adsabs/WIESP2022-NER huggingface dataset:
Paper: 2019ApJS..240...37L (fulltext)
model that simulates moist convection and cloud formation across various planetary conditions. Using a regional nonhydrostatic model to study moist convection is standard practice for Earth’s atmosphere, and many numerical models—named cloud-resolving models (CRMs) or large eddy simulations (LES)—have been developed accordingly (Pielke et al. 1992 ; Bryan Fritsch 2002 ; Khairoutdinov Randall 2003 ; Pressel et al. 2015 ). Similar nonhydrostatic models have been developed for Mars (Rafkin et al. 2001 ), Jupiter (Hueso Sánchez-Lavega 2001 ; Sugiyama et al. 2014 ), and Saturn (Hueso Sánchez-Lavega 2004 ), but they lack a well-documented comparison against an accepted nonlinear solution, which seems to be the first step in developing a robust numerical model. Because there are no standard tests of nonhydrostatic models for planets other than Earth, we will primarily perform simulations against standard tests for Earth-like conditions. Then, we perform an idealized simulation of the Jovian atmosphere in radiative-convective equilibrium (RCE) to study moist convection in hydrogen atmospheres. The structure of this work is organized as follows. Section 2 is devoted to the equation of motion, which includes dry air, vapors, clouds, and precipitation. Section 3 discusses the basic microphysics scheme employed in the model. Section 4 describes the numerical schemes that are designed for simulating atmospheric flows. Section 5 provides a series of benchmark tests against known solutions in the literature. Section 6 performs an idealized RCE simulation of the Jovian atmosphere. Section 7 concludes and outlines the future applications. To make the notations consistent and clear, major symbols used in this article are summarized in Appendix A for reference. 2. Equation of Motion We solve the most generic form of the equation of motion, the fully compressible Euler equations, to avoid unnecessary assumptions that are valid only for a particular type of planet. Though Euler equations can be written in many mathematically equivalent forms, they are different when discretized and implemented in a numerical model. Bryan Fritsch ( 2002 ) have compared five different ways of implementing the Euler equations, using potential temperature, equivalent potential temperature, and liquid water potential temperature. They concluded that the form of governing equations used in a numerical model has a profound effect on the simulation of a warm rising bubble. Satoh ( 2002 ) pointed out that in a model with diabatic forcing, the change in the domain integral of total energy is generally different from energy gain/loss from the boundaries if the potential temperature is used as the prognostic variable, which causes an error of the energy budget that accumulates with time. Furthermore, the expressions of potential temperature and equivalent potential temperature become complicated when the heat capacity of the atmosphere varies with temperature or when multiple condensing
Paper: 2018MNRAS.477L..55A (fulltext)
and calibrated with the use of miriad (Sault, Teuben Wright 1995 ). miriad was also used to perform phase and target self-calibration as well as final imaging of each configuration. The images were then primary beam corrected and exported to casa (Common Astronomy Software Applications) for processing. The 6 km and 750 m images were analysed within casa to determine flux densities and ejecta dimensions. The final set of images created had varying resolutions. The 6 km pointing at 5.5 GHz had a beam size of 2.92 × 1.54 arcsec (PA −2.50°) and at 9 GHz, a beam size of 1.71 × 0.99 arcsec (PA 0.79°). Images created from the 750 m pointing had a beam size of 13.79 × 6.98 arcsec (PA 5.04°) at 5.5 GHz, and 6.98 × 4.44 arcsec (PA 6.28°) at 9 GHz. Calibration and imaging is still on-going for the 1.5 km pointings at both spectral windows. A full combination of all the data is underway, with results from the concatenated data set to be provided in a future work (Andrews, in preparation). In this letter we focus on the presence of asymmetric spatially extended emission associated with all but one of the cool super/hypergiants, seen in the 5.5 GHz observations at the 6 km pointing. Clark et al. ( 1998 ) previously identified a cometary nebula around the RSG Wd1-26, with D10 confirming similar nebulosity around a second RSG Wd1-20, and an elliptical structure around a third RSG, Wd1-237, as well as more compact but still extended emission around three of the YHGs, Wd1-4a, -12a, and -265. The greater sensitivity of our new observations reveals striking additional detail for these structures, while resolving the nebulae associated with the last RSG, Wd1-75 and two further YHGS, Wd1-16, and -32. This leaves only a single cluster YHG, Wd1-8, with no detection at any mm or radio frequency. In Fig. 1 we present 5.5 GHz maps of these six stars, while Fig. 2 presents an optical/radio montage indicating the nebulae location and orientation. Figure 1. Shown are images of the YHGs and RSGs and their associated extended emission, from the 5.5 GHz observations at 6 km. Sources are the YHGs Wd1-4a (top − left) , Wd1-12a (top − centre) , Wd1-265 (top − right) , Wd1-16a (middle − left) , and Wd1-32 (centre) . These images are followed by the RSGs, Wd1-20 (middle − right) , Wd1-26 (bottom − left) , Wd-237 (bottom − centre) , and Wd1-75 (bottom − right) . The colourscale shows the hypergiants from the 5.5 GHz observations at the 6 km pointing, with the overlaid contours from 100 GHz ALMA observations of the cluster with a resolution of 750 × 570 mas (Fenech et al. 2018 ). W265 was out of the field of view for ALMA, so is overlaid with contours of the 9 GHz ATCA observations from the 6 km pointing. The contour levels of the ALMA observations are −1, 1, 1.414, 2, 2.828, 4, 5.656, 8, 11.31, 16, 22.62, 32, 45.25, 64, and 90.50 × 3σ (σ = 52.4 Jy for Wd1-4a, 40.0 Jy for Wd1-12a, 24.3 Jy for Wd1-16a, 28.1 Jy for Wd1-32, 30.5 Jy for Wd1-20, 63.7 Jy for Wd1-26, 31.9 Jy for Wd1-237
Paper: 2015A&A...581A.120B (acknowledgments)
We thank the anonymous referee for the very useful suggestions that helped us improve this work. R.H.B. acknowledges support by FONDECYT Regular project No. 1120668. A.R.L. is grateful for financial support from ALMA-CONICYT Fund, and Dirección de Investigación of Universidad de La Serena through project DIULS REGULAR PR13144. J.L.N.C. also acknowledges financial support from the ALMA-CONICYT postdoctoral program No. 31120026. M.S. acknowledges support from ESO-Chile Joint Committee and “Becas Chile de Postdoctorado en el Extranjero” project No. 74150088. V.F. acknowledges support from the ESO-Chile Joint Committee and DIULS. M.H. acknowledges the support of the Basal PFB-06 and the Milenio Milky Way Nucleus. We gratefully acknowledge use of data from the ESO Public Survey programme ID 179.B-2002, taken with the VISTA telescope, data products from the Cambridge Astronomical Survey Unit, and funding from the FONDAP Center for Astrophysics 15010003, the BASAL CATA Center for Astrophysics and Associated Technologies PFB-06, and the Millennium Institute of Astrophysics MAS. D.M. acknowledge financial support from CONICYT by Proyecto FONDECYT Regular No. 1130196. R.K.S. acknowledges support from CNPq/Brazil through projects 310636/2013-2 and 481468/2013-7. This research has made use of SIMBAD, VizieR, and “Aladin sky atlas” operated and developed at CDS, Strasbourg Observatory, France. Also, this research has made use of NASA’s Astrophysics Data System.
Paper: 2019MNRAS.483.1802T (acknowledgments)
ACKNOWLEDGEMENTS The authors acknowledge contribution from the grant CTA–SKA, ‘Probing particle acceleration and gamma-ray propagation with CTA and its precursors’ (PI F. Tavecchio) of the Istituto Nazionale di Astrofisica (INAF). This research has made 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. We gratefully acknowledge financial support from the agencies and organizations listed here: http://www.cta-observatory.org/consortium_acknowledgments . This research made use of ctools, a community-developed analysis package for Imaging Air Cherenkov Telescope data. ctools is based on GammaLib, a community-developed toolbox for the high-level analysis of astronomical gamma-ray data. This research has made use of the CTA instrument response functions provided by the CTA Consortium and Observatory, see https://www.cta-observatory.org/science/cta-performance/ (version prod3b-v1) for more details. This paper has gone through internal review by the CTA Consortium.
