adsabs/WIESP2022-NER huggingface dataset:
Paper: 2020A&A...640A.121G (fulltext)
Table 1 Parameters of the model atmosphere. The spatial and temporal variability in the cloud cover is derived from observations by MODIS, the Moderate Resolution Imaging Spectroradiometer (for a detailed description of the MODIS data sets, including retrieval algorithms, see King et al. 2004 ; Parkinson Greenstone 2000 ). We describe a cloud by the pressure of its top, p c , its optical thickness, b c , and the cloud particle size distribution and composition. Each cloudy model pixel has a cloud fraction. This is zero for a cloud-free pixel. Even with as many as 100 pixels along the light equator of the model planet, the pixels are much larger than typical horizontal variations in clouds, and they are much larger than MODIS ground pixels. For a mixture of cloud-free and partly and fully cloudy MODIS ground pixels within a model pixel, we computed the locally reflected Stokes vector for a cloud-free and a cloudy model pixel, and took their weighted sum to compute the reflected Stokes vector for the pixel as a whole. In this way, we accounted for the cloud fraction as reported for all cloudy MODIS ground pixels. The mean cloud fraction of our model planet is about 66%. The MODIS database provides a cloud top pressure for all of its pixels, and we computed p c of a cloudy model pixel by taking the average of the cloud top pressures of the MODIS pixels within our model pixel, weighted by their cloud fractions. To limit the number of different atmosphere-surface models, we divided p c for the model pixels into three categories: 500 mbar for 0 ≤ p c 600 mbar, 700 mbar for 600 ≤ p c 800 mbar, and 850 mbar for p c ≥ 800 mbar (see Table 1 ). We computed b c for a cloudymodel pixel by taking the mean of the cloud optical thickness values of the MODIS ground pixels within the model pixel. In particular, we take the mean of the MODIS logarithmic daily mean data set (see Table 2 ). This data set provides the cloud optical thickness for a given MODIS pixel i as log b c i , where b c i is the cloud optical thickness. When we computed the mean b c , we weighted log b c i of each MODIS pixel with its cloudiness fraction. This logarithmic mean as a good approximation for the cloud optical thickness has been proposed by Hubanks et al. (2015) and Oreopoulos et al. (2007) . The wavelength at which a cloud optical thickness is provided in the MODIS data set depends on the surface: b c pertains to 645 nm above a dry surface, to 858 nm above an ocean, and to 1240 nm above snow or ice. We obtain b c at another wavelength by multiplying the value from the data set with the ratio of the cloud particle extinction cross-section at that other wavelength and at the given wavelength. The cloud optical thickness depends somewhat on the wavelength: for a cloud with b c = 10, composed of particles with r eff = 12.5 μ m and v eff = 0.1, the cloud optical thickness, for example, ranges from 9.775 to 10.002, from 350 to 865 nm. The extinction cross-sections of the cloud
Paper: 2020MNRAS.492..413R (acknowledgments)
ACKNOWLEDGEMENTS This work was supported by Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). PT-I acknowledges funding from ANILLO-ACT-1417 and Pontificia Universidad Católica for hosting her during the creation of this work. NDP acknowledges support by BASAL CATA AFB-170002 and Fondecyt Regular 1191813. This research made use of astropy , 1 a community-developed core python package for Astronomy (Astropy Collaboration et al. 2018 ), numpy (van der Walt, Colbert Varoquaux 2011 ), scipy (Jones et al. 2001 ), and matplotlib (Hunter 2007 ). Funding for the Sloan Digital Sky Survey IV (SDSS-IV) has been provided by the Alfred P. Sloan Foundation, the US 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 web site 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: 2019A&A...624A..50C (acknowledgments)
We thank the referee for their comments that helped us to improve the manuscript. PLUTO is developed at the Turin Astronomical Observatory in collaboration with the Department of Physics of Turin University. We acknowledge the “Accordo Quadro INAF-CINECA (2017)” the CINECA Award HP10B1GLGV and the HPC facility (SCAN) of the INAF – Osservatorio Astronomico di Palermo, for the availability of high performance computing resources and support. This work was supported by the Programme National de Physique Stellaire (PNPS) of CNRS/INSU, co-funded by CEA and CNES. This work has been done within the LABEX Plas@par project, and received financial state aid managed by the Agence Nationale de la Recherche (ANR), as part of the programme “Investissements d’avenir” under the reference ANR-11-IDEX-0004-02. The authors (R. B. and C. A.) acknowledge modest financial contribution from the agreement ASI-INAF n.2017-14.H.O.
