adsabs/WIESP2022-NER huggingface dataset:
Paper: 2019A&A...621A..29V (acknowledgments)
CV thanks Andreas Floers, Stefan Lietzau and Markus Kromer for stimulating discussions during various stages of this project. The authors gratefully acknowledge Stefan Taubenberger for sharing his enormous expertise in the field of supernovae and for being a key member of the supernova cosmology project that motivated this work. CV would also like to thank Michael Klauser for providing help and guidance during the start of this project. The authors thank the anonymous reviewer for valuable comments. This work has been supported by the Transregional Collaborative Research Center TRR33 “The Dark Universe” of the Deutsche Forschungsgemeinschaft and by the Cluster of Excellence “Origin and Structure of the Universe” at Munich Technical University. SAS acknowledges support from STFC through grant, ST/P000312/1. Data analysis and visualization was performed using M ATPLOTLIB ( Hunter 2007 ), N UMPY ( Oliphant 2006 ) and S CIPY ( Jones et al. 2001 ).
Paper: 2015ApJ...808..158B (acknowledgments)
This work was supported by the cluster of excellence “Origin and Structure of the Universe.” Thanks to the referee for valuable comments that substantially improved the paper. I thank my CAST group at the University Observatory, Munich for inspiring discussions and suggestions. Special thanks also go to Edvige Corbelli, Avishai Dekel, Ken Freeman, Pavel Kroupa, Go Ogiya, Jerry Ostriker, Paolo Salucci, and David Spergel for interesting discussions and a careful reading of the manuscript. Finally, I would like to thank the Harvard Center for Astrophysics for support, lively discussions, and an infinite supply of coffee that was essential and the driver for finishing this paper.
Paper: 2016MNRAS.456L..16F (acknowledgments)
It is a pleasure to thank Seppo Mattila, Rubina Kotak, Nancy Elias-Rosa, Stephen Smartt, Anders Jerkstrand, John Eldridge and Justyn Maund for useful discussions and comments on this work, and Gerry Gilmore for ongoing support. We thank the anonymous referee for a careful reading of the Letter. This Letter is based on observations made with ESO Telescopes at the La Silla Paranal Observatory under programme ID 094.D-0351. This work was partly supported by the European Union FP7 programme through ERC grant number 320360.
Paper: 2020ApJ...896L..14B (fulltext)
midplane values n e0 and n CR0 for the electron densities. For (corresponding to ), , and , we have . This is large compared to the typical Galactic magnetic field strength of a few , so Faraday rotation effects are weak. We perform the line-of-sight integration by computing on a ( θ , φ ) mesh with 36 × 72 meshpoints for distances s from the observer going up to in steps of . 4.2.3. Results from the Mean-field Model In Figure 3 we show the results for Model B of Brandenburg Furuya ( 2020 ). In spite of the parameters being unrealistic for the Galaxy, there are characteristic features that are similar to what is seen in Figure 1 for the Galaxy: positive Q at φ = 0 and 180°, along with negative E at φ = 90° and 270°. The results for U and B are not immediately obvious because there are two nearly equally big patches of opposite sign in each hemisphere. Only after φ -averaging do we recognize a latitudinal dependence that is similar to that of the Galaxy; see Figure 4 . The observed sign of emerges only when we place the observer at a distance sufficiently far away from the Galactic center ( μ = A), while for smaller distances ( μ = B), the sign changes and the profile becomes similar to that shown in the top right panel of Figure 1 of Brandenburg ( 2019 ). Faraday rotation is weak, but it contributes a profile that is symmetric about the equator. This is because the global magnetic field has quadrupolar symmetry; see Brandenburg ( 2019 ) for a corresponding result for a dipolar field. Changing the sign of α 0 results in a qualitatively different (oscillatory) dynamo, but, to our surprise, it does not change the sign of . The sign only changes when the differential rotation changes and thereby the global Galactic spiral. Changing the signs of α 0 and Ω 0 simultaneously has the advantage of leaving the dynamo properties unchanged. Figure 3. Polarization results for the mean-field model with the Faraday rotation term in Equation ( 6 ) included. Top: and . Bottom: and . Figure 4. Azimuthally averaged polarization results for the mean-field model with Faraday rotation using (solid lines) and without Faraday rotation (dashed lines). Top: and . Bottom: and . The statistical error of the mean and the standard deviation are indicated by dark and light shades, respectively, except for panels (b) and (d), where only the former is shown. An important difference between model and observation is the fact that in our model, the amplitude of is several hundred times smaller than that of , while for the Galaxy, it is only about 10 times smaller; see Table 1 . We recall that the quadratic EE correlation for dust polarization was found to be about twice that of the BB correlation (Planck Collaboration 2016 ). This came as a major surprise (Kandel et al. 2017 ) and triggered numerous investigations trying to explain this (Kritsuk et al. 2018 ). In the present Letter, however, we have not studied quadratic correlations, but the signed functions E and B themselves.
