adsabs/WIESP2022-NER huggingface dataset:
Paper: 2016A&A...586A..75S (fulltext)
wind. Thus, we simulate the transonic hydrodynamic planetary winds. At the Roche lobe height, all simulated atmospheres reach velocities between 10 and 20 km s. 4.2.1. Atmosphere of HD 209458 b First, we focus on the atmosphere of HD 209458 b, which is depicted by the green solid lines in Fig. 5 . Panel a shows how the density decreases from the boundary density of to cm. The extent of the Roche lobe for HD 209458 b is 4.2 above the substellar point and the sonic point is reached at 3.5. The optical depth for EUV photons (60 eV) reaches one at a height of 1.03. This height corresponds well with the atmospheric layer that experiences the maximum volume heating rate. Panel b in Fig. 5 shows that the absorption of XUV emission around the height of 1.03 increases the temperature. This raises the atmospheric scale height and the density gradient becomes more shallow above this height. The temperature reaches a maximum of 9100 K. The bulk velocity strongly increases along with the temperature in the lower atmosphere (see panel c). Panel d shows the net specific radiative heating rate throughout the atmosphere. We plot the specific heating rate, which is the heating rate per gram of material, because it clearly shows where the atmospheric material gains most of the energy for the escape. The net heating rate has a maximum close to the temperature maximum, but declines above 1.6 where the atmosphere is more strongly ionized. There is a distinct dip in the net heating rate at 1.15, which is caused by hydrogen line cooling. This can be seen in panel e, where we show the radiative heating and cooling rates separately as thin, solid lines. Subtracting the radiative cooling rate from the heating rate gives the net radiative-heating rate (solid thick line), which is displayed in panels d and e. Between 1.05 and 1.8 about 45% of the radiative heating produced by the absorption of XUV radiation is counterbalanced by hydrogen line emission, which is mainly Ly cooling. In panel e we further compare the radiative heating rate to the hydrodynamic sources and sinks of internal energy. In the atmosphere of HD 209458 b the advection of internal energy is a heat sink below 1.7, but acts as a heat source above this level, providing 50% of the energy in the upper thermosphere. The adiabatic expansion of the gas is a heat sink throughout the atmosphere. This term stands for the energy, which is converted into gravitational potential and kinetic energy. It now becomes clear why the temperature decreases in the upper thermosphere: Radiative heating becomes inefficient due to a high degree of ionization, but the adiabatic cooling term remains large. Therefore, the advected thermal energy is used to drive the expansion of the gas. Panel e also shows cooling due to thermal conduction, which is largest where the temperature increases most strongly, but it is not relevant in any of the simulations. In Fig. 6 the H+He atmosphere of HD 209458 b is depicted in the middle
Paper: 2021A&A...645A..49G (fulltext)
moderately warm ( T dust ≈ 50 K). With these conditions, the low-lying H 2 O lines at submm wavelengths (240 − 400 μ m) are efficiently pumped, but little absorption is produced in the far-IR with only significant absorption in the H 2 O lines at 75 and 108 μ m. Nevertheless, the inferred colums are more than enough to extinguish any line emission at short wavelengths, and indeed the Pa- α emission within r = 0.5 kpc primarily probes the western (near) side of the nuclear bar, with a morphology different from that of the continuum submm emission (Fig. 17 b). It is within the envelope region where the CO 2–1 line becomes very broad (Fig. 15 c), which is probably a direct consequence of the shocks produced by the inflowing gas and may be evidence of disordered motions that would eventually lead to a pseudobulge. High-lying molecular absorption lines in the far-IR are produced when the columns are so high that the far-IR continuum becomes optically thick ( González-Alfonso et al. 2015 ), and these conditions are also linked to the emission in the H 2 O448 line. In ESO 320-G030, a nuclear disk with projected radius of ≈40 pc attains these conditions, though still with moderately warm dust ( T dust ≈ 55 K). The disk is distorted, elongated in the direction of the bar, and highly turbulent (Δ V / V rot ≈ 1); it is thus expected to be geometrically thick (e.g., Cazzoli et al. 2020 ). At the center of the disk, an unresolved, extremely