Datasets:
Tasks:
Token Classification
Languages:
English
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Annotations Creators:
expert-generated
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Identifier
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82
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9.23k
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|---|---|---|---|---|---|---|
2021MNRAS.501.4035R__Vigren_&_Galand_2013_Instance_1 | The study of cometary plasma composition has been subjected to a great interest after the ion mass spectrometer onboard Giotto spacecraft detected many peaks in the mass range 12 and 120 amu (Balsiger et al. 1986; Krankowsky et al. 1986; Mitchell et al. 1987; Altwegg et al. 1993). By developing photochemical models, numerous studies focused on comet 1P/Halley explained the observed ion distribution in a water-dominated coma (Allen et al. 1987; Wegmann et al. 1987; Schmidt et al. 1988; Cravens 1989; Bhardwaj, Haider & Singhal 1990, 1996; Gan & Cravens 1990; Ip et al. 1990; Haider, Bhardwaj & Singhal 1993; Häberli et al. 1995; Haider & Bhardwaj 1997, 2005; Bhardwaj 1999; Rubin et al. 2009; Cordiner & Charnley 2014). By making 2 yr of observations, the recent Rosetta space mission on comet 67P/Churyumov–Gerasimenko has revolutionized our understanding of the activity of the cometary coma. During the Rosetta observation period, continuous measurements around the nucleus were helpful to study the evolution of ion and neutral distribution and also the driving photochemical processes in the coma. Several modelling works on this comet have shown that ion composition in the coma varies based on the sublimation rate of the nucleus (Vigren & Galand 2013; Fuselier et al. 2015, 2016; Galand et al. 2016; Heritier et al. 2017, 2018; Vigren et al. 2017; Beth, Galand & Heritier 2019). All these studies show that solar photons are the primary energy source that determines the ion composition in the inner coma. Solar extreme ultraviolet photons having an energy more than 12 eV ionize H2O and produce H2O+, and the collisions among these species quickly lead to the formation of H3O+. The sublimated parent species such as CH3OH, NH3, HCN, HCOOH, and CH3CHO, have high proton affinities compared to that of H2O, causing the loss of H3O+ in the inner coma. Haider & Bhardwaj (2005) developed a comprehensive chemical network to study the ion distribution in comet 1P/Halley. Their calculations show that NH$_4^+$ is the most dominant ion in the inner coma followed by H3O+ and CH3OH$_2^+$ ions. Similarly, the model calculations of Heritier et al. (2017) on comet 67P/Churyumov–Gerasimenko showed that NH$_4^+$, CH3OH$_2^+$, H3O+, H3S+, and HCNH+ are the important ions in the inner coma. They also showed that the densities of these ions vary with the relative mixing ratios of corresponding proton affinity species coming from the nucleus. Even if the mixing ratios of parent species, which have high proton affinity, are very low (2 per cent), they can play a significant role in modifying the ionospheric composition of the inner coma. Hence, the ion distribution in the cometary coma essentially depends on the neutral composition and photochemical reactions. | [
"Vigren & Galand 2013"
] | [
"Several modelling works on this comet have shown that ion composition in the coma varies based on the sublimation rate of the nucleus"
] | [
"Background"
] | [
[
1242,
1262
]
] | [
[
1107,
1240
]
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2022MNRAS.512.2222V__Granato_et_al._2004_Instance_1 | As for the ETGs, which are spheroid-dominated, most of these that are more massive than ∼2 × 1010 M⊙ are old, implying that the SF has strongly declined long time ago and no recent bursts of SF have occurred. Early formation and rapid quenching mechanisms are expected for those galaxies, where the quenching mechanisms are likely to be associated with their morphological transformation through wet major mergers and disc instabilities. These processes lead to compaction and strong bursts of SF that consume the gas (e.g. Hopkins et al. 2008; Barro et al. 2013; Dekel & Burkert 2014), as well as strong AGN/QSO and Supernova feedback that will heat and expel the gas (e.g. Granato et al. 2004; Sijacki et al. 2007; Somerville et al. 2008; Vogelsberger et al. 2014). At intermediate and low masses, the environment-driven quenching mechanisms (e.g. ram-pressure and tidal striping, strangulation, etc.) can also be relevant (e.g. Kauffmann et al. 2004; Peng et al. 2010; Schawinski et al. 2014). Note that these mechanisms are expected to lead also to morphological transformation (e.g. Gunn & Gott 1972; Moore et al. 1996; Abadi, Moore & Bower 1999; Bekki, Couch & Shioya 2002; Aragón-Salamanca, Bedregal & Merrifield 2006). However, as M* is lower there is an increasing fraction of ETGs with intermediate values of Agelw, or even low values (Table 3), though not as low as in the case of low-mass LTGs (see Fig. 16). This population of ETGs is partially associated to the Blue Star-forming and Recently Quenched Early-type galaxies, for which rejuvenation processes (Thomas et al. 2010) by gas infall or late gas-rich mergers were proposed in Lacerna et al. (2016, 2020). In fact, the $Age_{\rm mw}/{Age_{\rm lw}}$ ratio of these galaxies is large, which implies that they did not form so late but they contain some (small) fractions of very young stellar populations. Finally, for the ITGs, the Agelw distribution in the ∼0.5–5 × 1010 M⊙ mass range is roughly bimodal (Fig. 16), with a large fraction of them in the intermediate age region (or green valley in the colour–M* diagram), showing that the quenching time-scales for these galaxies with a significant bulge are slow (quenching mechanisms like those driven by morphology, halo mass, and environment; see above). For the most massive S0–Sa galaxies, ${Age_{\rm lw}}\gt 4$ Gyr, that is, they are mostly quenched, while for the lest massive, ${Age_{\rm lw}}\lesssim 2$ Gyr, which imply some rejuvenation processes. | [
"Granato et al. 2004"
] | [
"as well as strong AGN/QSO and Supernova feedback that will heat and expel the gas (e.g."
] | [
"Background"
] | [
[
675,
694
]
] | [
[
587,
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2016AandA...595A..72M__Vergani_et_al._2015_Instance_1 | On the other hand, the Australia Telescope Compact Array (ATCA) 21 cm line survey of GRB host galaxies revealed high levels of atomic hydrogen (H i), suggesting that the connection between atomic gas and star formation is stronger than previously thought (Michałowski et al. 2015). Star formation may be directly fuelled by atomic gas, as has been theoretically shown to be possible (Glover & Clark 2012; Krumholz 2012; Hu et al. 2016), and this is supported by the existence of H i-dominated, star-forming regions in other galaxies (Bigiel et al. 2008, 2010; Fumagalli & Gavazzi 2008; Elmegreen et al. 2016). This can happen in a low metallicity gas that is recently acquired, even if the metallicity in other parts of a galaxy is higher, near the onset of star formation because cooling of gas (necessary for star formation) is faster than the H i-to-H2 conversion (Krumholz 2012). Indeed, large atomic gas reservoirs, together with low molecular gas masses (Hatsukade et al. 2014; Stanway et al. 2015b) and stellar masses (Perley et al. 2013, 2015; Vergani et al. 2015), indicate that GRB hosts are preferentially galaxies that have very recently started a star formation episode. This provides a natural route for forming GRBs in low-metallicity environments, as found for most GRB hosts (Fruchter et al. 2006; Modjaz et al. 2008; Levesque et al. 2010a; Han et al. 2010; Boissier et al. 2013; Schulze et al. 2015; Vergani et al. 2015; Japelj et al. 2016; Perley et al. 2016), except of a few examples of hosts with solar or super-solar metallicities (Prochaska et al. 2009; Levesque et al. 2010b; Krühler et al. 2012; Savaglio et al. 2012; Elliott et al. 2013; Schulze et al. 2014; Hashimoto et al. 2015; Schady et al. 2015; Stanway et al. 2015a). Indeed, the GRB collapsar model requires that most of the GRB progenitors have low metallicity (below solar) in order to reduce the loss of mass and angular momentum that is required for launching the jet (Yoon & Langer 2005; Yoon et al. 2006; Woosley & Heger 2006). We note however that other models, while still predicting the metallicity preference (e.g. Izzard et al. 2004; Podsiadlowski et al. 2004; Detmers et al. 2008), allow higher metallicities owing to differential rotation (Georgy et al. 2012), binary evolution (Podsiadlowski et al. 2010; van den Heuvel & Portegies Zwart 2013), or weaker magnetic fields (Petrovic et al. 2005). | [
"Vergani et al. 2015"
] | [
"Indeed, large atomic gas reservoirs, together with low molecular gas masses",
"and stellar masses",
"indicate that GRB hosts are preferentially galaxies that have very recently started a star formation episode."
