adsabs/WIESP2022-NER huggingface dataset:
Paper: 2017A&A...598L...8P (fulltext)
because of the strength of the field. We changed the initial conditions of the blobs as little as possible from one case to the other. The compromise was to use the same initial velocity, which the blobs may acquire when they flow inside very large arches, such as in huge prominences. The evolution that we find is strikingly different. In the fully aligned case, the blobs and the slow-mode shocks flow along the field lines and do not perturb the intense magnetic field. The blobs remain compact and move inside independent magnetic channels. In the misaligned case, the shuffling of the field lines driven by the blobs creates a feedback on the blobs themselves and mixes them. At the same time, the conglomeration is structured into thinner filaments. In this case, it is impossible to establish the native channel or the initial shape of the blobs, they lose their identity completely. Misaligned propagation is also an efficient way to excite fast Alfvén wave fronts, which travel ahead of the cloud, in addition to shocks. In summary, this work highlights the possible back-effect of the confining magnetic field on the propagation of fragmented flows inside it. When they are perfectly channelled, plasma fragments keep their identity as single blobs with no mixing, and the magnetic field is left unchanged as well. When there is some misalignment, the magnetic field can react with a shuffling of the field lines that mixes and merges the fragments, thus changing the plasma configuration completely. This represents a very effective mechanism of plasma mixing in the presence of a magnetic field, different from standard shear-like instabilities. The field lines can be effectively shuffled by irregular plasma motion and its feedback to the plasma is naturally chaotic. We may wonder which is the most common situation: aligned or misaligned fragment motion. We expect that if the plasma is confined since the beginning and the magnetic field does not change much along the track, the motion should be mostly aligned to the field and even more if blob velocity is lower, as in the coronal rain, in which similar blobs fall by gravity and reach loop footpoints with a velocity of about 60 km s ( Fang et al. 2013 , 2015 ; Moschou et al. 2015 ). All our evolution occurs on timescales about two orders of magnitudes shorter than in these other studies, so that our results might only apply to the very final stages of their modelling. On the other hand, downfalling from large distances through a significantly changing magnetic field might result in misaligned fragment motion. A situation like this may occur in the accretion onto young protostars from circumstellar disks, both at the flow origin (disk) and close to the flow impact, where the magnetic field of the star might become very complex. This process might therefore lead to further mixing of downflows and increase their fine substructure. For this exploratory work, the initial conditions of our simulations differ in
Paper: 2018MNRAS.481.1028H (fulltext)
as a function of metallicity and the data (see e.g. fig. 10 of Nomoto et al. 2013 ). Regardless of this fact, we can empirically compare the derived values of [V/Fe] for our stars with those from known populations. Fig. 3 shows the derived values of [V/Fe] as a function of metallicity for the extreme-velocity stars (black) compared to the Galactic disc (light green circles Battistini Bensby 2016 ), the Galactic halo (Yong et al. 2013 ; Roederer et al. 2014 ), and the LMC (Van der Swaelmen et al. 2013 ). The candidate extreme-velocity stars have a wide range in [V/Fe], again consistent with the large scatter observed for the Galactic halo. Cu : Copper (Cu) is an odd-Z element that is thought to be largely produced via SNIa and hypernovae but is also produced by secondary phenomena in massive stars and the weak s-process (e.g. Mishenina et al. 2002 ). Like many elements, the exact nucleosynthetic process that forms Cu is still under debate (e.g. Andrievsky et al. 2018 ). As shown in Fig. 4 , previous surveys found a large scatter in [Cu/Fe] at the metallicities of our stars, and similar low values in the LMC and stellar halo. Again, the stars in our sample fit within the scatter of the stellar halo, but Cu does not allow us to distinguish between stars born in the Galactic disc, halo or LMC. Figure 4. The [X/Fe] ratios of the program stars (black filled symbols) as a function of [Fe/H] for Cr, Mn, Ni, and Zn from top to bottom, respectively, on the left and Sc, Co, and Cu from