adsabs/WIESP2022-NER huggingface dataset:
Paper: 2020ApJS..249...35B (fulltext)
al. 2016 ) in phases. Therefore, the CMZoom survey mirrors this variable bandwidth coverage over time, with the first observations being limited to the 8 GHz asic correlator and the final observations containing the full 16 GHz swarm coverage (Figure 2 ). The early observations covered 216.9–220.9 GHz in the lower sideband, and 228.9–232.9 GHz in the upper sideband. The most extended coverage with swarm was 211.5–219.5 GHz in the lower sideband and 227.5–235.5 GHz in the upper sideband, while observations in between are bookended by these extremes (Figure 2 ). The spectral resolution is consistently about 0.812 MHz (1.1 km s −1 ) over the entire bandwidth across the published data sets.We note that the newer raw swarm data are of substantially higher spectral resolution (a factor of 8), but are spectrally smoothed to 1.1 km s to maintain consistency with previous asic data and to maintain manageable file sizes for image processing and analysis. Due to high turbulence, spectral lines in the CMZ are generally wider than this (e.g., Shetty et al. 2012 ; Kauffmann et al. 2017a ), therefore this smoothing should not substantially affect the results. This will be discussed further in the forthcoming publication releasing the spectral line data. Figure 2. Spectral coverage of the CMZoom survey over time. Observations for the CMZoom survey took place over the period of 2014 May–2017 July. During this time, the SMA transitioned from the asic to the swarm correlator, starting with asic only (spectral coverage shown in blue) and ending with swarm (spectral coverage shown in red) only, with varying degrees of overlap in between. The asic * from 2016 April to June indicates a transitionary period where asic was operating differently than its standard mode. Our key target spectral lines are shown as dashed lines in the plot. Coverage of these lines was maintained over the lifetime of the survey, except for a few tertiary lines in the three tracks observed in 2017 and a few other oddities that will be discussed in the spectral line data release paper. In addition to the 230 GHz dust continuum, which is the focus of this paper, the following spectral lines were targeted and consistently included in all observations. In the lower sideband, CMZoom observed the triplet of para-H 2 CO lines of –2, –2, and –2 at 218.222192, 218.475632, and 218.760066 GHz (all frequencies are rest frequencies from the Cologne Database for Molecular Spectroscopy, Müller et al. 2005 , as compiled on splatalogue 22 22 https://www.cv.nrao.edu/php/splat/index.php ), respectively, 13 CO and C 18 O J = 2–1 at 220.39868420 and 219.56035410 GHz, respectively, SiO 5–4 at 217.104980 GHz, and a number of CH 3 OH and CH 3 CN lines. In the upper sideband, CMZoom observed the 12 CO J = 2–1 line at 230.538000 GHz, the H30 α recombination line at 231.90092784 GHz, as well as a number of CH 3 OH transitions. We note that the extended bandwidth observations cover substantially more spectral lines
Paper: 2019MNRAS.483L...1D (fulltext)
d for the longitudinal field, veiling, and radial velocity (RV), respectively. Modulation is also obvious in Ca ii IRT and He i emission (with periods of 5.82 ± 0.16 d and 5.65 ± 0.08 d, respectively) and longitudinal fields from Ca ii IRT emission (with period of 5.50 ± 0.15 d). Since all periods we derive are quite consistent (within 1.5σ) with the rotation period used to phase our data (5.70 d, see Table 1 ), we report no evidence for differential rotation at the surface of LkCa 15. 4 TOMOGRAPHIC MODELLING OF LkCa 15 We use tomographic imaging, and more specifically Zeeman–Doppler Imaging (ZDI), to simultaneously reconstruct the large-scale magnetic field at the surface of LkCa 15, and the distributions of photospheric brightness and accretion-induced excess emission in Ca ii IRT lines. To achieve this we proceed as in previous studies (e.g. Donati et al. 2011 , 2012 ) where the imaging method was outlined. We thus only recall the main steps in this paper. ZDI iteratively looks for a set of images with lowest information content that fits the data at a given reduced chi-square level, starting from blank images containing no information. Whereas photospheric brightness (with cool spots only) and accretion-induced excess emission (with bright features only) are directly described through their distributions at the surface of the star, the large-scale magnetic field, decomposed into its poloidal and toroidal components, is expressed as a set of spherical harmonics (SH, Donati et al. 2006 ). We assume the field is dominated by odd SH modes (as in, e.g. Donati et al. 2011 ) to ensure that accretion occurs mostly towards the polar regions. The local Stokes I and V profiles of both photospheric lines and Ca ii emission