adsabs/WIESP2022-NER huggingface dataset:
Paper: 2018MNRAS.479..495G (fulltext)
The effect is best understood by examining Fig. 6 . The particular explosion energy for which incomplete silicon burning mostly ceases inside the oxygen-burning shell is shown by the dashed line at 5.75 B in Fig. 6 ( top ). For explosion energy 1 B − 2 B below this value, incomplete silicon burning occurs extensively against the inner edge of the boundary, and for greater explosion energy, incomplete silicon burning does not occur at all within the oxygen-burning shell. Examining the peak temperature profile in Fig. 6 ( bottom ), we see a 'bump' of increased temperature at the inner edge of the shell boundary (location shown by the dashed line), indicating that material in this region is subject to some source of extra heating. We understand the cause of the 'bump' in the temperature profile against the outer edge of the oxygen-burning shell as follows: as the initial supernova shock travels through the composition boundary, a reverse shock is launched as a consequence of the change in the sign of the gradient in ρ r 3 at this point. The quantity ρ r 3 is important for the shock velocity in supernovae. As is described by Kompaneets ( 1960 ); Klimishin Gnatyk ( 1982 ); Bethe ( 1990 ); and Matzner McKee ( 1999 ), the shock velocity, U , can be approximated by Here β is parameter that varies with the properties of the material that the shock is propagating through, typically, 0.2 ≲ β ≲ 0.5. Nevertheless, for the our purposes the important point is that the shock velocity is inversely proportional to ρ r 3 , so when ρ r 3 is increasing, the shock must decelerate, and when ρ r 3 is decreasing, the shock accelerates. The inner ρ r 3 profile is shown for the 15 M ⊙ model in Fig. 7(a) . We see that there is a reversal in the sign of the gradient of the ρ r 3 profile at the oxygen-burning/carbon-burning shell interface. Such a rapid change in ρ r 3 , from a negative to positive gradient, leads to a rapid slowing of the shock velocity. This abrupt deceleration results in an increased density at this point, as interior matter piles up against the slowed mass. This has a chain effect on the matter behind it, and so on, which propagates as an ingoing shock. Figure 6. In the upper and middle plots, we show chromium and iron mass fractions, respectively, as a function of mass coordinate and explosion energy for the 15 M ⊙ model, as in Fig. 1 . The lower plot shows the peak temperature profiles for four models with explosion energy at which explosive silicon burning is affected by the reverse shock. Figure 7. The ρ r 3 profile (black line) and electron mole fraction, Y e (grey line) for the inner 10 M ⊙ of each of the 15 M ⊙ –80 M ⊙ progenitor models. The piston location is indicated by the dashed line. Note, Y , where η is the neutron excess. The reverse shock provides additional heating to the material immediately interior to the shell boundary, as can be seen in the temperature profile at various time intervals (Fig. 8 ). This results in an approximately
Paper: 2021A&A...651A.110G (fulltext)
values of according toEq. ( 8 ). We chose six values for the scaling size of the core, 0.1, 0.2, 0.4, 0.6, 0.8, 0.9. All lines cross at point A which is the bulk density of a homogeneous Phobos. For core densities lower than the bulk density (left of point A shown in Fig. 3 ), the mantle is denser than the core, and vice versa, for core densities higher than the bulk density (right of point A), the mantle is less dense than the core. Figures 4 a and 4 b show the dependence of the mantle density on the size of the core for selected core densities. In Fig. 4 , only physical values (from 500 kg m −3 to 5000 kg m −3 ) for the densities of the mantle and the core are listed. For a given scaling factor of the core λ and the density of the core ρ c , 46 layering cases are considered in this paper. We removed the cases exceeding the allowable density range. Fig. 3 Range of densities for the Phobos two-layer model. The x -axis is the assumed density of the core, the y-axis is the resulting density of the mantle according to Eq. ( 8 ). Plots in Figs. 5 and 6 show that at the 3 σ level, the modeled and observed C 20 agree well when the mantle is denser than the core (see also Tables 3 and 4 ). To verify the effect of the core shape on the gravity field of the two-layer Phobos model, we used a triaxial ellipsoid core shape (homotheticto the best-fit triaxial ellipsoid of Phobos ( Willner et al. 2014 ), and recalculated the second-degree coefficients in a setting identical to the one used for Figs. 5 and 6 . The gravity potential of a homogeneous ellipsoid canbe computed using Ivory’s formula ( Garmier et al. 2002 ). Compared to the minimum absolute value of from Yang et al. (2019) , when the mantle is denser than the core, the