top to bottom, respectively, on the right. These largely represent the Fe-peak elements. The symbols are the same as in Fig. 3 . Sc : Scandium (Sc) is an odd-Z element that, similarly to vanadium, has a poorly understood nucleosynthesis production mechanisms. This is evident by the large discrepancies between the theoretically computed and observed trends of [Sc/Fe] as a function of [Fe/H] (e.g. Kobayashi et al. 2006 ; Nomoto et al. 2013 ). As seen in Fig. 4 stars belonging to either the LMC or Galactic disc show [Sc/Fe] increasing with decreasing metallicity, with [Sc/Fe] lower in the LMC at fixed metallicity compared to the Galactic disc (Van der Swaelmen et al. 2013 ). On the other hand, stars in the Galactic halo have [Sc/Fe] values which are either slightly enhanced (Yong et al. 2013 ) or solar (Roederer et al. 2014 ) though with large intrinsic scatter. The candidate extreme-velocity stars are all enhanced in [Sc/Fe] at levels consistent with the Galactic halo but not with the LMC. 4.4 Fe-peak elements: Cr, Mn, Co, Ni, Zn Unlike the α or odd-Z elements, the Fe-peak elements, such as chromium (Cr), scandium (Sc), manganese (Mn), cobalt (Co), nickle (Ni), and zinc (Zn), are formed through a variety of paths (Iwamoto et al. 1999 ; Kobayashi et al. 2006 ) but are largely dispersed into the ISM in a similar way as iron. As such, these Fe-peak elements largely track the abundance of Fe. At the metallicity range of the candidate extreme-velocity stars (–2 [Fe/H] –1),
Paper: 2018ApJ...858..121L (fulltext)
The sheared arcades were likely to reconnect during the flare, and led to the formation of a flux-rope-like core structure that drove the outward eruption. The structure rose slowly with writhing motion and mass drainage, and finally stopped, and gradually became invisible afterward. The process fits into the scenario of a failed eruption of a helical kinked flux rope (e.g., Fan 2005 ; Guo et al. 2010 ; Török et al. 2010 ; Hassanin Kliem 2016 ). The core structure had a peak velocity of 178 km s −1 , and ceased at a height around 0.24 R Sun . For the successful eruption (eruption2), two sets of sheared arcades above the PIL were also identified before its onset. Their corresponding footpoints brightened during the flare, indicating a reconnection between them. The eruption rapidly evolved into a fast CME (with a peak velocity of 1041 km s −1 ) that propagated into the heliosphere. 2. Before both eruptions, continuous flux emergence existed in the source AR. For the source polarity pair, the positive one displayed a faster westward motion than the negative one, resulting in a net convergence toward the PIL. Due to continuous flux emergence and shear motion on the photosphere, magnetic helicity was injected, with a dominating shear term. A larger quantity of magnetic free energy and magnetic helicity was accumulated before the successful eruption. Before the onset of the eruptions, the core region, i.e., the source FPIL of the successful eruption, displayed a larger non-potentiality than the failed eruption. For example, before the successful eruption, more magnetic free energy resided above the FPIL, and larger values were derived for the mean current density, current helicity, and the shear angle that measures the core region’s non-potentiality. The decay index distributions showed no significant difference, although the critical height for the successful eruption was slightly lower (around 3 Mm) than that for the failed eruption. The ratio of magnetic fluxes at 42 Mm and 2 Mm (in the FPIL mask) was smaller before the successful eruption, indicating a relatively weaker confinement. 3. Before the failed eruption, two sets of sheared field lines that corresponded well with the observed sheared arcades, could be identified in the coronal magnetic fields extrapolated by the NLFFF method. After the eruption, the sheared field lines disappeared, while near-potential loops were identified above the PIL. Combined with the observed eruption process, we conjecture that a reconnection between the sheared arcades may have occurred. A similar topology change was found during the successful eruption. Significant enhancements of B h were found in the FPILs after both eruptions, while the value of the Lorentz force change during the successful eruption was an order of magnitude larger than that for the failed eruption. Decreases in magnetic free energy were also found after both eruptions, although the magnitude for the successful eruption was larger
Paper: 2015MNRAS.446.1347M (acknowledgments)
RM thanks the NRF's Thuthuka Grant for funding.
