adsabs/WIESP2022-NER huggingface dataset:
Paper: 2017ApJ...846...32D (acknowledgments)
We thank the referee for her/his useful comments. T.D.-S. would like to thank M. Wolfire, J. Pineda, C. Ferkinhoff, D. Brisbin, and N. Scoville for stimulating discussions about PDR physics and models. T.D.-S. acknowledges support from ALMA-CONICYT project 31130005 and FONDECYT regular project 1151239. G.C.P. was supported by a FONDECYT Postdoctoral Fellowship (no. 3150361). N.L. acknowledges support from NSFC grant no. 11673028. K.I. acknowledges support by the Spanish MINECO under grant AYA2016-76012-C3-1-P and MDM-2014-0369 of ICCUB (Unidad de Excelencia “María de Maeztu”). This work was carried out in part at the Jet Propulsion Laboratory, which is operated for NASA by the California Institute of Technology. This work is based on observations made with the Herschel Space Observatory , a European Space Agency Cornerstone Mission with science instruments provided by European-led Principal Investigator consortia and significant participation from NASA. The Spitzer Space Telescope is operated by the Jet Propulsion Laboratory, California Institute of Technology, under NASA contract 1407. This research has made use of the NASA/IPAC Extragalactic Database (NED), which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration, and of NASA’s Astrophysics Data System (ADS) abstract service. T.D.-S. wants to thank the NASA Herschel Science Center (NHSC), and in particular D. Shupe, for providing access to their computer cluster, with which most of the Herschel /PACS data sets were processed. Part of this work was carried out at the Aspen Center for Physics, which is supported by the National Science Foundation grant PHY-1066293.
Paper: 2018MNRAS.476.1840F (fulltext)
), equation ( 37 ) becomes At far from the centre, the flow speed is almost constant, and this equation is solved to yield a solution and the flux roughly varies as . Similarly, at far from the centre, where B 0 is dominated and the flow speed is constant, equation ( 38 ) with equation ( 39 ) is also solved to yield an approximate solution: and the mean intensity roughly varies as at least on the main dependence. In Fig. 8 , the emergent intensities I + ( p, z out ) at the outer boundary R out normalized by I * are plotted as a function of the impact coordinate p normalized by R * . The normalized luminosity is Γ * = 5, the typical optical depth τ * = 3, the blackbody intensity B 0 / I * = 1, and the values of β out are 0.1, 0.3, 0.5 from top to bottom. In contrast to the scattering case (Fig. 4 ), the emergent intensity in the outer envelope is quite large. This is also because the source emissivity is uniformly distributed in the entire space in the isothermal wind. Similar to the relations obtained in the scattering case (Fig. 5 ), in this isothermal wind we can also the relations on the parameters, although we do not discuss them for simplicity. Finally, we should mention the opacity effect. In this isothermal wind, we assume that the absorption opacity κ 0 is constant. In the realistic case, the absorption opacity depends on the physical quantities, e.g. the free–free opacity is proportional to . Hence, it is in the isothermal case. In this case, the results are quite similar to the scattering case. The reason is because the density is concentrated in the centre and quickly decreases towards the outer envelope, and therefore, the emissivity is also concentrated in the central core. 5 CONCLUDING REMARKS In this paper, we have examined the radiatively driven relativistic spherical winds from the central object with mass M and luminosity L * under Newtonian gravity and special relativity, by numerically solving the relativistic radiative transfer equation and relativistic hydrodynamical ones for spherical geometry, simultaneously and consistently. Namely, using the initial trial velocity profile, we iteratively solved the relativistic formal solution of the transfer equation to obtain specific intensities and moment quantities in the inertial and comoving frames. Using the comoving flux obtained, we then solved the relativistic hydrodynamical equations to obtain the refined velocity profile, and the mass-loss rate as an eigenvalue. We repeat these double-iteration procedures until both the intensity and velocity converge. We found that the momentum-driven winds with scattering are quickly accelerated near the central luminous core to reach the terminal speed (Fig. 2 ), similar to the radiative outflows without gravity (Fukue 2017b ). The behaviour of moment quantities and emergent intensity is quite similar to the previous results (figs 3 and 4 in Fukue 2017b ). The results of numerical solutions are roughly fitted by a relation of , which
Paper: 2016ApJ...825..109Z (fulltext)