] | [
"Compare/Contrast",
"Compare/Contrast",
"Compare/Contrast"
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[
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2015AandA...582A..22L__Todorov_et_al._2014_Instance_2 | Dust distribution:We employed the standard flared disk model with well-mixed gas and dust, which has been successfully used to explain the observed SEDs of a large sample of young stellar objects and BDs (e.g., Wolf et al. 2003; Sauter et al. 2009; Harvey et al. 2012a; Joergens et al. 2013; Liu et al. 2015). The structure of the dust density is assumed with a Gaussian vertical profile (1)\begin{equation} \rho_{\rm{dust}}=\rho_{0}\left(\frac{R_{*}}{\varpi}\right)^{\alpha}\exp\left[-\frac{1}{2}\left(\frac{z}{h(\varpi)}\right)^2\right], \label{dust_density} \end{equation}ρdust=ρ0R∗ϖαexp−12zh(ϖ)2,and the surface density is described as a power-law function (2)\begin{equation} \Sigma(\varpi)=\Sigma_{0}\left(\frac{R_{*}}{\varpi}\right)^p, \end{equation}Σ(ϖ)=Σ0R∗ϖp,where ϖ is the radial distance from the central star measured in the disk midplane, and h(ϖ) is the scale height of the disk. The disk extends from an inner radius Rin to an outer radius Rout. To the best of our knowledge, among our sample, there are five objects that have been identified as binary systems so far. They are 2M1207 (a~55 AU, Chauvin et al. 2004), J04221332+1934392 (a~7 AU, Todorov et al. 2014), J04414489+2301513 (a~15 AU, Todorov et al. 2014), USD161833 (a~134 AU, Bouy et al. 2006), and USD161939 (a ~ 26 AU, Bouy et al. 2006), where a refers to the separation within the system. The disks around individual components in binary systems are expected to have truncation radii of the order of (0.3 − 0.5)a (Papaloizou & Pringle 1977). We adopted 0.5 a as the disk outer radii for 2M1207, USD161833, and USD161939. For the close pairs (a ≲ 15 AU, J04221332+1934392 and J04414489+2301513), dynamical simulations of star-disk interactions suggest that individual disks are unlikely to survive (e.g., Artymowicz & Lubow 1994). Disk modeling is complicated in those close multiple systems. For simplicity, we assume that the emission is associated with circumbinary disks of 100 AU in size. For other objects, we fix Rout = 100 AU in the modeling because the choice of this parameter value makes essentially no difference to the synthetic SEDs in the simulated wavelength range (Harvey et al. 2012a). The scale height follows the power-law distribution(3)\begin{equation} h(\varpi) = H_{100}\left(\frac{\varpi}{100\,\rm{AU}}\right)^\beta,\\ \end{equation}h(ϖ)=H100ϖ100 AUβ,with the exponent β characterizing the degree of flaring and H100 representing the scale height at a distance of 100 AU from the central star. The indices α, p, and β are codependent through p = α − β. We fix p = 1, which is the typical value found for T Tauri disks in the sub-millimeter (e.g., Isella et al. 2009; Guilloteau et al. 2011), since only spatially resolved data can place constraints on this parameter (e.g., Ricci et al. 2013, 2014). Dust properties:We assume the dust grains to be a homogeneous mixture of 75% amorphous silicate and 25% carbon with a mean density of ρgrain = 2.5 g cm-3 and the complex refractive indices given by Jäger et al. (1994, 1998), and Dorschner et al. (1995). Porous grains are not considered because the fluxes at wavelengths beyond ~ 2 μm are almost independent of the degree of grain porosity in low-mass disks, as shown by Kirchschlager & Wolf (2014). The grain size distribution is given by the standard power law dn(a) ∝ a-3.5da with minimum and maximum grain sizes amin = 0.1 μm and amax = 100 μm, respectively. The choice of the minimum value for the grain size, amin, ensures that its exact value has a negligible impact on the synthetic SEDs. Since there is no information about the maximum grain sizes of our target disks, as provided, e.g., by the (sub)millimeter spectral index, we adopt amax = 100 μm. The Herschel/PACS far-IR observations are sensitive to dust grains with this assumed sizes. Strong grain growth up to millimeter sizes as detected in some BD disks (e.g., Ricci et al. 2012, 2013, 2014; Broekhoven-Fiene et al. 2014) would remain undetected in our data and could affect the disk mass. Our prescription for the dust properties is identical to those used in Liu et al. (2015). | [
"Todorov et al. 2014"
] | [
"J04414489+2301513 (a~15 AU,"
] | [
"Uses"
] | [
[
1210,
1229
]
] | [
[
1182,
1209
]
] |
2019ApJ...882..144K__Berk_et_al._2001_Instance_2 | The FOCAS and NIRSPEC spectra of PSO J006+39 were obtained at two different epochs separated by 1 yr and 9 months (by slightly less than 3 months in the quasar rest frame). Previously, we found that the PS1 y-band light curve of PSO J006+39 shows brightness variations with a peak-to-peak amplitude of ∼0.7 mag over ∼4 yr (Koptelova et al. 2017), which might be due to the flux variations of both continuum and Lyα line of PSO J006+39. To infer the brightness state of PSO J006+39 at the epochs of its FOCAS and NIRSPEC observations, we first calculated the spectral slope of the quasar continuum from the NIRSPEC spectrum with a wider wavelength coverage than that of the FOCAS spectrum. Using wavelength intervals of 11100–11300, 11400–11600, 13085–13400, and 14700–15200 Å we measured a spectral slope of αλ = −1.35 ± 0.26, where the quoted uncertainty is the statistical error of the fit. The fitted power law is shown in Figure 2 with a solid line. The estimated continuum slope is consistent but somewhat flatter than the typical slope of luminous quasars (Zheng & Malkan 1993; Vanden Berk et al. 2001; Selsing et al. 2016). We then fitted the FOCAS data using the power law with a fixed spectral slope of αλ = −1.35 and spectral windows of 9700–9850 and 10050–10100 Å. The spectral windows adopted for the analysis of the FOCAS and NIRSPEC spectra were taken to be similar to the rest-frame wavelength intervals commonly used to fit the continua of quasars (Vanden Berk et al. 2001; Decarli et al. 2010; Lusso et al. 2015) and less affected by the contribution from emission lines on the red side of the Big Blue Bump (BBB; e.g., Malkan 1983). The estimated continuum flux of PSO J006+39 at the epoch of its FOCAS observations is shown in Figure 2 with a dashed line. By comparing the continuum flux at the epochs of the FOCAS and NIRSPEC observations, we find that the brightness state of PSO J006+39 was different at these two epochs. PSO J006+39 was brighter by about 0.8 mag during the FOCAS observations than during the NIRSPEC observations. Thus, the continuum flux of PSO J006+39 might be different at different epochs depending on the brightness state of the quasar. Figure 2 also shows the fluxes of PSO J006+39 in the FOCAS Y, and NIRSPEC N2, N4, and N6 bands at the epochs of the FOCAS and NIRSPEC observations (see also Table 1). | [
"Vanden Berk et al. 2001"
] | [
"The spectral windows adopted for the analysis of the FOCAS and NIRSPEC spectra were taken to be similar to the rest-frame wavelength intervals commonly used to fit the continua of quasars"
] | [
"Uses"
] | [
[
1465,
1488
]
] | [
[
1276,
1463
]
] |
2017ApJ...835..246Y__Yoon_&_Seough_2014_Instance_1 | The present analysis builds upon the macroscopic-kinetic model of the solar wind, originally formulated by Yoon & Seough (2014) for the proton temperatures. The same model was recently generalized to include collisional dissipation (Yoon 2016a, 2016b). The basic methodology is similar to that of Marsch & Tu (2001) and Jasperse et al. (2006), especially in regards to treating the particle aspect, but unlike earlier works (Marsch & Tu 2001; Jasperse et al. 2006), which do not treat the waves self-consistently, Yoon & Seough (2014) and Yoon (2016a, 2016b) discuss the wave generation in a self-consistent manner by solving the adiabatic dispersion relation and wave kinetic equation for each spatial location. We now extend the original formalism (Yoon & Seough 2014) in another direction. We include dynamic electrons, but unlike the two later works (Yoon 2016a, 2016b), we ignore collisional dissipation. For an inhomogeneous plasma immersed in a diverging or converging magnetic field, the kinetic equation for the particles subject to perturbations propagating in parallel direction, s, is given by
1
where, for cylindrical velocity coordinate system, the velocity diffusion coefficient tensor is given by
2
and where
is the complex angular frequency, which must be determined by the local dispersion relation,
3
In the above relation, ea and ma are unit electric charge and mass for particles species a (a = p for protons and a = e for electrons,
for protons and
for electrons);
stands for cyclotron frequency for species a, B0 and c being the ambient magnetic field intensity and the speed of light in vacuo;
is the square of the plasma frequency defined for species a, n0 being the ambient plasma density, and
being the perturbed electric field associated with the unstable transverse mode propagating parallel (and anti-parallel) to the ambient magnetic field, ± denoting the right/left-hand circular polarization. The spectral electric field wave energy density
must be determined by solving the wave kinetic equation, the simplest form of which is given by the quasilinear theory,
4
| [
"Yoon & Seough (2014)",
"Yoon & Seough 2014"
] | [
"and Yoon (2016a, 2016b) discuss the wave generation in a self-consistent manner by solving the adiabatic dispersion relation and wave kinetic equation for each spatial location.",
"We now extend the original formalism",
"in another direction."
] | [
"Motivation",
"Extends",
"Extends"
] | [
[
514,
534
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]
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[
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[
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[
771,
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2021MNRAS.503.1319G__Chae_&_Mao_2003_Instance_2 | In the first scenario, we assume that neither the characteristic velocity dispersion (σ*) nor the number density (n*) of galaxies evolves with redshifts (νn = νv = 0). Given the redshift coverage of the lensing galaxies in the lens sample (0.06 zl 1.0), if we constrain a non-evolving VDF using the lens data, then, assuming the VDF evolution with redshift is smooth, the fits on the VDF parameters may represent the properties of ETGs at an effective epoch of z ∼ 0.5. Such non-evolving VDF has been extensively applied in the previous studies on lensing statistics (Chae & Mao 2003; Ofek et al. 2003; Capelo & Natarajan 2007; Cao et al. 2012a). By applying the above-mentioned χ2 – minimization procedure to Sample A – we obtain the best-fitting values and corresponding 1σ uncertainties (68.3 per cent confidence level): $\alpha =0.66^{+2.13}_{-0.66}$, $\beta =2.28^{+0.24}_{-0.18}$. It is obvious that the full sample analysis has yielded improved constraints on the high-velocity exponential cut-off index β, compared with the previous analysis of using the distribution of image separations observed in CLASS and PANELS to constrain a model VDF of ETGs (Chae 2005). Suffering from the limited size of lens sample, such analysis (Chae 2005) found that neither of the two VDF parameters (α, β) can be tightly constrained, due to the broad regions in the α − β plane. Consequently, the image separation distribution is consistent with the SDSS measured stellar VDF (Sheth et al. 2003) and the Second Southern Sky Redshift Survey (SSRS2) inferred stellar VDF (Chae & Mao 2003), although the two stellar VDFs are significantly different from each other concerning their corresponding parameter values. We also consider constraints obtained for the Sample B (defined in previous section), with the likelihood is maximized at $\alpha =1.00^{+2.38}_{-1.00}$ and $\beta =2.34^{+0.26}_{-0.24}$, from which one could clearly see the marginal consistency between our fits and recent measurements of three stellar VDFs (especially the SDSS DR5 VDF of ETGs). | [
"Chae & Mao 2003"
] | [
"Consequently, the image separation distribution is consistent with the SDSS measured stellar VDF",
"and the Second Southern Sky Redshift Survey (SSRS2) inferred stellar VDF",
"although the two stellar VDFs are significantly different from each other concerning their corresponding parameter values."