cases listed in Table 3 (homothetic surface shapes) and Table 5 (homothetic ellipsoids) coincide. A test simulation for a core with a scaling factor of 0.6 and a density of 1400 kg m −3 produced a very small deviation of 0.097%, therefore, the deviation is not sensitive to the core shape, if the interface core-mantle is deeply buried. Only one test simulation is compatible with the data when the core is denser than the mantle. In this case, the core had a scaling factor of 0.1 and a density of 2200 kg m −3 , and the corresponding deviation was 0.002%.These results are summarized in Tables 5 and 6 . The disrupted and reaccreted body (DAR-F1) model (a rubble-pile internal structure), with a denser outer layer considered by Le Maistre et al. (2019) , is close to our two-layer model for a core with a scaling factor of 0.9 (the interface depth is about 1 km). Fig. 4 Mantle (a) and core (b) densities as a function of the core scaling factor of Phobos’ two-layer models. ( ρ c is the density of the core, λ is the scalingfactor of the core, and ρ m is the density of the mantle, units: kg m −3 ). All small bodies (radius smaller than 20 km) with known second order and degree gravity models ( Miller et al. 2000 ; Zuber et al. 2000 ;
Paper: 2017MNRAS.471L..87O (fulltext)
of SFRs and molecular gas fraction. The initial density profile of the dark matter halo in a disc galaxy is modelled using the density distribution of the NFW halo (Navarro, Frenk White 1996 ) as suggested from cold dark matter (CDM) simulations. The c -parameter ( c r vir r s , where r vir and r s are the virial radii of a dark matter halo and the scale length, respectively) and r vir are chosen appropriately by using recent predictions from cosmological simulations (Neto, Gao Bett 2007 ). We adopt the Hernquist density profile for the bulge of a disc galaxy and the bulge mass fraction ( M b M s ) is a free parameter ranging from 0 to 1. The size ( R b ) and the mass of the bulge have the following scaling relation that can reproduce the properties of the Galactic bulge: kpc. The radial ( R ) and vertical ( Z ) density profiles of the stellar disc are assumed to be proportional to exp( R R 0 ) with a scale length R 0 0.2 R s and to sech 2 ( Z Z 0 ) with a scale length Z 0 0.04 R s , respectively. The gas disc with a size of R g has the radial and vertical scale lengths of 0.2 R g and 0.02 R g , respectively. Since we investigate disc models with M h similar to that of the Galaxy (i.e. M h 10 12 M ), the exponential disc has R s 17.5kpc for all models in the present model. The initial Toomres parameter Q is set to be 1.5 for gas and stars and the vertical velocity dispersion at a given radius is set to be 0.5times as large as the radial velocity dispersion at that point so that the dynamical equilibrium in the vertical direction can be achieved. A gas particle is assumed to be converted into a new star if the local H 2 density (, where and g are the H 2 mass function and gas density, respectively) exceeds a threshold density ( th ) and we investigate the models with th 10, 30 and 100cm 3 . These are H 2 -dependent SF models, and we also investigate H-dependent one in which g should be higher than th . We adopt these values because our previous numerical simulations of galaxy evolution with dust demonstrated that the models with the above values can explain the observed SFR g relation (see fig.3 in Yozin Bekki 2014 for the case of the Magellanic Clouds). We assume that SFR ( sf 1.5) in this study. Chemical enrichment processes, dust formation and evolution in ISM and SN feedback effects are included in the same way as B13 and B15 . We investigate disc models with corotating (referred to as standard rotation and labelled as S for convenience) and counter-rotating (C) gas discs for a given set of disc parameters. By comparing between the two models, we try to understand how counter-rotating gas can influence dynamics and star formation histories of disc galaxies. We show the results for only 24 models in this study and Table 1 describes the model parameters for each of the SC pairs. The total number of particles used for a simulation is 1033400 for a fiducial model (M1 and M2) and different initial gravitational softening lengths () are
Paper: 2021MNRAS.502.3101N (fulltext)