Paper: 2016MNRAS.456..366T (acknowledgments)
The work presented in this paper has been supported by STFC through the grant ST/K000802/1. The authors would like to gratefully acknowledge the advice received from both J. M. Bizau (Blancard et al. 2012 ) and B. McLaughlin (Covington et al. 2011 ) and also for providing their data sets presented in this paper. The authors would finally like to acknowledge that this work has been carried out on the Cray XC40 Hazel Hen machine in Stuttgart, Germany through the grant number 44009 and the PAMOP project.
Paper: 2017ApJ...834...79Z (fulltext)
which is proposed and numerically simulated in two dimensions (2D), and 3D (Heyvaerts et al. 1977 ; Shibata et al. 1992 ; Yokoyama Shibata 1995 , 1996 ; Shimojo et al. 1996 ; Nishizuka et al. 2008 ; Pariat et al. 2009 ). In this model, the closed magnetic arch emerges into the ambient unipolar field and then reconnection occurs between the unipolar field and one branch of the arch with an opposite polarity to the unipolar field. The other is the blowout model (Moore et al. 2010 , 2013 ) with two magnetic reconnection processes. The first magnetic reconnection, which is similar to that in the standard model, occurs between the emerging magnetic arch and the ambient unipolar field. Then a filament with a large amount of pent-up free energy by shear (or twist) dominates the second magnetic reconnection (Liu et al. 2011a , 2011b ; Moreno-Insertis Galsgaard 2013 ; Hong et al. 2014 ; Lee et al. 2015 ). Recently, Sterling et al. ( 2015 ) suggested that all of the jets in the coronal hole essentially come from mini-filament eruptions. According to the latest review (Raouafi et al. 2016 ), the standard jets are intensively collimated, usually form an inverse-Y shape with a narrow spire, and seldom rotate. However, the blowout jets strongly rotate and posses a relatively broad spire. As suggested by Pariat et al. ( 2010 ), a jet process is always dominated by a synthetic role from magnetic geometrical characteristics of the jet source, such as size, flux distribution, null point position, and asymmetry. Many observations find that jets could appear with similar morphology and outflow, but might possess distinctive magnetic structures in the low coronal source region (Nisticò et al. 2009 ; Zhang et al. 2012 ). In total, a large number of observations and theoretical models basically describe and explain the morphology, dynamical and physical properties of the jets. However, for the limitation of observational capability, there is no appreciable resolution to distinctly resolve the motions of the plasma blobs (Zhang Ji 2014b ) and the related variation of magnetic topological structure inside a jet. Fortunately, benefitting from the extremely high spatial and temporal resolution in special wavelength observations by the Interface Region Imaging Spectrograph ( IRIS ; De Pontieu et al. 2014 ) and all ultraviolet (UV) and EUV wavelengths of the Atmosphere Imaging Assembly (AIA; Lemen et al. 2012 ) on board the Solar Dynamics Observatory ( SDO ; Pesnell et al. 2012 ), a cusp-shaped structure jet was captured with unprecedented detailed observations. The formation and evolution processes of the jet, including the motions of the blobs and topological variation of its skeleton, are described in Section 2 . Section 3 contains a discussion and conclusions. 2. OBSERVATIONS 2.1. Data From 05:51 UT to 06:39 UT on 2014 August 29, IRIS narrow-band slit-jaw images (SJIs; see Figure 1 ) in the 1330 Å channel captured a cusp-shaped jet located at N08W90 (Solar-X:
Paper: 2020ApJ...896..128M (fulltext)
for mass loss may be necessary to obtain observed results, as done by Neilson et al. ( 2012a ). This is because the rate of period change is directly related to the mass-loss rate from taking the derivative of the period–mean density relation, typically . The greater the mass-loss rate the greater and more positive the rate of period change and if the average mass-loss rate is high enough it could cause more Cepheids to have positive rates of period change even while evolving on the second crossing of the instability strip where the rate of period change is expected to be less than zero. 4. Results For each initial rotation rate and convective core overshooting value we compute the relative fraction of models with positive and negative