adsabs/WIESP2022-NER huggingface dataset:
Paper: 2016MNRAS.462..715W (fulltext)
similar to those presented in this paper to fully validate such methods. APPENDIX A: Implementing <italic toggle="yes">f</italic>(<italic toggle="yes">R</italic>) model in <sc>mgenzo</sc> We present here a brief overview of the modified gravity (Hu–Sawicki) model used in this paper which has been implemented via our mgenzo software. This software is a variant of the well-established enzo code and is fully described in Zhao et al. (in preparation). mgenzo has been extensively studied using several independent N -body codes including mgmlapm (Zhao, Li Koyama 2011 ) and ecosmog (Li et al. 2012 ). The mgenzo code uses the same algorithm to solve for the non-linear scalar field equations as the mgmlapm and ecosmog code. Previous results from mgenzo have been validated against other N -body and hydrodynamical simulations of the Hu–Sawicki model, including the code comparison work of Winther et al. ( 2015 ) and Hammami et al. ( 2015 ). These papers show that all these independent codes give consistent solutions for the scalar field, as well as the power spectrum and the mass function of dark matter. In detail, we can write the action of the f ( R ) model as (Capozziello 2002 ) where with . Under the quasi-static approximation, the equation of motion of the scalar field δ f R can be obtained as (Noller, von Braun-Bates Ferreira 2014 ) where , and . One can invert equation ( A2 ) to relate R to f R using where the approximation holds if the background cosmology is close to a ΛCDM+GR model and, in this case, one can approximate as At redshift z = 0, where a flat universe is assumed. Combining equations ( A4 ) and ( A6 ), one can rewrite equation ( A4 ) in terms of f R0 , which is the background value of f R at redshift z = 0, as and δ R is given explicitly as The scalar field f R can then be solved numerically by combining equation ( A3 ) with equation ( A8 ), given the model parameters f R0 and n with background cosmological parameters. The modified Poisson equation for the gravitational potential Φ can be obtained by summing the 00 and ii component of the modified Einstein equation in the Hu–Sawicki f(R) model (Hu Sawicki 2007 ), namely The dynamics of the system are determined by equations ( A3 ) and ( A9 ). Equation ( A3 ) is a non-linear Poisson equation, and it has to be solved numerically on a regular, or self-adaptive, grid using iteration methods (Oyaizu 2008 ; Zhao, Li Koyama 2011 ; Li et al. 2012 ; Puchwein, Baldi Springel 2013 ). We chose Hu–Sawicki model as it has been implemented to several simulations and, as shown in Terukina et al. ( 2014 ) and Wilcox et al. ( 2015 ), is insensitive to the form of the potential of the chameleon field. Thus our constraints are applicable to a wide class of chameleon models, and contains GR as a limiting case. Thus our test also serves as a consistency check of the LCDM model. The weak equivalence principle is not violated in this model as all matter is coupled to the scalar field universally. However,
Paper: 2018A&A...617A...1K (fulltext)
with consistent dust/ice opacities and dust disk thermal structure. We demonstrate that the photodesorption of water ice is key in the quantitative interpretation of the peak strengths of the 45 and 63 μ m features. The water ice features originate from grains smaller than ~10 μ m. The water ice features originate predominantly at the surface snow line of the disk between 10 and 100 au, which means that they are very robust against several disk parameters such as inner and outer radii, the grain size distribution (within limits), and dust settling. However, the feature strength scales with disk dust mass in the range of typical T Tauri disks. The features also change substantially with the thickness of the ice mantle, although the strength levels off for mantles much thicker than 2.5 times the original grain sizes. Most interestingly, the features do carry an imprint of the thermal history of the ice and thus can distinguish between a warmup scenario for the water ice (where water ice is formed in cold, optically thick regions and then moves to warmer areas in the disk) and a cooldown scenario (where water ice is formed in warm areas close to the midplane snow line and then moves outwards to colder areas in the disk). The direct deposit scenario (ice stays where it was formed locally in the disk) resembles qualitatively the warmup scenario and while the peak strength change of the 45 μ m feature maynot allow a discrimination, the shift in the peak wavelengths to shorter values might be a discriminator. Given the results of our ice model series, simulations using the sensitivities for the planned SOFIA/HIRMES instrument show that the lowresolution and the sensitivity will lead to severely limited ice studies – beyond