adsabs/FOCAL huggingface dataset:
Although the magnetic (i.e., one-photon) pair production is also taken into account, most electron–positron pairs are found to be produced via photon–photon (i.e., two-photon) collisions, which take place via two paths. One path is through the collisions of two MeV photons, both of which were emitted from the equatorial ADAF. Another path is through the collisions of TeV and eV photons; the former photons were emitted by the gap-accelerated leptons via inverse Compton process, while the latter were emitted from the ADAF via the synchrotron process. There is, indeed, a third path, in which the gap-emitted GeV curvature photons collide with the ADAF-emitted keV inverse Compton photons; however, this path is negligible, particularly when 





. If the pairs are produced via TeV–eV collisions (i.e., via the second path) outside the gap outer boundary, they have outward ultrarelativistic momenta to easily “climb up the hill” of the potential k0 (Takahashi et al. 1990; see also Figure 2 of HP16) and propagate to large distances without turning back. However, if the pairs are produced via MeV–MeV collisions (i.e., via the first path), they are produced with subrelativistic outward momenta; thus, they eventually return to fall onto the horizon owing to the strong gravitational pull inside the separation surface (Figure 2 of HP16). When the returned pairs arrive at the gap outer boundary, only positrons can penetrate into the gap because of E∥  0. Accordingly, electrons accumulate at the boundary, whose surface charge leads to the jump of the normal derivative of E∥. Thus, although the stationary gap solutions show that the γ-ray spectrum little depends on the injected current density (Section 5.5), the gap solution inevitably becomes time dependent owing to the increasing discontinuity of 





