adsabs/WIESP2022-NER huggingface dataset:
Paper: 2020MNRAS.499.1140A (fulltext)
pointings (what we will call translational dithering), and with multiple angles due to offsets of the camera rotational angles (what we will call rotational dithering). These aspects of the observing strategy can be used in addition to traditional methods to mitigate WL systematics. Related studies that explore possible translational dithers to determine how the LSST observing strategy can be used to reduce systematic errors in measurements of the LSS have already been conducted (Carroll et al. 2014 ; Awan et al. 2016 ; LSST Science Collaboration et al. 2017 ). In this paper, we study how different aspects of the observing strategy help mitigate the additive shear bias, and rank a set of simulated strategies based on their performance for WL systematics (while the statistical trade-offs are not addressed here). In Section 2 , we explain WL and its systematics in more detail; in Section 3 , we present a representative set of LSST survey strategies and separately the three translational dithering strategies that are studied in this paper, although our method can be easily applied to new observing strategies in the future as they are released. In Section 4 , we present our methodology, using both a direct effect on the cosmic shear bias, and simpler statistical tests of uniformity; and in Section 5 , we analyse the results, and discuss them in the context of the 2018 call 2 for proposals on optimizing the LSST observing strategy for different science cases. 2 BACKGROUND This section includes background information on WL, the observable quantities that are measured and used to constrain cosmological parameters, and the observational systematics that can be affected by different choices in observing strategy. 2.1 WL measurements WL is a ubiquitous statistical effect that modifies the light profiles of galaxies as the light rays from those galaxies pass by other mass along the line of sight before they are observed. WL by the LSS of the universe distorts the shapes and sizes of galaxies according to the distortion matrix: where κ is the convergence, a measure of the magnification due to WL, and γ 1 , γ 2 are spin-2 shear, a measure of the shape distortion due to WL (Bartelmann Schneider 2001 ). The distortion matrix can be used to transform lensed coordinates into unlensed coordinates, such that for unlensed and lensed positions on the sky and , (Mandelbaum et al. 2015 ). The cosmic shear signal can be measured using shear–shear correlation functions between pairs of galaxies, as follows: where t and × are the tangential and cross components of the shear, θ is the angular separation on the sky, φ is the polar angle (Kilbinger 2015 ), refers to the expected value, and R () refers to the real component. We only consider ξ + in our analysis because the biases on ξ − are much closer to 0, and so not much work is needed to mitigate them (Jarvis et al. 2016 ). It is clear from the definition of these correlation functions that any bias in the measured
Paper: 2019A&A...624A..27G (acknowledgments)
Acknowledgements This work was supported by WOW from INAF through the Progetti Premiali funding scheme of the Italian Ministry of Education, University, and Research. This research has made use of data and/or software provided by the High Energy Astrophysics Science Archive Research Center (HEASARC), which is a service of the Astrophysics Science Division at NASA/GSFC and the High Energy Astrophysics Division of the Smithsonian Astrophysical Observatory. M.P. and I.R. acknowledge support from the Spanish Ministry of Economy and Competitiveness (MINECO) and the Fondo Europeo de Desarrollo Regional (FEDER) through grant ESP2016-80435-C2-1-R, as well as the support of the Generalitat de Catalunya/CERCA programme. J.I.G.H., R.R., and B.T.P. acknowledge financial support from the Spanish Ministry project MINECO AYA2017-86389-P. B.T.P. acknowledges Fundación La Caixa for the financial support received in the form of a Ph.D. contract. J.I.G.H. acknowledges financial support from the Spanish MINECO under the 2013 Ramón y Cajal program MINECO RYC-2013-14875. A.S.M. acknowledges financial support from the Swiss National Science Foundation (SNSF). G.S. acknowledges financial support from “Accordo ASI-INAF” No. 2013-016-R.0 July 9, 2013, and July 9, 2015. A.S.M. acknowledges financial support from the Swiss National Science Foundation (SNSF). M.Pi. gratefully acknowledges the support from the European Union Seventh Framework Programme (FP7/2007-2013) under Grant agreement no. 313014 (ETAEARTH).
