adsabs/WIESP2022-NER huggingface dataset:
Paper: 2016A&A...586A.103W (fulltext)
CO , CO and [OI] 63 m, respectively. However, the CO mm-line fluxes do not fully converge to the results obtained by the time-independent reference model, see arrows on the r.h.s. of Fig. C.1 , even for integration times as long as 10 Myr. This is consistent with the very long chemical relaxation timescales we find for those lines, namely 20 Myr, 50 Myr and 100 Myr in the line forming regions of CO , CO , and CO , respectively. The difference of the CO concentration between the Myr disk model and the time-independent reference model is shown in Fig. C.2 . All upper disk regions have practically indistinguishable CO concentrations, however, in the dark icy midplane (vertical visual extinction ), CO cannot freeze out directly where the dust temperature exceeds about 20 K (at radii AU in this model). Instead, the CO is very slowly dissociated in these regions by reactions with He created by cosmic rays. Most of the liberated oxygen atoms re-form CO, but a small part can form other molecules with higher adsorptions energies like water, and these will freeze out immediately. This mechanism provides a slowly ticking chemical clock in the dark midplane regions of protoplanetary disks, leading to gaseous carbon-to-oxygen ratios on Myr timescales between the water and the CO ice-lines, and to on even longer timescales, see ( Öberg et al. 2011 ; Helling et al. 2014 ). The (sub-)mm CO isotopologue line fluxes are somewhat affected by these differences, for example remainders of cold gaseous CO in the dark icy midplane can partly re-absorb the CO line photons emitted by the warm surface of the disk on the opposite side which cross the midplane. In this way, the CO isotopologue line fluxes of the time-independent model can be up to 30% larger than those of the time-dependent models. However, these effects are small compared to the impact of disk mass, size and shape, dust size distribution and settling, and the dust/gas ratio, and negligible for most optical and near-IR to far-IR lines. We conclude that the emission lines of chemically robust gas tracers, such as CO, H and the oxygen atom, are little affected by time-dependent chemical effects in our models. Disk evolution will rather have an impact on those lines via the changing stellar parameters, the changing shape of the disk, and physical gas and dust evolution. See e.g. Akimkin et al. (2013) for time-dependent disk models which include those effects. Appendix D: Properties derived from the model The mean gas temperature in the disk , the mean dust temperature , the near-IR excess, the m SED amplitude, the dust absorption mm and cm-slopes , and the millimetre and centimetre flux-slopes , are calculated as where is the gas mass density, the dust mass density, the local dust-to-gas mass ratio, the volume element, the distance, the spectral flux per wavelength interval, the flux from the naked star and the dust absorption opacity . Appendix E: Fluxes of optically thick emission lines It is noteworthy
Paper: 2015A&A...580A..12L (acknowledgments)
G.L. and Ch.H. highlight the financial support of the European community under the FP7 ERC starting grant 257431. Our respective local computer support is highly acknowledged. We thank P. Woitke, C.R. Stark and P. Rimmer for helpful discussions and feedback. We thank L. Neary for insightful discussion on atmospheric mixing.