 with an accumulated surface charge (in this case, electrons) at the outer boundary. If the injected current is much small compared to the GJ current, the time dependence will be mild. However, if the injected current becomes a good fraction of the GJ current, the assumption of the stationarity becomes invalid, as pointed out by Levinson & Segev (2017). In this sense, a caution should be made in the applicability of the stationary solutions presented in this paper, when the injected current is non-negligible compared to the current created within the gap.
Citation: Takahashi et al. 1990
Citation function: Compare/Contrast; Compare/Contrast
In regarding AGNs, the Te method tends to underestimate the oxygen abundance by an average value of about 0.6 dex in comparison to estimations based on strong-line methods and it produces subsolar O/H values for most of these objects (Dors et al. 2015; Dors, Freitas-Lemes & Âmores 2020). An alternative method to derive the metallicity or abundances in the nuclear regions of spiral galaxies is the extrapolation of the radial oxygen abundance. Along decades, results based on this indirect method have indicated Z near or slightly above the solar value in nuclear regions (Vila-Costas & Edmunds 1992; Zaritsky, Kennicutt & Huchra 1994; van Zee et al. 1998; Pilyugin, Vílchez & Contini 2004; Gusev et al. 2012; Dors et al. 2015; Zinchenko et al. 2019), in consonance with predictions of chemical evolution models (e.g. Mólla & Díaz 2005) and with the use of strong-line methods (e.g. Groves, Dopita & Sutherland 2004; Groves, Heckman & Kauffmann 2006; Feltre, Charlot & Gutkin 2016; Pérez-Montero et al. 2019; Thomas, Kewley & Dopita 2019; Dors et al. 2020). Therefore, Temethod does not seem to work for AGNs. The origin of the discrepancy between Z values calculated via Te method and via strong-line methods, the so-called Teproblem, could be attributed, in part, to the presence of heating/ionization by gas shock in the narrow-line region (NLR) of AGNs. In fact, Contini (2017) carried out detailed modelling of AGN optical emission lines by using the SUMA code (Contini & Aldrovandi 1983) and suggested the presence of gas shock with low velocity ($v \: \lesssim \: 400 \: \rm km \:s^{-1}$) in a sample of Seyfert 2 nuclei. This result is supported by recent spatially resolved observational studies of Seyfert 2 nuclei, in which the presence of gas outflows with velocity of the order of 100–300 $\rm km \: s^{-1}$ have been found (e.g. Riffel, Storchi-Bergmann & Riffel 2017; Riffel, Hekatelyne & Freitas 2018). Moreover, the Te problem can also be originated due to the use of an unappropriate calculation of the ionization correction factor (ICF) for oxygen in AGNs (Pérez-Montero et al. 2019; Dors et al. 2020).
Citation: Pérez-Montero et al. 2019
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Citation: Pérez-Montero et al. 2019
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The results presented in this paper are based on data from IllustrisTNG,1the next-generation suite of state-of-the-art magnetohydrodynamical cosmological simulations of galaxy formation (Marinacci et al. 2018; Naiman et al. 2018; Nelson et al. 2018; Pillepich et al. 2018b; Springel et al. 2018). Building on the success of its predecessor Illustris (Genel et al. 2014; Vogelsberger et al. 2014a,b; Nelson et al. 2015; Sijacki et al. 2015), IllustrisTNG follows the same fundamental approach but includes improved aspects and novel features in its galaxy formation model and expands its scope to several simulated volumes and improved resolution. The models for galaxy formation include physical processes such as gas heating by a spatially uniform and time-dependent UV background, primordial and metal-line gas cooling, a subgrid model for star formation, and the unresolved structure of the interstellar medium (Springel & Hernquist 2003), as well as models for the evolution and chemical enrichment of stellar populations, which track nine elements (H, He, C, N, O, Ne, Mg, Si, and Fe) in addition to europium and include yields from supernovae Ia, II, and AGB stars (Vogelsberger et al. 2013; Torrey et al. 2014). Furthermore, IllustrisTNG incorporates improved feedback implementations for galactic winds caused by supernovae as well as accretion and feedback from black holes. In particular, depending on accretion, black hole feedback occurs in two modes: low accretion rates result in purely kinetic feedback while high accretion rates invoke thermal feedback (Weinberger et al. 2017). Galactic winds are injected isotropically and the wind particles’ initial speed scales with the one-dimensional dark matter velocity dispersion (Pillepich et al. 2018a). Magnetic fields are amplified self-consistently from a primordial seed field and follow ideal magnetohydrodynamics (Pakmor & Springel 2013). The TNG simulations were run using the moving mesh code arepo (Springel 2010). Here, concepts from adaptive mesh refinement and smooth particle hydrodynamics are combined to create an unstructured, moving Voronoi tessellation. IllustrisTNG follows the ΛCDM framework, adopting cosmological parameters according to recent constraints from Planck data: matter density $\Omega _\rm {m} = 0.3089$, baryonic density $\Omega _\rm {b} = 0.0486$, cosmological constant $\Omega _\Lambda = 0.6911$, Hubble constant h = 0.6774, normalization σ8 = 0.8159, and spectral index $n_\rm {s} = 0.9667$ (Planck Collaboration I 2016).
Citation: Springel & Hernquist 2003
Citation function: Uses
Observed high mass end power-law index of the galaxy-wide IMF resulting from the calculated IGIMF, \hbox{$\alpha_3^{\mathrm{gal}}$}α3gal (i.e., αgal in Eq. (15) for m> 1 M⊙), for a constant SFR over δt = 10 Myr in dependence of the galaxy-wide SFR. In Fig. 5, \hbox{$\alpha_3^{\mathrm{gal}}$}α3gal values diverge for different SFRs and also vary for different m at the high mass end. As at each m value there exists a different \hbox{$\alpha_3^{\mathrm{gal}}$}α3gal–SFR relation, we plot solid lines for log 10(m/M⊙) = 0.2, 0.4, ..., 2, i.e., 1.58, 2.51, ..., 100 M⊙ from black to gray (top to bottom) for the fiducial model and dotted lines for the corresponding SolarMetal model defined in Sect. 2.1. The blue squares are data from the GAMA galaxy survey (Gunawardhana et al. 2011). The red triangles and red dash-dotted line are data from Weidner et al. (2013b); the left triangle is for the MW field, the middle three triangles are galaxy studies, the right triangle is for the bulges of the MW and M 31, and the dash-dotted line is their IGIMF model assuming β = 2. A recent study has suggested that the 2 M⊙/yr SFR for MW is overestimated (Chomiuk & Povich 2011), but we leave this data point the same as in Weidner et al. (2013b). Gargiulo et al. (2015) report consistency between their IGIMF model assuming β = 2 (thick yellow dashed line) and the [α/Fe] abundance ratios of elliptical galaxies. The purple diamond is an individual analysis for the dwarf galaxy NGC 2915 (Bruzzese et al. 2015). Green stars are based on the Lee et al. (2009) 11HUGS observations of dwarf galaxies. The black circle is an observation for the solar neighborhood from Rybizki & Just (2015) with adopted MW SFR from Robitaille & Whitney (2010) as an upper limit of the solar neighborhood SFR because the Sun is located in an inter-arm region where the relevant SFR is significantly smaller (toward the direction indicated by the arrow; see Sect. 4.6 for further details). The thin horizontal dashed line represents the canonical IMF index α2 = α3 = 2.3.
Citation: Gunawardhana et al. 2011
Citation function: Uses
To constrain the size of outflows that we could have missed, we performed simple simulations. We placed artificial, unipolar secondary sources next to a primary point source model representing Sgr A* and compared the closure phases obtained from the resulting artificial visibility data with the observations. We considered two geometries: a single-point source and a jet composed of ten equally spaced point sources (knots) with equal fluxes. We probed four orientations for the simulated outflows (see Fig. 2): along the major axis, along the minor axis of the beam, the jet direction claimed by Li et al. (2013), and the jet direction claimed by Yusef-Zadeh et al. (2012). We used total fluxes of 0.2 Jy and 0.55 Jy for the artificial sources; these values ensure that our simulated outflows are sufficiently faint to not violate the constraints given by the known recent brightness evolution of Sgr A* (0.2 Jy from the mean variability of ≈15% from June 2013 to February 2014 at 41 GHz, with 0.55 Jy corresponding to the strongest variation in the same period, Chandler & Sjouwerman 2014). For each simulation setup, we measured the average of absolute values of the closure phases for each triangle. We varied the distances of the model sources (for the jet model: the largest distance) from Sgr A* until we found a critical distance at which the absolute values of the simulated closure phases exceeded those of the observations by more than the 1σ error at all triangles. We summarize our results in Table 1. As expected, the critical distances are smaller for brighter outflows. Jet-like structures lead to larger critical distances than equally luminous single, compact sources. As a consequence of the very elongated beam, the critical distances for sources located along the major axis of the beam are larger by a factor of ≈7 than for those located along the minor axis. In a few cases (denoted “N/A” in Table 1), the absolute values of the simulated closure phases were similar to those of the observations for all distances of the model sources, meaning that we were unable to identify a critical distance. Overall, our observations limit the extension of asymmetric (in the observer frame) jet-like outflows from Sgr A* to projected distances of ≈2.5 mas along the major axis and ≈0.4 mas along the minor axis.
Citation: Chandler & Sjouwerman 2014
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Citation: Li et al. (2013)
Citation function: Uses; Uses
There is good observational and theoretical evidence that supermassive black holes (SMBHs) exist in nearly every galaxy in universe. Understanding the properties of these SMBHs will clarify their roles in galaxy formation and evolution across the cosmology history (e.g. Kormendy & Ho 2013). There are mainly two parameters for an SMBH, i.e. mass (MBH) and spin, which need to be determined. For a few very nearby (100 Mpc) quiescent galaxies, including our Galaxy, SMBH masses can be measured through the stellar or gaseous dynamics method (e.g. Tremaine et al. 2002; McConnell et al. 2011). It has been found that nearby quiescent galaxies follow a tight correlation between the central SMBH mass and the bulge or spheroid stellar velocity dispersion (σ*), which is called MBH–σ* relation (e.g. Kormendy & Ho 2013). Active galactic nuclei (AGNs) can be classified into type 1 or type 2 AGNs, depending on whether the broad-line regions (BLRs) can be viewed directly. For type 1 AGNs, the BLR can be used as a probe of the gravitational potential of the SMBHs. The SMBH mass can be weighed through the BLR clouds for type I AGNs across cosmos time. The SMBH masses in type I AGNs can be calculated as follows (e.g. Kaspi et al. 2000; Bian & Zhao 2002; Peterson et al. 2004; Collin et al. 2006; Du et al. 2016a; Yu et al. 2019):
(1)$$\begin{eqnarray*}
M_{\rm BH} =f_{\rm BLR}\frac{R_{\rm BLR}~(\Delta V)^2}{G},
\end{eqnarray*}$$where G is the gravitational constant. RBLR is the distance from black hole to the BLRs, and can be estimated from the reverberation mapping (RM) method (e.g. Blandford & McKee 1982; Peterson 1993). ΔV is the velocity of the BLR clouds, and usually traced by the full width at half-maximum (FWHM) or the line dispersion (σH β) of the broad H β emission line. fBLR is a virial factor to characterize the kinematics, geometry, and inclination of the BLR clouds. Using the MBH–σ* relation, we recently did the calibration of fBLR and found $f_{\rm BLR} \propto \rm FWHM^{-1.11}$ when FWHM(H β) is used as the tracer of ΔV in equation (1) (Mejia-Restrepo et al. 2018; Yu et al. 2019). It is consistent with the results by the BLR dynamical model to fit simultaneously the AGNs continuum/H β light curves and H β line profiles (e.g. Li et al. 2018; Pancoast et al. 2018; Williams et al. 2018).
Citation: McConnell et al. 2011
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Based on previous works (Kawamuro et al. 2013; Tazaki et al. 2013), we start with a base-line model,