Paper: 2018MNRAS.475..839S (acknowledgments)
Acknowledgements This work has made use of the VALD data base, operated at Uppsala University, the Institute of Astronomy RAS in Moscow, and the University of Vienna. This work is based on observations obtained at the Canada–France–Hawaii Telescope (CFHT) that is operated by the National Research Council of Canada, the Institut National des Sciences de l'Univers of the Centre National de la Recherche Scientifique of France, and the University of Hawaii. All authors acknowledge the advice and assistance provided on this and related projects by the members of the BinaMIcS and MiMeS collaborations. MS acknowledges the financial support provided by the European Southern Observatory studentship program in Santiago, Chile. MS and GAW acknowledge support from the Natural Sciences and Engineering Research Council of Canada (NSERC). EA acknowledges financial support from the Programme National de Physique Stellaire (PNPS) of INSU/CNRS. We acknowledge the Canadian Astronomy Data Centre (CADC). This project used the facilities of SIMBAD.
Paper: 2018ApJ...855...65H (acknowledgments)
We greatly acknowledge the anonymous referee for comments. We thank Dr. Shuhong Yang for many discussions, suggestions, and comments, and Dr. Xiaoshuai Zhu for helping to handle the HMI full-disk vector magnetic field. This research is supported by the National Natural Science Foundation of China (41474150, 41627806, 41474149, 41404135, and 41274178). Z.H. thanks the China Postdoctoral Science Foundation and the Young Scholar Program of Shandong University, Weihai (2017WHWLJH07). IRIS is a NASA small explorer mission developed and operated by LMSAL with mission operations executed at NASA Ames Research center and major contributions to downlink communications funded by the Norwegian Space Center through an ESA PRODEX contract. Courtesy of NASA/SDO, the AIA and HMI science teams, and JSOC.
Paper: 2018A&A...609A.116R (acknowledgments)
L.R.-D. acknowledges financial support from the Centre National d’Etudes Spatiales (CNES) fellowship programme. This work has made use of data from the European Space Agency (ESA) mission Gaia ( https://www.cosmos.esa.int/gaia ), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium ). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. This publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation. L.R.-D. acknowledges support from Agence Nationale de la Recherche through the STILISM project (ANR-12-BS05-0016-02). This research has also made use of VizieR databases operated at the Centre de Données astronomiques de Strasbourg (CDS) in France.
Paper: 2018MNRAS.477L..66M (acknowledgments)
Acknowledgements We thank the referee for providing very useful comments which helped to improve the paper. We thank the staff of the GMRT that made these observations possible. GMRT is run by the National Centre for Radio Astrophysics of the Tata Institute of Fundamental Research.
Paper: 2021ApJ...913..130H (fulltext)
simulation results revealed a variation in the plasma conditions in the vicinity of the planetary magnetosphere with changing wind conditions. Since many of the runs produced similar results, we present here a limited selection of four cases representative of the different stellar wind regimes experienced by TRAPPIST-1e throughout its orbit: two sub-Alfvénic regions, a super-Alfvénic region, and the transition between the sub-Alfvénic and super-Alfvénic regimes (Figure 3 ). The stellar wind conditions corresponding to these simulations are listed in Table 3 . Figure 3. Magnetospheric structure of a planet situated at the orbit of TRAPPIST-1e. The planet is represented by a magenta isosurface, and it was modeled to have a magnetic field strength of 0.3 G and an evaporative outflow with a temperature of 10 4 K, escape velocity 10 km s −1 , and density of 4 × 10 8 amu cm −3 . The stellar wind flows from the positive x -axis. The solutions are for the sub-Alfvénic (top panels), transition (bottom left), and super-Alfvénic (bottom right) stellar wind cases. The stellar wind conditions were extracted from a 3D MHD simulation of TRAPPIST-1a by Garraffo et al. ( 2017 ). The color scale shows an equatorial projection (plane z = 0) of the particle number density. Planetary magnetic field lines connected to the planet are shown in white, while stellar field lines are shown in cyan. The planetary outflow is denoted by velocity streamlines (black with arrows). Note that the lines transition in color as they pass through the equatorial plane. The motion of the planet is toward the positive y -axis. All of the stellar wind conditions experienced by TRAPPIST-1e are much more extreme than the solar wind conditions experienced by Earth. In the region surrounding the planets, the stellar wind speeds reach close to 1400 km s −1 and plasma densities reach 10 3 –10 5 times the solar value at 1 au (Garraffo et al. 2017 ). We consider the effect of these strong stellar wind conditions on a planetary outflow in Figure 3 . In each case, the planet is represented by a magenta isosurface at the center of