Paper: 2020A&A...634A..14B (fulltext)
(in agreement with expectations about Gaia for this separation). But they do have very similar parallaxes (the average is 33.82 mas and the difference 0.04 mas) and radial velocities (Simbad gives − 4.6 ± 2.0km s −1 for HD 224636), so they are almost certainly a physical binary. If they were in a common plane perpendicular to the line-of-sight, their physical separation would be 73 au and their relative velocity 4.8 km s −1 . This compares to a relative orbital velocity of two solar-mass stars in a mutual circular orbit of this radius of 4.9 km s −1 (and their period would be 440 yr). As their proper motion difference of 35 mas yr −1 is about a quarter of their absolute proper motions, the velocity of their center-of-mass could differ significantly from that of either component. If we knew the masses of both components of the binary, we could solve for both the center-of-mass and the Keplerian orbital elements (6+6 parameters from the 3D position and 3D velocity for each star). The spectral type of this pair is given by Struve Franklin (1955) as F8+G1, with F8 presumably referring to GJ 4384 because this is slightly brighter and bluer (by 0.3 mag and 0.05 mag respectively in Gaia DR2). This agrees with their T eff and positions in the color-absolute magnitude diagram, as given by Gaia DR2. We adopt a mass of 1 M ⊙ for each component to compute the position and velocity of the center-of-mass. Integrating the center-of-mass’s motion back in time, we find the time, distance, and relative speed of its closest encounter with 2I/Borisov to be −1380 kyr, 3.64 pc, and 20.9 km s −1 respectively. This is considerably more distant than the encounter found when neglecting the binary motion (the second line of Table 2 ). We do not compute the covariance on these parameters due to an inadequately characterized correlation in the Gaia astrometric uncertainties for sources close to one another. The largest uncertainty is the radial velocity of s528. If we change this by ± 2 σ , the encounter distance remains between 3.3 and 4.0 pc. We conclude that the binary motion renders the GJ 4384–HD 224636 system a much more distant encounter than is shown in Table 2 . Although a binary system is an attractive option for ejecting 2I/Borisov, this encounter distance is far larger than the size of the system. We note that GJ 4384 is listed as the second closest encounter to 2I/Borisov as found by Hallatt Wiegert (2019) with similar encounter parameters to ours ( = 0.32 pc) when we neglect binarity. 3.3 Other candidates We note that several of our other close encounters are binary systems. One of these, HD 22781, has a planetary companion ( Díaz et al. 2012 ), but the encounter velocity of 36 km s −1 is rather high for this planet to be plausibly involved in ejecting 2I/Borisov. It is worth examining in addition those encounters beyond 1 pc (not listed in Table 2 ) that are particularly slow. The slowest encounter we find within 5 pc is with Gaia DR2
Paper: 2018ApJ...855...26A (fulltext)
the normalized results from Chapman et al. ( 2005 ; black, dashed), Wardlow et al. ( 2011 ; blue, solid), and Danielson et al. ( 2017 ; green, dotted). For the sample with robust and tentative counterpart identifications, the median redshifts are and , respectively. These results are in reasonable agreement with those from Chapman et al. ( 2005 ; median z = 2.2 ± 0.1 for a radio pre-selected sample); from the LABOCA Extended Chandra Deep Field South (ECDFS) submillimeter survey (LESS; Wardlow et al. 2011 ; median z = 2.2 ± 0.1); and also with the more recent ALMA surveys of Danielson et al. ( 2017 ; median z = 2.4 ± 0.1) and Brisbin et al. ( 2017 ; median z = 2.48 ± 0.05). In our photometric redshift distribution, there is a comparatively larger fraction of sources at z > 3, and the high-redshift tail extends farther out than that of the LESS distribution including one SMG with z phot ∼ 4.9. The existence of this tail is consistent with the millimeter spectroscopic confirmation of a growing number of SMGs at (e.g., Capak et al. 2008 ; Smolčić et al. 2012 ; Weiß et al. 2013 ; Smolčić et al. 2015 ; Strandet et al. 2016 ), and with the spectroscopic and photometric redshift distributions obtained by Danielson et al. ( 2017 ) and Brisbin et al. ( 2017 ) for samples of SMGs observed at the spatial resolution of ALMA. Su et al. ( 2017 ) also estimate photometric redshifts for nine strongly lensed DSFGs selected by ACT at 218 GHz (1.4 mm) and obtain a higher median redshift , which is expected since the highest-redshift sources remain bright at this lower frequency due to the negative K -correction. Our photometric redshift estimates support the existence of a SMG population, but it is unclear whether these sources’ number counts are consistent with the predictions of cosmological models. For example, semianalytic models that assume a top-heavy IMF and star formation driven by merger-triggered starbursts (Baugh et al. 2005 ) predict a redshift distribution centered at z ∼ 2, with very few sources at much higher redshifts. As a reference, the expected redshift distribution from Baugh et al. ( 2005 ) predicts that only ∼5% of SMGs with S 850 = 8 mJy ( S 870 ∼ 7.5 mJy) lie at z > 4, so for our subset of 25 SMGs with robust counterpart identifications, we would expect only one to two objects in this redshift range, in contrast to the ∼5 that we estimate (Table 5 ). Additional data are critical to confirm the existence and abundance of very high- z SMGs in our sample and confirm or refute our preliminary results; in particular, high-resolution submillimeter imaging is key to confirm counterpart identification for SMGs that are undetected at radio wavelengths. 