in the XSPEC terminology. This model includes absorbed primary X-ray emission (i.e., a cut-off power law), a scattered component, and a reflection continuum from distant cold matter accompanied by a narrow iron-Kα line. Optically thin thermal emission from the host galaxy (apec in XSPEC) and other emission/absorption lines (zgauss) are also added if they are significantly required with a confidence level above 90% in terms of Δχ2. Because it is difficult to determine the cut-off energy from our data, we fix it at 300 keV, which is a typical value measured in nearby AGNs (Dadina 2008). The first constant factor, NXIS, is applied to the primary power-law component in the Suzaku spectra to absorb possible time variability between the Suzaku (one epoch) and Swift/BAT (averaged for 70 months) observations. The second constant term represents the scattered fraction, fscatt. As a reflection component from the torus, we employ the pexrav model, which calculates a reflected spectrum from an optically thick slab with a solid angle of Ω irradiated by a point source (Magdziarz & Zdziarski 1995). We set the reflection strength, R = Ω/2π, as a free parameter, and fix the inclination angle at 60°. It is confirmed that even if 30° is adopted, best-fit parameters do not significantly change. The shape of the incident spectrum is assumed to be the same as the power-law component. We basically assume that the reflection and scattered components did not vary between the Suzaku and Swift/BAT observations, considering that the size of the reflector most likely has a parsec scale. In the three low-mass LLAGNs (NGC 4395, NGC 5273, and NGC 5643), however, we assume that the reflection component varied in accordance with the primary emission because of a smaller size of the emitting regions. Thus, in these targets, R is defined with respect to the primary component in the Suzaku data. The zgauss component represents an iron-Kα fluorescence line. The line width is fixed at 20 eV, which corresponds to a typical velocity dispersion of ∼2000 km s−1 measured with Chandra/HETGS in local Seyfert galaxies (Shu et al. 2010). We always consider the Galactic absorption 