] | [
"Similarities",
"Similarities",
"Compare/Contrast"
] | [
[
1564,
1579
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[
1373,
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1490,
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2020AandA...639A.107S__Helling_et_al._2019a_Instance_1 | Micro-porosity is the porosity arising from the organisation of the condensate monomers (e.g. Mg2 SiO4 in Mg2 SiO4[s]) within a cloud particle during growth. This is different from the porosity that can be used to characterise aggregates that originate from particle-particle collision processes (coagulation, e.g. Dominik & Tielens 1997; Blum & Wurm 2000), which we do not considerhere. On Earth, the material density of water ice is dependent on the ambient temperature at formation. Snowflakes are known to form many types of crystal structures that can be up to 84% porous for millimetre-sized cloud particles when compared toice material density (Hales 2005), leading to the possibility of altitude-dependent porosity in terrestrial snow clouds. Earth-like exoplanets, mini-Neptunes, and T-type brown dwarfs may form water clouds, composed of liquid or solid particles, but warmer planets and brown dwarfs of L-type and later have been shown to form cloud particles made of a mix of materials that is dominated by Mg, Si, Fe, and O and to a lesser extent by Ti, Al, K and other elements (e.g. Witte et al. 2009; Lee et al. 2015; Helling et al. 2019a). There are many ways in which this micro-porosity might be incorporated into mineral cloud particles, for example lattice faults at the interfaces between two different condensation species owing to the different lattice structures. Even for homogeneous growth, single species often have multiple crystal structures (Sood & Gouma 2013), which can also generate lattice faults at their interfaces. For example, the TiO2 [s] rutile and anatase forms are both stable at atmospheric pressures for temperatures greater than 1100 K (Jung & Imaishi 2001; Hanaor & Sorrell 2010). Additionally, within crystal structures, there are many known types of defect that might further decrease material density (e.g. Schottky defects in TiO2 [s] and MgO[s] crystals Ménétrey et al. 2004). Furthermore, these cloud particles not only change their material composition when falling through the atmosphere, but their particle sizes will also change such that the largest cloud particles are forming the innermost part of the cloud, which often sits deep inside the optically thick part of the atmosphere. Because cloud particles made of a mix of many thermally stable materials fall into warmer atmospheric regions, the low-temperature materials (such as SiO[s], MgSiO3[s]) become thermally unstable, they evaporate and leave behind a skeleton made of high-temperature materials (such as Fe[s], TiO2[s], Al2O3[s]). Whilst this may be a source of micro-porosity of cloud particles, Juncher et al. (2017) noted that this may also lead to a reduction in micro-porosity because the structural integrity of the particle is weakened and dangling structures break off. These micro-porous mineral cloud particles we call “mineral snowflakes”. | [
"Helling et al. 2019a"
] | [
"Earth-like exoplanets, mini-Neptunes, and T-type brown dwarfs may form water clouds, composed of liquid or solid particles, but warmer planets and brown dwarfs of L-type and later have been shown to form cloud particles made of a mix of materials that is dominated by Mg, Si, Fe, and O and to a lesser extent by Ti, Al, K and other elements"
] | [
"Background"
] | [
[
1134,
1154
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[
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2018ApJ...852...45W__Ghisellini_et_al._2013_Instance_1 | Similarly to former works (e.g., Zhang et al. 2010, 2012; Kang et al. 2014, 2016; Yan et al. 2016), we neglect the low-frequency radio data and consider the data with
(or
) in our SED fitting with the one-zone model due to the fact that radio emission should come from the large-scale jet and cannot be accounted for with a one-zone model. The variability correlation between millimeter, optical, X-ray, and γ-ray emission support the fact that they come from more or less the similar region (e.g., Sikora et al. 2008; León-Tavares et al. 2012; Wehrle et al. 2012; D’Ammando et al. 2013; Orienti et al. 2013). In four LSP blazars (0333 + 321, 0430 + 052, 2145 + 067, 2230 + 114), the putative UV excesses are not included in our SED fitting, as they should come from the cold accretion disk (Shakura & Sunyaev 1973; Ghisellini et al. 2013; Ajello et al. 2016). On average, there are 17 data points in our fitting. As an example, we show the multi-wavelength SED and its fitting for 2200 + 420 (BL Lac) in Figure 1 (left panel), where only the SSC process is considered due to the EC not being important in this source. In the right panel of Figure 1, we show the probability distributions of the model parameters, where
G,
,
,
,
,
, and
(upper and lower limits represent 1σ errors, see also Table 1). The source of 1219+285 is also a BL Lac object, for which the EC component is negligible. For the remaining 23 LSP sources, both the SSC and EC component are considered, where the SEDs and the fitting are shown in Figures 2–6. For each source, the SED fitting with seed photons from the torus and BLR are presented in left and right panels, respectively. In our SED fitting, we find that most LSP blazars have
(20 of 23 sources,
for the two other sources and only one has the ratio ∼0.6, see Table 1), where the distribution of the ratio
is shown in Figure 7. Our results suggest that the SED fitting with the seed photons from torus are better than with those from the BLR, which supports the notion that the location of the γ-ray emitting region should stay outside of the BLR. In the following work, therefore, we consider the model parameters from the SED fittings with the torus seed photons. | [
"Ghisellini et al. 2013"
] | [
"In four LSP blazars (0333 + 321, 0430 + 052, 2145 + 067, 2230 + 114), the putative UV excesses are not included in our SED fitting, as they should come from the cold accretion disk"
] | [
"Uses"
] | [
[
829,
851
]
] | [
[
623,
803
]
] |
2015AandA...575A.111D__Drimmel_&_Spergel_2001_Instance_1 | Using our stellar parameters, we derived an estimate of the spectroscopic distances of XO-2N and XO-2S by means of the following procedure. We generated Monte Carlo (MC) normal distributions for each spectroscopic parameter Teff, [Fe/H], and log g, composed of 10 000 random values and centred on the best estimates (Table 2). By keeping the stellar radii fixed to the values listed in Table 2 (for XO-2N we used the most accurate estimate), for each MC simulation we first determined the stellar bolometric luminosity L∗ (in solar units) from the Stefan-Boltzmann law, and then we derived the absolute bolometric magnitude Mbol from the relation Mbol = 4.75 − 2.5·log (L∗). By estimating the appropriate bolometric correction (BC), a value for the absolute magnitude in V-band MV was then obtained. The BC term was evaluated using the code provided by Casagrande & VandenBerg (2014). An additional input is the colour excess E(B − V) of the star, which we derived through the relation E(B − V) = AV(s)/3.1, where AV(s) is the interstellar dust extinction in V-band integrated at the distance s of the star (in pc) and measured along the line of sight. We derived AV(s) by adopting a simplified model of the local distribution of the interstellar dust density (Drimmel & Spergel 2001), expressed by the relation ρ = ρ0·sech2(z/hs), where z is the height of the star above the Galactic plane and hs is the scale-height of the dust, for which we adopted the value of 190 pc. The term z is related to the distance s and the Galactic latitude of the star b by the formula z = s·sinb. From this model we obtained the relation AV(s) = AV(tot)·sinh(s·sin b/hs)/cosh (s·sin b/hs), where AV(tot) is the interstellar extinction in V band along the line of sight integrated through the Galaxy, and can be estimated from 2D Galactic maps. For this purpose we used the value AV (tot) = 0.16 mag derived from the maps of Schlafly & Finkbeiner (2011)6. By assuming s = 150 pc as a prior distance of the stars (Burke et al. 2007), we obtained AV (150 pc) ~ 0.06 mag, corresponding to E(B − V) = 0.019 mag. This is the value used as input to the code of Casagrande & VandenBerg (2014) to obtain a first guess of the BC in V-band. This in turn was used in the distance modulus formula V − (Mbol − BCV) = 5·log (s) −5 − AV(s), to obtain a new value for the stellar distance s. The new distance was used to repeat the procedure iteratively, by determining at each step a new value of AV(s) and BCV(s), and finally another estimate of s. When the absolute difference between the last and previous calculated values of s was below 0.1 pc, the iterative process was interrupted and the last derived value for s was assumed as the distance of the star for the Nth Monte Carlo simulation. The adopted estimates for the distance of the XO-2 components are the median of the distributions of the 10 000 MC values, and the asymmetric error bars defined as the 15.85th and 68.3th percentile (see Table 1). Because they are model-dependent, we do not argue here whether the difference of ~2.5 pc between the XO-2S and XO-2S distances is real. We only note that the two values are compatible within the uncertainties and that our best estimate for the distance of XO-2N locates the star a few parsec closer than reported by Burke et al. (2007). | [
"Drimmel & Spergel 2001"
] | [
"We derived AV(s) by adopting a simplified model of the local distribution of the interstellar dust density",
"expressed by the relation ρ = ρ0·sech2(z/hs), where z is the height of the star above the Galactic plane and hs is the scale-height of the dust, for which we adopted the value of 190 pc."
] | [
"Uses",
"Uses"
] | [
[
1262,
1284
]
] | [
[
1154,
1260
],
[
1287,
1473
]
] |
2019ApJ...875...90L__Pontieu_et_al._2011_Instance_1 | When energy flows from the interior of the Sun outward into the solar atmosphere, why is the Sun’s outer atmosphere, the corona, much hotter than the inner atmosphere, the underlying chromosphere and photosphere? This is the long-standing problem of the coronal heating, which is one of the eight key mysteries in modern astronomy (Kerr 2012). For about 80 yr since the discovery of the extremely hot corona around the late 1930s (Grotian 1939; Edlen 1945), people have worked hard on addressing this issue, and great advances have been made in observation and theoretical studies (Parnell & De Moortel 2012; Amari et al. 2015; Arregui 2015; Cargill et al. 2015; De Moortel & Browning 2015; Jess et al. 2015; Klimchuk 2015; Longcope & Tarr 2015; Peter 2015; Schmelz & Winebarger 2015; Velli et al. 2015; Wilmot-Smith 2015). Especially during recent decades, high-resolution observations of solar super-fine structures indicate that small spicules, minor hot jets along small-scale magnetic channels from the low atmosphere upwards to the corona, petty tornados and cyclones, and small explosive phenomena such as mini-filament eruptions and micro- and nano-flares—all of these small-scale magnetic activities contribute greatly to coronal heating (De Pontieu et al. 2011; 2018; Zhang & Liu 2011; Parnell & De Moortel 2012; Klimchuk 2015; Peter 2015; Schmelz & Winebarger 2015; Henriques et al. 2016; Li et al. 2018a). Additionally, contributions of MHD waves to heating the corona have been observationally illustrated (van Ballegooijen et al. 2011; Jess et al. 2015; Kubo et al. 2016; Morton et al. 2016; Soler et al. 2017; Morgan & Hutton 2018). Meanwhile, with the progress of observational studies, two groups of theoretical models, magnetic reconnection models and magnetohydrodynamic wave models, have traditionally attempted to explain coronal heating, but so far no models can address the key mystery perfectly (van Ballegooijen et al. 2011; Arregui 2015; Cargill et al. 2015; Peter 2015; Velli et al. 2015; Wilmot-Smith 2015). Maybe we do not need to intentionally take to heart such the classical dichotomy, because waves and reconnections may interact with each other (De Moortel & Browning 2015; Velli et al. 2015). Additionally, statistical studies may look at coronal heating from a comprehensive perspective. Li et al. (2018b) found that the long-term variation of the heated corona, which is represented by coronal spectral irradiances, and that of small-scale magnetic activity are in lockstep, indicating that the corona should statistically be effectively heated by small-scale magnetic activity. Observational and theoretical model studies through heating channels and modes, and statistical studies by means of heating effect (performance of the heated corona), both suggest that coronal heating originates from small-scale magnetic activity. | [
"De Pontieu et al. 2011"
] | [
"Especially during recent decades, high-resolution observations of solar super-fine structures indicate that small spicules, minor hot jets along small-scale magnetic channels from the low atmosphere upwards to the corona, petty tornados and cyclones, and small explosive phenomena such as mini-filament eruptions and micro- and nano-flares—all of these small-scale magnetic activities contribute greatly to coronal heating"
] | [
"Background"
] | [
[
1248,
1270
]
] | [
[
824,
1246
]
] |
2016ApJ...825..150C__Bermúdez_et_al._2013_Instance_1 | The rotational spectrum of NaCl has been obtained using two different FTMW spectrometers constructed at the University of Valladolid. A solid rod was prepared by pressing the NaCl fine powder mixed with a small amount of commercial binder and was placed in the ablation nozzle (Alonso et al. 2009; Mata et al. 2012). A picosecond Nd:YAG laser (12 mJ per pulse, 20 ps pulse width) was used as a vaporization tool. Then, NaCl neutral molecules were supersonically expanded using the flow of a carrier gas (Ne at backing pressure of 15 bars) into the spectrometer chamber. NaCl was first investigated using a chirped-pulse Fourier transform microwave (CP-FTMW) spectrometer with a laser ablation source (Mata et al. 2012; Bermúdez et al. 2013) operating between 6.0 and 12.0 GHz to sample swiftly the rotational spectra of the different species present in the supersonic expansion. Chirped pulses of 4 μs directly generated by the 24 Gs s−1 AWG were amplified to about 300 W peak power using a traveling wave tube amplifier. The amplified pulse is broadcasted into the vacuum chamber through two microwave horns, interacting with the vaporized molecules in the pulsed jet. Finally, a total of 40,000 free induction decays (4 FID emissions per gas pulse), of 10 μs length duration, were averaged and digitized using a 50 Gs s−1 digital oscilloscope. Line widths of the order of 100 kHz FWHM were achieved. The sub-Doppler resolution LA-MB-FTMW spectrometer, described elsewhere (Alonso et al. 2009), operating from 4 to 26 GHz, was used to record the NaCl spectra with the resolution necessary to analyze the hyperfine structure due to the presence of two nuclei with I = 3/2 in the molecule. Microwave pulses of 0.3 μs duration with powers of 140 mW were applied to polarize the molecules in the jet. The free induction decay (FID) was recorded for 100 μs in the time domain at 40–100 ns sample intervals and then converted to the frequency domain by Fourier transformation. All the transitions appeared as Doppler doublets due to the parallel configuration of the molecular beam and the microwave radiation. The resonance frequency was determined as the arithmetic mean of the two Doppler components. The estimated accuracy of the frequency measurements is greater than 3 kHz. From 10 (in the case of the ground state and the lower vibrational states) to 2500 (for the higher vibrational states) averages were phase-coherently co-added to achieve reasonable signal-to-noise ratios. | [
"Bermúdez et al. 2013"
] | [
"NaCl was first investigated using a chirped-pulse Fourier transform microwave (CP-FTMW) spectrometer with a laser ablation source",
"operating between 6.0 and 12.0 GHz to sample swiftly the rotational spectra of the different species present in the supersonic expansion."
] | [
"Background",
"Background"
] | [
[
719,
739
]
] | [
[
570,
699
],
[
741,
878
]
] |
2019MNRAS.489..855C__Husemann_et_al._2013_Instance_1 | The size of ENLRs have been defined in different ways in the literature. Bennert et al. (2002) and Schmitt et al. (2003b) used the Hubble Space Telescope (HST) to obtain narrow band images of $\rm [O\, III]$, and adopted the maximum 3σ detected radius as the radius of the ENLR. This method is subject to the instrumental sensitivity limit that could be very different in different observations. Studies with long-slit spectroscopic observations define the radius based on isophote (Greene et al. 2011; Hainline et al. 2013, 2014), or the distance at which the ionization state changes from AGN to star-forming activities (Bennert et al. 2006a,b). The long-slit based observations also have drawbacks: the morphology of ENLR is sometimes irregular so that the derived size depends on the orientation of slits (Greene et al. 2011; Husemann et al. 2013). We have compared the measured size based on the IFU and the mock long-slit observation in Fig. 4 following the method discussed below. In most cases, long-slit observations tend to underestimate the true size of ENLR. IFU spectroscopic data allow us to use 2D maps to define the sizes of ENLRs. Common definitions include the radius of a specified $\rm [O\, III]$ surface brightness isophote (Liu et al. 2013, 2014), or the $\rm [O\, III]$ flux weighted radius (Husemann et al. 2013, 2014; Bae et al. 2017). We followed the same method as Liu et al. (2013) but chose a different threshold. The isophote threshold of 10−15$\rm erg\, s^{-1}cm^{-2}arcsec^{-2}$ was used for quasars related studies. This is suitable for such bright objects but are not as useful for fainter Syferts in our sample as it will leave a large number of AGN undetected. The typical 3σ depth of the MaNGA observation in $\rm [O\, III]$ surface brightness can reach 10−17$\rm erg\, s^{-1}cm^{-2}arcsec^{-2}$. For our AGN sample, the majority of AGN spaxels have surface brightnesses above 10−16$\rm erg\, s^{-1}cm^{-2}arcsec^{-2}$ which is thus adopted in this work as the threshold to define the sizes of the ENLRs (hereafter R16). If all spaxels are above this threshold, we extrapolated the fitted $\rm [O\, III]$ surface brightness profile to determine R16 (see Section 3.4 for more detail). It should be noted that the surface brightness can be affected by cosmological dimming, which has a scale factor of (1 + z)4 (Liu et al. 2013; Hainline et al. 2014). That is important for works trying to compare sample with different redshift, especially for high redshift quasars. | [
"Husemann et al. 2013"
] | [
"The long-slit based observations also have drawbacks: the morphology of ENLR is sometimes irregular so that the derived size depends on the orientation of slits"
] | [
"Motivation"
] | [
[
830,
850
]
] | [
[
648,
808
]
] |
2021AandA...656A.122D__Triana_et_al._2015_Instance_1 | Understanding how angular momentum and chemicals are transported in the interiors of stars (and planets) along their evolution is one of the key challenges of modern stellar (and planetary) astrophysics. Indeed, rotation modifies their structure, their chemical stratification, their internal flows and magnetism, and their mass losses and winds (e.g. Maeder 2009; Mathis et al. 2013; Aerts et al. 2019, and references therein). In this quest, asteroseismology has bought a fundamental breakthrough by demonstrating that all stars are the seat of a strong extraction of angular momentum during their evolution in comparison with the predictions by stellar models taking the rotation into account following the standard rotational transport and mixing theory (Eggenberger et al. 2012; Marques et al. 2013; Ceillier et al. 2013; Cantiello et al. 2014; Ouazzani et al. 2019). This was first obtained thanks to mixed pulsation modes splitted by rotation propagating in evolved low- and intermediate-mass stars (Beck et al. 2012, 2014, 2018; Mosser et al. 2012; Deheuvels et al. 2012, 2014, 2015; Deheuvels et al. 2020; Di Mauro et al. 2016; Triana et al. 2017; Gehan et al. 2018; Tayar et al. 2019). Then, observations of oscillation modes in F- and A-type stars (Kurtz et al. 2014; Saio et al. 2015; Bedding et al. 2015; Keen et al. 2015; Van Reeth et al. 2015, 2016, 2018; Schmid & Aerts 2016; Murphy et al. 2016; Sowicka et al. 2017; Guo et al. 2017; Saio et al. 2018, 2021; Mombarg et al. 2019; Li et al. 2019, 2020; Ouazzani et al. 2020) and in B-type stars (Pápics et al. 2015, 2017; Triana et al. 2015; Moravveji et al. 2016; Kallinger et al. 2017; Buysschaert et al. 2018; Szewczuk & Daszyńska-Daszkiewicz 2018; Pedersen et al. 2021; Szewczuk et al. 2021) provided us new Rosetta stones to constrain the transport of angular momentum in the whole Hertzsprung-Russell diagram. More particularly, this pushes gravity- and gravito-inertial mode pulsators such as γ-Doradus and SPB stars at the forefront of this research. For instance, recent theoretical developments have demonstrated how it is possible to probe stellar internal rotation in γ-Doradus stars from their surface to their convective core (Ouazzani et al. 2020; Saio et al. 2021). These stars are rapid rotators for a large proportion of them. Therefore, it is necessary to study gravito-inertial modes. These modes are gravity modes, which propagate only in stably stratified stellar radiation zones under the action of the restoring buoyancy force in the absence of rotation, which are modified by rotation. If their frequency is super-inertial (i.e. above the inertial frequency 2Ω, Ω being the stellar angular velocity), they are propagating in stellar radiation zones and evanescent in convective regions. If their frequency is sub-inertial (below 2Ω) they propagate in an equatorial belt in radiation zones and they become propagative inertial waves in convective regions (e.g. Dintrans & Rieutord 2000; Mathis et al. 2014). The challenge of studying these waves is that the equation describing their dynamics are intrinsically bi-dimensional and non-separable (Dintrans et al. 1999; Prat et al. 2016, 2018; Mirouh et al. 2016). This makes the development of seismic diagnosis difficult analytically (Prat et al. 2017) or expansive in computation time when using 2D oscillation and stellar structure codes (e.g. Ouazzani et al. 2017; Reese et al. 2021) in the general case. | [
"Triana et al. 2015"
] | [
"Then, observations of oscillation modes in",
"and in B-type stars",
"provided us new Rosetta stones to constrain the transport of angular momentum in the whole Hertzsprung-Russell diagram."