6.3. Gravitational Magnification The detection of SMGs in LASCAR may be facilitated by the foreground galaxy clusters acting as gravitational lenses, but the resulting flux magnifications also affect the analysis of the intrinsic counts distribution and enhance the scatter in the contamination of
Paper: 2018MNRAS.473..969T (fulltext)
, z BOSS magnitudes. We have renormalized Maraston etal. ( 2013 ) stellar masses to a Chabrier IMF, by subtracting 0.05dex, and converted to our cosmology by subtracting 0.035dex, too. On average, our stellar masses are 0.08dex larger, this discrepancy is related to differences in data sample and template prescription adopted. However, the difference is also stronger at z 0.5, i.e. 0.12dex, and is inverted at 0.6 z 0.7, where our masses get smaller than BOSS estimates of 0.06dex. The trends of M dyn / M stay qualitatively the same. Thus, the results of this paper do not change if different stellar mass estimates are adopted, and conclusions are unaffected. Stellar mass uncertainties. The median uncertainty of the Chabrier IMF stellar masses determined in Section 2.3 in our massive galaxy sample is 0.13dex. We studied the impact of these uncertainties on our mass selection and all the trends discussed in this paper. We have randomly perturbed each mass, assuming a Gaussian with as mean the best-fitting mass and standard deviation the error of the best-fitting mass. Thus, we have selected the most massive galaxies with log M /M 11.2, using the new perturbed masses. The impact on the M dyn / M z trend is negligible. Stellar M / L gradients. We already shown how the gradients impact the results by comparing the g - and K -band results for the SPIDER sample in Section 3 . However, in general, at masses log M /M 11.2 the colour and stellar M / L gradients are weak, thus the correction would be small (Tortora etal. 2011 ). Later analysis would also take into account possible gradients in the IMF (Martn-Navarro etal. 2015 ). Mass profile slope. In addition to uncertainties in stellar mass estimates, the choice of the mass profile can be inappropriate for lower e (or M ) galaxies and cause an excess of negative M dyn / M values, mainly at high- z (e.g. Sonnenfeld etal. 2013 ). In particular, M dyn / M and the slope of total mass density are tightly correlated, with shallower density profiles corresponding to larger M dyn / M (Humphrey Buote 2010 ; Remus etal. 2013 ; Dutton Treu 2014 ; Tortora etal. 2014b ). To quantify the impact of a free-varying total mass density slope, , we have adopted a power-law mass density r , with slope steeper and shallower than isothermal. In Tortora etal. ( 2014c ) we have shown that using two extreme values for the density slope, i.e. 2.5 and 1.5, which bracket most of the results in the literature, then we find that the average M dyn / M get smaller (larger) of 0.1 (0.05)dex for 2.5 (1.5). However, in the realistic case with a varying slope with mass, smaller changes would be expected (Dutton Treu 2014 ; Tortora etal. 2014b ). If is constant with time, then, at fixed mass, these corrections would shift all the results of the same factor, leaving naturally unaffected the observed trend with redshift. On the other hand, if we assume that the slope is varying with redshift, then the only way to totally remove any M dyn / M
Paper: 2020ApJ...899...18P (fulltext)
general for the other hydrogenated PAHs. It is also worth noting that the absence of bands at 3.51 and 3.56 μ m is characteristic of hydrogenated PAHs in which extra H atoms are located by pairs in different parts of the PAH (isomers a and e of Figure 5 and the lower spectrum in Figures 6 and 7 , which include the most stable hydrogenated PAHs predicted at the DFT level). Figure 6. Convoluted theoretical harmonic spectra of four stable isomers of C 54 H 18+12 . Isomers are schematically depicted as an inset. Bands located around 3.51 and 3.56 μ m are indicated by orange and green arrows, respectively. The corresponding H atoms that mostly contribute to those bands are identified with the same colors. Energy differences ( E rel ) correspond to the DFT values. Figure 7. Convoluted theoretical harmonic spectra of four stable isomers of C 96 H 24+10 . Isomers are schematically depicted as an inset. Bands located around 3.51 and 3.56 μ m are indicated by orange and green arrows, respectively. The corresponding H atoms that mostly contribute to those bands are identified with the same colors. Energy differences ( E rel ) correspond to the DFT values. 