are computed using Unno-Rachkovsky’s analytical solution to the polarized radiative transfer equations, taking into account the local values of the modelled distributions (i.e. the brightness map for photospheric lines, the accretion map for Ca ii emission, and the magnetic map for both sets of lines). Local profiles are then integrated over the visible hemisphere to obtain the synthetic profiles of the rotating star at each observed phase. Our model is able to convincingly reproduce most observed profile distortions and Zeeman signatures, as shown in Fig. 2 . We note that the sharp increase and decrease of the longitudinal field of Ca ii IRT lines are better matched for an inclination angle i of 70° than of 50° (the angle measured for the outer accretion disc, Thalmann et al. 2014 , with no reliable inclination estimate for the inner disc). We also obtain that the data are best fit for km s −1 and for an average radial velocity of LkCa 15 with respect to the Sun of km s −1 . Figure 2. Observed (thick black line) and modelled (thin red line) LSD Stokes I and V profiles of the photospheric lines (lef-handt panels) and of the emission core of IRT lines (right-hand panels) of LkCa 15. Rotation cycles and 3σ error bars (for Stokes V
Paper: 2018ApJ...868L..14O (fulltext)
a simple threshold of 450 km s −1 . It is clear that in general, inverted HMF is much more similar to slow wind than fast wind. Indeed, inverted HMF is distinct from fast uninverted HMF in all parameters except α :p. The CDFs of Fe:O for inverted and fast uninverted HMF are clearly separated in the upper part of the distribution, despite the fairly modest β ′ value. Inverted HMF is nevertheless distinct from slow wind in terms of the HMF properties, which is weaker and increasingly inclined the radial direction. 4. Discussion and Conclusions Inverted HMF occurs in short bursts and preferentially in slow, dense solar wind. It generally exhibits lower HMF intensity and increased inclination to the radial direction compared to the solar wind as a whole. We have further shown that inverted HMF is similar to slow solar wind in terms of elemental composition and oxygen, carbon, and iron ion charge states, suggesting common coronal source conditions. Inverted HMF is strongly differentiated from fast uninverted HMF in all parameters except the elemental composition measures and iron ion charge-states. Specifically, inverted HMF is weakly differentiated from fast uninverted HMF in terms of Fe:O abundance ratios, but there is little difference in the α :p abundance ratio, as is often the case with the slow wind in general (Fu et al. 2017 ). It is possible that gradients in elemental abundance are produced in the corona, but that differential streaming of heavy ions relative to the bulk (proton) solar wind (Berger et al. 2011 ; Alterman et al. 2018 ) is able to traverse the short inverted HMF intervals and remove this signature by 1 au (though this should equally wash out the carbon and oxygen charge-state signatures). It may be possible to identify any such compositional signatures using observations from close to the Sun, discussed below, or focusing only on the longer-lived HMF inversions, though this prohibits statistical analysis. Interpretation of ion charge states in terms of coronal temperature is not straightforward, with coronal electron density, temperature, and plasma velocities all contributing to the observed in situ values (Zhao et al. 2014 ). But in general, elevated oxygen and carbon charge states are produced by increased temperatures in the lower corona, whereas elevated iron charge states are more likely to result from heating through the extended corona (Song et al. 2016 ). Thus inverted HMF is associated with increased heating in the lower corona, which suggests that the material was released from hot coronal loops. This is consistent with previous results that show an association between inverted HMF and closed coronal loops in dipolar and unipolar coronal streamers (Owens et al. 2013 ). Hot coronal material on closed coronal loops can be released by interchange reconnection (Crooker Owens 2011 ) with an open magnetic flux tube. This could be initiated by either random foot-point motions or more large-scale convection of open
Paper: 2019A&A...622A..99L (fulltext)