] | [
"Background",
"Background",
"Background"
] | [
[
1586,
1604
]
] | [
[
1196,
1238
],
[
1539,
1558
],
[
1760,
1879
]
] |
2018AandA...613A..15S__Becker_et_al._2016_Instance_1 | In this study, we have outlined and successfully tested a refined technique to measure in contemporary lensing surveys the scale-dependent galaxy bias down to non-linear scales of k ~ 10 h−1 Mpc for lens galaxies at z ≲ 0.6. To test our reconstruction technique, we employ a fiducial survey with a sky coverage of ~ 1000 deg2, and a photometry and a survey depth as in CFHTLenS. To construct realistic samples of lenses and sources, we have prepared mock catalogues that are consistent with those used in SES13 and Saghiha et al. (2017). Despite some variations in survey depth and area, these survey parameters are similar to the ongoing Kilo-Degree Survey (KiDS), Dark Energy Survey (DES), or the survey with the Hyper Suprime-Cam (Kuijken et al. 2015; Becker et al. 2016; Aihara et al. 2018). If the galaxy-bias normalisation is perfect, our technique applied to these data can achieve a statistical precision within the range of 5–10% (68% CL), if similar lens and source samples are targeted, and a slightly better accuracy of 3−7% (68% CL; see Table 3). For the high-z samples, the accuracy will be somewhat higher with 3−5%. On the other hand, it is clear from our overview Table 4 that the accuracy of the galaxy-bias normalisation is in fact limited, mainly by our knowledge of the intrinsic alignment of sources, cosmological parameters, and the galaxy redshift distributions. With a broad knowledge of |Aia|≲ 2 and the specifications for the normalisation errors in Table 4, we conclude that systematic errors would potentially degrade the overall accuracy to approximately 15% for b(k) and 10% for r(k). For fully controlled intrinsic alignment of sources, these errors could be reduced by 5%. An additional reduction by 3% may be possible by controlling the redshift distributions (their mean and variance) in the normalisation to 1% accuracy. For the fiducial cosmology, the knowledge of Ωm is of most importance while the normalisation of the ratio statistics is less affected by σ8. | [
"Becker et al. 2016"
] | [
"Despite some variations in survey depth and area, these survey parameters are similar to the ongoing Kilo-Degree Survey (KiDS), Dark Energy Survey (DES), or the survey with the Hyper Suprime-Cam"
] | [
"Similarities"
] | [
[
755,
773
]
] | [
[
538,
732
]
] |
2016ApJ...817..156W__Yan_et_al._2014a_Instance_1 | Recently, one of the hot topics in solar physics is the understanding of solar filaments in the corona, including their distribution, formation, eruption, and stability (Yang et al. 2008; Kong et al. 2015; Su et al. 2015; Yan et al. 2015). Martin (1998) and Gaizauskas (2002) have shown that convergence and cancellation of flux play an important role in the formation of filament channels and filaments. Flux ropes and magnetic dips represent the magnetic structures of filaments, which were reported by many authors (van Ballegooijen & Martens 1989; Mackay et al. 1999; Litvinenko & Wheatland 2005; Aulanier et al. 2006; Canou & Amari 2010). Many reports on the eruption of filaments are concerned with torus instability or/and kink instability (Török & Kliem 2003; Kliem & Török 2006; Török et al. 2010; Yan et al. 2014a, 2014b), and magnetic flux emergence and cancellation are also known to play a key role in these eruptions (Magara & Longcope 2003; Archontis & Török 2008; Yan et al. 2011). The transverse component of photospheric magnetic fields near the PIL increase after a filament’s eruption or flares (Liu et al. 2012; Sun et al. 2012; Wang et al. 2013). Sun et al. (2012) indicated that the substantial electric current increases with the emergence of flux during the formation of the filament. A downward collapse of coronal current after the eruption of the filament was also reported by Liu et al. (2012). Nonlinear force-free field (NLFFF) model extrapolation is the most powerful tool to reconstruct the magnetic field above the photosphere from photospheric vector magnetograms (VMs) thus far (Sakurai 1981; Wheatland et al. 2000; Amari et al. 2006; Canou & Amari 2010; Jiang et al. 2014), since the chromospheric and coronal magnetic fields are hard to measure exactly. Even so, it is still a long way to completely understand filaments. Regardless of its formative or eruptive process, and the variation of parameters including the electric current, magnetic field and plasma motion in the evolution of filament are not yet really clear. Investigating the electric current associated with the filament is helpful for understanding the characteristic of solar filaments. | [
"Yan et al. 2014a"
] | [
"Many reports on the eruption of filaments are concerned with torus instability or/and kink instability"
] | [
"Background"
] | [
[
807,
823
]
] | [
[
644,
746
]
] |
2021MNRAS.507..175S___2008_Instance_1 | Momentum and kinetic energy can be directly transferred to the gas, suppressing inflows. The fast-moving jets can also shock heat the surrounding gas. Many models have invoked kinetic jets to suppress cooling flows and SFRs in massive haloes (e.g. Dubois et al. 2010; Gaspari et al. 2012a; Li & Bryan 2014a; Prasad et al. 2015; Yang & Reynolds 2016a). Many models in the literature also invoke the idea that AGN can effectively drive strong pressure-driven outflows and offset cooling if a large fraction of the accretion energy is thermalized (Begelman 2004; Springel, Di Matteo & Hernquist 2005; Di Matteo, Springel & Hernquist 2005; Hopkins et al. 2006a, b, 2007, 2008; Johansson, Naab & Burkert 2009; Hopkins & Elvis 2010; Ostriker et al. 2010; Faucher-Giguère & Quataert 2012; Dubois et al. 2013; Barai et al. 2014; Weinberger et al. 2017a; Pillepich et al. 2018; Richings & Faucher-Giguère 2018a, b; Torrey et al. 2020). Physically, as the jet propagates, part of the kinetic energy can thermalize through shocks. Some studies have argued that the heat from those weak shocks can suppress cooling flows and SFRs in massive haloes (Yang & Reynolds 2016b; Li, Ruszkowski & Bryan 2017; Martizzi et al. 2019). The magnetic fields carried by the jet at its launch might also help suppress cooling flows by providing additional pressure support (Soker & Sarazin 1990; Beck et al. 1996, 2012), although our studies find that they have limited effects on global star formation properties of sub-L* galaxies (Su et al. 2017).1 Finally, CRs arise generically from processes that occur in fast shocks, so they could come from shocked winds or outflows. But they are particularly associated with relativistic jets from AGN (where they can make up the bulk of the jet energy; Berezinsky, Gazizov & Grigorieva 2006; Ruszkowski, Yang & Reynolds 2017b) and hot, relativistic plasma-filled ‘bubbles’ or ‘cavities’ (perhaps inflated by jets in the first place) around AGN. Different authors have argued that they could help suppress cooling flows by providing additional pressure support to the gas, driving pressurized outflows in the galaxy or CGM, or via heating the CGM/ICM directly via collisional (hadronic & Coulomb) and streaming-instability losses (Guo & Oh 2008; Sharma, Parrish & Quataert 2010; Enßlin et al. 2011; Fujita & Ohira 2011; Fujita, Kimura & Ohira 2013; Pfrommer 2013; Wiener, Oh & Guo 2013; Jacob & Pfrommer 2017a, b; Pfrommer et al. 2017; Ruszkowski et al. 2017a, b; Jacob et al. 2018). | [
"Hopkins et al.",
"2008"
] | [
"Many models in the literature also invoke the idea that AGN can effectively drive strong pressure-driven outflows and offset cooling if a large fraction of the accretion energy is thermalized"
] | [
"Background"
] | [
[
636,
650
],
[
667,
671
]
] | [
[
352,
543
]
] |
2022AandA...663A..70F___2017_Instance_1 | Out of these sites (a) might provide the conditions for a very weak r-process and νp-process, whether only up to Sr, Y, Zr or up to (but not beyond) the A = 130 peak is still debated (Wanajo et al. 2018; Curtis et al. 2019; Fischer et al. 2020a; Ghosh et al. 2022). (b) is a class of supernovae whose existence is put into question after recent re-determinations of the electron capture rate of 20Ne (Kirsebom et al. 2019a,b), but is not firmly excluded, however, leading to a too strong decline in abundances as a function of A for realistic Ye-conditions (Wanajo et al. 2011). (c) could plausibly lead to magnetars, neutron stars with surface magnetic fields of the order 1014 G, which form in ∼1 out of 10 of core collapse supernovae (e.g., Beniamini et al. 2019). Dependent on the initial fields, varying weak (probably dominating) to strong r-process conditions can be obtained, the latter, however, only for precollapse fields beyond 1012 G (Winteler et al. 2012; Mösta et al. 2014, 2015, 2018; Halevi & Mösta 2018; Nishimura et al. 2015, 2017; Bugli et al. 2020; Reichert et al. 2021). Case (d) has been proposed for a while. Dependent on the nuclear equation of state for massive core-collapse events, the collapse of the proto-neutron star to a black hole can be avoided (in a narrow stellar mass range) due to a quark-hadron phase transition with the right properties. The ejecta would experience a weak r-process, but populating even the actinides, however, with negligible abundances (Fischer et al. 2020b). Case (e) has been extensively discussed in the context of long-duration gamma-ray bursts (Woosley 1993; MacFadyen & Woosley 1999; MacFadyen et al. 2001). They involve the collapse of massive stars that rotate rapidly enough so that an accretion torus can form outside of the last stable orbit of a forming black hole, and they go along with relativistic polar and nonrelativistic torus outflows. This scenario has been proposed by Cameron (2003) as an r-process site and recently been examined in more detail by Siegel et al. (2019) and Siegel (2019). The remaining site, (f), is related to compact binary mergers (see Thielemann et al. 2017; Rosswog et al. 2017; Cowan et al. 2021, for overviews). | [
"Nishimura et al.",
"2017"
] | [
"Dependent on the initial fields, varying weak (probably dominating) to strong r-process conditions can be obtained, the latter, however, only for precollapse fields beyond 1012 G"
] | [
"Uses"
] | [
[
1022,
1038
],
[
1045,
1049
]
] | [
[
768,
946
]
] |
2021ApJ...921...18K__Kushwaha_et_al._2018a_Instance_1 | The most unique and characteristic observational feature of blazars’ highly variable broadband emission is the broad bimodal SED extending from the lowest accessible EM band, i.e., the radio, to the highest accessible, i.e., GeV-TeV γ-rays. The broadband SED of all blazars can be categorized into three different spectral subclasses: low-energy-peaked (LBL/LSP), intermediate-energy-peaked (IBL/ISP), and high-energy-peaked (HBL/HSP; Fossati et al. 1998; Abdo et al. 2010), based on the location of the low-energy hump. A remarkable property of each spectral subclass is the stability of the location of the two peaks despite huge variations in flux and often spectral shape. Only in a few rare instances has an appreciable shift in the location of the peaks been observed, e.g., the 1997 outburst of Mrk 501 (Pian et al. 1998; Ahnen et al. 2018) and the activity of OJ 287 from the end of 2015 to the middle of 2017 (Kushwaha et al. 2018a, 2018b). Even these two cases are remarkably different. In the case of Mrk 501, the locations of both the peaks shifted to higher energies. On the contrary, in OJ 287, a shift in the location of only the high-energy peak was observed during the 2015–2016 activity (Kushwaha et al. 2018a, 2019), while in 2016–2017 a new broadband emission component overwhelmed the overall emission, appearing as an overall shift in both the peaks as revealed in the detailed study by Kushwaha et al. (2018b). With the SED being the prime observable for exploration of the yet-debated high-energy emission mechanisms, such changes offer invaluable insights about the emission processes. For example, in Mrk 501 the shift in both peaks strongly implies the same particle distribution for the overall emission, while for OJ 287 the shift of only the high-energy peak can be reproduced by either inverse Compton scattering of the broad-line region photon field (Kushwaha et al. 2018a) or emission of hadronic origin (Oikonomou et al. 2019; Rodríguez-Ramírez et al. 2020). | [
"Kushwaha et al. 2018a"
] | [
"Only in a few rare instances has an appreciable shift in the location of the peaks been observed, e.g., the 1997 outburst of Mrk 501",
"and the activity of OJ 287 from the end of 2015 to the middle of 2017"
] | [
"Compare/Contrast",
"Compare/Contrast"
] | [
[
919,
940
]
] | [
[
677,
809
],
[
848,
917
]
] |
2017MNRAS.472..772M__Cassata_et_al._2015_Instance_1 | Fig. 7 also shows that there is little evidence for a relation between the Ly α luminosity and M1500 for Ly α-selected sources at z = 5.7 in our UV and Ly α luminosity range. As both M1500 and LLy α are, to first order, related to the SFR, we would have expected a correlation. To illustrate this, we show lines at constant Ly α escape fractions (based on the assumption that SFRUV = SFRH α, case B recombination with T = 10 000 K and ne = 100 cm−3 and no attenuation due to dust). This result resembles the well-known Ando et al. (2006) diagram, which reveals a deficiency of luminous LAEs with bright UV magnitudes between z ≈ 5 and 6. More recently, other surveys also revealed that the fraction of high-EW Ly α emitters increases towards fainter UV magnitudes (e.g. Schaerer, de Barros & Stark 2011; Stark, Ellis & Ouchi 2011; Cassata et al. 2015). The lack of a strong correlation between M1500 and LLy α might indicate that the SFRs are bursty (because emission-line luminosities trace SFR over a shorter time-scale than UV luminosity), or that the Ly α escape fraction is anti-correlated with M1500 (such that Ly α photons can more easily escape from galaxies that are fainter in the UV). A possible explanation for the latter scenario is that slightly more evolved galaxies (which are brighter in the UV) have a slightly higher dust content (e.g. Bouwens et al. 2012), affecting their Ly α luminosity more than the UV luminosity. It is interesting to note that several galaxies lie above the 100 per cent Ly α escape fraction line. This implies bursty or stochastic star formation (which is more likely in lower mass galaxies with faint UV luminosities, e.g. Mas-Ribas, Dijkstra & Forero-Romero 2016), alternative Ly α production mechanisms to star formation (such as cooling), a higher ionizing production efficiency (for example due to a top-heavy IMF or binary stars, e.g. Gotberg, de Mink & Groh 2017), or dust attenuating Ly α in a different way than the UV continuum (e.g. Neufeld 1991; Finkelstein et al. 2008; Gronke et al. 2016). | [
"Cassata et al. 2015"
] | [
"More recently, other surveys also revealed that the fraction of high-EW Ly α emitters increases towards fainter UV magnitudes"
] | [
"Background"
] | [
[
831,
850
]
] | [
[
638,
763
]
] |
2022ApJ...934..126K__Lotekar_et_al._2016_Instance_1 | We considered a homogeneous, collisionless two species plasma consisting of electrons and ions (H+ ions) in the simulation model. The ambient plasma parameters for ions and electrons are given in Table 2. The ions and electrons are considered to be fluid and their dynamic is incorporated into the simulation model using the following model equations viz., the continuity, momentum, and pressure equations of each species, and the Poisson equation (Kakad et al. 2014) given by
1
∂nj∂t+∂(njvj)∂x=0,
2
∂vj∂t+vj∂vj∂x+1mjnj∂Pj∂x−qjmjE=0,
3
∂Pj∂t+vj∂Pj∂x+γjPj∂vj∂x=0,
4
∂E∂x=∑jqjnj/ϵ0.