Paper: 2016MNRAS.462...48S (acknowledgments)
MP is supported by NASA through Einstein Postdoctoral Fellowship grant number PF3 140113 awarded by the Chandra X-ray Center, which is operated by the Smithsonian Astrophysical Observatory for NASA under contract NAS8-03060 . We thank Katya Giannios for suggestions on the title. The simulations were performed on XSEDE resources under contract No. TG-AST120010 , and on NASA High-End Computing (HEC) resources through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center. We also gratefully acknowledge access to the PICSciE-OIT High Performance Computing Center and Visualization Laboratory at Princeton University.
Paper: 2019MNRAS.484.4711M (acknowledgments)
ACKNOWLEDGEMENTS We acknowledge support from the ISF-ICORE grant 1829/12. The authors acknowledge the University of Maryland supercomputing resources ( http://hpcc.umd.edu ) made available for conducting the research reported in this paper.
Paper: 2021A&A...651A...5K (fulltext)
2 ) are subtracted from the DM values to produce this plot. The DMs obtained with only using BAND5 data are not shown in the plot as their uncertainties are large. The four pulsars presented in this work have different frequency evolution of their parameters like flux density, profile shapes, scintle sizes and scatter broadening. To illustrate this, frequency-resolved profiles for all four pulsars are shown in Fig. 1 . As a result, we had to obtain ToAs with different frequency resolution for each of them as described in Sect. 4 . 4. Results and discussions The DM time series obtained using the methods described in Sect. 4 for the four pulsars are shown in Fig. 3 . The left panel shows the DM measured using METHOD1 and the right panel shows DM obtained using METHOD2 . The median DM values and their uncertainties for the four pulsars are listed in Table 2 . We have only reported the measurements for which a reduced χ 2 10 is obtained with TEMPO2 . Some epochs show reduced χ 2 values worse than 10, but looking at each of them individually showed that they were affected by heavy RFI. Although we put a higher limit on χ 2 for getting the good measurements, most of them have reduced χ 2 much less than 10 and close to 1. The median value of the DMs estimated using METHOD1 and METHOD2 differs slightly for PSRs J1713+0747 and J1909−3744, while there is a clear offset between the DMs for PSRs J1939+2134 and J2145−0750. The possible cause of this difference is the underlying difference in the profile alignment methods used. Table 2. Median values of ToA uncertainties and DM. Notes. The ToA uncertainty for each pulsar is shown using the frequency and time averaged profiles with the analytic template created in METHOD2 for both bands. The median DM and DM uncertainty obtained from the DM time series of each pulsar using METHOD1 and METHOD2 are also given. In the present work, we have used the data obtained by observing simultaneously at both BAND3 and BAND5 using a 100 MHz bandwidth. The fractional bandwidth at BAND5 is a factor of ∼4−5 smaller than those used by most of the other PTAs, which reduces the precision with which we can obtain DM at BAND5. But a better fractional bandwidth at BAND3 enables us to get a good handle on the DM. The DM precision we can obtain in general by using this dataset with the BAND3 data alone is ∼10 −3 and while combining the two bands it gets better by an order of magnitude to ∼10 −4 . In particular, we achieve an order of magnitude better precision of 10 −4 with BAND3 and 10 −5 with BAND3 and BAND5 for PSR J1939+2134. Combining the two widely separated bands for measuring DM can create a bias due to the slightly different IISM the rays of these two bands pass through ( Cordes et al. 2016 ). Comparing our results obtained using the two methods described in this work to that of the recently published ones by Alam et al. (2021) and Donner et al. (2020) show interesting trends. For two pulsars, J1713+0747 and J2145−0750, we
Paper: 2018ApJ...864...73W (acknowledgments)
This paper makes use of the following ALMA data: ADS/JAO.ALMA#2015.1.00582.S. ALMA is a partnership of ESO (representing its member states), NSF (USA) and NINS (Japan), together with NRC (Canada), MOST and ASIAA (Taiwan), and KASI (Republic of Korea), in cooperation with the Republic of Chile. The Joint ALMA Observatory is operated by ESO, AUI/NRAO and NAOJ. The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc. N.K. acknowledges support from the Department of Science and Technology via a Swarnajayanti Fellowship (DST/SJF/PSA-01/2012-13).