buried ( τ 100 ≫ 1) and very warm ( T dust ∼ 100 K for the far-IR photosphere; see González-Alfonso Sakamoto 2019 ) core component is identified from the absorption detected in very high-lying lines of H 2 O, of which the H 2 O 7 07 − 6 16 line at 71.95 μ m ( E lower = 640 K) is an excellent tracer. We estimate a core radius of R = 9 − 16 pc, but higher angular resolution observations are required to better determine its size. HCN vibrational emission has been recently detected in ESO 320-G030 (Falstad et al., in prep.), additionally indicating the presence of a very warm optically thick region. In such environments, trapping of IR radiation raises T dust and the mid-IR radiation density within the cocoon of dust, but the resulting SED does not show any enhanced mid-IR emission as only the photosphere is probed at mid- and even far-IR wavelengths ( González-Alfonso Sakamoto 2019 ). Because of their extreme extinction, the nature of these very compact nuclear components has been long debated; even X-rays and mid-IR high ionization tracers from a putative AGN are expected to be severely attenuated. ESO 320-G030 is undetected with the Swift /BAT all-sky survey observations 1 in the 14 − 195 keV band with a sensitivity of 8.4 × 10 −12 erg s −1 cm −2 , which translates into a luminosity of 6 × 10 8 L ⊙ . Assuming a ∼5% contribution to the bolometric AGN luminosity in the quoted band, the upper limit for L AGN is ≲10 10 L ⊙ ; however, absorption at 30 keV is still relevant for N H ∼ 10 25 cm −2 , and an AGN with ∼10% of the
Paper: 2015ApJ...811...99L (acknowledgments)
This work has been partially supported by the Italian Ministry of the University under grant RBFR082838 and “LNS-Astrofisica Nucleare (fondi premiali)” by PRIN-MIUR 2010-2011 ( Chemical and dynamical evolution of the Milky Way and Local Group galaxies , PI F. Matteucci), by PRIN-INAF 2012 ( The M4 Core Project with Hubble Space Telescope , PI L. Bedin), and by INFN ( Iniziativa specifica TAsP ).
Paper: 2019MNRAS.485.4045G (fulltext)
; Ghosh Chakrabarti 2018 ). So, Θ itself indicates (see Fig. 5 ), from its day-to-day time evolution, the arrival time lag, i.e. the size of the disc. It is shown recently by Ghosh et al. ( 2019 ) that the temporal evolution of RXTE /ASM soft and hard photon fluxes is, respectively, similar to that of disc and halo mass rates obtained from the TCAF-extracted RXTE /Proportional Counter Array (PCA) (2.5–25 keV) spectra. Also, during an outburst, the Comptonizing efficiency (CE) computed from ASM data behaves in a similar manner with the accretion rate ratio obtained from PCA data. According to TCAF, the Keplerian disc component is mainly responsible for the soft photon counts, whereas the halo component controls the hard photon counts. It is customary to assume soft and hard photons to represent multicolour blackbody distribution and power law, respectively (see Ghosh Chakrabarti 2018 ; Ghosh et al. 2019 ). Since TCAF is a general paradigm, it can be always utilized whether phenomenological descriptions such as power law plus blackbody fits the data already or not. Even if we have only ASM data, the knowledge of behaviour of the flows from TCAF enable us to choose Θ as the unique variable to classify the outbursts. Therefore, Θ is used for cross-correlation (CC) with individual fluxes, as the former represents relative change of one flux with respect to the other. So, the relative time lag between the hard flux and the soft flux of either photons or energy would be defined as (Ghosh Chakrabarti 2018 ), τ r > 0 implies that the disc radiation flux lags behind the halo radiation flux. Both evolve simultaneously if τ r = 0. Typical behaviour of Θ during a normal outburst is schematically shown in Fig. 4 . We wish to mention that while taking CCs, the direct hard flux versus soft flux correlation is not the proper quantity to discuss (see Fig. 6), because the hard flux does not depend on the soft flux alone. It also depends on the properties of the Compton cloud such as its size (CENBOL) and its optical depth. Furthermore, in an outburst, hard flux will always be seen increasing with the soft flux. So the lag between hard and soft, in general, would be seen to be zero. What is important is the rate at which two accreting masses change since these are guided by the viscosity in the halo and disc components. Since RXTE /ASM did not record X-ray data continuously from any particular source, there are gaps in the data, in particular, due to the annual solar constraints. We smoothed out the unevenness of the data interval by using a fortran code for interpolation. The fits files obtained from these daily light curves are used to produce CCs between Θ and two fluxes using crosscor task of heasoft/xronos package in order to obtain the time lags estimated from Θ. 3 RESULTS We present the photon energy fluxes, Θ-behaviour, their CCs, and most importantly, the hysteresis property of the standard Keplerian disc for showing difference in temporal and spectral
