors. 5. Discussion We have presented a new calculation of the total neutrino flux from beta processes in a presupernova star, inclusive of time-dependent emissivities and neutrino energy spectra. This is part of a complete and detailed calculation of presupernova neutrino fluxes from most relevant processes—beta and thermal—done using the state-of-the-art stellar evolution code MESA. The beta neutrino flux is strongest in the channel, where it is comparable to the flux
Paper: 2018A&A...611A.102M (acknowledgments)
Acknowledgements M. Maercker acknowledges support from the Swedish 83 Research Council under grant number 2016-03402. M.B. acknowledges funding through the uni:docs fellowship of the University of Vienna, and funding by the Austrian Science Fund FWF under project number P23586. E.D.B. acknowledges funding by the Swedish National Spaceboard. We acknowledge with thanks the variable star observations from the AAVSO International Database contributed by observers worldwide and used in this research.
Paper: 2018A&A...614A.121N (acknowledgments)
We acknowledge useful discussion with S. Ettori, G. Brunetti, G. Ghisellini, R. Decarli, E. Torresi, E. Lusso, S. Gallerani. We thank the anonymous referee for his/her useful comments and suggestions that improved the quality of this work. We acknowledge financial contribution from the agreement ASI-INAF n.2017-14-H.O and ASI-INAF I/037/12/0. The scientific results reported in this article are based on observations made by the Chandra X-ray Observatory. This work made use of data taken under the ESO program ID 095.A-0714(A). FC acknowledges funding from the INAF PRIN-SKA 2017 program 1.05.01.88.04.
Paper: 2017MNRAS.472L..65N (fulltext)
is hotter. Consequently these two effects increase the significance of the CS. The vertical red dashdotted line indicates the f sky of the Planck Common Field mask. 3.4 The ISW for the coldest spots The ISW contribution to the coldest spots in simulations was measured and is shown in Fig. 5 . Here, we display the mean and 1 contours for all the full-sky minima and the most extreme 3percent (which approximately corresponds to the CSs p-value). The profiles are poorly constrained and very similar, with the more extreme case tending to be slightly more negative. The result illustrates that it is very likely that the ISW plays a minor role in the CS profile: 10percent of the full profile. The reconstructed ISW profiles (Nadathur etal. 2014 ; Rassat etal. 2014 ; Finelli etal. 2016 ; Planck Collaboration XXI 2016c ) appear to be consistent with the predicted ISW shown in Fig. 5 . The presence of prominant voids in the LOS (see Szapudi etal. 2015 ; Kovcs Garca-Bellido 2016 ) are therefore precisely what we would expect from CDM. Figure 5. The 1 contours of the ISW of all the full-sky minima are shown in blue. The most extreme 3percent are indicated by the grey hatched area. The mean for all the coldest spots and the most extreme 3percent are indicated by the blue and grey dashed lines, respectively. The ISW in either case is not very well constrained and consistent with zero but, on average, appears to contribute 10percent to the minimas profiles. 3.5 Dependence on angular scale Up to this point, we have used a preselected angular scale, R 5, where the CS was measured to be most significant by Planck Collaboration XVI ( 2016b ). However, our conclusions for the CS significance may not necessarily hold true for other angular scales. To test this, R is varied between 4 and 7, roughly equaling the range of R over which Zhang Huterer ( 2010 ) found the CS to be significant. The same procedure is carried out as before except with a smaller number of realizations (10000). In Table 1 , we summarize these results. The probability, , is roughly equal to the fraction of unmasked pixels of the effective mask. However, is found to be 0.85 for the angular scales considered. When the cut-sky significance 2 the probability is even higher (0.93). This makes it appropriate to compare the CS to full-sky minima in simulations where it is 2 for 4 R 7. Combined with previous studies (e.g. Vielva etal. 2004 ) means the CS is 2 for all angular scales. Table 1. The probability that the full-sky and cut-sky minima (Cold Spot) are equivalent for any and for the CSs is indicated by and , respectively, for each angular scale R . The significance of the CS is shown in comparison to the cut-sky and full-sky minima in CMB realizations. For each value of R (except R 5, where 100000 realization were previously made) 10000 CMB realizations were simulated. 4 CONCLUSIONS We measure the cut-sky and full-sky minima (Cold Spot) in 100000 simulations using the Planck Common Field mask,
Paper: 2016MNRAS.456....2W (fulltext)