4. Astrophysical Implications Hydrogenated PAH molecules have been experimentally and theoretically studied in their neutral and cationic forms (Thrower et al. 2012 ; Klærke et al. 2013 ; Cazaux et al. 2016 , 2019 ; Jensen et al. 2019 ; Campisi et al. 2020 ). It has been demonstrated that specific isomeric forms are more abundant than others but that hydrogenation on the different positions (secondary and tertiary) occurs. For example, in the case of neutral coronene, the preferred isomeric forms of 2, 4, and 6 H atoms of the main and alternative sequences of hydrogenation (Jensen et al. 2019 ) are among the most stable isomers shown in Figure 3 . The structures with six additional H atoms previously found (isomers b and d) but also others found in this work (isomers c, f, and g) of Figure 3 are already hydrogenated in tertiary positions, therefore showing that even for low degrees of hydrogenation, tertiary positions are hydrogenated. The conditions in some regions of the ISM, for instance at the surface of PDRs, cause hydrogenated PAHs to become ionized, showing stable structures that are different from those of their neutral counterparts (Cazaux et al. 2019 ). In addition, it has been shown that H atoms attached to cationic PAHs can roam over the peripheral carbon atoms producing a “scrambling” of the different isomers upon absorption of interstellar FUV photons (Wiersma et al. 2020 ). Thus, although not all possible isomers are going to contribute equally to spectral features in the ISM, it is still under study which are the different isomers that contribute depending on the reactions that can take place under the particular conditions of the ISM. If “scrambling” of H atoms inside PAHs is a feasible process, it can be expected that the most stable isomers may have strong contributions to the
Paper: 2018ApJ...863...18G (acknowledgments)
We thank Uri Keshet for useful discussions. This research was supported by a grant from the GIF, the German-Israeli Foundation for Scientific Research and Development.
Paper: 2016ApJ...825...79S (fulltext)
abundance used in our chemical reaction model. This table is from Garrod ( 2013 ). 4.2.2. The Physical Model The physical conditions used as input to the chemical model are based on the “fast warm-up model” from Garrod ( 2013 ). We have run four different models (A, B, C, and D) with different peak densities and/or temperatures as listed in Table 9 . The peak temperatures and densities were selected considering the recent observations toward hot cores (e.g., Hernández-Hernández et al. 2014 ). We will see how CH 2 NH formation processes depend on densities through the comparison of models A, B, and C, and on temperatures through the comparison of models A and D. The gas densities () were initially set to be 3 × 10 3 cm −3 , which gradually increased up to their peak densities along with the free-fall equation during the collapsing phase. While gas temperatures were fixed at 10 K in the collapsing phase, dust temperatures decreased from 16 to 8 K depending on the visual extinction, which was calculated from the gas density of the cloud. Once the peak densities were achieved, we fixed the densities, and the gas and dust temperatures were raised from ∼10 K to their peak temperatures in 7 × 10 4 years. Table 9 Peak Temperatures and Densities for the Models 4.2.3. Gas and Ice Phase Formation of CH<sub>2</sub>NH As a result of our model, CH 2 NH is formed both in the gas phase and on the dust grain surface. We summarize the main chemical reactions that form CH 2 NH on the surfaces in Table 10 . The dust surface reaction rates are proportional to both the probability of the reaction κ and the diffusion rates of reactant species (Hasegawa et al. 1992 ). κ is proportional to exp(- E ), where E A represents the value of the activation barrier. The diffusion rates depend on the exponential of the dust temperature. For the activation barriers of the hydrogenation processes of HCN and CH 2 NH, theoretically predicted values by Woon ( 2002 ) were employed. Table 10 Dust Surface Reactions Related to CH 2 NH Note. The dust surface reactions related to CH 2 NH are shown. E A represents the value of the activation barrier. Since radical species are so reactive, radical–radical reactions would have no activation barriers. The activation barriers for HCN and CH 2 NH were cited from the theoretical study by Woon ( 2002 ). The main reactions in the gas phase that form CH 2 NH are summarized in Table 11 . CH 2 NH is formed both by dissociative recombination processes and neutral–neutral reactions. The rate coefficients of gas-phase reactions are given by the Arrhenius equation, using the coefficients α , β , and γ :where T represents the gas temperature. As shown in Table 11 , the dissociative recombination processes have larger reaction rates. Table 11 Gas-phase Reactions Related to CH 2 NH Note. α , β , and γ represent the coefficients for the Arrhenius equation. 4.2.4. Modeling Results and Discussion The simulated gas-phase CH 2 NH abundances (relative to the
Paper: 2018MNRAS.473.3385P (acknowledgments)
Acknowledgements I sincerely thank my PhD advisor, A. R. Rao, for helpful discussions and suggestions during the entire course of the work; Pawan Kumar for his comments on the manuscript, thus improving its quality; and the referee for his critical comments which immensely improved the quality of the work.
