adsabs/WIESP2022-NER huggingface dataset:
Paper: 2016ApJ...829L...7G (fulltext)
are from MERLIN 5 GHz observations of the radio jet (Gallimore et al. 2004 ); the MERLIN beam is 4.2 pc FWHM. Upper right: spectral map from a simulation of a bipolar outflow with the axis tilted 5° from the plane of the sky and rotated to PA 33° (see the text for details). Colors are as for the left panel. The outflow axis of ionized gas traced by optical emission lines in the narrow-line region is inclined 5° out of the plane of the sky (Crenshaw Kraemer 2000 ), and we assume the same for the CO outflow. Can such a small inclination produce the red–blue spatial separation observed in CO? To test this possibility we conducted a numerical simulation of a bipolar outflow. We employ a truncated cone geometry with a disk base diameter of 1 pc (comparable to the H 2 O maser disk), 4.4 pc total bicone height (based on the spread of CO features in Figure 2 ), and half-opening angle of 30°. To model the outflow, we randomly placed a total of 10 4 clumps inside the cone. Clumps were evenly distributed in cylindrical radius ρ (i.e., radius projected onto the disk plane) and distance along the polar axis. The direction of motion for a clump is vertical for clumps directly above and below the disk (i.e., clumps with ρ ≤ 0.5 pc) and radial from the edge of the disk for clumps with ρ > 0.5 pc. We further assume uniform acceleration from 30 km s −1 at the molecular disk to 800 km s −1 at the cone height; these values were selected from interactive trials to give a reasonable match to the observations. Finally, all clumps are equally luminous point sources of CO emission, added as beam-shaped, two-dimensional Gaussians to the planes of a simulated data cube. The cone was then inclined by 5°, and we repeated the cube analyses on the simulated data. To simulate the effects of measurement uncertainty, each measured peak position was displaced randomly, assuming 0.5 pc errors, comparable to the relative, observed position uncertainties. The simulation results shown in the right panel of Figure 2 broadly reproduce a parsec-scale asymmetry of redshifted and blueshifted peaks similar to that observed (left panel). This simple simulation was not meant to replicate any physical model or explain every aspect of the data; in particular, the systemic-velocity emission is concentrated to the east, at odds with the random distribution we use. Our simulation is only meant to demonstrate that the small 5° tilt detected in narrow-line observations is sufficient to produce the red–blue asymmetry of the excited CO emission. In addition to the outflow component described above, we also find evidence for rotation consistent with the compact H 2 O maser disk. Figure 3 shows the position–velocity ( p – v ) diagram constructed by slicing the CO spectral line cube along the axis tracing the extended systemic emission. Surface brightnesses were averaged within the three-pixel extraction width (green dashed lines in Figure 1 ). The data were smoothed using a Savitzky–Golay
Paper: 2018MNRAS.476.5579X (acknowledgments)
ACKNOWLEDGEMENTS We thank Prof. W. A. Coles and the anonymous referee for very helpful discussions on the interpretation of curvature variation. This work was supported by the National Natural Science Foundation of China (U15311243), the National Basic Research Program of China and the 973 Program (2015CB857101, XDB23010200, 11690024, 11373011, 11303093, U1431113, 11178001 and 11573008). KJL is supported by the Max-Planck Partner Group.