atmospheric dispersion corrector in the fall of 2009, reducing the crosstalk below 1 per cent. Periodic monitoring of the crosstalk confirms that it has remained stable since 2009. However, higher crosstalk levels were likely present (with levels as high as 5 per cent) during the first three semesters of MiMeS LP observations. The absence of any significant impact of crosstalk on most MiMeS observations is confirmed through long-term monitoring of TC targets as standards, and is addressed in Section 4.2 . 5 The crosstalk evolution and mitigation is described in more detail by Barrick, Benedict Sabin ( 2010 ) and Silvester et al. ( 2012 ). Change of the ESPaDOnS CCD: until semester 2011A, ESPaDOnS employed a grade 1 EEV CCD42-90-1-941 detector with 2k × 4.5k 0.0135 mm square pixels (known as EEV1 at CFHT). This was replaced in 2011A with a new deep-depletion E2V CCD42-90-1-B32 detector (named Olapa). Olapa has exquisite cosmetics and much less red fringing than EEV1. Another major difference is that Olapa's quantum efficiency in the red is about twice as high as with EEV1. Commissioning experiments by CFHT staff, as well as within the MiMeS project, were used to confirm that observations acquired before and after the CCD replacement are in excellent agreement. This is discussed further in Section 4.2 . 2.4 Narval 2.4.1 Instrument Narval 6 is a near-twin of ESPaDOnS installed at the 2 m TBL in the French Pyrénées. It is composed of a Cassegrain polarimeter unit similar to that of ESPaDOnS, and a similar spectrograph located in the TBL coudé room. Compared to ESPaDOnS, the instrument was only adapted to the smaller telescope size. Small differences include the diameter of the entrance pinhole of the Cassegrain unit (2.8 arcsec for Narval, versus 1.6 arcsec for ESPaDOnS) and the lack of a fibre agitator. However, the sampling of the (sliced) pinhole image is identical to that of ESPaDOnS. The CCD used at TBL (a back illuminated e2v CCD42-90 with 13.5 μm pixels) differs from that used at CFHT. However, each Narval spectrum also captures 40 spectral orders covering a similar spectral range (370–1050 nm) with the same resolving power of about 65 000. All other technical characteristics of Narval are effectively identical to those of ESPaDOnS described in Section 2.3.1 . 2.4.2 Observations Observations of MiMeS targets with Narval were initiated in 2009 March, and continued until 2013 January. A total of 1213 h were allocated to the MiMeS programme, first in the framework of three single-semester programmes and then as an LP for five additional semesters (all of these observations are hereinafter considered to be ‘LP’ observations). TBL programme identifications associated with MiMeS were prefixed by the letter ‘L’, followed by the year (e.g. ‘12’ for 2012) and the semester (1 or 2 for semesters A and B, respectively), then ‘N’ for Narval, and the ID of the programme itself (e.g. ‘02’ in the case of the LP). The MiMeS Narval runs are thus L091N02,
Paper: 2017ApJ...842...62S (acknowledgments)
R.S. acknowledges financial support under the research grant SR/FTP/PS-058/2012 by SERB, DST, and from IISER Bhopal. P.K.A. is supported by the Claude Leon Post-doctoral Fellowship program of the Claude Leon Foundation, South Africa, at UCT. We use the publicly available HEALPix (Górski et al. 2005 ) package available from http://healpix.sourceforge.net to perform forward and backward spherical harmonic transformations and for visualization purposes. We acknowledge the use of the Legacy Archive for Microwave Background Data Analysis (LAMBDA). LAMBDA is a part of the High Energy Astrophysics Science Archive Center (HEASARC). HEASARC/LAMBDA is supported by the Astrophysics Science Division at the NASA Goddard Space Flight Center.
Paper: 2017MNRAS.469L...6F (acknowledgments)
Acknowledgments We thank Stevie Bergman, Jeffrey Filippini, William Jones, Lyman Page and George Efstathiou for useful discussions. SMF was partially supported by Science and Technology Facilities Council (STFC) in the United Kingdom. The Center for Computational Astrophysics is supported by the Simons Foundation. HVP was partially supported by the European Research Council under the European Community's Seventh Framework Programme (FP7/2007-2013) ERC GA no. 306478-CosmicDawn. LV acknowledges support by Spanish Ministerio de Economía, Industria y Competitividad (MINECO) under projects AYA2014-58747-P and MDM-2014-0369 of Institut de Ciències del Cosmos, Universitat de Barcelona (ICCUB) (Unidad de Excelencia Maria de Maeztu). JEG acknowledges support by Katherine Freese through a grant from the Swedish Research Council (Contract No. 638-2013-8993). The work of JE was performed within the LabEx Institut Lagrange de Paris (ILP) (reference ANR-10-LABX-63) part of the Idex Sorbonne Universités à Paris pour l'Enseignement et la Recherche (SUPER) and was supported by the Agence Nationale de la Recherche (ANR), as part of the programme Investissements d'avenir under the reference ANR-11-IDEX-0004-02.