12 CO(2–1) transition at 230.53 GHz with a high spectral resolution of 0.485 MHz (or 0.63 km s −1 ). Each of our nine sources was observed for ~1.4 min in total. The system temperature has a mean value of 91 K. The data was pipeline-calibrated using standard procedures of CASA 4.5.2. The continuum was imaged concatenating together the 128 channels of the spectral window dedicated to the continuum emission, which is a valid approach for pre-stellar structures for which no complex organic molecule emission lines are expected ( Motte et al. 2018a ). The 12 CO(2–1) emission line was slightly smoothed to a spectral resolution of 0.7 km s −1 . Both the continuum and 12 CO line emissions were imaged with the Clark method using the weighting Briggs with a robust parameter of 0.5 1 . The mean achieved root mean square (rms) noise level is of ~0.34 mJy/beam in continuum and of 16.6 mJy beam −1 per channel in 12 CO(2–1), at a resolution of 0.7 km s −1 . Table A.1 details the rms for each source. Fig. 1 Herschel -SPIRE-250 μ m emission of the NGC 6334 region. The 9 MDCs of the present work are located by the blue stars together with their number, following the nomenclature by Tigé et al. (2017) . Red arrows and Roman numerals (I, V) denote bright far-infrared sources from Kraemer Jackson (1999) . Credits: ESA, Herschel Science Archive. 2.2. MOPRA observations These observations were performed in September 2008 with the ATNF MOPRA 22-m telescope with the 3 mm receiver and the MOPRA spectrometer (MOPS) in the “zoom mode” that allows to observe simultaneously up to 16 different frequencies, among them the HCO + (1–0) at 89.18 GHz, the H 13 CO + (1–0) at 86.75 GHz, and the N 2 H + (1–0) at 93.17 GHz emission lines. Small maps (between 3′ × 3′ and 5′ × 5′) were observed in the direction of the 40 dense cores of Russeil et al. (2010) . These maps cover seven of our nine MDCs. These maps were done in the OTF mode and the data reduction was performed with Livedata and Gridzilla tools 2 producing data-cubes with a spectral and spatial resolution of 0.11 km s −1 and 30′′, respectively. The MOPRA dataset is complemented with observations from the MALT90 survey ( Jackson et al. 2013 ) to cover one additional MDC. To sum up, we gather a coherent sample of spectral lines from the MOPRA telescope for all our nine MDCs but the MDC #44. 3. Analysis 3.1. Large-scale view of the MDCs Figure 1 shows the Herschel 250 μ m emission of NGC 6334, overshowing the column density map plotted with the positions of the nine MDCs studied here. Figures 2 – 4 show the column density map over each MDC (left columns) and the molecular line emissions in the MDC (right columns). All observed MDCs are detected in HCO + . Five MDCs are detected in H 13 CO + , and seven in N 2 H + (see Table 1 ). Only the MDC #11 was undetected in both N 2 H + and H 13 CO + . We fitted the lines in CLASS 3 using the hfs procedure to fit the multiplet N 2 H + molecular emission line and Gaussian functions to fit
Paper: 2016MNRAS.456.4015K (fulltext)
elements of Mercury given by the DEA431 analytical series and by DE431 numerical ephemerides. Table 2. Maximum differences between orbital elements of Venus given by the DEA431 analytical series and by DE431 numerical ephemerides. Table 3. Maximum differences between orbital elements of the Earth–Moon barycentre given by the DEA431 analytical series and by DE431 numerical ephemerides. Table 4. Maximum differences between orbital elements of Mars given by the DEA431 analytical series and by DE431 numerical ephemerides. Table 5 gives the number of terms in the DEA431 analytical series, that is, the value of j i in equation ( 8 ) for the i th orbital element of every terrestrial planet. Table 5. Number of terms in the DEA431 analytical series. We also made a comparison of planetary heliocentric distances R , ecliptic longitudes L , and ecliptic latitudes B calculated using the DEA431 analytical series with those obtained from DE431 numerical ephemerides. Tables 6 – 9 present the maximum deviations between the two sets of spherical coordinates for every terrestrial planet over the total time interval of 30 000 yr covered by DE431. For comparison, some corresponding data available for the VSOP2013 theory from Simon et al. ( 2013 ) and a description of the theory's files on ftp 2 are given. In the case of VSOP2013, the numerical ephemerides INPOP10a (Fienga et al. 2011 ) extended to the time interval [−4 000, 8 000] were used as a reference. Table 6. Maximum differences between the spherical coordinates of Mercury given by the analytical series and by numerical ephemerides. Note. the coordinates R *, L *, B * are related to VSOP2013 planetary theory; the corresponding differences are taken from Simon et al. ( 2013 ). Table 7. Maximum differences between the spherical coordinates of Venus given by the analytical series and by numerical ephemerides. Note. the coordinates R *, L *, B * are related to VSOP2013 planetary theory; the corresponding differences are taken from Simon et al. ( 2013 ). Table 8. Maximum differences between spherical coordinates of the Earth–Moon barycentre given by the analytical series and by numerical ephemerides. Note. the coordinates R *, L *, B * are related to VSOP2013 planetary theory; the corresponding differences are taken from Simon et al. ( 2013 ). Table 9. Maximum differences between the spherical coordinates of Mars given by the analytical series and by numerical ephemerides. Note. the coordinates R *, L *, B * are related to VSOP2013 planetary theory; the corresponding differences are taken from Simon et al. ( 2013 ). Tables 6 – 9 show that the VSOP2013 theory better predicts the motion of terrestrial planets over 100 yr or so, but that the DEA431 solution performs better over long-term intervals such as thousands and tens of thousands of years. From Tables 1 – 4 and Tables 6 – 9 it can be seen that the DEA431 development has a rather stable accuracy over approximately 24 000 years centred at epoch J2000. In