, which is calculated with the nh command (Kalberla et al. 2005) in FTOOLS.
Citation: Dadina 2008
Citation function: Uses
We suggest that the jet–facula collision does not cause a change in the field-line connectivity and only leads to the redistribution of jet material. There are two main reasons supporting this viewpoint. The first is the 3D magnetic configuration at the collision region. The penumbra and facula are both located at negative-polarity magnetic fields and the relative orientation of the two flux systems is nearly parallel (Fig. 5). When the magnetic field lines are parallel it is not easy to have reconnection (Feynman & Martin 1995; Galsgaard et al. 2007). As suggested by Gopalswamy et al. (2009), there are two possibilities during the CME–CH interaction. When the magnetic fields in the CME and the CH are parallel, deflection of the CME takes place. When the CME field lines are antiparallel to the CH field lines, magnetic reconnection is possible. In our event, the jet–facula collision is similar to the first situation of CME–CH interaction. The second reason is the absence of reconnection signatures. The jet–facula collision does not produce any impulsive brightenings in the collision region in the H α and EUV images. Although RFJ was heated after the collision, the heating of RFJ is less intense and concentrated than the reconnection heating, and is probably caused by collision-induced conversion of kinetic energy to thermal energy. Due to the interaction of the primary FJs with the facula structure, the material of primary FJs is redistributed, with partial material propagating along the QSL fan plane and forming the AFJs. It is the apparent material end that differentiates the primary FJs and AFJs observationally. In the aspect of magnetic fields, the primary FJs and AFJs are along the same magnetic field lines from the sunspot. Direct observations of the jet–facula collision process and apparent fan-shaped jets are very rare. Thus it is difficult to give an exact physical explanation based on the present observations. If more related cases could be observed in future, we expect to be able to interpret in depth the physical mechanism of collision-induced apparent jets.
Citation: Galsgaard et al. 2007
Citation function: Uses
Gamma-ray bursts (GRBs) are among the most powerful gamma-ray sources in the universe. They could be generated from the merger of binary compact objects (BCOs; Duncan & Thompson 1992; Usov 1992; Thompson 1994; Metzger et al. 2011) or the death of massive stars (Woosley 1993; Paczyński 1998; Woosley & Bloom 2006a). The merger of BCOs; a black hole (BH)–a neutron star (NS) or NS–NS, leading to kilonovae (KNe), is correlated with short-duration gamma-ray bursts (sGRBs; T
90

10


10

T
90 is defined as the time during which the cumulative number of collected counts above background rises from 5% to 95%. ≲ 2 s; Li & Paczyński 1998; Rosswog 2005; Metzger et al. 2010; Kasen et al. 2013; Metzger 2017). On the other hand, long-duration gamma-ray bursts (lGRBs; T
90 ≳ 2 s; Kouveliotou et al. 1993) are associated with the core collapse (CC) of dying massive stars (Woosley 1993; Galama et al. 1998) leading to supernovae (SNe; Bloom et al. 1999; Woosley & Bloom 2006b). It is believed that in both scenarios large quantities of materials with a wide range of velocities are ejected. In the framework of CC-SNe (depending on the type of SN association), several materials ejected with sub-relativistic velocities less than β ≲ 0.4
11