rates of period change. We find that regardless of the initial rotation rate or convective core overshooting parameter, the fraction of Cepheids with positive period change is about 90% and the fraction with negative period change is about 10%, as can be seen in Table 1 . This suggests that period change, at least statistically, is insensitive to the physics of core overshooting and rotational mixing. Table 1 Predicted Fractions of Cepheids with Positive and Negative Period Changes This insensitivity has been noted before for overshooting. Neilson et al. ( 2012b ) and Neilson ( 2014 ) found similar results in that overshooting acts to change the mass–luminosity relation for Cepheids. That is, in terms of period change, Cepheids with different masses have the same rates of period change for different values of core overshooting. This is because each Cepheid crossing of the instability strip depends on the physics driving stellar evolution. During the first crossing the evolutionary timescale is related to the Kelvin–Helmholtz timescale, hence it is proportional to the mass of the star. Evolution along the second crossing of the instability strip occurs as the star generates energy through mostly hydrogen shell-burning and is beginning helium core-burning. The timescale for blueward evolution is driven by the timescale for the star to have shell-burning, but not have ignited significant helium core fusion. The third crossing is determined by helium core-burning, hence its timescale is also a function of helium core mass. Over the mass range we consider in this paper, overshooting will not change the timescales, and thus the fraction of Cepheids on the first crossing, while the impact on the second and third crossings also remains unchanged. The same argument is also true for rotation. Rotational mixing impacts the mass of the helium core and rotation can change the shape of the Cepheid blue loop. However, neither appears to impact the relative timescales of evolution significantly. The fraction of Cepheids with positive period change decreases to about 77% for models with zero convective core overshooting. The fraction is smaller, but not enough to be consistent with the observed fraction of 67%. This
Paper: 2019MNRAS.487.3998B (fulltext)
gas and solids in discs (e.g. Öberg et al. 2011 ; Madhusudhan et al. 2014 ). We first explore the evolution of the C/O ratio in models without radial drift (Fig. 6 ). In these models, the total abundance (gas and ice phase) of carbon and oxygen bearing species does not change, only the partitioning of these species between the gas and ice phases. Figure 6. Evolution of the C/O ratio for models with viscous transport, but without radial drift or diffusion. For comparison the left-hand panel shows the evolution without transport. The solid lines denote the gas-phase abundances, while the dotted lines show the ice abundances. The changes in composition driven by chemical processes are best seen in the model without transport (and α = 10 −3 ). Inside the water ice line (0.5 au), all of the major carbon and oxygen are in the gas phase and thus chemical processing does not change the gas-phase carbon or oxygen abundance. Between the water and CO 2 ice lines (1.5 au) the gas-phase carbon and oxygen abundance is dominated by CO and CO 2 , with a small contribution from hydrocarbons (CH 4 and C 2 H 2 – a proxy for C 2 H 6 ; see Section 3.1 ). Here, the C/O ratio increases as CO 2 is destroyed, producing CO and O, with O eventually forming H 2 O, which freezes out. Between the CO 2 and CH 4 ice lines (10 au), CO and CH 4 are initially the main gas-phase carbon and oxygen carriers. CH 4 gets converted to larger hydrocarbons (C 2 H 2 ), which freeze out causing the C/O ratio to reduce to 1. The spike in C/O ratio near the CO 2 ice line is due to the slightly lower binding energy of C 2 H 2 than CO 2 (note that C 2 H 6 also has a lower binding energy than CO 2 , so Eistrup et al. ( 2018 ) see a similar spike in C/O). Beyond the CH 4 ice line CO is always the dominant the gas phase carbon and oxygen carrier, so the C/O ratio does not evolve. The nitrogen abundance evolution can be derived from Fig. 5 and is slow, thus the C/N of N/O ratio evolution will be driven primarily by the evolution of carbon and oxygen, respectively. As the speed of the viscous transport