Paper: 2017ApJ...846...74P (fulltext)
but not part of the interacting pair (UGC 10549, z = 0.009, 50 kpc projected separation). The integrated spectrum shows a somewhat complex profile, with the velocity of the peak emission at ≳50 km s −1 lower velocity than the redshifts of the two components of dm1647+21. This peak corresponds to the redshift of UGC 10549, suggesting a substantial amount of the single-dish H i flux is associated with that galaxy. In support of this interpretation of the single-dish profile, follow-up interferometric observations with the Very Large Array (VLA) reveal a clumpy H i distribution in dm1647+21 and emission associated with UGC 10549 (S. Stierwalt et al. 2017, in preparation). Unfortunately, the VLA observations (taken in the B-array) do not recover the total single-dish H i flux, so we cannot reliably separate the single-dish H i mass into contributions from dm1647+21 and UGC 10549. Considering the uncertain distribution of the H i mass, the single-dish measurement implies an upper limit to the gas depletion time of 2 Gyr when considering only the SFR of dm1647+21. The true gas depletion time for dm1647+21 is likely shorter than this estimate. 3.3. ISM Properties We use the line images created from the MUSE data to construct optical line ratio maps, based on classic optical diagnostic plots (e.g., Baldwin et al. 1981 ; Veilleux Osterbrock 1987 ; Kewley et al. 2006 ). Maps of [O iii ]/H β , [N ii ]/H α , and [S ii ]/H α are shown in Figure 2 . The system-integrated values for these ratios are: log 10 ([O iii ]/H β ) = 0.51, log 10 ([N ii ]/H α ) = −1.8, and log 10 ([S ii ]/H α ) = −1.0. In Figure 3 , we show the line diagnostic diagrams with the distribution of values from Figure 2 and the source separation lines from Kewley et al. ( 2006 ). The line ratios in the ratio maps and diagnostic diagrams are all consistent with excitation from star formation, and we see no evidence for LINER-like or Seyfert emission. Figure 2. Optical line ratio images. First row, from left to right: [O iii ]/H β , [N ii ]/H α , [S ii ]/H α . Second row, from left to right: A H α and [S ii ] 6718/[S ii ] 6732. The ratio maps were all masked to the fainter of the two lines (Figure 1 ). No extinction corrections have been applied. Figure 3. Optical line diagnostic diagrams based on the narrow-band images in Figure 2 . Left: [O iii ]/H β vs. [N ii ]/H α . Right: [O iii ]/H β vs. [S ii ]/H α . The colored contours and small points show the distribution of values for individual 02 × 02 spaxels in the data cube; the number in the bottom left gives the number of spaxels shown in each panel. The plotted spaxels are those with a ≥5 σ detection in [N ii ] 6585 (left) or [S ii ] 6718 + 6732 (right). The cyan crosses mark the locations of the three brightest clumps identified from the H α map (Section 3.2 , 15 diameter apertures). The colored lines are the Kewley et al. ( 2006 ) separations between star-forming galaxies, Seyferts, and LINERs. The line ratios are consistent with
Paper: 2018ApJ...865..116I (fulltext)
events for both the pn and MOS. The events detected in the two MOS cameras were combined into a single data set, and we used averaged response files. Since with the ML analysis it is possible to derive an accurate estimate of the background at the source position, it was not necessary to remove time intervals of high background. We applied the ML in a circular region positioned to avoid the gaps between the CCD chips (radius of 60, center at R.A. = 11 h 54 m 232, decl. = −62°49′47′′). For the spectral extraction we fixed the source position at the coordinates found by the ML in the pn+MOS image in the 0.4–2 keV range (R.A. = 11 h 54 m 204, decl. = −62°50′044). This position is consistent with that found with the SAS pipeline. In the energy range 0.4–2 keV the source was detected with 113 ± 21 counts (pn) and 66 ± 15 counts (MOS), which correspond to a total count rate of (3.4 ± 0.5) × 10 −3 count s −1 . The energy bins for the spectral analysis were chosen from the requirement to have a signal-to-noise ratio greater than 2.5 σ in each spectral channel. This resulted in four energy bins for the pn and three for the MOS. Below 0.4 keV and above 2 keV, the source detection was below our significance threshold; therefore we derived upper limits on the source counts in these energy bins. 3. Possible Optical Counterparts In the Gaia database there are no stars closer than 4′′ to the corrected X-ray position; see Figure 1 . The closest object, at 406, is Gaia DR 2 5334588220496359424 which has g = 17.48. A slightly brighter star, Gaia DR2 5334588151811060992 with g = 14.15, is located at 429. It has B = 16.4, I = 13.11, J = 11.937, and K = 10.951, while the fainter source has B = 19.6, I = 16.08, J = 14.07, and K = 12.86 (Epchtein et al. 1999 ). Based on the color differences I − J and J − K , we identify the brighter star as a main sequence star of spectral type K5 and the fainter one as an M5 star. We fitted the spectra of our X-ray source with thermal plasma models ( apec by Smith et al. 2001 ; mekal by Mewe et al. 1985 ), as expected in the case of coronal emission from normal stars. Acceptable fits could be obtained with temperatures in the range kT = 0.23–0.26 keV, absorption N H ∼ 10 22 cm −2 , and flux ∼3 × 10 −15 erg cm −2 s −1 . The resulting X-ray-to-optical flux ratios (Agüeros et al. 2009 ) were −3.34 and −2.6 for the K and M star, respectively. These values are compatible with X-ray emission from late-type stars and therefore we cannot exclude these objects as potential counterparts of the X-ray source based on spectral and/or flux arguments. However, we note that both stars are outside the 3 σ confidence level error circle of the X-ray source and therefore we consider that PSR J1154–6250 is much more likely responsible for the detected X-ray emission. 4. Results The results of the spectral analysis obtained with the two methods are summarized in Table 3 . The absorption column density was poorly constrained due to the small