Paper: 2019A&A...623A..17L (fulltext)
sets in some specific cases – in particular in the second outermost shell when using projct . We speculate that these discrepancies may be due to a combination of remaining calibration issues and artifacts propagated when projct is used. Nevertheless, in both cases the deprojected EPIC spectra clearly reveal the presence of central drops for the Fe, Si, S, Mg and Ca abundances. Despite the formal consistency reported above, we note that the uncertainties of the XMM-Newton abundances of Ar and Ca are much larger than the uncertainties of the Chandra measurements. This point is discussed in more detail in Sect. 3.5 . 3.5. Broad-band versus narrow-band fits Whereas fitting the spectra using the full energy band (i.e., typically ∼0.5–7 keV for Chandra ACIS) is the standard procedure for deriving the best-fit parameters, this approach may bias the metal abundance measurements. In fact, since the abundance of a given element is directly proportional to the equivalent width of its line (namely, the ratio between the total line flux and the continuum flux at the centroid energy of the line), incorrect determination of the continuum in the vicinity of the line would lead to incorrect measurement of the corresponding elemental abundance. Because no instrument is calibrated with infinite precision, some slight imperfections of the effective area may produce these local over- or underestimates of the continuum. In the case of very deep observations, that is, when statistical uncertainties become smaller than the above systematic effect, such a bias may become highly significant (e.g., Mernier et al. 2015 ; Simionescu et al. 2019 ). A good way to minimize such biases is to refit the spectra between several local energy bands, each of them including the K-shell emission line(s) used to derive the abundance of a given element as well as part of the surrounding continuum. In these “narrow-band” fits (by contrast to the above “broad-band” approach), the only parameters that were kept free were the (local) normalization and the abundance of the considered element. All the other parameters were fixed to the best-fit value of the broad-band fit. A comparison of the resulting narrow-band fit profiles with the ones obtained using broad-band fits (assuming a vgadem model and using dsdeproj ) is shown in Table 2 and Fig. 4 . We used the 1.5–2.8 keV energy range for Si and S, 2.9–3.5 keV for Ar, 3.3–4.3 keV for Ca, and 5.0–7.0 keV for Fe. Fig. 4. Deprojected profiles of Fe, Si, S, Ca, and Ar abundances, and the Ar/Fe (Fe taken from the broad-band fits) ratio, using broad- (red) and narrow-band (blue) fits, obtained using the vgadem model and the dsdeproj deprojection method. All errors are quoted at the 68.27% (1 σ ) confidence level based on . The blue data points have been shifted slightly on the X-axis for clarity. The narrow-band Fe profile in Fig. 4 is consistent with the broad-band profile and also shows a drop in the innermost two bins (at r ≲10 kpc). The
Paper: 2018ApJ...861...42B (fulltext)
between observed and calculated intensities expressed as a percentage of the observed intensity for all the spectral lines used in the emission measure analysis, except the those beyond 1000 Å. The data are plotted at the wavelength of the relevant line. We show the full line-list with wavelengths for cross-checking in Table 1 . Results are shown for all daily spectra analyzed (1103 observations). 3.2. Comments on the Accuracy of the Li-like Spectral Lines There is a caveat to our threshold condition. While the atomic structure of Li-like ions is very simple (three electrons only) and lines emitted from these ions are therefore expected to be spectroscopically accurate, they are well known to sometimes show anomalously large intensities (Dupree 1972 ; Judge et al. 1995 ). Based on off-limb observations from Hinode /EIS, where the solar corona is close to isothermal and so atomic data discrepancies are readily apparent, Warren et al. ( 2016 ) found that the contribution functions for some O vi lines need to be adjusted upward by a factor of 3.4 to bring them into agreement with other lines. Other work has found that these discrepancies are wavelength dependent (Muglach et al. 2010 ), and several studies have successfully used the longer wavelength O vi lines we use here for composition studies (Feldman et al. 1998 ; Landi Testa 2015 ). In our analysis, we also found that the Li-like O vi 1031.93 Å, O vi 1037.64 Å, Ne viii 770.42 Å, and Ne viii 780.38 Å observed line intensities were several factors brighter than the intensities calculated from the EM distribution. Excluding the Ne viii lines and adjusting the G ( T , n ) functions for O vi 1031.93 Å and O vi 1037.64 Å upward by the factor of 3.4 determined from EIS off-limb spectra by Warren et al. ( 2016 ) improves the