galaxies, not the lower z ones in our low-mass sample (see XXL paper XXVII). We label these two as BG? in the table. Removing all seven likely or possible contaminants, 8 all of which have s > 5 arcsec, then leaves us with 20 likely genuine matched low-mass emission-line objects (though alternate matches may still exist for a few of them, cf. XXL paper XXVII). The X-ray sources matched to these 20 emission-line galaxies lie in the range L Xs = 10 39.2 to 10 41.1 erg s −1 . The highest X-ray luminosities appear to (just) fit in the expected range, which cuts off at ∼10 41 erg s −1 (e.g. Mineo et al. 2012 ) if the extension of HMXBs into ULXs is included. In total, then, a reasonable number, ≃20, likely XRBs have been found, probably mostly HMXBs in low-mass star-forming galaxies. For these, there is no correlation between X-ray luminosity and emission-line luminosity, which can easily be explained if the X-rays are from individual single HMXBs while the line emission reflects the ISM conditions and star formation in the galaxy. It is difficult to relate our present results to those in the literature on the prevalence of HMXBs in brighter/more massive star-forming galaxies, for a number of reasons. In particular, we are able to detect only the brightest X-ray sources and have a flux limited rather than volume limited sample. Our nearest and faintest source is at 10 39.2 erg s −1 while at the redshift of our most distant matched low-mass galaxy ( z ≃ 0.1) the detection limit is approaching 10 41 erg s −1 . This can be contrasted with, for example, the general study of local star-forming galaxies by Mineo et al. ( 2012 ) who found about one HMXB for every 0.3 yr −1 of star formation, but with a detection limit 10 38 erg s −1 , considerably below our accessible limits. Using a reasonable slope of the HMXB luminosity function (e.g. Grimm et al. 2003 ), we would need to correct the numbers detected in even nearby redshift bins (say at z ≃ 0.03, where the effective limit is around 10 39.5 erg s −1 ) by an order of magnitude, and in our more distant bins we are in the tail of the LF, near the upper cut-off, requiring very large (around two orders of magnitude) and very uncertain corrections. The best we can probably say is that, given our 20 actual detections, we would expect perhaps of order 500 detections if we had a similar X-ray limit to Mineo et al. In addition, the intercomparison of SFRs is problematic: translating H α luminosities to total SFRs (e.g. Kennicutt 1994 ) involves numerous uncertain steps (e.g. use of a particular initial mass function) and Mineo et al. ( 2012 ) use a completely different method based on infrared and ultraviolet luminosities. If, for a concrete example, we simply translate H α luminosity to an ‘indicative’ SFR via Kennicutt ( 1983 )’s relation SFR ≃ L H α /(10 41 erg s −1 ) yr −1 , ignoring any systematics in this translation, 9 then the total indicative SFR summed over our 21 low-mass host galaxies (we exclude
Paper: 2019ApJ...873..112L (fulltext)
which Geotail was inside the solar wind, produced by the NASA at the GFSC ( ftp://spdf.gsfc.nasa.gov/pub/data/geotail/merged/sw_min_merged_ascii ), and by assuming a shock-simplified model (from Cairns et al. 1995 ; Farris et al. 1999 ) we considered only the time intervals in which the spacecraft was located inside the solar wind but outside the foreshock. These conditions are verified by examining magnetic field data from both Geotail and IMP-8 and by comparing these measurements with corresponding observations made by both ACE and WIND , which are located inside the solar wind. Table 2 reports the time periods when Geotail was in the solar wind. Table 2 Time Periods When Geotail Was in the Solar Wind In particular, we used the Geotail EPIC-ICS experiment data related to the proton flux measured in 9 different energy channels, from 58 keV to 3 MeV, characterized by 16 azimutal sectors (Williams et al. 1994 ). By averaging the fluxes over all azimutal sectors we computed the omnidirectional fluxes at hourly resolution. Table 1 shows the details of the EPIC-ICS energy ranges. Figure 3 shows the proton flux for the different energy channels. As expected, low-energy channels measure greater proton fluxes than high-energy ones: typically, G1–G4 show one (up to two) order of magnitude proton flux increases with respect to G5–G9. Finally, a reduction in the proton flux during the period 1995–1997, corresponding to the minimum phase of SC No. 22, is observed at high energies. Figure 3. Time history of the proton flux measured in the nine energy channels (G1–G9) of the EPIC-ICS experiments on board Geotail . The x -axis labels refer to the time periods when Geotail was in the solar wind. 3. Background Proton Fluxes: CDF Analysis To investigate the variability of the background proton fluxes we used a statistical approach based on the evaluation of the CDF for each energy channel. For each considered data set from ACE , IMP-8 , and Geotail , the PDFs, from which CDFs can be obtained, have been evaluated using a non-parametric approach based on the kernel density estimator technique (e.g., Silverman 1998 ; Alberti et al. 2014 , 2017b , for more details) with the definition of a non-negative function, called a kernel function, with zero mean and integrating to one, and by choosing an appropriate smoothing parameter, called the bandwidth. From the class of kernel functions (Gaussian, Epanechnikov, Triangular, and so on) a good choice is the Epanechnikov kernel, which is optimal in a minimum variance sense. Kernel density estimates are closely related to histograms, but can be endowed with properties such as smoothness or continuity by using a suitable kernel. Thus, when PDFs have been evaluated, CDFs are obtained as the probability that F ′ will take a value less than or equal to a value F (with being F the proton flux). In the case of a continuous distribution, it gives the area under the probability density function from minus infinity to F :In