simple detection – in T Tauri disks at the distance of typical star forming regions. The 45 μ m ice feature is strong enough to be detected if it originates from warm grains with thick ice mantles that are crystalline in nature. Similar simulations for the SPICA/SAFARI instrument show that the differences in peak strengths and the wavelength shifts in the peak position can both be easily measured in samples of several hundred T Tauri disks (exposure times of 10 min). At low spectral resolution ( R = 300) weak flat ice features at 45 μ m (e.g., amorphous, direct deposit, warmup of ice) require a good continuum characterization in deep surveys. Appendix A SEDs and disk structures A.1 Disk inner radius and tapering-off radius Figures A.1 and A.2 illustrate the temperature distribution in the disk models with varying inner radius and tapering-off radius. To assess where the water ice features originate, we also show the snow line and the vertical optical depth τ = 1 contours for 45 and 63 μ m and the radial optical depth τ = 1 at 0.55 μ m. A.2 Dust settling Figure A.3 shows the 2D temperature distribution for disk models with various degrees of settling ( α turb = 10 −2 to 10 −4 ). The change in opacities is strongest in the outer
Paper: 2018MNRAS.473.1656T (fulltext)
we find the following results: The central regions of the simulated MW mass-sized galaxies are found to be populated mainly by stars older than 10 Gyr in three of the analysed haloes (Aq-B has ∼50 per cent of its stars >10 Gyr). Most of these stars formed in situ, with a fraction of old stars in the range ∼0.10–0.35 contributed by satellite accretion. The spatial distributions of in situ and accreted stars are different – accreted stars form centrally concentrated spheroidal distributions, while the in situ components exhibit clear bar structures or elongated distributions. The predicted kinematics are consistent with these properties. In particular, the rotational velocity and velocity dispersion distributions of the central region of Aq-C resemble those reported by Zoccali et al. ( 2017 ). Both in situ and accreted stars in the central regions formed in main starbursts (in the progenitor and accreted satellites, respectively). However, accreted stars formed early, so that there is mean age difference of ∼0.5–1 Gyr between the in situ and accreted stars. The age distributions of in situ stars exhibit a tail towards younger ages. Aq-B has a more uniform star formation history for both in situ and accreted stars, since it is affected by a more recent merger event. The age distributions are consistent with the central regions being dominated by stars older than 10 Gyr. This finding is in agreement with the observational results of Santucci et al. ( 2015 ) and Carollo et al. ( 2016 ), who identified an ACS in the MW, extending out to beyond the Sun's location. The metallicity distributions of the in situ and accreted stars are slightly different. The metallicity distributions of the accreted stars are shifted towards lower abundances than those of the in situ stars, and the former have higher α-element enhancements. These trends are consistent with their formation history, since the accreted stars are formed in satellite galaxies with dynamical masses smaller than 10 10 M ⊙ (Tissera et al. 2014 ), while the in situ stars formed in the main progenitors. Regarding the old stars, they represent most of the stars in the central regions, on average. In our simulations, old, accreted stars belong preferentially to the stellar haloes within the inner 10 kpc. A mass fraction of ∼35 per cent is part of the bulge components. The accretion histories show that Aq-A and Aq-C received larger contributions from smaller satellites. On the other hand, the central regions of Aq-B and A-D experienced a greater contribution from a few massive accreted dwarf galaxies. As a consequence, the former have more metal-poor and α-element enhanced stellar populations. At a fiducial solar radius, we estimate that ∼40 per cent of the old stars are accreted. This fraction is in reasonable agreement with the recent results of An et al. ( 2015 ) for the solar neighbourhood. All the analysed central regions have a small fraction of stars younger than 0.1 Gyr, ∼3 per cent, on
Paper: 2019ApJS..240...21A (fulltext)