increases, the changes in composition driven by chemical reactions become restricted to regions of the disc at larger and larger radii. Already at α = 10 −3 , the effect of transport is first noticeable between the H 2 O and CO 2 ice lines, since CO 2 no longer depletes (see also Bosman et al. 2018a ), while at α = 10 −2 the carbon and oxygen abundance hardly evolve. At α = 10 −2 , the inward movement of the ice lines as the disc cools generates the only significant changes in abundance ratio. The influence of radial drift on the bulk abundances is sensitive to whether radial drift or viscous evolution is faster. When radial drift is included we see spikes in the gas-phase C/H ratio at α = 10 −3 (Fig. 7 ), as reported by Booth et al. ( 2017 ). These spikes are driven by volatile species being left at their snow lines when grains drift past them. We also see a peak in the C/O ratio inside of 10 au,
Paper: 2020ApJ...891..180Z (fulltext)
conclusion that for positive (negative) helicity the apex of a filament rotates clockwise (counterclockwise). But the filament is believed to be associated with a flux rope taking on an S shape that is opposite to the corresponding sigmoid, the latter of which represents a current layer wrapping around the flux rope (Titov Démoulin 1999 ; Kliem et al. 2004 ). Green et al. ( 2007 ) hence rejected those models implying identical orientation for the sigmoid and the flux rope (e.g., Rust Kumar 1996 ; Kusano 2005 ). But in our sample and in the literature (e.g., Pevtsov 2002 ; Cheng et al. 2014 ; Zhou et al. 2017 ) often the cold filament and the hot sigmoid are co-spatial and have the similar S shape, suggesting that the filament is associated with a low-lying magnetic flux rope with its axis dipped in the middle (e.g., Zhou et al. 2017 ). Not all of these filament eruptions that are initiated make it to a full eruption; some of these cases expelled material flows back down to the Sun. Specifically, cases #4,#7,#9, and #11 expel material flows back down the legs of an erupting prominence and have no corresponding CME in the coronagraph observations, this subset of events are known as failed eruptions or confined eruptions, likely because of interactions with external magnetic field structures that may arrest the eruption or facilitate additional draining (McCauley et al. 2015 ; Zhou et al. 2019 ). This interaction may induce alternative rotation mechanism concerning the mutual orientation of the overlying arcade field and the erupting filament body (Isenberg Forbes 2007 ). For a given chirality of the erupting field, this mechanism yields the same rotation direction as the kink instability (e.g., Kliem et al. 2012 ). To summarize, by applying the method proposed by Chen et al. ( 2014 ) to determine filament chirality and using multiviewpoint observations to investigate the filament rotation, we established a strong relationship that during eruption sinistral/dextral filaments, which are located in the southern/northern hemisphere rotate clockwise/counterclockwise, when viewed from above, and corroborated a weak hemispheric preference that both the filament and related sigmoid exhibit a forward (reverse) S shape in the southern (northern) hemisphere. The one-to-one relationship between filament chirality and rotation direction may help understand the transformation of CMEs to interplanetary ejecta, and help predict statistically the latter’s characteristics, such as the axial orientation, the chirality of helical fields, and the strength and duration of southward magnetic field. As illustrated in Figure 4 , for both odd and even cycles, the rotation of eruptive active-region filaments makes their axes tilt toward the east–west direction. Such a statistical trend is already known for interplanetary magnetic clouds (Crooker 2000 ; Yurchyshyn et al. 2009 ), yet its connection with filament rotation has not been noticed. On the other hand, Figure 4
Paper: 2018MNRAS.474L..27H (acknowledgments)
Acknowledgements Based on observations obtained in the framework of the ESO Prgs. 097.D-0233(A) and 098.D-0185(A). LS acknowledges financial contribution from the grant from PRIN-INAF 2014 ‘Towards a unified picture of accretion in High Mass X-Ray Binaries’. AK acknowledges financial support from RFBR grant 16-02-00604A. We thank the referee Jerzy Madej for his useful comments.