Paper: 2018ApJ...856..126C (fulltext)
scale of PSF, which causes correlation of the fluctuations in adjacent pixels; (e) estimating the “residual variance” from contaminating sources remaining in the masked image and subtracting this variance from the power spectrum amplitude to obtain the corrected SBF magnitude ; (f) adopting a value for from either an empirical or theoretical SBF calibration (generally based on galaxy color) to obtain the distance modulus, . For this NGVS SBF analysis, we adopted the sky background estimates and galaxy isophotal models described by Ferrarese et al. ( 2012 ). The large-scale residuals, still present in the frame after subtracting the galaxy model, were removed using the background map obtained with SExtractor (Bertin Arnouts 1996 ) adopting a mesh size ≈10 times the FWHM (Tonry et al. 1990 ; Cantiello et al. 2005 ). We refer to the image with the sky, galaxy model, and large-scale residuals all subtracted as the residual frame. The photometry of the external sources (stars, background galaxies, and GCs) was done by running SExtractor on the residual frame after masking saturated stars, very extended galaxies, and other large features that could be problematic for SExtractor. We used an input weight image that included the galaxy photometric noise as well as additional variance caused by the SBF (for details, see Jordán et al. 2004 ; Cantiello et al. 2005 ) to avoid detecting the fluctuations as objects themselves. The SExtractor MAG_AUTO measurements include roughly 90% of the light from faint sources; the aperture corrections for these magnitudes were obtained from a number of isolated sources in each frame using a curve-of-growth analysis out to large radii (Cantiello et al. 2009 , 2011b ). The cutouts of the NGVS images used for the analysis are wide on each side; on such scales the PSF variation is small enough that the typical rms scatter is ∼0.01 mag for the aperture corrections. 9 9 For galaxies close to MegaPrime image tile edges, where the PSF or the image quality might be rapidly changing on spatially small scales, we limited our aperture corrections, PSF selection, and SBF analysis to the regions with the best image quality. Once the catalog of sources had been derived, the next step was to fit the luminosity function of the sources, which was necessary in order to estimate the amount of contamination from unmasked faint sources in the residual frame. We fitted a source magnitude distribution to a model, including a combination of the GCLF and a power-law background galaxy luminosity function (examples are shown in Figure 1 , discussed below). As noted above, bright stars and the most extended sources had been masked and were therefore not present in the catalog. At these high Galactic latitudes, the surface density of fainter stars is small compared the GCs in the vicinity of bright galaxies. The best fit to the combined GCLF and galaxy luminosity function was used to derive the background fluctuation correction term, P r , as
Paper: 2017ApJ...836..176H (acknowledgments)
The authors would like to thank Marco Castellano, Dijana Vrbanec, Benedetta Ciardi, Darren Croton, and Manodeep Sinha for useful discussions and comments. The authors acknowledge Peter Creasey for permission to use his Python library as a basis for the computation of the power spectra, and Benedetta Ciardi for a collaboration in developing pCRASH. A.H. is supported under the Australian Research Council’s Discovery Project funding scheme (project number DP150102987). P.D. acknowledges support from the European Commission’s CO-FUND Rosalind Franklin program. C.M.T. is supported under the Australian Research Council’s Discovery Early Career Researcher funding scheme (project number DE140100316) and the Centre for All-sky Astrophysics (an Australian Research Council Centre of Excellence funded by grant CE110001020). Finally, this research was supported by the Munich Institute for Astro- and Particle Physics (MIAPP) of the DFG cluster of excellence “Origin and Structure of the Universe.”