Paper: 2016ApJ...818...71W (fulltext)
value (see review in Zinnecker Yorke 2007 ). Increasing or decreasing the assumed excitation temperature by 5 K changes the column density by about 30%. If CS(1–0) is optically thick, as we assume for three sources in Section 4.2 below, then our calculation would be a lower limit. Given these assumptions we used the following relation (see Miettinen ( 2012 ) for a detailed discussion of the relations below): where Here 0 is the vacuum permittivity, μ el is the permanent electric dipole moment, S is the line strength, Z rot is the rotational partition function, ν is the frequency, g K is the K-level degeneracy, g I is the reduced nuclear spin degeneracy, E u is the energy of the upper-transition state, T ex is the excitation temperature and T bg is the background temperature. The dipole moment line strength ( S ) is taken from the JPL spectral line catalog (Pickett et al. 1998 ). The partition function ( Z rot ) is a linear fit to JPL data between T = 37 and 75 K. T bg was taken to be the cosmic microwave background temperature, 2.725 K. The uncertainty in the fit amplitudes and derived column densities is dominated by our flux-calibration uncertainty. Since the relationships are linear, we estimate the uncertainty in both as 20%. Figure 1. Detection of CS emission (gray) toward a candidate YSO (N92-3) on the rim of bubble N92. The Gaussian fit to the emission is shown in black. 3.2. CS Mapping The three mapped regions are shown as boxes overlaid on the GLIMPSE 8 μ m images in Figures 2 – 4 . The maps were cropped to just those regions showing emission above 3 σ . The regions containing emission were then exported to a FITS file using custom-built IDL tools and the FITS-format datacubes were analyzed using CASA. The standard moment maps (total intensity, average velocity and velocity width) are shown next to the corresponding 8 μ m emission images in Figures 2 – 4 . Figure 2. N56: (a) The region surrounding N56 mapped in CS (white outline) overlaid on a GLIMPSE 8 μ m survey image. (b) The integrated intensity map (c) the average velocity map (d) the velocity width map. Figure 3. N65: (a) The region surrounding N65 2 mapped in CS (white outline) overlaid on a GLIMPSE 8 μ m survey image (b) the integrated intensity map (c) the average velocity map (d) the velocity width map, (e) a spectrum centered on the primary peak marked in part (b), (f) a spectrum centered on the secondary peak and the shift in velocity, marked in part (c). Figure 4. N77: (a) The region surrounding N77 1 mapped in CS (white and black outline) overlaid on a GLIMPSE 8 μ m survey image (b) the integrated intensity map (c) the average velocity map (d) the velocity width map. The three maps of CS in N56, N65, and N77 (Figures 2 – 4 ) show evidence of supersonic gas motion in areas near each YSO. N56 has a weak peak in CS that corresponds to a velocity shift of ∼2 km s −1 in the gas immediately to the north. The CS emission in N65 has a clear, strong comma-like shape. The peak
Paper: 2019ApJ...876..122Y (fulltext)
geometrically thin optically thick, radiatively efficient, and steady-state accretion disk (Shakura Sunyaev 1973 ), which is expected in AGNs. We assume the disk has viscosity parameter α = 0.1, and radiation efficiency , where and are the Eddington luminosity and Eddington accretion rate of an SMBH with mass M • . We further assume the accretion rate is constant during the lifetime τ agn of an AGN. These parameters determine the disk surface density Σ( r ), scale height H ( r ), isothermal sound speed c s ( r ), and midplane temperature T ( r ), which are dependent on the distance r from the SMBH. To derive these quantities we follow the model of Sirko Goodman ( 2003 ), assuming that viscosity in the disk is proportional to the total pressure: where T eff ( r ) is the blackbody temperature of the disk at r . , where r min is the inner radius of the disk; we set here, where . Ω is the Keplerian angular velocity of the disk, which is . τ is the optical depth at midplane. We assume the mean molecular mass . σ is the Stefan–Boltzmann constant, and k is Boltzmann constant. In order to solve these equations, we still need to provide the opacity κ . We approximate the opacity with (see Figure 1 in Thompson et al. 2005 ):where g −1 cm 2 K −2 and κ 1 = κ 0 (100 K) 2 = 2.4 g −1 cm 2 . κ m is the molecular opacity, which is about 0.1 Z , where Z indicates the mass fraction of heavy elements. We adopt Z = 0.01 in our simulations (Iglesias Rogers 1996 ). is the opacity due to the negative hydrogen ion:where and . The electron scattering opacity κ e can be written as X is the mass fraction of hydrogen. The Kramers opacity κ K is due to free–free, bound–free, and bound–bound electronic transitions:The equations above are valid where the Toomre Q -parameter Q = C s Ω/( πG Σ) ≳ 1. Beyond that region, out to 0.1 pc, we assume that the disk self-regulates, which we take into account by fixing the Q -parameter at 1 and replace Equation ( 1 ) with (see Equation (15) of Sirko Goodman 2003 ): 2.2. Orbital Variation Due to AGN Disk Crossing Consider a Cartesian coordinate system with the SMBH in its center, in which the AGN disk lies in the XY plane, and the major axis of the orbit of the stellar-mass BH orbiting the SMBH is in the YZ plane (see Figure 1 ). Let be the unit vector pointing in the direction of the major axis of the BH’s orbit in Cartesian coordinates, with θ being the angle is the orbit’s inclination angle compared to the AGN disk plane. Let a be the semimajor axis, e the eccentricity, and is the normal vector of the BH’s orbital plane. Let be the angle between and the YZ plane, where is the unit vector along the x axis. 5 5 Here we adopt the coordinates ( θ , ψ , φ ) that are the most suitable for the derivation of the results, even though these are not standard Keplerian orbital elements. They can be converted to Keplerian coordinates as follows. Longitude of the ascending mode: . Argument of periapsis: φ . Inclination: . We haveLet φ be the angle
Paper: 2019MNRAS.489...52F (fulltext)
given that the resulting cooling rate peaks in a temperature regime where the gas is expected to be fully ionized. To calculate an approximate cooling function, we solve equation ( C1 ) for a densities in the range 10 −2 –10 6 cm −3 and in the temperature range of 1–10 8 K. For each species, cooling rates are calculated at collisional excitation equilibrium. The net cooling is the sum of these terms: where the first sum is over species, n i ,s is the number density of an excited state for a given species, and ν ij is the frequency of the photon emitted by a transition from level i to level j . The two-dimensional table of cooling rates is averaged along the density axis to get an average cooling rate as a function of temperature. The average cooling function is show in Fig. C1 alongside the piecewise fit used in our models (equation 32 ). Figure C1. Average volumetric cooling rate (solid) and piecewise approximation (dashed) for collisionally excited line radiation. The shaded region indicates the 1σ error region, and the hatched region highlights the range of values averaged over to obtain the approximate cooling function used. APPENDIX D: DISC FINDING ALGORITHM We have developed an efficient parallelized disc finding routine that allows us to track the formation and evolution of formed discs in our models irrespective of scale or orientation. We implement this routine directly into athena for two reasons. First, this tool provides the advantage of ‘on-the-fly’ analysis which yields much greater time accuracy than is reasonably managed through post-processing. Secondly, the method is designed to take advantage of the parallelized structure of athena , which dramatically reduces the amount of time required to execute the necessary operations. The algorithm takes the following steps: (1) On each processor, or local grid, the total mass and angular momentum with respect to the origin are calculated within a search radius, R search . For simulations with refinement, overlapped cells are excluded from this total. The net angular momentum ( L net ) and mass ( M net ) are then calculated across all processors. (2) For each cell, the deviation angle is calculated as where L cell is the angular momentum vector of the cell. (3) The total mass for cells with θ dev θ thresh is then calculated. For our simulations, we found that setting θ thresh = 30° was a sufficiently strict condition for capturing the formation of a disc. (4) A mass fraction is then calculated as For our models, we consider f M > 0.75 to be indicative of a potential disc. (5) For disc candidates, we continue to a three-dimensional rotation of the mesh from the simulation reference frame into a reference frame in which the axis is parallel to L net , which we call the disc frame. We construct a new mesh in the disc frame with identical dimensions and hierarchical structure to the simulation frame of reference. We loop over all cells on the disc frame mesh and calculate the