bars, but in most cases are very small. Figure 3.312. Image of V417 Cen. Normalized SED profiles of S-, S+IR-, D-, and D′-type SySts. The blue dots correspond to the photometric data from the 2MASS and WISE surveys, the black lines are the BB models for each component, and the red line is the final fit only for cases with multicomponent SEDs. The errors of the data are portrayed as vertical red bars, but in most cases are very small. Figure 3.313. Image of V704 Cen. Normalized SED profiles of S-, S+IR-, D-, and D′-type SySts. The blue dots correspond to the photometric data from the 2MASS and WISE surveys, the black lines are the BB models for each component, and the red line is the final fit only for cases with multicomponent SEDs. The errors of the data are portrayed as vertical red bars, but in most cases are very small. Figure 3.314. Image of V835 Cen. Normalized SED profiles of S-, S+IR-, D-, and D′-type SySts. The blue dots correspond to the photometric data from the 2MASS and WISE surveys, the black lines are the BB models for each component, and the red line is the final fit only for cases with multicomponent SEDs. The errors of the data are portrayed as vertical red bars, but in most cases are very small. Figure 3.315. Image of V852 Cen. Normalized SED profiles of S-, S+IR-, D-, and D′-type SySts. The blue dots correspond to the photometric data from the 2MASS and WISE surveys, the black lines are the BB models for each component, and the red line is the final fit only for cases with multicomponent SEDs. The errors of the data are portrayed as vertical red bars, but in most cases are very small. Figure 3.316. Image of WISE J192140.40+155354.6. Normalized SED profiles of S-, S+IR-, D-, and D′-type SySts. The blue dots correspond to the photometric data from the 2MASS and WISE surveys, the black lines are the BB models for each component, and the red line is the final fit only for cases with multicomponent SEDs. The errors of the data are portrayed as vertical red bars, but in most cases are very small. Figure 3.317. Image of WRAY 16-312. Normalized SED profiles of S-, S+IR-, D-, and D′-type SySts. The blue dots correspond to the photometric data from the 2MASS and WISE surveys, the black lines are the BB models for each component, and the red line is the final fit only for cases with multicomponent SEDs. The errors of the data are portrayed as vertical red bars, but in most cases are very small. Figure 3.318. Image of [JD2002] 11. Normalized SED profiles of S-, S+IR-, D-, and D′-type SySts. The blue dots correspond to the photometric data from the 2MASS and WISE surveys, the black lines are the BB models for each component, and the red line is the final fit only for cases with multicomponent SEDs. The errors of the data are portrayed as vertical red bars, but in most cases are very small. Figure 3.319. Image of AS 201. Normalized SED profiles of S-, S+IR-, D-, and D′-type SySts. The blue dots correspond to the photometric data from the
Paper: 2020MNRAS.492.4884I (fulltext)
H , in which the vertical component of the magnetic field is large, σ c / H . Here, the velocity is the velocity of matter in a vortex. The vortex revolution time is ≃ H /. Apparently, the numerical magnetic viscosity (inversely to the conductivity) in the calculations satisfies this condition. Also, the real conductivity of the turbulent matter is anomalous and significantly less than the classical one. Because of this, the magnetic lines above the disc are directed tangentially to the disc (Teixeira, Avara McKinney 2018 ) and the poloidal magnetic field in magnetosphere is close to radial one due to its strong compression by the plasma pressure of the disc near the central object (Kathirgamaraju et al. 2019 ; Liska et al. 2019 ). Split monopole magnetic field lines directly exit from the vicinity of the central black hole. They are involved into the rotation by the black hole and rotate with an angular velocity of Ω F , which for optimal matching is the half of the angular velocity of rotation of a black hole Ω H , Ω F = Ω H /2 (Blandford Znajek 1977 ). The rotating radial magnetic field excites in the magnetosphere a θ-component of the electric field, E θ , which, by virtue of Faraday’s law, is Here, the element of length d l is taken along the θ direction. We get The relation ( 3 ) looks like a condition ( 1 ) in ideal MHD, where instead of the fluid velocity u the azimuthal rotation velocity appears, u = e φ r sin θΩ F . The electric field ( 3 ) in the magnetosphere arises near the black hole horizon due to its rotation and is transmitted along the radial magnetic field to the magnetosphere, which extends up to the light cylinder surface r = c /Ω F sin θ. The polar field E θ in the magnetosphere is the agent that transfers the black hole rotation to the rotation of plasma of the magnetosphere and, when charged particles move in the polar direction, transfers energy to them. We emphasize here that the polar electric field E θ ( 3 ) is the result the central object rotation, and is not a consequence of MHD, which may not be satisfied in the magnetosphere. This topic is discussed in the section ‘Discussion’. Thus, in the magnetosphere there is an electromagnetic field with components Here, r L = c /Ω F is the natural size of the magnetosphere in the transverse direction. This is the radius of the light cylinder, at which the electric field is compared with the magnetic one. For a spherical distance r , the light surface is at the distance r = r L /sin θ. The value of B 0 is the value of the radial magnetic field at the distance r = r L . At the light cylinder the value of the radial field falls from the value of B 0 near the accretion disc (θ ≃ π/2) to B 0 sin 2 θ. The coefficient α is the ratio of the toroidal magnetic field to the poloidal one at the distance r = r L from the centre. Since the split monopole field and the toroidal field differently depend on the radial distance r , then at ‘small’ distances r α −1 r L the poloidal magnetic