the GM domain. The z = 0 plane of number density shows the planetary outflow, which is strongly dependent on the stellar wind conditions and therefore varies substantially between the different cases. Under all four stellar wind regimes, the planetary magnetic field lines are strongly advected by the wind, causing changes in the magnetospheric configuration, which results in an asymmetric outflow in three dimensions. The shape of the planet’s outflow is strongly influenced by the direction and relative magnitudes of the components of both the magnetic field and velocity of the incoming stellar wind. By comparing cases 1 and 2, where the planet is within the sub-Alfvénic region, the stellar wind components (shown in Table 3 ) are broadly similar apart from the y and z magnetic field components. As can be seen in Figure 3 , this produces wholly different magnetospheric
Paper: 2018A&A...610A...2C (acknowledgments)
N.J.C. is grateful to the Paris Observatory for funding as an invited researcher at the IMCCE. We thank the FP7-ESPaCE European program for funding under the agreement No. 263466. N.J.C. and C.D.M. thank the Science and Technology Facilities Council (Grant No. ST/P000622/1) for financial support. This work was also supported by the International Space Science Institute (ISSI). The authors thank their colleagues in the Encelade working group at the IMCCE of the Paris Observatory ( http://www.issibern.ch/teams/saturnastrometry/?page%20id=21 ), and the members and associates of the Cassini ISS team. We are heavily indebted to the authors of the SPICE software toolkit, without whom the development of Caviar would have been a considerably more difficult task.
Paper: 2021MNRAS.501.3061T (fulltext)
per degree of freedom lies in the range 0.4–3.0 increases from 1098 to 1123 when fitting this simpler model. We therefore proceed in the knowledge that the excess rest-frame 1–3 μ m emission in our sample of quasars can be adequately described using a fixed temperature blackbody in our SED model, consistent with emission from dust at its sublimation temperature (e.g. Barvainis 1987 ). However, we ascribe no further significance to the exact value of this temperature, noting instead that it is merely the temperature describing the blackbody which best describes the infrared colours of the quasars, and not necessarily the exact physical temperature of the emitting dust. In particular, we note that this temperature is degenerate with the slope of the power-law continuum (−1.84) which we assume in our model, and a different continuum slope would lead to a slightly different hot dust temperature. Our subsequent results would be qualitatively unchanged. 3.4 Primary sample Fixing the blackbody temperature allows us to fit our model to higher redshift objects, where we no longer have two independent data points probing the hottest dust emission. For what we hereafter refer to as our ‘primary’ sample, we take all quasars in the redshift range 1.2 z 2.0 (see Appendix D for a discussion of the limitations of higher redshift objects). For our primary sample, the W2 band probes rest-frame wavelengths ≈2 μ m where the hot dust blackbody is expected to be the dominant contributor to the total flux. We require detections in all of the JKW12 bands. To avoid biases against hot-dust-faint objects which might drop out of one or more of these bands we restrict our primary sample to Y 19.3, where the sample is better than 95 per cent complete in all UKIDSS bands, giving a total of 12 294 objects. We have verified that restricting our sample to a brighter flux limit does not change any of the subsequent results. When constructing the sample, only 243 objects are lost due to missing unWISE data, meaning our primary sample is more than 98 per cent complete in W1 and W2 . Some of these objects will be missed due to crowded fields as the WISE point spread function is significantly broader than that of SDSS. However, we cannot rule out the possibility that a small fraction of objects are lost due to intrinsically faint fluxes in the rest-frame near-infrared. We fit our primary sample with two free parameters in the model, fixing T blackbody = 1280 K and allowing just the E ( B − V ) and normalization of the hot dust component to vary. The median χ 2 per degree of freedom when fitting our model to this sample is 1.30. We show in Appendix E that our subsequent results remain unchanged when instead using a hotter or cooler blackbody in our model quasar SED. 5022 objects from our primary sample with z > 1.56 also have C iv line information from Rankine et al. ( 2020 ). As the sample is restricted to z 2.0, Mg ii emission is present in the SDSS spectra to enable black hole
Paper: 2018MNRAS.474.3817K (acknowledgments)
Acknowledgements We thank Andrei Mesinger for making 21cmfast publicly available and an anonymous referee for helpful comments and suggestions that improved this paper. This research was supported by National Science Foundation (NSF) grants AST-1333360 and AST-1614333, NASA grant NNX17AG23G, and Hubble theory grants HST-AR-13895 and HST-AR-14326.