minimization of the EM solution, and helps to anchor the distribution around their formation temperatures. We therefore make the adjustment solely for the purpose of determining the best EM solution. We make no adjustment for the subsequent abundance ratio correction since Ne viii is also Li-like and it is necessary to treat them consistently. Note also that the Warren et al. ( 2016 ) adjustment factor was computed using off-limb EIS spectra taken near solar minimum in 2007, November. Our analysis suggests that this factor is also representative of the rest of the solar cycle, since the computed O vi line intensities are maintained within 25% of the observed intensities in all the daily spectra. If there was a cycle dependent variation greater than 25% in this adjustment factor, perhaps due to the presence or absence of the high temperature component in the emission measure found by Morgan Taroyan ( 2017 ), then it would be detected in our analysis as a discrepancy between the calculated and observed intensities. It is interesting that the same adjustment factor works well for both our EVE analysis and the independent EIS off-limb spectral analysis. For a further cross-check of
Paper: 2021MNRAS.505.2309C (fulltext)
synchrotron emission. The XMM–Newton upper limit (black arrow) and the Fermi -LAT data (red squares) are from this work. The other data are taken from Aliu et al. ( 2014 ) (VERITAS – green diamonds) and Abdo et al. ( 2007 ) (MILAGRO – pink hexagons). The blue and grey butterflies are the HAWC models from Abeysekara et al. ( 2020 ) and from Abeysekara et al. ( 2017 ), plotted for comparison, but not used in the fit. We performed a binned analysis with five bins per energy decade and spatial pixel size of . In the maximum likelihood fitting, the normalization parameter of all the sources within 3° of the ROI centre, as well as the diffuse emission components, was left free to vary. Instead the parameters of all the other sources at more than 3° were fixed to the values given in the 4FGL catalogue (Abdollahi et al. 2020 ). To describe the spatial morphology of MGRO J1908+06, we used the VERITAS emission region at 3σ level (i.e. the outermost contour in Fig. 1 ), while for the spectral model we assumed a power law with photon index Γ = 1.6. This leads to a detection significance in the energy band considered. The γ-ray flux was obtained by binning the γ-ray data in the range from 10 to 1000 GeV into four energy intervals, and performing a binned likelihood analysis in each energy bin. The resulting Fermi -LAT SED is plotted in Fig. 4 . 3.3 X-ray analysis To study the X-ray emission in the vicinity of PSR J1907+0602, we used a 52 ks long observation carried out on 2010 April 26 with the XMM–Newton satellite. We analysed the data of the European Photon Imaging Camera (EPIC)-Metal Oxide Semiconductor (MOS) instrument that was operated in full frame imaging mode and with the medium thickness optical filter. We excluded time intervals with high background, resulting in net exposure times of 36 and 38 ks for the two MOS cameras. Using the Extended Source Analysis Software ( esas 3 ), we extracted the spectra from a circular region of 5 arcmin radius centred at the position of PSR J1907+0602 (excluding a circle of 30 arcsec radius around the source) and from a concentric annular region with radii 5 and 12.5 arcmin. The latter was used to estimate the X-ray background (which in this sky region is dominated by the Galactic ridge diffuse emission). Comparison of the two spectra showed no evidence for diffuse emission associated with PSR J1907+0602, with an upper limit (at 95 per cent confidence level) of 1.2 × 10 −15 erg cm −2 s −1 arcmin −2 on the surface brightness in the 1–10 keV energy range. 4 ORIGIN OF THE γ-RAY EMISSION Emission at TeV energies indicates the presence of ultrarelativistic particles that, in principle, can produce it through inverse Compton (IC) scattering of the cosmic microwave background (CMB), infrared (IR), and/or starlight seed photons by electrons, or through the decay of neutral pions resulting from proton–proton (and/or other nuclei) interactions. In this section, we first explore the possibility that a single mechanism is
Paper: 2015A&A...578A..52D (acknowledgments)
We thank the anonymous referee for constructive comments that helped to improve the paper. This work is partially supported by the Bundesministerium für Wirtschaft und Technologie through the Deutsches Zentrum für Luft und Raumfahrt (grant FKZ 50 OG 1301). V.D. and A.S. thank the Deutsches Zentrum für Luft- und Raumfahrt (DLR) and Deutsche Forschungsgemeinschaft (DFG) for financial support (grant DLR 50 OR 0702). Partial support comes from NewCompStar, COST Action MP1304. Part of this work is based on the publicly available “GBM Accreting Pulsar Histories” provided by the Fermi team.