Paper: 2018ApJ...853...87R (fulltext)
uncertainty: the propagation of the individual uncertainty spectra (left panel) and the jackknife uncertainty (right panel). Vertical ticks and labels mark the expected positions of other lines of interest, color-coded as in Figure 3 . The plotted transitions trace large-scale galactic winds and have ionization potentials of 15.0 eV (Mg ii ) and 16.2 eV (Fe ii ). (b) Same as Figure 5 (a), for transitions with ionization potentials from 13.6 eV (top panel) to 24.4 eV (bottom panel). The weighted average stack is shown in the left panel and the median stack in the right panel. (c) Same as Figure 5 (a), for transitions with high ionization potential. Transitions are plotted in order of increasing ionization potential, from top to bottom, from 28.4 to 97.9 eV. The weighted average stack is shown in the left panel and the median stack in the right panel. In Figure 5 (a), we consider the transitions of Mg ii 2796, Fe ii 2344, and Fe ii 2383. 12 12 Fe ii 2600 is unusable due to adjacent Mn ii absorption. These transitions have ionization potentials of 15.0 eV (Mg ii ) and 16.2 eV (Fe ii ) and are associated with spatially resolved, large-scale outflows in galaxies at –2 (Martin and Bouché 2009 ; Weiner et al. 2009 ; Rubin et al. 2010 , 2011 ; Giavalisco et al. 2011 ; Erb et al. 2012 ; Kornei et al. 2013 ; Bordoloi et al. 2014 ; Rigby et al. 2014 ; Rubin et al. 2014 ). In the M eg a S a ura weighted-average shape-normalized stack, these transitions have a maximum velocity of = 900 km s −1 (Table 3 .) Bordoloi et al. ( 2016 ) analyzed the velocity profiles of four regions within one of these galaxies, RCS-GA 032727−132609, and found 95th percentile velocities of 460–610 km s −1 for these transitions. Mg ii is at the extreme red end of the M eg a S a ura stack and so only four galaxy spectra went into the stack; seven galaxies contribute to the stack for Fe ii 2344 and Fe ii 2383. Knot E of RCS-GA 032727−132609 contributed to the stack for both Mg ii and Fe ii . Despite those small numbers, the maximum velocities we measure for Mg ii and Fe ii confirm and extend the conclusion of Bordoloi et al. ( 2016 ): a substantial fraction of the Mg ii and Fe ii gas column has velocities far exceeding the plausible escape velocity of their galactic hosts. 3.5. Galactic Winds as Probed by Other Low-ionization Transitions We next analyze the absorption velocity profiles of other low-ionization transitions, plotted in Figure 5 (b). The main transitions that trace the neutral gas are Ly α and O i 1302, as they have low ionization potentials (13.6 eV). However, a maximum wind velocity cannot be measured for O i 1302 because of nearby photospheric absorption lines, and Ly α is difficult to interpret due to resonant scattering. Instead, we must estimate the wind velocity from Si ii , Al ii , and C ii , which have ionization potentials of 16.3, 18.8, and 24.4 eV, respectively, and therefore trace a mixture of neutral and ionized gas. This absorption has ∼ 630–940 km s −1 in
Paper: 2016ApJ...827...17X (fulltext)
excited state along the HT pathway. In the previous He i photoelectron study (Reutt et al. 1986 ), the IE values for the formation of the ( X 2 Π u and states were determined as 11.403 and 16.297 eV, respectively. Taking into account that the IE(N 2 ) = 15.581 eV, the first excited electronic state is expected to become accessible when E cm is greater than 0.72 eV. Compared with the distinct increase of σ HT ( v + = 0) at E cm = 0.70–1.00 eV, the σ CT ( v + = 0) only exhibits a slight decline at the same E cm range, indicating that the accessibility to the excited state only enhances the HT channel. While the σ CT ( v + = 0) curve of Figure 2 (a) is consistent with a long-range CT mechanism, the σ HT ( v + = 0) may involve an efficient coupling between kinetic energy and internal vibrational energy, enhancing the formation of N 2 H + in shorter ranges. We note that the thermal motion of neutral reactant molecules C 2 H 2 at room temperature T = 298 K can affect the kinetic energy resolution (Δ E cm ) for a given E cm value. Chantry has shown that the Δ E cm value or the Doppler width caused by the thermal motion of the target gas alone is