Paper: 2021ApJ...912L..29L (fulltext)
for such an effect. We point out that these X-ray reprocessing models cannot simultaneously explain several other aspects of AGN UV/optical variability, including the timescale dependent color variations (i.e., the lamp-post SSD can explain the variable spectra, but cannot account for the fact that the color variations are timescale dependent; see, e.g., Zhu et al. ( 2018 ) and the anti-correlations between variability amplitude and L (e.g., MacLeod et al. 2010 ; Sun et al. 2018b ). Below, we discuss the alternative disk-corona magnetic coupling scenario (Sun et al. 2020a ), which has shown to be successful in reproducing the color variations and the dependences of the variability amplitude upon L (Sun et al. 2020b ), to understand our results in Figure 1 . 3.2. Implications for the Magnetohydrodynamic Accretion Physics Theoretically speaking, disk temperatures ( T ) should vary in response to the time-dependent magnetohydrodynamic (MHD) turbulent heating with a response on the thermal timescale ( τ TH ). For an SSD, , where α , G , and R are the dimensionless viscosity parameter, the gravitational constant, and the distance to the central black hole, respectively. Therefore, the short-wavelength emission, which is produced by the inner hotter plasma, has a smaller response thermal timescale than the long-wavelength emission. The differences in the response thermal timescale would add an additional inter-band time lag ( τ add ), beyond the light-travel time lags. On short timescales ( t dur ), the observed UV/optical variations are mainly produced in the similar small- R regions with τ TH ≤ t dur as the gas in these regions can vary its temperature significantly, and τ add is small and negligible (and vice versa). For an SSD, at the characteristic radius R λ (with k B T ( R λ ) = hc / λ , where k B and h are the Boltzmann and Planck constants, respectively; and ), τ TH ( R λ ) scales as α −1 L 0.5 λ 2 . Therefore, τ add would only be prominent for AGNs with small L (i.e., short τ TH ( R λ )) or large t dur . Below, we consider a specific thermal-fluctuation model to qualitatively reproduce the observed result. In earlier work, we proposed the corona-heated accretion-disk reprocessing model (hereafter the CHAR model) by assuming the accretion disk and the extremely compact X-ray corona are magnetically coupled (Sun et al. 2020a ). Magnetic fluctuations in the corona can alter the disk surface magnetic field, drive variations in the disk MHD turbulent dissipation, and eventually induce coherent multi-band variations. We have predicted that τ dif increases with decreasing L for sources with similar monitoring durations (see Figures 8 and 16 of Sun et al. 2020a ). The first two model parameters, M BH and , are fixed according to the observational constraints. The only free parameter, α , might be 0.1–0.4 according to studies of the outbursts of dwarf nova or soft X-ray transients (e.g., King et al. 2007 ). We fix 10 10 Note that the CHAR model
Paper: 2018ApJ...859..158S (fulltext)
4 . The two small circles in the NUV spectral window mark the downflow components in the Mg ii h and k lines. Figure 4. Average IRIS spectra at specific locations of two slits as marked in Figures 2 and 3 . The black lines represent the spectra of the typical plage region, whereas the green lines represent the spectra of a typical umbral region (marked on the right side of each panel of Figure 2 ). The red and blue lines are the average spectra of two regions where supersonic downflows are observed. These two regions are marked at the right side of each panel of Figures 2 and 3 , respectively. The red spectra show a downflow only in TR lines, whereas the blue spectra show a downflow in TR lines as well as in the chromospheric C ii and Mg ii h and k lines. Two arrows in the NUV spectral window mark the downflow components seen in the Mg ii h and k lines (spectra shown in blue). For the identification of different lines, we refer to Tian ( 2017 ). 