Paper: 2017A&A...602A...8G (fulltext)
in general (see e.g. Viti et al. 2001 ; and Hollenbach et al. 2009 , for a discussion of this specific aspect). Meaningful constraints on the oxygen chemistry could then be obtained through the observation of HO and O. Unfortunately, no velocity-resolved observations of water have been performed in Cep E by Herschel , and no instrument can allow them at the moment. O is best observed from space observatories (the transition at 487.249 GHz is close to an atmospheric absorption feature), but it has not been observed in Cep E, and its symmetry makes its detection difficult from the outset. Another possibility is that the shock that we observed is illuminated by the protostar that drives the outflow. In such irradiated shocks (e.g. Lesaffre et al. 2013 ; Melnick Kaufman 2015 ), both HO and CO can be photo-dissociated, increasing the gas-phase abundance of O i . This effect is not taken into account in the Paris-Durham code. However, the possibility that shocks at position BII could be affected by the distant protostar is relatively low: the BII and mm position are pc away. The Cep E-mm protostar has a luminosity of about 100 , and a T-Tauri star typically emits between 10 and 10 of its total luminosity in the UV range between 3200 and 5200 Å ( Gullbring et al. 1998 ). Conservatively assuming that Cep E-mm is radiating 10% of its total luminosity in this UV range and taking dilution into account, we found that the radiation field in BII is about 4.8 in units of Draine’s ( Draine 1978 ) or Mathis’s ( Mathis et al. 1983 ) interstellar radiation field (ISRF). This value has then to be corrected for the absorption by dust grains. We assumed an average local density in the outflow cavity of 10 cm, which translates into a column density of cm and into a visual extinction of mag ( Lefloch et al. 1996 provided local estimates for this value: 61 mag around the driving protostar, and 3.2–3.4 mag in the H knots along the flow). Using the exponential attenuation approximation , where , and is the effective attenuation cross section from Draine Bertoldi (1996) , we found that the radiation field really felt in BII is about in Draine’s or Mathis’s ISRF units. Another explanation is that several shock structures are present in our beam. In this case, the missing O i emission could be accounted for by the presence of another shock structure. This additional shock layer must present different physical characteristics, as simply combining shock layers similar to those we used would simultaneously increase the [OI] emission insufficiently and increase the CO emission too much, producing another type of discrepancy between observations and models. One such shock structure could be a stationary dissociative -type shock. In particular, a -type shock with cm, magnetic field parameter , and shock velocity km s ( Flower Pineau des Forêts 2015 ) could be combined with our current best-fit solution, providing a satisfying fit for the O i and CO emission. The additional
Paper: 2020MNRAS.494.3616N (fulltext)
internal energy per unit mass, g is the gravitational acceleration of the black hole located at ( r , θ) = ( z 0 , π), and f is the radiation force per unit mass (see Section 2.2 for detail). An adiabatic equation of state p /ρ = (γ − 1) e with γ = 5/3 is assumed in our calculations. In the last term of equation ( 5 ), is the approximate formula of the net heating rate introduced by Blondin ( 1994 ) where, n is the number density, G Compton is the heating rate via the Compton scattering G X is the difference between the heating rate by the X-ray photoionization and the cooling rate via the recombination and L b,l is the cooling rate by the bremsstrahlung and line emission In equation ( 9 ), the first term represents the effect of the bremsstrahlung and the last two terms show the line cooling in an optically thin atmosphere. The temperature T is obtained by T = μ m p p/k B ρ, where μ (=0.5) is the mean molecular weight, m p is the proton mass, and k B is the Boltzmann constant. The ionization parameter, ξ, is defined as where F X is the X-ray flux. In this study, the X-ray is assumed to come from the point source at the centre with luminosity L X = f X L D , where f X is a parameter. We also assume the temperature of the X-ray radiation to be . The X-ray flux is attenuated via the absorption of which the cross-section is set to be σ X = σ e for ξ > 10 5 , or 100σ e for ξ ≤ 10 5 , where σ e is the mass-scattering coefficient for free electrons. Such a treatment is employed in previous works (Proga et al. 2000 ; Nomura et al. 2016 , N17 ). We note that the scattered and reprocessed photons are ignored in our simulations (see also Section 4.2 ). 