Paper: 2017MNRAS.468..824B (acknowledgments)
Acknowledgments The authors thank D. Giannios for use of the numerical code. AP acknowledges support from an NWO Vidi Fellowship. The authors also thank the referee, Rosario Iaria, for useful comments.
Paper: 2018MNRAS.476.3310D (acknowledgments)
ACKNOWLEDGEMENTS We thank Srikara S (IISER Pune) for taking part in discussions during initial part of the work. PD thanks Nagendra Kumar for helpful discussions on QPOs. We thank the anonymous reviewer for thoughtful suggestions. This work is partly supported by an India–Israel joint research grant (6-10/2014[IC]) and by the ISRO project with research Grant No. ISTC/PPH/BMP/0362. PS and PD thank KITP for their participation in the program ‘Confronting MHD Theories of Accretion Disks with Observations’. This research was supported in part by the National Science Foundation under Grant No. NSF PHY-1125915. Some of the simulations were carried out on Cray XC40-SahasraT cluster at Supercomputing Education and Research Centre (SERC), IISc.
Paper: 2020MNRAS.492..405S (acknowledgments)
ACKNOWLEDGEMENTS SS and AI acknowledge support from the Royal Society. We acknowledge useful comments from the referee Javier Garcia that improved the paper. 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.
Paper: 2019A&A...622A...9M (fulltext)
one-to-one correspondence of the brightest H II regions and the brightest LOFAR emission neither spatially nor in flux/intensity. This may be an effect of the dust absorption, which affects the H α line flux in the disc. The number of H II regions that coincide with LOFAR emission are therefore at the front side of the galaxy. The H α bright central region is also the brightest region in radio continuum, implying efficient dust removal, probably due to a wind from this central region. There are several kiloparsec-sized radial filaments visible in the LoTSS image extending into the halo; see arrow marks in Fig. 12 . In most cases (#2, 3, 4, and 7) these filaments connect back to large H II regions in the disc of NGC 3556, or broader filaments (#1, 5, 6, and 8) connect to a large, bright region containing DIG. It is tempting to identify these filaments as magnetised chimneys from giant H II regions and more evolved, bright regions of DIG with still significant SNe activity. Despite the lower resolution and smaller signal-to-noise ratio, the overall morphology of the radial filaments extending into the halo resembles that of the starburst galaxy M82, see for example the unpublished 5 GHz map (NRAO News Release, 2014 February 3). The non-detection of a diffuse large-scale outflow in our H α data is most probably due to the relatively low sensitivity of our optical data. Still, the clear connection of non-thermal radio continuum filaments to large star-forming regions and regions of large diffuse H α emission implies an outflow/wind driven by the combined pressure from cosmic rays and hot thermal gas as result of SNe activity. Fig. 12. Sub-image measuring 9′ × 6′ of the high-resolution LoTSS tile containing NGC 3556 plotted as greyscale image; our continuum-subtracted H α image is overlaid as a pseudo-colour image (intensity scale rainbow: from low intensity = violet and blue to high intensity = red). North is up, east is left in the image. Several radio structures are marked and numbered. 4. Discussion As shown in Sect. 3 , the extent of the faint halo increases from high to low frequency. The radial extent, however, does not increase. This has been observed in many spiral edge-on galaxies (e.g. in the CHANG-ES sample) and can be interpreted as a cosmic-ray driven galactic wind ( Butsky Quinn 2018 ). Furthermore, the extent in the CHANG-ES maps is generally smaller than in the LOFAR map. This can be a result of the missing-spacing problem, where an interferometer does not “see” emission on angular scales above a certain size. For the D-array/ C -band combination, however, the largest angular scale is about 4′ in size 7 . This is comparable to the extent seen in the LOFAR map, so it is reasonable to assume that the halo would be seen in its entirety. Hence, we conclude that since the observed halo extent is smaller than in the 144 MHz map, the CRe did not propagate any further as a result of spectral ageing. As the top panel of Fig. 5 shows, the
Paper: 2015ApJ...806..271S (acknowledgments)
We are grateful to the referee for valuable comments. This work was supported by the NSFC under grants 11303016 and 11373023, and by the NKBRSF under grants 2011CB811402 and 2014CB744203.
Paper: 2018MNRAS.476.5377M (acknowledgments)
ACKNOWLEDGEMENTS The authors thank Dr M. Mollá for a scrupulous reading of the manuscript and many important remarks and suggestions which improved our paper.
Paper: 2019ApJ...886..107W (acknowledgments)
We appreciate the anonymous referee’s valuable comments. This work was supported by JSPS KAKENHI grant No. 18K18774. The authors thank Akio Inoue and Tohru Nagao for suggestions on metallicity and the dust-to-gas ratio in AGNs.
Paper: 2019MNRAS.486.3180K (fulltext)
population thought to result from satellite galaxy accretion (e.g. Forbes Bridges 2010 ; Leaman, VandenBerg Mendel 2013 ). These results suggest that the detailed age–metallicity distribution of GCs may be used to infer the accretion history of the host galaxy. The key ingredient enabling us to extract the wide range of information encoded in the Galactic GC population is the E-MOSAICS 1 project (Pfeffer et al. 2018 ; Kruijssen et al. 2019 ). Cluster formation and disruption are well known to depend on the local environmental conditions within galaxies (see recent reviews by Kruijssen 2014 ; Forbes et al. 2018 ). Modelling the co-formation and co-evolution of GC populations and their host galaxies thus requires following the spatial and kinematic phase-space distributions of the cluster populations self-consistently in their cosmological context. This prohibits the use of models based on semi-analytic or particle tagging techniques. Instead, E-MOSAICS self-consistently couples environmentally dependent sub-grid models for the formation, evolution, and tidal disruption of stellar clusters (MOSAICS, Kruijssen et al. 2011 , 2012 ; Pfeffer et al. 2018 ) to the locally resolved baryonic conditions obtained with the state-of-the-art cosmological galaxy formation model EAGLE (Schaye et al. 2015 ; Crain et al. 2015 ). The initial set of 25 hydrodynamical cosmological zoom-in simulations of Milky Way-mass galaxies allows us to follow the co-formation and co-evolution of galaxies and their GC populations. Specifically, we show in Kruijssen et al. ( 2019 ) that the distribution of GCs in age–metallicity space is a sensitive probe of the host galaxy’s formation and assembly history. The GC age–metallicity distributions obtained in E-MOSAICS exhibit strong galaxy-to-galaxy variations, resulting from differences in their evolutionary histories. By correlating several metrics describing the GC age–metallicity distributions of the 25 simulated galaxies with quantities describing their formation and assembly histories (such as halo properties, formation and assembly redshifts, stellar mass assembly time-scales, numbers of major and minor mergers, redshift distribution of mergers), we identify a set of 20 correlations with high statistical significance. These correlations show that the GC age–metallicity distribution is a sensitive probe of the host galaxy’s stellar mass growth, metal enrichment, and minor merger history. Moreover, it is shown that the mass dependence of galaxy evolution in age–metallicity space enables the use of individual GCs to infer the masses and metallicities of their natal galaxies as a function of redshift. We demonstrate that this can be used to reconstruct the merger tree of the host galaxy. Applying any of these individual results to the GC population of the Milky Way may already significantly increase our understanding of its formation and assembly history. In this paper, we take the comprehensive approach of employing the full
Paper: 2015ApJ...812...49H (acknowledgments)
The authors thank the anonymous referee for the thorough review and constructive suggestions that lead to an improvement of the paper. S.E.H. was supported by the National Research Foundation of Korea through grant 2007-0093860. H.K. was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education (2014R1A1A2057940). The work of D.R. was supported by the year of 2014 Research Fund of UNIST (1.140035.01).