Rope System The evolution of a flux rope in a partially open bipolar background field as discussed in Sections 3.1 and 3.2 is summarized in Figure 3 , where h stands for the geometric parameter and λ the control parameter. There are two branches of equilibrium states for the flux rope: the lower branch ( D ∼ A in Figure 3 ) and the upper branch ( C ∼ B in Figure 3 ). The two branches are separated by the upward (from lower to upper branch) and downward (from upper to lower branch) catastrophes. The upward (downward) catastrophe is an irreversible but reproducible process, and it takes place when the solution jumps from the lower (upper) branch to the upper (lower) branch with increasing (decreasing) control parameter. Therefore, the two branches and the two catastrophes form a circulation, as shown by in Figure 3 (a). Figure 3. Schematic representations of the equilibrium solutions of the magnetic flux rope system: the profile of (a) a certain geometric parameter of the rope ( h ) and (b) the magnetic energy in the computational domain ( E ) vs. a certain control parameter of the system ( λ ). An upper catastrophe occurs at λ = λ u , whereas a downward catastrophe occurs at λ = λ d . The subscripts 1, 2, 3, and 4 label the state of the system immediately before and after the upward catastrophic point, and immediately before and after the downward catastrophic point, respectively. Although the jump of h is opposite in sign, the jump of E is always negative, implying a magnetic energy release for both of the two catastrophes. The evolution of magnetic energy (Figure 3 (b)) is also a circulation consisting of the two branches and two catastrophes, but it is quite different from that of the geometric parameter (Figure 3 (a)). At the lower branch (), magnetic energy is stored with increasing control parameter, whereas it is reduced during both upward and downward catastrophes, and during the shift of the solution along the upper branch from B to C as well. The constraint exerted by the background field on the flux rope is larger for solutions at the lower branch than that at the upper branch, so that the growth rate of the magnetic energy with λ , dE / dλ , is larger for lower-branch solutions than upper-branch solutions. Consequently, at the upward catastrophic point ( λ = λ u ), the magnetic energy of the upper-branch solution is smaller than that of the lower-branch solution ( E 2 E 1 ), whereas at the downward catastrophic point ( λ = λ d ), the opposite is true ( E 3 > E 4 ). This provides the essential energy condition under which the downward catastrophe could occur. 3.4. Mechanism of Magnetic Energy Release During the Catastrophe It is widely accepted that magnetic energy is released by magnetic reconnection in solar eruptive activities (Benz 2008 ; Shibata Magara 2011 ). However, magnetic reconnections are prohibited during our simulation (see Section 2 ). There should be other mechanisms of magnetic energy release in addition to magnetic
Paper: 2019MNRAS.488.5075R (fulltext)
ones are for the same voids after cleaning. The vertical dotted lines mark the void radius in both cases. We also show the background density level (solid horizontal black line) and the underdensity threshold of equation ( 12 ) computed for the different redshifts (dashed horizontal black line) as a reference. It can be noticed that, while vide void limits reside close to the compensation wall and embed a density that approaches the background, our voids are, by construction, defined in much deeper regions of the density field. These observations have to be kept in mind to understand how the algorithm we apply to clean the cosmic void catalogues affects the void structure. Thanks to this modification, we can be confident that the voids we are using to measure the size function are as close as possible to the objects for which we are able to construct the theoretical model. Fig. 2 compares the measured and modelled void size functions, defined as the comoving number density of voids in logarithmic bins of effective radii, divided by the logarithmic extent of the bins. The four panels show the results at different redshifts. The different symbols in the upper part of each panel show the void size distributions measured in the simulation snapshots at different resolutions, while the gray shaded regions represent the model predictions. The model depends on two thresholds, the one of the shell-crossing, which is fixed at the value , corresponding to our choice of threshold in the void catalogue cleaning, and the overdensity one, δ c , used to account for the void-in-cloud effect. There is a persisting uncertainty on the definition of the latter, since it is not clear if this effect becomes relevant at turn-around (corresponding to a density contrast of δ c ≈ 1.06) or when the overdensity collapses (at a density contrast δ c ≈ 1.69). Since in realistic occurrences we do not expect the spatial resolution of tracers to be high enough to inspect the radii range in which the void size function becomes sensitive to the void-in-cloud effect, we leave the overdensity threshold free to vary in the range 1.06 ≤ δ c ≤ 1.69, thus the shaded region of Fig. 2 . Figure 2. Upper part of each panel: Void size function prediction (gray shaded region) at four different redshifts (different panels) compared to the distribution of cosmic voids after applying the cleaning method described in Section 2.2 (different markers correspond to different simulations, the values of L box in legend corresponding to those of Table 2 ). Lower part of each panel: Logarithmic differences between the measured distribution and the Vdn model prediction. For the largest simulation () we only have snapshots at z = 0 and z = 1, thus the corresponding abundances are missing from the z = 0.5 and z = 1.5 panels. We cut the distribution measured in each of the simulations at twice the m.i.s. of the given simulation box (see Table 2 ). To highlight the difference between the theoretical model
Paper: 2020ApJ...891...22H (fulltext)
attention paid to the cryogenic solids of astrochemical relevance, it should be possible to verify additivity given a sufficiently large and varied number of measurements on ices. For our initial study with amorphous ices, we have adopted the method of bond contributions and the values of Denbigh ( 1940 ) to calculate R M values. Bonds used (and contributions to R M in cm 3 mole −1 ) were as follows: C–H (1.69), C–C (1.25), O–H (1.73), C–O (1.51), C=O (3.38), C=C (4.16), and C≡C (6.4). For example, from the five bonds of CH 3 OH, one finds R M = 3 (1.69) + 1.73 + 1.51 = 8.31 cm 3 mole −1 . Figure 7 compares calculated R M values for our compounds to our measured values for amorphous ices. The correlation between the observed and computed values is obvious. Admittedly, the agreement largely reflects the fact that the bond contributions used are from liquids, for which Figure 4 (c) already shows reasonable agreement with our work, but nevertheless the linearity of Figure 7 for ices is gratifying. Figure 7. Molar refractions measured for amorphous ices compared to values computed with a bond-additivity approach. All values are taken from Table 3 . 4.3. Isomers and Molar Refractions Isomeric pairs of molecules in which the number of each type of bond is the same provide another check on our results. For example, since the isomers propionaldehyde (propanal) and acetone each have six C–H bonds, two C–C bonds, and one C=O bond then on the basis of additivity the two compounds should have about the same R M value. Table 4 shows that for this pair of compounds and five others, the R M values are within about 1 cm 3 mole −1 for our 15 K measurements on amorphous ices. A propagation-of-error analysis using Equation ( 6 ) leads to uncertainties in R M of about 0.1 cm 3 mole −1 for the smaller molecules we studied up to about 0.4 cm 3 mole −1 for the larger ones. This implies that the values in Table 4 for isomers are within or almost within experimental error for our ices. Table 4 Molar Refractions of Six Isomeric Pairs Note. a The units of R M are cm 3 mole −1 . Values of R M are from Table 3 . 4.4. Comparisons to Earlier Work The lack of published laboratory data corresponding to that in our Tables 2 and 3 makes it difficult to compare our results directly to those in the literature. To two decimal places, our n for amorphous methyl formate at 15 K is 1.32, near the 1.30 at 20 K reported by Modica Palumbo ( 2010 ). Our n for amorphous CH 3 OH at 15 K is 1.296, roughly the average of the 1.257 and 1.33 at 20 and 25 K, respectively, already published (Luna et al. 2018 ; Sciré et al. 2019 ). In an earlier paper we combined room-temperature data for methyl propionate and n for the corresponding amorphous ice to estimate ρ for amorphous methyl propionate at 16 K (Hudson Mullikin 2019 ). The estimated density value was 0.702 g cm −3 , in contrast to the measured value of 0.764 g cm −3 reported here. The densities we determined for amorphous (15 K) and
Paper: 2016MNRAS.463L..99S (acknowledgments)
We thank Wenfei Yu for helpful discussions. This work was supported by the National Basic Research Program of China (973 Program) under grants 2014CB845800 and 2015CB857004 , the National Natural Science Foundation of China under grants 11573023 , 11573009 , 11473022 , 11403074 , 11333004 , 11222328 , 11133005 and U1331101 , the Knowledge Innovation Program of the Chinese Academy of Sciences , the CAS Open Research Program of Key Laboratory for the Structure and Evolution of Celestial Objects under grant OP201503 , and the Fundamental Research Funds for the Central Universities under grants 20720140532 and 20720160024 .