Paper: 2017MNRAS.470..561D (fulltext)
Several molecular clouds and two star formation regions, Sgr B1 and Sgr B2, have been marked in the top panel. In the bottom panel, H ii regions in the GC are labelled, such as H1-8 (Yusef-Zadeh Morris 1987 ). In addition, new H ii regions, identified from our HST /NICMOS Paschen- survey, are outlined in an ellipse, two circles and boxes. Besides H2, several well-known H ii regions, as well as newly discovered ones (Wang etal. 2010 ), fall on to the orbit of molecular clouds and could represent the star formation induced by their pericentre passages. First, we consider H3, H4, H6 and H7, among the eight H ii regions (H 18) identified by Yusef-Zadeh Morris ( 1987 ) in the region between the Arches cluster and Sgr A*. Dong etal. ( 2015 ) show the presence of a single evolved massive star in each centre of H5 and H8. They find that the radial velocities of these stars are significantly different from those of nearby ionized and neutral gas. This indicates that the stars are likely interlopers and did not form in situ . In the other four H ii regions, H3, H4, H6 and H7, no evolved massive stars have been found, although the possibility exists that there are still embedded massive main-sequence stars in these H ii regions. The massive main-sequence stars normally have hydrogen or helium absorption lines. Therefore, they cannot be identified by their Paschen- emission lines in the work by Dong etal. ( 2012 ). Another possibility is that the hydrogen emission lines from the central evolved massive stars are diluted by the emission from the surrounding dust, like the dusty WC stars (Dong etal. 2012 ). Furthermore, H6 and H7 with a size of 0.1pc could be ultracompact H ii regions. Compared to H2, the embedded stars could be less massive and therefore neither have enough ionization luminosities nor have they had time to disperse the surrounding dense molecular gas. Secondly, let us consider several new H ii regions identified by our HST /NICMOS Paschen- survey in the region Galactic West to Sgr A* (see the circles, ellipse and boxes in the bottom panel of Fig. 14 ). The detailed Paschen- image of the H ii region enclosed by the ellipse can be found in fig. 3 of Wang etal. ( 2010 ). All of these regions contain evolved massive stars, such as WN, Ofpe/WN9, WC9d, B supergiant and their candidates (Muno etal. 2006 ; Cotera etal. 1999 ; Mauerhan etal. 2010a , b ; Dong etal. 2012 ). Some of them are close to the molecular cloud orbit, which include those marked by the ellipse and the two circles. Therefore, they may be molecular clouds that have experienced star formation induced by the pericentre passage around Sgr A*. The two regions marked by the boxes are somewhat off the orbit and may have different origins. In conclusion, we have demonstrated that star clusters associated with the H ii regions, aided by the CMD analysis, could help us constrain their ages and the star formation history in the GC. 5 SUMMARY In this work, we have mapped the radial
Paper: 2018ApJS..237...21M (fulltext)
types is generally similar throughout. That said, we note two small biases: (i) cool stars (K stars and the only M star of the sample) have in general a small presence in the subsamples; and (ii) when the density is in the relation, there is a larger contribution of F-stars and G-stars, since asteroseismology provides most of its data for these stellar types. Table 8 Percentage of Stars in the Different Subsets Used for Obtaining the Regressions with Different Spectral Types 5.2. Linear Regression Consistency In addition to using R 2 , relative accuracy, and relative precision as the main statistics for studying the quality of the regressions, we have also developed additional consistency tests to ensure that the linear regressions are representative of the observational data. In Figure 7 , we show q – q plots of the 38 selected relations selected in a form to show whether the standardized residuals are normally distributed. The ordered standardized residuals are plotted on the ordinate of each plot, while the expected order statistics from a standard normal distribution are on the abscissa. Points close to the straight line are consistent with a normal distribution. In this figure we can see that all the relations do in general follow this straight line. Therefore, the use of linear regression is justified. Only in a few cases are there extreme departures from this straight line, but in general the departures are not statistically significant. Figure 7. q – q plots of the 38 relations. See the text for details. In Figure 8 we present the residuals as a function of the fitted values of these 38 relations. Any clear trend in these residuals can be a signature of inaccurate or inefficient regression. We have also added a LOESS (local polynomial regression) curve to guide the eye. In this figure we can see that, in general, there are no clear trends in the distributions of the residuals. In every plot, the main body of points is randomly distributed around the value zero. There are a few extreme cases, but they contain only a small percentage of the observational set. The impact of these values on the regression coefficients is analyzed in the next figure. Figure 8. Residuals vs. the fitted values of the 38 relations. The line is a LOESS curve to guide the eye. See the text for details. In Figure 9 we present a final and more complex consistency test. Here, we analyze the influence of every observational point in the regression coefficients. This influence is calculated using the Cook's distance (Sheather 2009 , D i ). This distance is calculated as a combination of the residual and the leverage (or how isolated a value is) for every point. The plots of Figure 9 show the standardized residuals as a function of the leverage, and the Cook's distance is represented by the size of the points. According to Weisberg ( 2005 ), “... if the largest value of D i is substantially less than one, deletion of a case will not change the estimate ... by much.”