3.2. Detection of Supersonic Downflows and Multi-Gaussian Fitting to Their Spectra To derive spectroscopic parameters of the supersonic downflows, we have selected a small spectral window of 1399.31–1403.89 Å, which contains the O iv 1400/1401 Å doublet and Si iv 1403 Å spectral lines. The primary reason for selecting this wavelength range is that Si iv 1403 Å is one of the strongest TR lines in the IRIS spectral range. Also, the O iv 1400/1401 Å doublet lines are useful to determine the electron density of the TR plasma. Figure 5 presents some examples of the spectra in the selected window. A total of six isolated components corresponding to the three spectral lines O iv 1400 Å, O iv 1401 Å, and Si iv 1403 Å and their satellite lines (due to supersonic downflows) can be seen at some locations. To increase the signal-to-noise ratio), we have made a three-point running smoothing along the wavelength and also along the slit dimensions. Figure 5. IRIS spectra containing two O iv lines and one Si iv line acquired along the vertical solid lines marked in Figure 1 . The spectral line profiles at the location indicated by the dashed line (also shown with the red dots in Figure 1 ) of each left panel are shown in the corresponding right panel. A six-component Gaussian fit to the spectra of the regular and downflow components of the O iv 1400/1401 Å and Si iv 1403 Å lines is shown as the overplotted blue line in each right panel. The fitting parameters (i—peak intensity, v—Doppler shift, w—line width) are also printed. The spectra within the red square box contain the Si iv line and its downflow component, which are used for the initial detection of the supersonic downflows (see the text for details). The detection of supersonic downflows is sometimes difficult, as the signal within sunspots is very weak (though it also depends on the exposure, binning of the spectra, etc.). Also, the TR is very dynamic and often shows broad line profiles due to different activities. To ensure that we primarily detect
Paper: 2021MNRAS.505..903C (fulltext)
allows for the simultaneous determination of Z g and Z ⋆ , tracing the ratio of oxygen to iron (O/Fe) in young stars and the surrounding ISM (Steidel et al. 2016 ). The O/Fe ratio is of interest because it is a sensitive probe of the star formation and chemical enrichment history of galaxies. Typical O/Fe ratios at high redshift are expected to be enhanced relative to the solar value due to the fact that the element abundance ratios in relatively young star-forming systems will be dominated by core-collapse supernova (CCSNe) yields (Maiolino Mannucci 2019 ). Indeed, this result has already been reported in the literature. Based on a simultaneous rest-frame FUV+optical analysis of 30 star-forming galaxies at z ≃ 2.4, Steidel et al. ( 2016 ) found O/Fe ≈ 4−5 × O/Fe ⊙ . Similar levels of O/Fe-enhancement have been reported for individual galaxies at z ≃ 2.3 in more recent studies (Topping et al. 2020a , b ). The observed O/Fe-enhancement (also referred to as α-enhancement) has a number of important implications. First, it places robust constraints on the typical star-formation histories at early cosmic epochs, confirming results from previous photometric analyses that the stellar populations at high redshift are typically 1 Gyr old (Reddy et al. 2012 ). Secondly, a deficit of Fe relative to O will mean that the stellar ionizing spectrum of typical high-redshift galaxies is harder at fixed oxygen abundance compared to galaxies in the local Universe. This relative hardening of the ionizing continuum at fixed O/H offers a natural explanation for the observed offset of z > 2 star-forming galaxies relative to z ≃ 0 galaxies in the common line ratio diagrams (e.g. the BPT diagram; Topping et al. 2020a ; Runco et al. 2021 ). Non-solar α/Fe ratios will also force us to re-think current stellar population techniques when applied to high-redshift galaxies. Almost universally, current stellar population synthesis models assume solar abundance ratios; accurate analyses of FUV-optical spectra at z > 6 with JWST will require new models allowing for non-solar abundance ratios. In this paper, we expand upon a number of previous works at z ≃ 2.5 (Steidel et al. 2016 ; Topping et al. 2020a , b ) and present a simultaneous analysis of FUV and optical spectra for a sample of 33 star-forming galaxies drawn from the VANDELS survey at z ≃ 3.4. Combining ultra-deep optical VIMOS/VANDELS spectroscopic observations (tracing the rest-frame FUV) with MOSFIRE H - and K -band near-IR follow-up (tracing the rest-frame optical), our analysis provides the first investigation of Z g and Z ⋆ for galaxies at z > 3, and we present the first estimates of O/Fe at these redshifts. In addition, we present both the stellar and gas-phase MZRs for our sample, tracing O/Fe as a function of stellar mass. The structure of this paper is as follows. In Section 2 , we discuss our combined VANDELS+MOSFIRE spectroscopic data set and describe our final z ≃ 3.4 galaxy sample (referred to
Paper: 2015ApJ...809....5X (acknowledgments)
We thank J. T. Gosling for many helpful discussions. This work is supported by the Science and Technology Development Fund of Macao SAR (080/2012/A3), the National Natural Science Foundation of China (NSFC) under grants 41204123, 41374174, 41231068, and 41331070, and the Science Foundation of Jiangxi Province under grant 20144BAB2110005. We acknowledge NASA contract NAS5-02099 and V. Angelopoulos for use of data from the THEMIS Mission. Specifically, we thank C. W. Carlson and J. P. McFadden for use of ESA, K. H. Glassmeier, U. Auster, and W. Baumjohann for use of FGM data, and D. Larson and R. P. Lin for use of SST data. We also thank ACE and Wind teams and NASA CDAWeb for providing the data.