Paper: 2017ApJ...836..152L (acknowledgments)
F.L. thanks G. Battaglia, F. Fraternali, G. Pezzulli, R. Sancisi, and M. Verheijen for many inspiring discussions over the years. Support for this work was provided by NASA through Hubble Fellowship grant # HST -HF2-51379.001-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 NAS5-26555. This publication was made possible through the support of a grant from the John Templeton Foundation. The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the John Templeton Foundation.
Paper: 2018ApJ...858....3R (acknowledgments)
Based on observations collected at Copernico telescope (Asiago, Italy) of the INAF—Osservatorio Astronomico di Padova. The William Hershel Telescope and its service programme are operated on the island of La Palma by the Isaac Newton Group of Telescopes in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofsica de Canarias (prog. ID: W/2017A/25, W/2017A/30, and SW2017a12). The Liverpool Telescope is operated on the island of La Palma by Liverpool John Moores University in the Spanish Observatorio del Roque de los Muchachos of the Instituto deAstrofisica de Canarias with financial support from the UK Science and Technology Facilities Council. The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement n. 320964 (WDTracer). Support for this work was provided by NASA through Hubble Fellowship grant # HST -HF2-51357.001-A, awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Incorporated, under NASA contract NAS5-26555. Facilities: 1.82-m Copernico(AFOSC) , 4.2-m WHT(ISIS) , Liverpool:2m .
Paper: 2017MNRAS.470L.122P (acknowledgments)
Acknowledgments We thank the referee for the useful discussion and comments that have greatly helped to improve this Letter. This Letter is based on data from the CALIFA Survey, funded by the Spanish Ministry of Science (grant ICTS-2009-10) and the Centro Astronómico Hispano-Alemán. This work has been supported by the Spanish Ministry of Science and Innovation under grants AYA2016-77237-C3-1-P, and Consolider-Ingenio CSD2010-00064; and by the Junta de Andalucía (FQM-108), and the AYA2014-53506-P grant, funded by the ‘Ministerio de Economía y Competitividad’ and by the ‘Fondo europeo de desarrollo regional FEDER’. RAM acknowledges support by the Swiss National Science Foundation. We acknowledge the contribution of Teide High-Performance Computing facilities. TeideHPC facilities are provided by the Instituto Tecnológico y de Energías Renovables (ITER, SA). URL: http://teidehpc.iter.es . IMV has been partially supported by MINECO AYA2014-583308-P. SFS thanks the Conacyt programmes 180125 and DGAPA IA100815.
Paper: 2017ApJ...850....9P (acknowledgments)
This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under grant No. DGE 1144083 and the National Science Foundation under grant No. 1616538. The National Solar Observatory is operated by the Association of Universities for Research in Astronomy under a cooperative agreement with the National Science Foundation. This work utilized the Janus supercomputer, which is supported by the National Science Foundation (award number CNS-0821794) and the University of Colorado Boulder. The Janus supercomputer is a joint effort of the University of Colorado Boulder, the University of Colorado Denver and the National Center for Atmospheric Research. The authors are grateful for the International Space Science Institute in Bern for hosting the International Team 335 “Toward New Models of Solar Spectral Irradiance Based on 3D MHD Simulations,” which resulted in fruitful discussions. The authors thank Matthias Rempel for providing the MHD snapshot, and both Han Uitenbroek and the referee for useful feedback to improve the quality of the work.
Paper: 2018MNRAS.478.1911P (acknowledgments)
ACKNOWLEDGEMENTS We thank J. Aguirre, A. Lidz, and A. Myers for helpful comments. AP was supported by a McWilliams Fellowship of the Bruce and Astrid McWilliams Center for Cosmology. SH is supported by DOE and NSF AST1412966. Part of the research described in this paper was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. This work is based on observations obtained with Planck ( http://www.esa.int/Planck ), an ESA science mission with instruments and contributions directly funded by ESA Member States, NASA, and Canada. 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: 2017MNRAS.469..968X (acknowledgments)
Acknowledgments LX and GDL acknowledge financial support from the MERAC foundation. MH acknowledges financial support from the European Research Council via an Advanced Grant under grant agreement no. 321323 NEOGAL.