Paper: 2018ApJ...860...72M (acknowledgments)
We thank the referee for the helpful suggestions. We acknowledge the use of the public data from the Fermi data archives. This work is supported by the National Basic Research Program (“973” Program) of China (grant No. 2014CB845800), the National Natural Science Foundation of China (grants No. 11725314, 11673068, 11433009, 11543005, 11603076, 11573014, 11533003, 11473012, 11722324, 11603003, 11633001, and 11690024), the Youth Innovation Promotion Association (2011231 and 2017366), the Key Research Program of Frontier Sciences (QYZDB-SSW-SYS005), the Strategic Priority Research Program “Multi-waveband gravitational-wave Universe” (grant No. XDB23000000) of the Chinese Academy of Sciences, and the Natural Science Foundation of Jiangsu Province (grant No. BK20161096). J.J.G. is supported by the National Postdoctoral Program for Innovative Talents (grant No. BX201700115) and China Postdoctoral Science Foundation funded project (grant No. 2017M620199). B.B.Z. acknowledges the support from the National Thousand Young Talents program of China.
Paper: 2019ApJ...876..146L (fulltext)
et al. 2007 ; Thornton et al. 2013 ; Petroff et al. 2015 , 2016 ). Although the progenitors of these events are debated, the large values of the dispersion measure (DM) in excess of the Galactic value of these events (Dolag et al. 2015 ) suggest they are extragalactic or even cosmological in origin. The localization of the repeating burst FRB 121102 at z ∼ 0.19 has firmly established the cosmological origin of at least this event (Scholz et al. 2016 ; Spitler et al. 2016 ; Chatterjee et al. 2017 ; Marcote et al. 2017 ; Tendulkar et al. 2017 ). The observed DM of an FRB therefore should at least have a significant contribution from the intergalactic medium (IGM). Based on the average DM– z relation, one can estimate that the FRBs are typically at distances of the order of a gigaparsec (Ioka 2003 ; Inoue 2004 ; Deng Zhang 2014 ; Zheng et al. 2014 ; Zhang 2018 ). The cosmological origin of FRBs allows them to become promising tools to study the universe and fundamental physics, e.g., probing baryon density and spatial distribution (Deng Zhang 2014 ; Mcquinn 2014 ), constraining the dark energy equation of state (Gao et al. 2014 ; Zhou et al. 2014 ; Weltman et al. 2018 ), probing the ionization history of the universe (Deng Zhang 2014 ; Zheng et al. 2014 ), tracing the large-scale structure of the universe (Masui Sigurdson 2015 ), testing Einstein’s equivalence principle (Wei et al. 2015 ; Nusser 2016 ; Tingay Kaplan 2016 ), constraining the rest mass of the photon (Wu et al. 2016 ; Shao Zhang 2017 ), measuring the cosmic proper distance (Yu Wang 2017 ), as well as constraining the magnetic fields in the IGM (Akahori et al. 2016 ). Thanks to another two properties of these mysterious transients, i.e., narrow durations (∼(1–10) ms; Lorimer et al. 2007 ; Keane et al. 2011 ; Thornton et al. 2013 ; Spitler et al. 2014 ; Petroff et al. 2015 ; Ravi et al. 2015 ; Champion et al. 2016 ; Petroff et al. 2016 ; Spitler et al. 2016 ) and a high event rate (∼10 3 –10 4 per day all sky; Thornton et al. 2013 ; Champion et al. 2016 ), lensed FRBs have been proposed as a probe of compact dark matter (Muñoz et al. 2016 ; Wang Wang 2018 ), motion of the FRB source (Dai Lu 2017 ), as well as precision cosmology (Li et al. 2018 ). In practice, there are some issues that hinder the application of FRBs for cosmological purposes. First, it is not easy to measure the redshifts of most FRBs. Localizing them is possible if they repeat, but it is possible that only a fraction of FRBs repeat (Palaniswamy et al. 2018 ). Recently, the Canadian Hydrogen Intensity Mapping Experiment (CHIME; using the CHIME/FRB instrument) has reported detections of 13 FRBs during a precommissioning phase (The CHIME/FRB Collaboration 2019a ). It is more exciting that 1 of the 13 FRBs is a second source of repeaters, which suggests that CHIME/FRB and other wide-field sensitive radio telescopes will find a substantial population of repeating FRBs (The CHIME/FRB Collaboration 2019b ). The second
Paper: 2019MNRAS.482..921S (acknowledgments)
ACKNOWLEDGEMENTS We thank Alis Deason, Kathryn Johnston, and Wyn Evans for insightful comments that helped to improve the quality of the paper. A special thanks to the anonymous referee who carefully read our manuscript and provided useful comments. 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 no. 308024, and PIFI Grant no. 2018PM0050. ITS and SEK thank the Center for Computational Astrophysics for hospitality.