11
Hereafter, we adopt natural units c = ℏ = 1. have been reported (see, e.g., Kulkarni et al. 1998; Bloom et al. 1999; Woosley & Bloom 2006b; Valenti et al. 2008; Gal-Yam 2017; Izzo et al. 2019, 2020; Modjaz et al. 2020; Nicholl et al. 2020). Regarding the merger of two NSs, sub-relativistic materials such as the cocoon, the shock breakout, and the dynamical and wind ejecta are launched with velocities in the range 0.03 ≲ β ≲ 0.8
12


12
Some authors have considered the shock breakout material in the sub-, trans-, and ultra-relativistic regimes (see, e.g., Kyutoku et al. 2014; Metzger et al. 2015; Fraija et al. 2019c). (see, e.g., Dessart et al. 2009; Metzger & Fernández 2014; Fernández et al. 2015; Kyutoku et al. 2014; Metzger et al. 2015; Nagakura et al. 2014; Murguia-Berthier et al. 2014; Lazzati et al. 2017, 2018; Goriely et al. 2011; Hotokezaka et al. 2013; Bauswein et al. 2013; Wanajo et al. 2014). While the mass and velocity inferred for the first GRB/KN association
13


13
GRB 170817A/AT 2017gfo. were M
ej ≈ (10−4−10−2)M
⊙ and β ≈ (0.1−0.3), respectively (Coulter et al. 2017; Arcavi et al. 2017; Cowperthwaite et al. 2017; Nicholl et al. 2017; Metzger 2019), the mass and velocity inferred for the first GRB/SN association
14


14
GRB 980425/SN1998bw. was M
ej ≈ 10−5
M
⊙ and β ≈ (0.2–0.3), respectively (Kulkarni et al. 1998).
Citation: Woosley & Bloom 2006b
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Citation: Woosley & Bloom 2006b
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HD 97048 is yet another disk for which the dust emission at (sub-)mm wavelengths shows evidence of axisymmetric ring-like structures, here on spatial scales of around tens of au (Walsh et al. 2014; ALMA Partnership et al. 2015; Andrews et al. 2016; Nomura et al. 2016; Zhang et al. 2016). We predict that this substructure will be clearly evident in images of HD 97048 at higher spatial resolution (≈10–20 au, see Figure 13). There remains much debate in the literature on the origin of such axisymmetric substructure in protoplanetary disks including gaps and dust traps carved by forming planets (see, e.g., Dipierro et al. 2015; Pinilla et al. 2015; Rosotti et al. 2016), a change in dust opacity properties at the positions of snow lines (e.g., Banzatti et al. 2015; Zhang et al. 2015; Guidi et al. 2016; Okuzumi et al. 2016), and toroidal dust traps created by hydrodynamic or magnetohydrodynamic effects (see, e.g., Pinilla et al. 2012b; Lorén-Aguilar & Bate 2015; Ruge et al. 2016). To distinguish between each of the scenarios requires observations of dust emission at multiple and well-separated frequencies to determine the radial dust size and density distribution (and dust opacity index) along with emission from optically thin gas tracers to determine the gas surface density. Planets will create deep gaps in the gas surface density as well as influencing the dust (note that this is dependent on the planet mass, see e.g., Rosotti et al. 2016), toroidal instabilities will create much shallower features in the gas surface density, and opacity changes at snow lines will affect only the dust emission and will have no effect on the gas. We note that the ringed substructure seen here has very recently been confirmed in scattered light images of HD 97048 taken with VLT/SPHERE (Ginski et al. 2016). An initial (and shallow) comparison of the data sets shows remarkable coincidence between the positions of the (sub-)mm peaks and gaps and those seen in scattered light. That such structure is seen in both small (≈μm-sized) dust grains in the disk atmosphere and large (≈mm-sized) dust grains in the disk midplane points toward a (proto)planetary system origin; however, further data, particularly to better constrain the gas structure, are needed for confirmation. Since this paper has been accepted for publication, ALMA Cycle 2 data of HD 97048, for which longer baseline data were available and imaged with a uv clip (>160 kλ), resulted in a beam of 048 × 026 (18°) and resolved the inner dust cavity (40 – 46 au) and the bright dust ring at ≈150 au (van der Plas et al. 2016).
Citation: Lorén-Aguilar & Bate 2015
Citation function: Motivation; Motivation