2.2 Line force The radiation force in equations ( 2 ) and ( 3 ) is described as where F D is the radiation flux of the disc emission integrated by the wavelength throughout the entire range, and F line is the line-driving flux (UV flux), which is the same as F D but integrated across the UV transition band of 200– Å. Both fluxes are calculated by integrating the radiation from the inner hot region of the disc, where the effective temperature is larger than . We divide the disc surface into 4096 grids for radial direction and 4096 grids for azimuthal direction, and numerically calculate and . The radial components of these fluxes are attenuated due to electron scattering, of which the optical depth is measured from the origin of the coordinate. On the other hand, θ-components of and are supposed not to be diluted. The force multiplier, M , is defined by Stevens Kallman ( 1990 ) Here, t is the local optical depth parameter written as Here, the thermal speed, v th , is set to that corresponds to the thermal speed of the hydrogen gas of the temperature of . The velocity gradient, d v /d s , depends on the direction of each light-ray from the disc surface to the point of interest. However, in order to reduce the computational cost, we evaluate d v /d s along the direction of the disc line-driving flux ( F
Paper: 2016MNRAS.457.3306O (fulltext)
−3 are the critical densities of the S(0):2–0 and S(1):3–1 rotational lines. r op is the ortho-H 2 /para-H 2 ratio (set to 3 which is the equilibrium value). For the cooling rates due to the [C ii ]158 μm and [O i ]63 μm+146 μm fine-structure lines we adopt the parametrizations by Röllig et al. ( 2006 ). The C ii cooling rate () is where a carbon to hydrogen abundance ratio that scales with metallicity according to χ [C] = 1.4 × 10 −4 Z ′ is assumed. For the parametrization of the O i cooling rate () we refer to equations (A.5) and (A.6) in Röllig et al. ( 2006 ) and simply note that we adopt (in accordance with Röllig et al. 2006 ) an oxygen to hydrogen abundance ratio of χ [O] = 3 × 10 −4 Z ′. Λ CO is the cooling rate due to CO rotational transitions. We use the parametrization provided by Papadopoulos Thi ( 2013 ): where χ CO /χ [C] is the relative CO to neutral carbon abundance ratio, the value of which we determine by interpolation, assuming that χ CO /χ [C] = (0.97, 0.98, 0.99, 1.0) for cm −3 , respectively (Papadopoulos Thi 2013 ). Λ gas–dust is the cooling rate due to gas–dust interactions and is given by (Papadopoulos et al. 2011 ) where the dust temperature ( T dust ) is calculated using equation ( 15 ) (Section 3.4.3 ). APPENDIX C: GMC MODELS Each SPH particle is divided into several GMCs as described in Section 3.4.1 , and we derive the molecular gas density and temperature within each from three basic parameters which are SFR density, GMC mass, m GMC , and metallicity, Z ′/ Z ⊙ . Derived from these basic parameters are the far-UV and CR field strengths, the H 2 gas mass fraction of each SPH particles, as well as the GMC properties used to derive the CO excitation and emission; H 2 density and temperature. Histograms of the basic parameters are shown in Fig. C1 , while properties derived thereof can be found in Fig. C2 . Figure C1. Mass-weighted histograms of the basic parameters of the GMCs in G1 (red solid), G2 (green dashed), and G3 (blue dotted). From top left and clockwise: the local far-UV field () (and CR ionization rate since ), GMC mass ( m GMC ), metallicity ( Z ′) and external pressure ( P ext ). Black vertical lines indicate the , m GMC , Z ′, P ext -values for which curves were calculated (see Fig. C2 ) – a total of 630 GMCs which make up our grid GMC models. Each GMC in the galaxies is assigned the curve of the GMC model at the closest grid point. Figure C2. Kinetic temperature versus H 2 density curves for 80 out of the 630 grid model GMCs that span the full (, M GMC , Z ′) parameter space set by and marked on top of the distributions in Fig. C1 (see also Section 3.4.4 ) for a pressure of K cm −3 . The grid model most often assigned to GMCs in G1 is indicated by the red dashed curve in the highlighted panel and corresponds to ( s −1 ), , and Z ′ = 3.2. In general, higher metallicity (from top to bottom) leads to more cooling via emission lines of ions, atoms and molecules, and hence lower temperatures. On the other