Paper: 2018ApJ...865...42H (acknowledgments)
We thank the members of the ENIGMA group at the MPIA, as well as the members of office 217, for the fruitful discussions and helpful comments. We thank the anonymous referee for carefully reading our manuscript and for insightful comments and suggestions that significantly improved the quality of this work. Special thanks to Martin White for providing us with collisionless simulations. Some data presented in this work were obtained from the Keck Observatory Database of Ionized Absorbers toward QSOs (KODIAQ), which was funded through NASA ADAP grants NNX10AE84G and NNX16AF52G, along with NSF award number 1516777. This research used resources of the National Energy Research Scientific Computing Center (NERSC), which is supported by the Office of Science of the U.S. Department of Energy under contract No. DE-AC02-05CH11231. Calculations presented in this paper used the hydra and draco clusters of the Max Planck Computing and Data Facility (MPCDF, formerly known as RZG). MPCDF is a competence center of the Max Planck Society located in Garching (Germany).
Paper: 2018A&A...617A.121K (fulltext)
called NLTE equations) for non-monotonic velocity law. To our knowledge, there is no such code that is able to treat this problem in its full complexity. Therefore, to make the problem tractable, we calculate a mean value of the mass-loss rate in the region close to the star, where the wind blanketing originates, where ρ and v are the wind density and radial velocity in particular time. Most of the flux in the optical domain is emitted from the region below the sonic point, which typically appears at radii 1.01 − 1.02 R * in the numerical simulations. Therefore, we selected r 1 = 1.01 R * and r 2 = 1.02 R * . However, the final light curve does not significantly depend on the choice of r 1 and r 2 . As a result of this choice, in Eq. ( 1 ) we average over 50 grid points of hydrodynamical simulation. A plot of is given in Fig. 1 . Fig. 1. Mass-loss rate from the numerical simulations averaged over r ∈ [1.01 R * , 1.02 R * ] (see Eq. ( 1 )). 2.2. Global wind models The variations of the emergent flux with wind mass-loss rate were derived from spherically symmetric stationary METUJE global wind models ( Krtička Kubát 2017 ). The code calculates the wind model in a global (unified) approach that integrates the description of the hydrostatic photosphere and supersonic wind. The model solves the radiative transfer equation in the co-moving frame (CMF) with opacities and emissivities calculated using occupation numbers derived from the kinetic equilibrium (NLTE) equations. For given stellar parameters, the model enables us to predict the radial dependence of the density, velocity, and temperature from hydrodynamical equations and to derive the wind mass-loss rate and the stellar emergent flux that accounts for the wind blanketing. For our modelling we assumed a typical parameters of O stars corresponding to HD 191612 , T eff = 36 000 K, R * = 14.1 R ⊙ , and M = 29.2 M ⊙ . To model the dependence of the emergent flux on the mass-loss rate with fixed stellar parameters, we artificially scaled the radiative force in the wind. This yields a series of wind models and emergent fluxes parameterized by the wind mass-loss rate. Because the amount of the flux redistributed by the wind depends on the effective temperature, we expect slightly different dependence for stars with different temperature. However, because we are concerned with typical light variations, we limited our study to just one star. On the other hand, such selection affects only the amplitude of the light curve. The preliminary results derived for 300-1 model of Krtička Kubát (2017 , the model has parameters close to that used in hydrodynamical simulations) indicate that the amplitude of the variability due to the wind blanketing does not significantly depend on stellar parameters. The light variability is derived from a relation between the H p magnitudes and mass-loss rate ( Krtička 2016 , Eq. ( 2 )) where Δ F = 1.6 × 10 7 erg s −1 cm −2 , F 0 = 9.0 × 10 8 erg s −1 cm −2 is the emergent