Paper: 2019MNRAS.485L..89S (fulltext)
ellipticals, reported in Fig. 3 , also occurs within the uncertainties considering five different redshift intervals for the ellipticals, from z = 0.1 to z = 0.35, each containing ∼200 sources. This is apparent in Fig. 3 , where the cases of ellipticals at 0.1 z 0.15 and at 0.1 z 0.33 are reported. Figure 3. Average excess surface density of galaxies (detected in i band, with magnitude threshold M * + 2) as a function of the projected distance from the BL Lac objects (green filled circles), inactive ellipticals matched in redshift with the BLL sample (orange filled triangles), FR Is (violet open stars) and inactive ellipticals (grey open triangles) matched in redshift with the FR I sample. The errors are the standard errors of the mean. The sample of FR I radio galaxies is limited to 0.1 z 0.15 (see Section 2 ), therefore, we can only do a direct comparison with the sample of inactive ellipticals in the same redshift range. We found that within ∼0.5 Mpc the excess density of the FR I radio galaxies is a factor of 2 larger than that of ellipticals (see Fig. 3 ). Since we have shown that the galaxy environment of ellipticals does not change in the redshift range 0.1 z 0.35, we are confident that also the comparison of environment between BLL and FR I radio galaxies is reliable. The result is illustrated in Fig. 3 . In particular, within 0.5 Mpc the excess density is ∼13 Mpc −2 for the FR Is, while for the BLLs it is ∼6 Mpc −2 . 5 CONCLUSIONS We find that the galaxy environment of low-redshift BL Lac objects is indistinguishable from that of low-redshift inactive ellipticals of comparable galaxy luminosity. This result is similar to that found by Karhunen et al. ( 2014 ) and Sandrinelli et al. ( 2018 ) who considered large samples of low-redshift quasi-stellar objects (QSOs), finding an overdensity within 0.5 Mpc of ∼1.1. So it seems that in the local Universe BLLs, quasars and inactive ellipticals are similar in terms of surrounding galaxies. We also find that the clustering of galaxies around radio galaxies of FR I type is on average a factor of ∼2 richer than that of BL Lac objects. In spite of the difference in the redshift distribution this difference appears robust since no variation of galaxy environment is found for inactive elliptical galaxies of same luminosity up to z ∼ 0.3 (see details in Section 4 ). This result is further illustrated in Fig. 4 , where we report the cumulative distributions of the excess density for the two classes of objects within the projected distance 350 kpc. The medians are 5.7 and 13.6 Mpc −2 for BLLs and FR Is, respectively, and the Kolmogorov–Smirnov (KS) test yields a p -value 4 × 10 −4 . The population of BLLs is positioned at lower excess densities with respect FR Is. Figure 4. The comparison of the cumulative distributions of excess galaxy density (within 350 kpc) of BL Lac objects (0.1 z 0.33) and FR I radio galaxies (0.1 z 0.15). The two distribution are significantly different (see text). The
Paper: 2015A&A...575A..60M (acknowledgments)
The authors thank Hideyuki Saio for his careful reading of the manuscript, as well as Luc Dessart and Ben Davies for interesting suggestions. G.M. acknowledges support from the Swiss National Science Foundation (project number 200020-146401) and thanks for the hospitality of the Lowell Observatory, where part of this work was done. C.G. acknowledges support from the European Research Council under the European Unions Seventh Framework Programme (FP/20072013)/ERC Grant Agreement No. 306901. P.M.’s involvement was supported by the National Science Foundation through AST-1008020.