Paper: 2017MNRAS.465..302M (acknowledgments)
This paper is based on data collected at Subaru Telescope, which is operated by the National Astronomical Observatory of Japan. GM and II are supported by Japan Society for the Promotion of Science KAKENHI Grant number: 24244018. GM acknowledges support by the Swedish Research Council (Vetenskapsrådet). AKI is supported by JSPS KAKENHI Grant number: 26287034. A part of this research has made use of the NASA/IPAC Infrared Science Archive, which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA. We extend a warm thank you to Yuichi Matsuda, Katsuki Kousai, Elisabeta Lusso, Cristian Saez, and Alice Shapley for providing us with their spectra, and with some clarifications on their work and helpful advice. We also thank Andrea Grazian for useful suggestions and comments on this work.
Paper: 2018ApJ...867..134J (fulltext)
two consecutive timesteps, it was flagged as cosmic-ray pixel and its value was substituted with the median value from the two previous and two posterior timesteps. This rather conservative approach made sure that we did not filter long-lasting events (more than two timesteps), but some cosmic rays remain, as can be seen in the figures. The left panel of Figure 2 shows the temporal evolution of the flare loops during the gradual phase between 16:01 and 16:47 UT when the WL continuum emission enhancement is observed by HMI. In the right column, we can see the variation of the specific intensity of the WL continuum radiation along the horizontal cut marked by a red dotted line through the flare loop after subtraction of pre-flare images. We later convert these intensities into electron densities and can thus also determine the maximum electron density n e in the flare loops. Figure 2. Temporal evolution of SDO /HMI WL loops and their intensity. The left panel shows the HMI WL image with a cut through the flare loop (dotted red line). The solid line in the right panel shows calibrated intensities with the pre-flare subtracted in CGS units along the marked red dotted line. The dashed line shows the pre-flare intensity divided by 10. We further coaligned the SDO /HMI data with all EUV channels of the SDO /AIA data. These channels cover the temperature range between 5 × 10 4 and 2 × 10 7 K by observing the transition region and corona (Lemen et al. 2012 ). The spatial resolution of AIA is 12, while for SDO /HMI it is 1′′ and the temporal resolution is 12 s for AIA images and 45 s for HMI observations. 3. Multi-thermal Loops Seen by <italic>SDO</italic>/AIA Apart from the SDO /HMI WL evolution, we also examine the behavior of the flare loops in various SDO /AIA channels. The AIA images clearly show a multi-thermal nature of the observed loop arcade and we can deduce spatial correlations between loops in different AIA channels and those detected by HMI in the WL. In this section, we provide a qualitative description of the multi-thermal behavior and discuss possible mechanisms responsible for the formation of AIA diagnostics. Most AIA channels and a pre-flare subtracted HMI image are shown in Figure 3 . In this HMI image, the cosmic rays were intentionally not removed to show their prevalence. We also plot the intensity variations along one cut through the loop system (red dotted line in Figure 3 ). The absolute intensity on the y axis refers only to HMI, all AIA signals were scaled to have their maximum at an arbitrary value. Figure 3. Example of flare loops of AR 12673 on the west limb on September 10, 2017 at 16:20:03.8 UT in SDO /HMI (upper left plot, in this case without a correction for cosmic rays) and various SDO /AIA passbands (labeled in their titles). In the HMI panel, a pre-flare image from 15:35:48.8 UT was subtracted. HMI loop contours (marked in blue) are overlaid on all images. The emission along the red dotted line is shown for all