Here, the electric field E = −∂ϕ/∂x and the variables n
j
, P
j
, and v
j
are the plasma density, thermal pressure, and velocity of species j, respectively. The subscripts j = e and j = i are, respectively, used for electrons and ions. m
j
and q
j
represent the mass and the charge of species j, respectively. For electrons q
e
= −e and ions q
i
= e., ϵ
0 is the electric permittivity. In Equation (3), electrons and ions are treated as adiabatic with the same adiabatic index γ
e
= γ
i
= 3. The above set of equations is solved numerically. The spatial derivatives in these equations are solved using the fourth order central finite difference method and time derivatives are integrated using the leap-frog method to achieve second order accuracy. The details of the development of the simulation model are given in Kakad et al. (2013). We used a compensated filter to eliminate the small wavelength modes linked with such numerical noise (Lotekar et al. 2016; Kakad et al. 2016b). These numerical schemes are highly stable, and in the past, several electrostatic solitary wave structures have been modeled using such fluid simulations in multispecies plasmas (Kakad et al. 2014, 2016a). Δx and Δt are respectively considered as the grid size in spatial and time domain, and their values are taken in such a way that it fulfills the Courant–Friedrichs–Lewy condition, i.e.,
cΔtΔx≤1
, which is necessary for the convergence of the explicit finite difference method. Here, c is the speed of light. We performed two simulation runs in a one-dimensional system with the periodic boundary conditions by considering the observed ambient parameters as (i) T
e
= 60 eV, T
i
= 300 eV, n
i0 = 15/cc, n
e0 = 15/cc, V
di = V
de = −50 km s−1 (2) T
e
= 30 eV, T
i
= 300 eV, n
i0 = 15/cc, n
e0 = 15/cc, V
di = V
de = −50 km s−1 (see Table 2 for more details). In the simulations, we considered the real mass ratio, i.e., m
i
/m
e
= 1836. The background electron and ion densities satisfy the quasi-neutrality, i.e., n
e0 = n
i0 = n
0. For electron temperature, two values are considered based on the observations, i.e., 60 and 30 eV (see Figure 6(d)). The values of ω
pi, ω
pe, λ
i
, and λ
e
for the considered parameters are 5.1 × 103 rad s−1, 2.18 × 105 rad s−1, 33.3 m, and 14.9 m, respectively. To initiate the simulations, we used a localized Gaussian-type initial density perturbation in the equilibrium electron and ion densities given by
5
δn=Δnexp−x−xcl02.
Here, Δn and l
0 are the amplitude and width of the initial density perturbations, respectively. Thus, the perturbed density at t = 0 is n
j
(x) = n
j0 + δn. We consider the simulation system length as L
x
, and x
c
= L
x
/2 is the center of the simulation system. We performed two simulation runs for the parameters given in Table 2. For these simulation runs, we consider the time interval dt = 1 × 10−3, the grid spacing dx = 0.2, system length L
x
= 7000, l
0 = 1, and Δn = 0.1. Here, time is expressed in units of ω
pi
−1, space is in λ
di, and density is in units of n
i0. | [
"Lotekar et al. 2016"
] | [
"We used a compensated filter to eliminate the small wavelength modes linked with such numerical noise"
] | [
"Uses"
] | [
[
1560,
1579
]
] | [
[
1457,
1558
]
] |
2017AandA...607A..71G__Hansen_&_Oh_(2006)_Instance_2 | An implication of the respective escape fractions of the two regimes is visible in Fig. 12. Here we show several values of NHI,cl for the static setup using τd,cl = 10-4 (empty symbols) and τd,cl = 1 (filled symbols), which correspond to metallicities of \hbox{$Z/Z_\odot = 0.63\left(\tau_{\rm d}/10^{-4}\right)\left(10^{17}\cm^{-2}/N_{\HI,\cl}\right)$}Z/Z⊙=0.63τd(/10-4)(1017 cm-2/NHI,cl) (Pei 1992; Laursen et al. 2009); this reaches clearly unrealistic values. However, as in this paper we are interested in the fundamental impact of the individual parameters, we also study these extreme values. Also shown in Fig. 12 (with a black [gray] solid line for the low [high] dust content) is the proposed analytic solution for fesc by Hansen & Oh (2006)(18)\begin{equation} f_{\rm esc}^{\rm HO06} = 1/{\rm cosh}(\!\sqrt{2 N_{\cl}\epsilon}), \label{eq:fescHO06} \end{equation}fescHO06=1/cosh(2Nclϵ),where for Ncl we used Eq. (8)(with (a1,b1) = (3/2, 2) as found in Sect. 4.1) and for the clump albedo (i.e., the fraction of incoming photons that are reflected) ϵ, we adopted a value of c1(1−e− τd,cl) with c1 = 1.6 [c1 = 0.06] to match the NHI,cl = 1022 cm-2 data points for τd,cl = 10-4 [τd,cl = 1]. The behavior for the low- and high-dust contents is quite different. On the one hand, the escape fractions versus NHI,cl scales for τd,cl = 1 (filled symbols in Fig. 12) as predicted by Hansen & Oh (2006) in their “surface scatter” approximation, that is, a larger clump hydrogen column density “shields” the dust better from the Lyα photons and thus prevents their destruction more efficiently. On the other hand, however, this is not the case for the low-dust scenario presented in Fig. 12 (with unfilled symbols) where a larger value of NHI,cl implies a lower fesc. This is because here the dust optical depth through all the clumps (shown in the black dotted line in Fig. 12) is lower than the accumulated dust optical depth through the subsequent random-walk clump encounters (black solid line), i.e., \hbox{$\exp(-4/3 \fc \tau_{\rm d, cl}) \lesssim f_{\rm esc}^{\rm HO06}$}exp(−4/3fcτd,cl)≲fescHO06. Consequently, configurations in the “free-streaming” regime can possess enhanced Lyα escape fractions compared to the “random walk” regime (see Sect. 5.2 for a more detailed discussion). Still, both cases possess (much) larger escape fractions than a homogeneous slab, which is shown in Fig. 12 with a black dashed line. Here, we use the derived escape fraction by Neufeld (1990) with NHI = 4/3 × fc1022 cm-2 and τd = 4/3fcτd,cl, i.e., with equal column densities as in the NHI,cl = 1022 cm-2 case. | [
"Hansen & Oh (2006)"
] | [
"The behavior for the low- and high-dust contents is quite different.",
"On the one hand, the escape fractions versus NHI,cl scales for τd,cl = 1 (filled symbols in Fig. 12) as predicted by",
"in their “surface scatter” approximation",
"On the other hand, however, this is not the case for the low-dust scenario presented in Fig. 12 (with unfilled symbols) where a larger value of NHI,cl implies a lower fesc."