Paper: 2018MNRAS.475.1549M (acknowledgments)
ACKNOWLEDGEMENTS This work is dedicated in memory of K. N. V. S. Kishore Babu, a dear friend who inspired KBM to pursue Astrophysics. We are grateful to Peter Behroozi, Mark Brodwin, Philip Hopkins, Kartheik Iyer, Allison Kirkpatrick, Viraj Pandya, Vicente Rodriguez-Gomez, Brett Salmon, and Raymond Simons for helpful comments and discussions during different manifestations of this work. Special thanks to Daniel Shanaberger for carefully reading the manuscript, thanks to Gillen Brown, Cody Ciaschi, Bandon Decker, Benjamin Floyd, Ripon Saha, and Madalyn Weston for their valuable inputs during the University of Missouri Kansas City (UMKC) Galaxy Evolution Group discussions. DHM and KBM acknowledge support from the Missouri Consortium of National Aeronautics and Space Administration (NASA)’s National Space Grant College and Fellowship Program, and funding from the University of Missouri Research Board. RSS acknowledges support from the Downsbrough family, and from the Simons Foundation. SL acknowledges support from the National Research Foundation of Korea grant, no. 2017R1A3A3001362, funded by the Korea government. This work is based on observations taken by the CANDELS Multi-Cycle Treasury Program with the NASA/ESA HST , which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555. Support for Program number HST-GO-12060 was provided by NASA through a grant from the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Incorporated, under NASA contract NAS5-26555. This publication makes use of the SDSS. Funding for the creation and distribution of the SDSS Archive has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, the US Department of Energy, the NASA, the Japanese Monbukagakusho, the Max Planck Society, and the Higher Education Funding Council for England. This publication also made use of NASA’s Astrophysics Data System Bibliographic Services, topcat (Tools for OPerations on Catalogues And Tables, Taylor 2005 ), the core python package for the astronomy community (Astropy 1.2.1; Astropy Collaboration et al. 2013 ).
Paper: 2021ApJ...908L..31O (fulltext)
physical motion of a single massive star-forming region. 3.1. Two Morphological Classes of FIRE-CMZs The FIRE galaxies presented here cover a range of morphologies in their centers because these simulations were not designed to match the detailed structural properties of our Galactic center. Within the sample of seven galaxies, we see two distinct classes of central morphology in their fiery cores (gas and star formation distributions within R ≈ 1.5 kpc): (a) “Asymmetric/Bursty” (m12b, m12c, m12f, and m12w): Large, asymmetric gas clouds and star-forming complexes are seen. Star formation is concentrated in intense starbursts whose feedback dramatically shapes the local gas environment (see m12b, upper subfigure of Figure 1 ). Two simulations falling in this category (m12b and m12f) simultaneously match the MW CMZ gas and SFR measurements. The two others (m12c and m12w) do not simultaneously have SFR and dense gas tracers within the central 145 pc at any point in this time window. (b) “Smooth” (m12i, m12m, and m12r): Gas and star formation is smoothly distributed within the galactic centers, with clear feeding of gas into center, and a cirrus of star formation (see m12m, lower subfigure of Figure 1 ). Feedback events do not dramatically alter the local gas environment, as the feedback is relatively dispersed across their centers. Interestingly, none of the galaxies here exhibit the ring structures, presumed to be long-lived, seen by studies of the central regions of other spiral galaxies and the MW CMZ (Kormendy Kennicutt 2004 ; Molinari et al. 2011 ). We note the lack of strong bars in the centers of any of these FIRE galaxies at this time (m12m did develop a strong bar around z ≈ 0.2, but it does not survive to z = 0; Debattista et al. 2019 ); without the presence of bars in these simulations at z = 0, we cannot speak to the dynamical importance of bars in producing central galactic environments similar to the MW CMZ. Other work has highlighted the potential impacts of bars in funneling gas core-ward and forming rings (Sormani et al. 2015 , 2018 ). However, bar-induced effects would likely push these simulated galactic centers toward more asymmetric states, supporting the idea that bursty, rather than steady-state, star formation is necessary to explain MW CMZ observations. Specifically, Sormani et al. ( 2018 ) showed that the gas flow in a barred potential naturally becomes turbulent and asymmetric, even in the absence of any type of stellar feedback. And so, we leave it to future work to investigate the gas flows driven in FIRE galaxies by the bars that form at higher redshift. The structures in the centers of the FIRE galaxies appear to be fairly transient in nature, existing for ≲10 Myr (similar to the GMC lifetimes seen in these simulations more broadly by Benincasa et al. 2020 ). We should be clear: spiral structures do exist core-ward in these simulations (see the clear presence of spiral arms in both m12b and m12m in Figure 1 ). In