Paper: 2019MNRAS.490.4945S (acknowledgments)
ACKNOWLEDGEMENTS We thank useful discussions with Phillip Busch, Neal Dalal, Benedikt Diemer, Bhuvnesh Jain, Andrey Kravtsov, Yen-ting Lin, Hironao Miyatake, Ryoma Murata, Masamune Oguri, Masahiro Takada, Simon White, Ying Zu, and the organizers and participants of the KITP program: The Galaxy–Halo Connection. KITP is supported by the National Science Foundation under Grant No. NSF PHY17-48958. TS is supported by Kakenhi grants 15H05893 and 15K21733. SM is supported by Kakenhi grant 16H01089.
Paper: 2016MNRAS.461L.102S (acknowledgments)
This work used the DiRAC Data Centric system at Durham University, operated by the Institute for Computational Cosmology on behalf of the STFC DiRAC HPC Facility ( www.dirac.ac.uk ). This equipment was funded by BIS National E-infrastructure capital grant ST/K00042X/1, STFC capital grant ST/H008519/1, and STFC DiRAC Operations grant ST/K003267/1 and Durham University. DiRAC is part of the National E-Infrastructure. We also acknowledge PRACE for access to the resource Curie at Trés Grand Centre de Calcul. This work received financial support from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013)/ERC Grant agreement 278594-GasAroundGalaxies, from the UK STFC (grant numbers ST/F001166/1 and ST/I000976/1), and from the Belgian Science Policy Office ([AP P7/08 CHARM]). RAC is a Royal Society University Research Fellow.
Paper: 2016A&A...586A..49B (fulltext)
listed in Cols. 2 and 3, respectively. Column 4 shows the isotopic ratio, while Col. 5 gives the references for the different elements. Table 2 Elemental abundances for individual lines in the solar spectrum. Notes. Columns 26 list the single abundances for the different instruments and resolutions. Columns 7 and 8 show the median abundance values for MIKE spectra for the different observation runs and the one dispersion, respectively. The mean abundances are used as solar abundance for MIKE spectra observed in the run with (see Table 1 in Bensby et al. 2014 ) since no solar spectra is available in this setting. Col. 9 lists the solar abundances values from Asplund et al. (2009) . 2.2. Spectral line synthesis The spectral lines from the heavy neutron-capture elements are usually located in the blue regions of the visible spectrum. The blue region is very crowded with spectral lines and is especially so for metal-rich disk stars, meaning that blends from other species are frequent. The crowdedness of the blue spectral regions also makes the placement of the continuum difficult. In addition, heavy elements usually consist of several isotopes, and their spectral lines can be affected by hyperfine splitting (hfs). Therefore, to determine abundances from these lines, one has to use spectral line synthesis in order to accurately account for wavelength shifts of the different isotopes, hyperfine components, and other blending features. Table 1 lists the spectral lines that we use in this study. It shows the analyzed lines with the isotopic ratios of the elements, ionisation stages, wavelengths, and excitation potential, along with reference work where these details were gathered. For Sm and Nd, which suffer in large part from isotopic shifts and also hfs, we use data from Roederer et al. (2008) , for La we used hfs-only components from Ivans et al. (2006) since La has only one naturally-occurring isotope, and for Eu we used shift correction for isotopic and hfs substructures from Lawler et al. (2001) . However, some of the lines of the elements affected by hfs are treated as single lines because the wavelength splitting is small enough to be ignored. In our linelists the lines treated as single lines are La ii at 4748 Å, Nd ii at 5130 Å, and at 5319 Å, and Sm ii at 4523 Å, 4577 Å, and 4669 Å. All lines from Sr ii , Zr ii, and Ce ii lines are treated as single lines since there is no information available on their hyperfine structure and isotopic shifts or because they do not suffer from any of these problems. Atomic data for blending lines and other nearby lines were taken from the compilation available in the Vienna Atomic Line Database (VALD, Piskunov et al. 1995 ; Ryabchikova et al. 1997 ; Kupka et al. 1999 , 2000 ). The complete linelists with hyperfine components can be found in Appendix A . 2.3. Abundance determination The methodology for abundance determination is the same as in Battistini Bensby (2015) where we analyzed Sc, V, Mn, and Co for