Paper: 2019MNRAS.488.5512H (acknowledgments)
ACKNOWLEDGEMENTS We thank Henrik Latter, Eugene Vasiliev, and Antranik Sefilian for useful conversations. The orbit integration in Section 7 was done using galpy ( http://github.com/jobovy/galpy ; Bovy 2015 ). The N -body calculations were done with mercury (Chambers 1999 ). CH is funded by a Science and Technology Facilities Council (STFC) studentship.
Paper: 2016ApJ...827...85H (acknowledgments)
We thank K. Sumiyoshi and T. Yoshida for productive suggestions. This work was supported in part by Grants-in-Aid for Scientific Research of JSPS (26105517, 24340060) of the Ministry of Education, Culture, Sports, Science and Technology of Japan. Work at the University of Notre Dame (GJM) supported by the U.S. Department of Energy under Nuclear Theory Grant DE-FG02-95-ER40934.
Paper: 2018MNRAS.481.3661V (fulltext)
have been considered (e.g. Lovell et al. 2014 ; Vogelsberger et al. 2016 ; Iršič et al. 2017b ; Robles et al. 2017 ), among which are the so-called warm dark matter models, where the corresponding particles have non-negligible thermal velocities. In particular, sterile neutrinos with masses of a few keV have been shown to be an interesting candidate for warm dark matter particles (e.g. Boyarsky, Iakubovskyi Ruchayskiy 2012 , and references therein). Moreover, the three sterile neutrino model, also known as the neutrino minimal standard model (νMSM), can also explain baryogenesis processes and neutrino oscillations (Boyarsky et al. 2012 , and references therein). Recently, sterile neutrinos have gained renewed attention following the apparent detections of a 3.5 keV X-ray line in several galaxy clusters as well as M31, and at the centre of the Milky Way (Boyarsky et al. 2014 ; Bulbul et al. 2014 ; Boyarsky et al. 2015 ); for a review see, e.g. Iakubovskyi ( 2014 ). However, sterile neutrino decay as a source of the line remains contentious (e.g. Anderson, Churazov Bregman 2015 ; Gu et al. 2015 ; Jeltema Profumo 2016 ). Recent results from the Hitomi collaboration (Aharonian et al. 2017 ) have ruled out an atomic transition as the origin of the 3.5 keV line, but a dark matter interpretation is still possible due to the different sensitivity of the Hitomi instrument to narrow (atomic) and broad lines. The 11σ detection of the 3.5 keV signal by NuStar (Neronov, Malyshev Eckert 2016 ) from a quiescent region of the sky and subsequent confirmation of this result with Chandra (Cappelluti et al. 2017 ) suggest that the line is not a statistical fluctuation nor an artefact of the XMM–Newton ’s instrumentation. It is therefore important to find complimentary probes of these models as well as supporting future X-ray observatory missions such as XARM and ATHENA that will provide still stronger X-ray constraints. Due to their appreciable thermal velocities at early times, warm dark matter particles free-stream out of density perturbations and are responsible therefore for a cut-off in the linear power spectrum and by extension in the formation of structures at small scales. The exact scale at which the suppression happens is strongly related to the dark matter particle production mechanism. For example, for 7 keV sterile neutrinos with a lepton asymmetry (defined in Section 3 ) much smaller or larger than L 6 = 8 this happens at the scale of progressively more massive dwarf galaxies (Lovell et al. 2016 ), while in a CDM model the suppression happens at much smaller scales. Quantifying the number of small mass structures is therefore an essential approach to distinguish among different dark matter models. For example, Kennedy et al. ( 2014 ) and Lovell et al. ( 2016 ) have used semi-analytic models to compare the abundance of luminous Milky Way satellites predicted by sterile neutrino dark matter models with the observed number of dwarf spheroidals, and