] | [
"Differences",
"Similarities",
"Similarities",
"Differences"
] | [
[
1384,
1402
]
] | [
[
1198,
1266
],
[
1267,
1383
],
[
1403,
1443
],
[
1594,
1766
]
] |
2016MNRAS.457.2433P__Nolan_et_al._2012_Instance_1 | From the result of the χ2 minimization, we found that the minimized χ2 values agree with the expected values, i.e. the computed χ2 are typically in the range of ($\mathrm{d.o.f.}-\sqrt{2 \mathrm{d.o.f.}}$, $\mathrm{d.o.f.}+\sqrt{2 \mathrm{d.o.f.}}$), where d.o.f. is the number of degrees of freedom. This means that the fits describe the observed data rather well. The only exception is with χ2 ≈ 20, which occurs for nearby AGN, z 0.2, and for the highest energy band, E > 10 GeV. Note that there is a strong contribution of the source, Mrk 421, in the first redshift interval at high energies, E > 10 GeV for quiescent states. Mrk 421 is a very hard spectrum γ-ray source with a photon index of ≈1.77 and its semiminor and semimajor axes at 68 per cent confidence are of 0$_{.}^{\circ}$0067 as derived in Nolan et al. (2012). Semiminor and semimajor axes of many 2FGL sources are derived with one order of magnitude higher uncertainties than those for Mrk 421 in the 2FGL catalogue (Nolan et al. 2012). We noted that the discrepancy between the observation and model is particularly strong in the annular bin, r 0$_{.}^{\circ}$05, for the redshift interval z 0.2 and for the highest energy band, E > 10 GeV. If we exclude photons from Mrk 421, then the minimized χ2 value is 7.5 and is consistent with the expected one. In the limit of a large number of counts in each bin, the likelihood is given by $\mathcal {L}=\text{exp}(-\chi ^{2}/2)$, so that minimizing χ2 is equivalent to maximizing the likelihood, $\mathcal {L}$. We found that the inclusion of a pair halo component in the model does not improve the likelihood value sufficiently to establish the presence of this pair halo component in the data. Therefore, we derived the one-sided 95 per cent upper limit on the fraction of photons attributable to a pair halo component by fitting the normalization of this component, for which we increase its normalization until the maximum likelihood decreases by 2.71/2 in logarithm. The computed upper limits are between 2 and 6 per cent depending on energy band and redshift interval. These upper limits are stronger than those obtained before. Note that the model for a point-like source used in the likelihood analysis is considered to be precisely established, however, the number of photons recorded during flaring states is close to those numbers of photons recorded during quiescent states for each of these redshift intervals. The expression, such as equation (1), leads to more conservative upper limits on the fraction of photons attributable to a pair halo component, since it takes the error bars assigned to the model into account. If the point-like source model is considered well established, then the error bars shown in Table 3 would decrease by a factor of ≈1.5. | [
"Nolan et al. (2012)"
] | [
"Mrk 421 is a very hard spectrum γ-ray source with a photon index of ≈1.77 and its semiminor and semimajor axes at 68 per cent confidence are of 0$_{.}^{\\circ}$0067 as derived in"
] | [
"Uses"
] | [
[
809,
828
]
] | [
[
631,
808
]
] |
2016AandA...586A..89C__Lo_2005_Instance_1 | The knowledge of physical properties, the structure, and the kinematics of the matter in the vicinity of supermassive black holes (SMBH) is essential to build detailed models of the clumpy outflow and to test the disc-wind scenario. While X-ray variability studies can provide accurate information on the atomic and ionized matter on scales of the BLR, the radio emission from luminous H2O masers (the so-called “megamasers”) constitutes a fundamental instrument to study the geometry and kinematics of the molecular gas at sub-parsec distance from SMBH. H2O masers may trace distinct regions in the AGN environment, from nearly edge-on accretion discs to nuclear outflows in the form of jets or winds (for recent reviews see Henkel et al. 2005; Lo 2005; Greenhill 2007; Tarchi 2012). Very Long Baseline Interferometry (VLBI) and single-dish monitoring studies of disc-masers allow us to map accretion discs and to determine the enclosed dynamical masses (e.g. Kuo et al. 2011). Jet-masers observations, instead, can provide estimates of the velocity and density of jet material (Peck et al. 2003). H2O maser emission have been also found to be associated with nuclear winds at 1 pc from the nuclear engine. In particular, water maser observations in Circinus (Greenhill et al. 2003) and NGC 3079 (Kondratko et al. 2005) seem to have resolved individual outflowing torus clouds. In fact, Greenhill et al. (2003) discovered that the H2O masers in Circinus trace both a Keplerian disc and a wide-angle outflow which appears to be collimated by the warps of the disc. In NGC 3079, VLBI observations of the maser emission revealed a clumpy thick disc. In addition to that, four maser features were found to be located at high latitude above the disc (at ~0.5 pc from the disc plane) and interpreted as part of a nuclear wind by Kondratko et al. (2005). Proper motion measurements and comparison of these outflow-masers with their disc counterpart provide the most promising method for probing the structure and kinematics of the torus molecular clouds (Nenkova et al. 2008). | [
"Lo 2005"
] | [
"While X-ray variability studies can provide accurate information on the atomic and ionized matter on scales of the BLR, the radio emission from luminous H2O masers (the so-called “megamasers”) constitutes a fundamental instrument to study the geometry and kinematics of the molecular gas at sub-parsec distance from SMBH. H2O masers may trace distinct regions in the AGN environment, from nearly edge-on accretion discs to nuclear outflows in the form of jets or winds (for recent reviews see"
] | [
"Motivation"
] | [
[
746,
753
]
] | [
[
233,
725
]
] |
2021MNRAS.501.2522J__Mukherjee_&_Paul_2004_Instance_1 | GX 301-2 is an HMXB consisting of a highly magnetized (B ∼ 4 × 1012 G, or even larger Doroshenko et al. 2010) pulsar and a B-type hyper-giant star Wray 977 (Vidal 1973; Kaper et al. 1995; Staubert et al. 2019). According to modelling of high-resolution optical spectra, Wray 977 has a mass of 43 ± 10 $\, \mathrm{M}_{\odot }$, a radius of 62 R⊙, and looses mass through powerful stellar winds at a rate of $\sim \! 10^{-5}\, \mathrm{M}_\odot \, {\rm yr}^{-1}$ with terminal velocity of 300 $\rm km\, s^{-1}$ (Kaper, van der Meer & Najarro 2006). The system is highly eccentric (e ∼ 0.46), with an orbital period of ∼41.5 d, and exhibits strong variation of the X-ray flux with orbital phase (Koh et al. 1997; Doroshenko et al. 2010). In particular, periodic outbursts at the orbital phase ∼1.4 d before the periastron passage (Sato et al. 1986), and a fainter one near the apastron passage are observed (Pravdo et al. 1995). The broad-band X-ray spectrum is orbital phase-dependent and can be approximately described as a power law with a high-energy cutoff and a cyclotron resonant scattering feature around 40 keV (Kreykenbohm et al. 2004; Mukherjee & Paul 2004; La Barbera et al. 2005; Doroshenko et al. 2010; Suchy et al. 2012; Islam & Paul 2014; Fürst et al. 2018; Nabizadeh et al. 2019). During the periastron flares, the source exhibits strong variability with an amplitude of up to a factor of 25, reaching a few hundreds mCrab in the energy band of 2–10 keV (e.g. Rothschild & Soong 1987; Pravdo et al. 1995). The flares are accompanied by the variability of the equivalent hydrogen column density ($\rm \mathit{ N}_{\rm H}$) and of the fluorescent iron lines, which is believed to be associated with clumpiness of the stellar wind, launched from the donor star (Mukherjee & Paul 2004). We note the clumpiness in this paper refers to any inhomogeneities in the stellar wind/stream, which are higher density regions, regardless of its specific formation mechanisms. On the other hand, Fürst et al. (2011) reported a long XMM–Newton observation in GX 301-2 around its periastron, which also exhibits systematic variations of the flux and $\rm \mathit{ N}_{H}$ at a time-scale of a few kiloseconds. Several wind accretion models, consisting of stellar winds and a gas stream, were proposed to explain the observed flares (e.g. Haberl 1991; Leahy 1991; Leahy & Kostka 2008; Mönkkönen et al. 2020). | [
"Mukherjee & Paul 2004"
] | [
"The broad-band X-ray spectrum is orbital phase-dependent and can be approximately described as a power law with a high-energy cutoff and a cyclotron resonant scattering feature around 40 keV"
] | [
"Background"
] | [
[
1142,
1163
]
] | [
[
925,
1115
]
] |
2019MNRAS.486.3741H__Susa_et_al._2015_Instance_1 | As the initial state of star-forming clouds, a critical Bonnor–Ebert (B.E.) density profile (Ebert 1955; Bonnor 1956) is adopted for each model. Note that the B.E. density profile or B.E. sphere is usually used as the initial condition of star-forming clouds (e.g. Matsumoto & Tomisaka 2004; Banerjee & Pudritz 2006; Machida et al. 2006a; Machida, Inutsuka & Matsumoto 2006b). The B.E. density profile is determined by the central density nc, 0 and isothermal temperature Tcl. The initial central density is set to $n_{\rm c,0}=10^4\, {\rm cm}^{-3}$ for all models. The temperature Tcl of each cloud is determined as the result of a one-zone calculation (for details, see Susa et al. 2015, and Paper I), and the results Tcl are given in Table 1. The cloud radius rcl, which depends on the initial cloud temperature, is also given in Table 1. To promote cloud contraction, the density is set to 1.8 times to the critical B.E. density profile (Machida & Hosokawa 2013). The initial cloud mass for each model is also listed in Table 1. Although the initial clouds have different radii and masses with different metallicities, the ratio α0 of thermal to gravitational energy, which significantly affects the cloud collapse (e.g. Miyama, Hayashi & Narita 1984; Tsuribe & Inutsuka 1999a,b), is the same for all models (α0 = 0.47). In addition, the ratio of rotational to gravitational energy in the initial cloud is set to β0 = 1.84 × 10−2 for all models (Goodman et al. 1993; Caselli et al. 2002). The initial magnetic field strength in each cloud is defined to satisfy μ0 = 3 (Troland & Crutcher 2008; Crutcher et al. 2010; Ching et al. 2017). The parameter μ0 is the mass-to-flux ratio of the initial cloud normalized by the critical value and is defined as
(1)
\begin{eqnarray*}
\mu _0 &=& \frac{\left(M/\Phi \right)}{\left(M/\Phi \right)_{\rm cri}},
\end{eqnarray*}
where M and Φ are the mass and magnetic flux of the initial cloud, respectively, and (M/Φ)cri is the ratio of the critical values of these parameters, which is (M/Φ)cri ≡ (2πG1/2)−1 (Nakano & Nakamura 1978). The direction of the magnetic field vector is parallel to the rotation vector (z-axis) in the initial cloud, in which a uniform magnetic field and rigid rotation are imposed. | [
"Susa et al. 2015"
] | [
"The temperature Tcl of each cloud is determined as the result of a one-zone calculation (for details, see"
] | [
"Uses"
] | [
[
672,
688
]
] | [
[
566,
671
]
] |
2019AandA...629A..54U__Marinucci_et_al._2015_Instance_4 | NGC 2110. NGC 2110 is another nearby (z = 0.00779, Gallimore et al. 1999), X-ray bright Seyfert galaxy. Diniz et al. (2015) report a black hole mass of
2
.