Paper: 2021A&A...647A.133A (fulltext)
) but in the range of the H α -excess galaxies at redshifts ∼4−5 that were recently identified in the Spitzer UltraVISTA ultra-deep stripes survey (SMUVS survey; Caputi et al. 2017 ). An important fraction (15%) of the SMUVS galaxies in the 9.4 ≤ log( M stellar [ M ⊙ ]) ≤ 11.0 mass range appear to be in a starburst phase with SFR of hundreds to thousands M ⊙ yr −1 and sSFR well above 24 Gyr −1 , and up to 120 Gyr −1 . The SMUVS galaxies in the starburst phase account for more than 50% of the cosmic SFR density at redshifts ∼3.9−4.9. Therefore, extreme UV luminous galaxies such as BOSS-EUVLG1 could represent the short lived phase of this class of H α -excess galaxies, and could be important contributors to the SFR density at intermediate and high redshifts. BOSS-EUVLG1, therefore, brings on the opportunity to investigate the presence and properties of ionized gas outflows for the first time in this class of extreme star-forming galaxies. In this article, we report the detection of the ionized phase of the outflow in BOSS-EUVLG1 using the H α emission line. Section 2 describes the observations and calibrations of the H α spectrum. Section 3 presents the analysis of H α emission and rest-frame UV absorption lines. The results of the analysis and interpretation as outflowing material are presented in Sect. 4 , including the overall kinematic and mass (Sect. 4.1 ), the outflowing mass rate and mass-loading factor (Sect. 4.2 ), the nature of the energy source (Sect. 4.3 ), and the mass escape fraction into the intergalactic medium (Sect. 4.4 ). The results are discussed in Sect. 5 , focusing in the comparison with low- and high- z SFGs (Sect. 5.1 ), the multi-phase nature of the outflows (Sect. 5.2 ), and the possibility of detecting these outflows with the future X-ray observatory Advanced Telescope for High ENergy Astrophysics (ATHENA; Sect. 5.3 ). Finally, Sect. 6 present the summary and outlook. We adopted H 0 = 67.7 km s −1 Mpc −1 and Ω m = 0.307 ( Planck Collaboration XIII 2016 ) as cosmological parameters and the Salpeter initial mass function (IMF; Salpeter 1955 ) throughout this paper. A factor of 1.66 ( Newman et al. 2012 ) is used to convert the SFRs and stellar masses ( M stellar ) from a Chabrier (2003) to a Salpeter (1955) IMF when using some published data. 2. Observations Near-infrared (Near-IR) long-slit spectroscopy of BOSS-EUVLG1 was obtained with the Espectrógrafo Multiobjeto Infra-Rojo (EMIR) instrument on the 10.4 m Gran Telescopio Canarias (GTC). Observations were taken in two service mode nights – 2020 February 10 and May 8 – in bright Moon and subarcsec seeing (≃0.8′′ full width half maximum) conditions, as part of the GTC program GTCMULTIPLE2E-19A (PI: R. Marques-Chaves). The observations used the K g r i s m with a dispersion of 1.71 Å pix −1 and a 0.8′′-wide long-slit, providing a spectral resolution of 82 km s −1 at ∼2.25 μm. The slit was centered on a bright ( K = 17.43 ± 0.02, AB) reference star (SDSS
Paper: 2018MNRAS.481.3148E (fulltext)
, and replace the bulge with a rotating bar using the analytic model from Long Murali ( 1992 ). For the bar parameters, we take a mass of 5 × 10 9 M ⊙ , a length of a = 3 kpc, a width of b = 1 kpc, and a present-day orientation of θ 0 = −30° (as in Hattori et al. 2016 ; Erkal et al. 2017 ). We vary the pattern speed between 0 and −100 km s −1 kpc −1 in steps of 0.1 km s −1 kpc −1 (where negative pattern speeds are prograde with the MW disc), more than encompassing the observed constraints on the pattern speed (e.g. Bland-Hawthorn Gerhard 2016 ). We find that the bar has a small effect on the stream, giving slightly different stream tracks depending on the pattern speed of the bar. Thus, the properties of the bar will also need to be marginalized over in order to measure the LMC mass from the misaligned proper motions. 