Paper: 2015ApJ...805...97K (acknowledgments)
Hinode is a Japanese mission developed and launched by ISAS/JAXA, with NAOJ as domestic partner and NASA and STFC (United Kingdom) as international partners. It is operated by these agencies in cooperation with ESA and NSC (Norway). We extend our gratitude to Hirohisa Hara and Toshifumi Shimizu who made a large number of insightful comments with their expertise in spectroscopy. We are also thankful to the GCOE program for proofreading/editing assistance. Facility: Hinode
Paper: 2016MNRAS.458..575L (fulltext)
( 2003 ), the polarization degree of the dust emission 6 is expected to be a few to 10 percent for a typical line of sight at an angle 45 o with respect to the magnetic field (Lee Draine 1985 ). Similar to the polarimetry of IR emission from AGN torus (e.g. Packham et al. 2007 ; Lopez-Rodriguez et al. 2013 ), future IR polarimetry of TDEs could potentially play an important role in studying the dust properties and magnetic field around non-AGN. 4.2 Possible refinements of the model A few other complexities, which are ignored in our simple model, can be taken into account in future works. (1) The heating by the scattered UV-optical photons and dust IR radiation could be included by considering the time delay and related absorption coefficient. In this way, a spectrum of dust IR emission can be calculated and compared with future observations. (2) The clumpiness of dusty clouds will affect the radiative transfer. Since every clump will have a bright (hot) side and a dark (cold) side, dust temperature distributions are different in clumpy and smooth environments (Nenkova et al. 2008 ). (3) In the radiative transfer model in Section 3 , a single dust radius of a = 0.1 μm is used, but the true interstellar grain population has a broad size distribution, extending from a few Å (PAH molecules) to about 0.2 μm (or even larger). Most mass is in the larger grains, with half-mass grain radius typically ∼ 0.1 μm (half of mass is in grains with radius above this value), and the smaller grains contribute most surface area and hence most UV extinction (e.g. Laor Draine 1993 ; Weingartner Draine 2001 ). However, at the same distance from the central source, smaller grains sublime faster than larger ones (mostly due to higher grain temperatures), so it is unclear which grain size contributes most IR emission. Also, the properties of graphite and silicate grains are sufficiently different that their sublimation radii could be separated. A systematic study of grain size distribution and chemical composition could be done in the future with dust continuum radiative transfer codes such as DUSTY 7 and HYPERION, 8 although the dynamical propagation of radiation coupled with dust sublimation requires some modification of the codes. 5 SUMMARY We consider the impact of the UV-optical radiation ( E rad ∼ 10 51 –10 52 erg) from TDEs on the circum-nuclear medium. If the medium is dusty, the UV-optical radiation energy will be absorbed by dust within ∼1 pc from the BH and re-radiated in the IR. We calculate the bolometric light-curve from a 1D radiative transfer model, taking into account the time-dependent heating, cooling and sublimation of dust grains. We show that the dust emission peaks at 3-10 μm and has typical luminosities between 10 42 and 10 43 erg s −1 (with sky covering factor f Ω ranging from 0.1 to 1). This is detectable by current generation of ground-based and space telescopes. In the near future, JWST will be able to perform photometric and
Paper: 2019A&A...623A..63M (fulltext)
UT ( middle ), and 10:44:00 UT ( right ), denoted by dashed black lines in panel a . The radio contours are overlaid on AIA 211 Å running-difference images and LASCO C2 running-difference images that show the progression of the CME. Panel c : flux density spectra at NRH (red dots) and RSTN (orange triangles) frequencies at the same times as in panel b . The NRH flux densities were estimated over the northern source denoted Type IV in panel b . Flux density spectra were computed using the flux densities of the second component of the Type IV burst source at three times: 10:47, 10:55 and 11:03 UT, in Fig. 7 c. There is a clear power-law decrease at all times in Fig. 7 c, and this trend remains consistent from 10:47 UT until ∼11:05 UT (Fig. 6 ). After 11:05 UT, at 408–445 MHz, the Type IV radio source emission becomes faint and is comparable in brightness to active region and quiet-Sun emissions, as it drops below 10 sfu. At 10:47 UT, we estimate a negative spectral index of −1.6 that also includes contributions from a second source to the north in Fig. 7 b. After 10:49 UT (Fig. 4 c), the power-law decrease becomes clearer because only the Type IV source is present, and we estimate spectral indices of −3.3 at 10:49 UT and −2.3 at 11:03 UT. The second component of the Type IV burst shows an outward movement through time at all frequencies. The centroid locations of the second component of the Type IV burst are shown in Fig. 8 at 298 MHz. The centroids have been split into two periods: a stationary period at 10:44:20–10:49:20 (Fig. 8 a) and a moving period at 10:49:20–11:10:00 UT (Fig. 8 b). The centroids are superimposed on an AIA 171 Å running-difference image in Fig. 8 a and on a 174 Å running-difference image from the Sun Watcher using the Active Pixel System detector and Image Processing (SWAP; Berghmans et al. 2006 ) on board PROBA2 in Fig. 7 b. The SWAP image is used to show a larger field of view, and it has been limb-enhanced to show faint coronal loops beyond the solar limb. Fig. 8. Moving Type IV centroids at 298 MHz split into two phases: a stationary phase ( panel a ) and a moving phase ( panel b ). The centroids are overlaid on AIA 171 Å ( panel a ) and SWAP 174 Å ( panel b ) running-difference images that show the expansion of coronal loops in the negative x -direction behind the CME. The movement of the radio sources in panel b is coincident with the outward growth of the cusp-shaped loop system. The Type IV burst appears stationary for ∼5 min, but at this time, other sources are present. It is possible that various radio sources are superimposed, and we cannot accurately determine a centroid location. The moving period is characterised by the radio source moving away from the solar disc, and it starts after 10:49 UT, when the spectral index also shows a clear power-law decrease that remains consistent over time (Fig. 7 ). In both panels, the centroids are coincident with a cusp-shaped loop system that rises to increasing
Paper: 2017MNRAS.466L..78V (fulltext)
for pairs of one-dimensional posteriors on the HL time of flight (Fig. 3 ). We see that with the HL network (solid lines), for 50percent of the skymaps the fidelity is above 0.8 for CBC-burst skymaps, and above 0.9 for LIB - cWB skymaps. The CBC-burst fidelity is a bit lower for the HLV network, while the LIB - cWB median fidelity stays close to 0.9. The two burst algorithms thus select the same sky ring very often. Strong correlation exists between the fidelity of the full skymap and that of the time of flight, implying that when slightly different rings are selected (low t HL fidelity) the overall fidelity is strongly reduced. Thus, the disagreement we found while comparing the full skymaps, Fig. 1 , is determined by both the placement of probability around the ring and the position of the ring itself, with the latter happening less frequently but having a large impact when present. Figure 3. The cumulative distribution of time-of-flight fidelity for pairs of algorithms in the HL (solid lines) and HLV (dashed lines) analyses. Fig. 4 shows the clear correlation between angular offsets and decreased fidelity using data from the HL network, as well as the corresponding values from GW150914 (stars), which fall within the scatter observed in simulations. We note that while there is quite a bit of scatter, the general trends seem to be independent of which algorithms are actually compared. This further suggests that low fidelity is driven by differences in the selected triangulation rings, because all algorithms produce triangulation rings. Figure 4. A scatter plot of the fidelity using the full skymap and the angular separation between triangulation rings. GW150914s values are shown as stars. We mentioned above that the GW150914 fidelity for LIB cWB was much lower than average. We can now understand why the LIB and cWB skymaps for GW150914 have support on different sky rings (see Abbott etal. 2016f ). They thus belong to this rarer class of reconstructed skymaps for which there is a significant drop of fidelity. Furthermore, one can compute the distribution of the angular distance between rings. We find that the distributions look unimodal, with mean smaller than 0.2 for all pairs of algorithms, and standard deviations in the range 2.54 (2.57) for the HL (HLV) network. 3.2 Searched area So far we have focused on the degree of similarity of skymaps, which was naturally prompted by the fact that burst and CBC skymaps were so different for GW150914. However, that is probably not the most relevant figure of merit to assess the chances of a successful EM follow-up. The fact that a skymap is larger or different might not lead to wasted telescope observation time as long as most of the probability is at the true position. In this section, we report the searched area found by the burst and CBC algorithms. We define the searched area as the amount of sky one needs to image, starting from the most likely skymap pixel and going down, until the true