equal to (11.1 γkTE cm ) 1/2 , where γ = m + /( m + + M ) (Chantry 1971 ). The estimated thermal broadening for the present reaction system is about one order of magnitude smaller than the E cm when E cm ≥ 1.00 eV. But the thermal broadening becomes comparable with E cm when 0.10 eV ≤ E cm 1.00 eV, and even larger than the E cm when E cm 0.10 eV. Because of the relatively large Doppler width at E cm 0.10 eV, the measured σ CT ( v + = 0) values at low E cm values shown in Figure 2 (a) could be distorted. Vibrational-state dependence. In order to investigate the effect of vibrational excitation on the chemical reactivity of ; v + ) toward C 2 H 2 , we have compared in Figures 3 (a) and (b) the respective σ CT ( v + ) and σ HT ( v + ) curves obtained at E cm = 0.03–10.00 eV with the reactant PFI-PIs prepared in the v + = 0, 1, and 2 vibrational states. As shown in the figures, after taking into account the experimental uncertainties, the σ CT ( v + ) and σ HT ( v + ) curves for v + = 1 and 2 vibrational states are found to be nearly in agreement with the corresponding σ CT ( v + = 0) and σ HT ( v + = 0) curves. Thus, we conclude that both the CT (reaction ( 2.1 )) and the HT (reaction ( 2.2 )) channels have only marginal vibrational effects. Nevertheless, the measured CT and HT cross sections seem to show weak vibrational inhibition at low E cm values and weak vibrational enhancement at high E cm values. In the range of E cm = 0.03–0.60 eV, the ( v + = 1) state shows the lowest CT reactivity. For E cm > 0.60 eV, the CT cross section is higher for reactant ion in the v + = 1 and 2 states compared to that in the v + = 0 state. For the convenience of utilizing the results obtained here for atmospheric modelings, we have listed in Table 1 all integral cross sections plotted in Figures 2 , 3 (a), and 3 (b). Figure
Paper: 2016ApJ...828...34F (fulltext)
to test its significance and simulating 500 CPSDs from the best-fit model, scattered around within the uncertainties of the measured CPSD, we find that a similar improvement in can occur by chance with probability. We therefore conclude that this feature is not significantly detected. 4. DISCUSSION We have presented time-resolved spectral and timing analysis of NuSTAR data of GX 339−4 , taken during a HIMS in early 2015. The time-resolved approach was necessary as the source was softening significantly over the course of the observation and at the same time the prominent type-C QPO increased in frequency. From the energy spectra we concluded that the accretion disk is truncated around 9 r g , independent of the assumed geometry. This value is larger than the ISCO for a spin of () or (), as measured by Parker et al. ( 2016 ) and Miller et al. ( 2008 ), respectively. We note that using the relativistic effects to constrain the inner radius of the accretion disk still has systematic uncertainties, as all available geometries are simple approximations, as discussed in F15 . Independent of these assumptions, the data show that within the uncertainties, the inner radius is not changing over the course of the observation, despite the observed changes in spectral hardness (Figure 5 (e)). Our best-fit model assumes that the power-law continuum incident on the reflector is harder than that observed as the underlying continuum. This configuration was invoked in F15 for the hard state and later confirmed by Parker et al. ( 2016 ) in a soft state observation, and indicates a complex geometry of the corona. Using this geometry, F15 found that the iron abundance is significantly reduced compared to other models. This is not the case in the observation presented here, and all models require an iron abundance around 4–5 solar, similar to the values found by Parker et al. ( 2016 ) and García et al. ( 2015 ), using NuSTAR and RXTE data, respectively. 4.1. Truncation of the Inner Accretion Disk Using relativistic reflection models, we find that the inner radius of the accretion disk is truncated significantly outside the ISCO, at around 9 r g . This result is independent of the assumed geometry, either a standard disk emissivity profile with an index of q = 3, or a lamppost geometry. This amount of truncation is similar to the one found by Tamura et al. ( 2012 ), assuming a black hole. This result indicates that the accretion disk does not move all the way to the ISCO before the source has entered the soft state. This seems to be at odds with results finding the accretion disk to be at the ISCO in bright hard states (e.g., Miller et al. 2015 ). On the other hand, it might simply show that different outbursts behave differently. It is in theory also possible that the truncation is not a strict function of luminosity, and truncation appears again during the HIMS, given its slightly different radiation balance at the accretion disk/corona boundary (e.g., a