5.4 Effect of LMC on other streams in the Milky Way The predicted misalignment between the stream track and proper motions should also be seen in any streams which receive a large tidal force from the LMC. Given the orbit of the LMC, we expect that the most affected streams will likely be in the southern Galactic hemisphere, e.g. the 11 streams newly discovered in Shipp et al. ( 2018 ), the Phoenix stream (Balbinot et al. 2016 ), the Jet stream (Jethwa et al. 2017 ), or the atlas stream (Koposov et al. 2014 ). In order to determine which are the most affected, each stream will need to be evolved in the presence of the LMC. Interestingly, some works have proposed assuming that stream tracks are aligned with their proper motions to measure the Sun’s proper motion (Majewski et al. 2006 ; Malhan Ibata 2017 ). If the significant misalignment predicted for the Tuc III stream is verified, this means that these methods must account for the perturbation of the LMC or only use streams which have received a negligible perturbation (possibly those in the northern Galactic hemisphere). 5.5 Effect of Tuc III on the Milky Way disc Our analysis in Section 3 found that Tuc III is on a very eccentric orbit with a pericentre of ∼1.8 kpc. This close passage of Tuc III with the MW could induce perturbations in the inner disc of our Galaxy (Feldmann Spolyar 2015 ). For these perturbations to be significant, Tuc III would have needed a substantial mass of ∼10 8 −10 9 M ⊙ and hence would have to be a dwarf galaxy. Given the current data, it is difficult to determine whether Tuc III is a globular cluster or a dwarf (see Li et al. in preparation). However, assuming that Tuc III is a dwarf, if Tuc III’s recent pericentre was its first approach to the MW (and thus Tuc III still retained the bulk of its dark matter halo) there could be detectable perturbations in the MW centre. We note that although we have assumed a disruption age of 3 Gyr, during which our best-fitting orbits have experienced multiple pericentric passages (e.g. Fig. 3 ), our model is not designed to determine when Tuc III began disrupting. Instead, it is designed to match the observed
Paper: 2017A&A...605A...2E (acknowledgments)
Based on observations made with ESO Telescopes at the La Silla Paranal Observatory under program 87.C-0040. We thank the anonymous reviewer for helpful comments and suggestions that helped us to improve our manuscript.
Paper: 2017MNRAS.466.1903G (acknowledgments)
Acknowledgments The SILCC project details are available at http://www.astro.uni-koeln.de/silcc . All simulations have been performed on the Odin and Hydra clusters hosted by the Max Planck Computing Data Facility ( http://www.mpcdf.mpg.de/ ). We thank M. Anderson, C. Federrath, J. Mackey, M. M. Mac Low, E. Pellegrini, and X. Shi for useful discussions and Leroy etal. ( 2008 ) and Ekstrm etal. ( 2012 ) for making their data publicly available. AG, SW, TN, PG, SCOG, RSK, and TP acknowledge the Deutsche Forschungsgemeinschaft (DFG) for funding through the SPP 1573 The Physics of the Interstellar Medium. SW acknowledges funding by the Bonn-Cologne-Graduate School, by SFB 956 The conditions and impact of star formation, and from the European Research Council under the European Communitys Framework Programme FP8 via the ERC Starting Grant RADFEEDBACK (project number 679852). TN acknowledges support by the DFG cluster of excellence Origin and Structure of the Universe. RW acknowledges support by the Czech Science Foundation project 15-06012S and by the institutional project RVO: 67985815. RSK and SCOG acknowledge support from the DFG via SFB 881 The Milky Way System (sub-projects B1, B2, and B8). RSK acknowledges support from the European Research Council under the European Communitys Seventh Framework Programme (FP7/2007-2013) via the ERC Advanced Grant STARLIGHT (project number 339177). The software used in this work was in part developed by the DOE NNSA-ASC OASCR Flash Center at the University of Chicago. We thank C. Karch for the program package fy and M. Turk and the yt community for the yt project (Turk etal. 2011 ).