Paper: 2017MNRAS.467L.100E (fulltext)
values of u 0 , are low. For rel , our prior is flat between 0 and 10masyr 1 (see Henderson 2015 ). The priors for and f , respectively, are flat from 0 to and 0 to 2rad. For inclination, the prior is flat in cos from 1 to 1. Note that while flat priors for some of our parameters are unrealistic, the assumptions are reasonable, given poor constraints and the resulting ease of computation. Since all of the priors are flat, the prior term can be pulled out of the integral in ( 3 ) as a factor of p V 1 , where V i ( i i ) is the volume of the priors. i is the upper boundary of the prior for parameter i and i is the lower boundary. Using the Fisher matrix approximation, the evidence is then We use Monte Carlo integration to compute the evidence integrals. 4 RESULTS The test in Bayesian statistics of support for one model over another is the Bayes factor, which is the ratio of the binary-lens evidence to the single-lens evidence: B E B / E S . We apply the scale from Jeffreys ( 1961 ) to determine support, where ln B 5 is strong evidence, 2.5 ln B 5 is moderate evidence, 1 ln B 2.5 is weak evidence and ln B 1 is inconclusive. In the limits that q 0 and s 0 0, the peak likelihood ratio 1, while ln B becomes negative, indicating that the single-lens model is favoured. We compute whether a BBH system with mass parameters similar to those of the first detected LIGO event, GW150914, would be detectable by microlensing in our own Galaxy. Our fiducial model is M 65M , q 0.8, rel 5.5masyr 1 and u 0 0.4 Einstein radii. We choose a lens distance D L 4kpc and a source star in the Galactic Bulge at D S 8kpc with apparent magnitude I 15, on the bright end of typical source magnitudes in current microlensing surveys. For this model, we find that BBH separations down to approximately s 0 0.0250 Einstein radii are detectable with strong evidence, given ideal observing conditions for one year around the peak of the event. For a dimmer source star with I 17, separations down to only s 0 0.0270 Einstein radii are detectable. We also calculate the 2 between the binary and single lenses, both for our fiducial separation s 0 0.01 Einstein radii and the minimum detectable separation s 0 0.0250 Einstein radii. For the fiducial case, ln B 7.65 corresponds to 2 1.36; for the minimum detectable s 0 0.0250 Einstein radii, ln B 5 and 2 53.4. The approximate merger time of BBHs is (see Peters Mathews 1963 ) as follows: where c is the speed of light and G is the gravitational constant. Therefore, BBHs that fit our fiducial model with a separation of s 0 0.0250 Einstein radii will merge in about 2.0810 3 Gyr, which is much greater than the 13.8Gyr age of the Universe. BBHs formed with these parameters in the early Universe can serve only as present-day GW sources if their initial separation was s 0 0.00716 Einstein radii, 3.5times smaller than the minimum separation detectable by KMTNet. The dependence of this minimum separation on the binary parameters is explored in Fig. 2 ,