Paper: 2020MNRAS.491.3606P (acknowledgments)
ACKNOWLEDGEMENTS The authors thank the referee, Dr. Leonardo J. Pellizza, for the constructive feedback provided on the manuscript. MB thanks Hai Fu for insightful discussions which helped to improve the quality of the paper. STSDAS is a product of the Space Telescope Science Institute, which is operated by AURA for NASA. We acknowlege the usage of the HyperLeda database ( http://leda.univ-lyon1.fr ). The scientific results reported in this article are based on joint observations made by the Chandra X-ray Observatory and the NASA/ESA Hubble Space Telescope . Support for this work was provided by the National Aeronautics and Space Administration through Chandra Award No. AR7-18005X issued by the Chandra X-ray Observatory Center, which is operated by the Smithsonian Astrophysical Observatory for and on behalf of the National Aeronautics and Space Administration under contract NAS8-03060.
Paper: 2018MNRAS.473.1841S (fulltext)
with data from observations taken from Pfuhl et al. ( 2015 ). Figure 7. The integrated Br γ luminosity as a function of time. The solid blue line results from our simulations while the points are the observed data taken from Pfuhl et al. ( 2015 ) with a 1σ error bar. As the cloud travels towards the SMBH, its volume decreases due to tides and hence its recombination rate and total emission increase. During pericentre passage, gas that passes through pericentre has its density greatly increased due to the vertical collapse. While the recombination rate for a fully ionized gas greatly increases during pericentre passage, the fact that the cloud is UV starved and that its total ionization rate is regulated by the background UV flux limit the increase in the Br γ emission to a mere doubling. This translates to roughly a doubling of the emission that is now limited by the UV flux. After pericentre passage, the emission decreases as the surface area of the cloud decreases due to the evolution of the cloud under tides. Our simulations also allow us to create mock PV diagrams that can be compared with observations. We create mock data cubes in the same manner as in Schartmann et al. ( 2015 ) using pixels of size 12.5 mas and 70 km s −1 . Fig. 8 shows the PV diagram for several different epochs before, during and after pericentre passage. There is good agreement between the observations before pericentre passage and our simulations. Figure 8. PV diagrams of the G2 cloud. The left-hand column is the observational data taken from Plewa et al. ( 2017 ) while the right-hand column are mock observations created from the simulations. The plots represent the epochs 2012.2, 2013.4, 2014.4, 2015.3 and 2016.4. 8 DISCUSSION We have presented a detailed model combining analytical arguments along with numerical simulations that successfully reproduce the observed Br γ emission. By utilizing the reduced diffusion of the moving mesh scheme along with high resolution and actively cooling the gas, we were able to simulate previously unnoticed physical phenomena. The tidal force combined with the efficient cooling collapses the vertical axis of the cloud during pericentre passage. Although the collapse produces a significant amount of ionizing radiation, due to the thinness of the cloud, most of the ionizing photons escape and only a small fraction of them end up ionizing neutral gas. The Br γ emission is regulated by the external UV flux from nearby massive stars. We find that the emission is UV starved, most of the gas is neutral during pericentre passage. This is true even for our enhanced ionizing background, which is 3.6 times larger than the Martins et al. ( 2006 ) rate. Motivated by the observed duration of simultaneous blueshifted and redshifted Br γ emission at pericentre passage, we chose to start our orbital plane simulation with a cloud that has an aspect ratio of 4, which is consistent with the observations due to viewing angles. If the elongated cloud is