7
−
2.1
+
3.5
×
10
8
M
⊙
$ 2.7^{+ 3.5}_{- 2.1} \times 10^{8}\,{{M}_{\odot}} $
, from the relation with the stellar velocity dispersion. From BeppoSAX data, Malaguti et al. (1999) found the X-ray spectrum to be affected by complex absorption. This has been later confirmed by Evans et al. (2007), who find the Chandra+XMM–Newton data to be well fitted with a neutral, three-zone, partial-covering absorber. Rivers et al. (2014) find the Suzaku data to be well fitted with a stable full-covering absorber plus a variable partial-covering absorber. A soft excess below 1.5 keV is also present (Evans et al. 2007), and possibly due to extended circumnuclear emission seen with Chandra (Evans et al. 2006). No Compton reflection hump has been detected with Suzaku (Rivers et al. 2014) or NuSTAR (Marinucci et al. 2015), despite the presence of a complex Fe Kα line. According to the multi-epoch analysis of Marinucci et al. (2015), the Fe Kα line is likely the sum of a constant component (from distant, Compton-thick material) and a variable one (from Compton-thin material). Concerning the high-energy cut-off, ambiguous results have been reported in literature (see Table 1). Ricci et al. (2017) report a value of
448
−
55
+
63
$ 448^{+63}_{-55} $
keV, while Lubiński et al. (2016) report a coronal temperature of
230
−
57
+
51
$ 230^{+51}_{-57} $
keV and an optical depth of
0
.
52
−
0.13
+
0.14
$ 0.52^{+ 0.14}_{- 0.13} $
. From 2008–2009 INTEGRAL data, Beckmann & Do Cao (2010) report a cut-off of ∼80 keV with a hard photon index, but these results are not confirmed by NuSTAR (Marinucci et al. 2015). Indeed, only lower limits to the high-energy cut-off have been found with NuSTAR (210 keV: Marinucci et al. 2015), Suzaku (250 keV: Rivers et al. 2014) and BeppoSAX (143 keV: Risaliti 2002). No hard X-ray spectral variability has been detected by Caballero-Garcia et al. (2012) and Soldi et al. (2014) from BAT data, despite the significant flux variability. | [
"Marinucci et al. 2015"
] | [
"Indeed, only lower limits to the high-energy cut-off have been found with NuSTAR (210 keV"
] | [
"Compare/Contrast"
] | [
[
1910,
1931
]
] | [
[
1819,
1908
]
] |
2018ApJ...864..158L__Pino_&_Lazarian_2005_Instance_1 | Inspection of Equation (25) reveals that for pitch angles satisfying
,
so that curvature drift energization is more efficient than generalized betatron energy loss during incompressible contraction/merging of small-scale flux ropes. When μ2 1/3, betatron energy loss dominates curvature drift energization. That is why the net acceleration obtained from the two competing acceleration mechanisms depends sensitively on the anisotropy characteristics of the energetic particle pitch-angle distribution as discussed above. Consider the following three possibilities: (1) If energetic particles maintain a highly beamed pitch-angle distribution (which requires negligible pitch-angle scattering), curvature drift energy gain strongly dominates generalized betatron energy loss, and for all practical purposes we have a first-order Fermi acceleration mechanism as a consequence of incompressible contraction or merging of curved flux-rope magnetic fields (de Gouveia dal Pino & Lazarian 2005; Drake et al. 2006, 2010). (2) If the energetic particle distribution stays purely isotropic (extremely strong pitch-angle particle scattering), we can average the last terms in Equation (25) over all μ values to find
, indicating that the probability for curvature drift energy gain equals the probability for betatron energy loss (Drake et al. 2010). This supports the conclusion made above that net acceleration requires and depends only on the anisotropic part of the distribution. (3) The energetic particle distribution maintains a particle distribution with a small pitch-angle anisotropy (efficient pitch-angle scattering consistent with the diffusion approximation). In this case particle energization by incompressible contraction or merging of curved flux-rope magnetic fields becomes a second-order Fermi acceleration process (Drake et al. 2013; Zank et al. 2014; le Roux et al. 2015a). The small anisotropy option is supported by self-consistent particle simulations of turbulent magnetic reconnection and island formation at stacked primary current sheets in the absence of a guide field (Schoeffler et al. 2011; Drake et al. 2013), because energetic particles are scattered by fluctuations generated by plasma instabilities such as the firehose and magnetic mirror instabilities, resulting in energetic charged particle distributions with small anisotropies. However, in the presence of a strong guide field, particle simulations suggest larger anisotropies owing to weaker instabilities (Dahlin et al. 2017; Li et al. 2018). | [
"de Gouveia dal Pino & Lazarian 2005"
] | [
"Consider the following three possibilities: (1) If energetic particles maintain a highly beamed pitch-angle distribution (which requires negligible pitch-angle scattering), curvature drift energy gain strongly dominates generalized betatron energy loss, and for all practical purposes we have a first-order Fermi acceleration mechanism as a consequence of incompressible contraction or merging of curved flux-rope magnetic fields"
] | [
"Uses"
] | [
[
966,
1001
]
] | [
[
535,
964
]
] |
2021MNRAS.506..813D__Fabricius_et_al._2014_Instance_1 | Traditionally, GCs have been considered as relatively simple spherical, non-rotating, and almost completely relaxed systems. However, observational results obtained in the past few years are demonstrating that they are much more complex than previously thought. In particular, the classical simplified approach of neglecting rotation in GCs has become untenable from the observational point of view. In fact, there is an increasing wealth of observational results suggesting that, when properly surveyed, the majority of GCs rotate at some level. As of today, more than $50{{\ \rm per\ cent}}$ of the sampled GCs show clear signatures of internal rotation (e.g. Anderson & King 2003; Bellazzini et al. 2012; Fabricius et al. 2014; Bianchini et al. 2018; Ferraro et al. 2018; Kamann et al. 2018a; Lanzoni et al. 2018a,b; Sollima, Baumgardt & Hilker 2019). Moreover, evidence of rotation has also been reported for intermediate-age clusters (Mackey et al. 2013; Kamann et al. 2018b), young massive clusters (Hénault-Brunet et al. 2012; Dalessandro et al. 2021), and nuclear star clusters (Nguyen et al. 2018; Neumayer, Seth & Böker 2020) indicating that internal rotation is a common ingredient across dense stellar systems of different sizes and ages. On the theoretical side, the presence of internal rotation has strong implications on our understanding of the formation and dynamics of GCs and affects, for example, their long-term evolution (Einsel & Spurzem 1999; Ernst et al. 2007; Breen, Varri & Heggie 2017) and their present-day morphology (e.g. Hong et al. 2013; van den Bergh 2008). Moreover, signatures of internal rotation could be crucial in revealing the formation mechanisms of the so-called multiple stellar populations (MPs) in GCs (Bekki 2010; Mastrobuono-Battisti & Perets 2013; Hénault-Brunet et al. 2015) differing in terms of their light-element (such as He, Na, O, C, N) abundances (see Bastian & Lardo 2018; Gratton et al. 2019 for recent reviews on the subject), and which are observed in almost all GCs now. Differences in the rotation amplitudes of MPs have been observed in two cases so far, namely M 13 and M 80 (Cordero et al. 2017; Kamann et al. 2020)1 and in both clusters the Na-rich population (also known as second population or generation – SP) is found to rotate with a larger amplitude than the first population FP (Na-poor). | [
"Fabricius et al. 2014"
] | [
"In particular, the classical simplified approach of neglecting rotation in GCs has become untenable from the observational point of view. In fact, there is an increasing wealth of observational results suggesting that, when properly surveyed, the majority of GCs rotate at some level. As of today, more than $50{{\\ \\rm per\\ cent}}$ of the sampled GCs show clear signatures of internal rotation (e.g."
] | [
"Background"
] | [
[
708,
729
]
] | [
[
262,
661
]
] |
2017MNRAS.469..521K__Redfield_2007_Instance_1 | Molecular CO gas is observed in the sub-mm with both single-dish telescopes (JCMT, APEX) and interferometers such as ALMA, the SMA or NOEMA. For the brightest targets, ALMA's high-resolution and unprecedented sensitivity allow us to obtain CO maps for different lines and isotopes showing the location of CO belts and giving an estimate of their mass (see the CO gas disc around β Pic, Dent et al. 2014; Matrà et al. 2017). Atomic species are also detected around a few debris disc stars. In particular, Herschel was able to detect the O i and C ii fine structure lines in two and four systems, respectively (e.g. Riviere-Marichalar et al. 2012, 2014; Roberge et al. 2013; Cataldi et al. 2014; Brandeker et al. 2016). Also, metals have been detected, using UV/optical absorption lines, around β Pictoris (Na, Mg, Al, Si and others, Roberge et al. 2006), 49 Ceti (Ca ii, Montgomery & Welsh 2012) and HD 32297 (Na i, Redfield 2007). Some of these metals are on Keplerian orbits but should be blown out by the ambient radiation pressure (Olofsson, Liseau & Brandeker 2001). It is proposed that the overabundant ionized carbon observed around β Pic, which is not pushed by radiation pressure could brake other ionized species due to Coulomb collisions with them (Fernández, Brandeker & Wu 2006). A stable disc of hydrogen has not yet been observed in these systems (Freudling et al. 1995; Lecavelier des Etangs et al. 2001) but some high velocity H i component (presumably falling on to the star) was detected recently with the HST/COS around β Pic (Wilson et al. 2017). All these observations need to be understood within the framework of a self-consistent model. Models of the emission of the gas around main sequence stars have been developed, but gas radial profiles were not derived self-consistently and often assumed to be Gaussian (e.g. Zagorovsky, Brandeker & Wu 2010) or not to be depleted in hydrogen compared to solar (as expected in debris discs, e.g. Gorti & Hollenbach 2004) or both (e.g. Kamp & Bertoldi 2000). | [
"Redfield 2007"
] | [
"Also, metals have been detected, using UV/optical absorption lines, around",
"and HD 32297 (Na i,"
] | [
"Background",
"Background"
] | [
[
915,
928
]
] | [
[
718,
792
],
[
895,
914
]
] |
2018MNRAS.475.1104B__Leonard_et_al._2001_Instance_1 | Observational evidence suggests that SNe IIn are aspherical and may have high polarization signals. An ∼ 20 per cent level of SN asphericity may result in a detectable 1 per cent linear polarization signal (Höflich 1991; Leonard & Filippenko 2005). While a number of efforts have been made to explain core-collapse SNe in terms of axisymmetric jets (Khokhlov et al. 1999; Wheeler, Meier & Wilson 2002; Wang et al. 2002), observational evidence in the form of loops in the Q/U plane suggests that even these axisymmetric models may not be sufficient for all types of core-collapse SNe (Hoffman et al. 2008; Wang & Wheeler 2008; Maund et al. 2009). In contrast to SNe IIn, SNe II-P generally have shown very low levels of polarization at early times (Leonard & Filippenko 2001; Leonard et al. 2002a; however, see Leonard et al. 2016; Mauerhan et al. 2017). The initially low polarization levels often rise during the plateau phase (e.g. Leonard et al. 2016), with a polarization angle that typically remains nearly fixed throughout (e.g. Leonard et al. 2001; Mauerhan et al. 2017). Occasionally, a sharp rise in the polarization signal is seen during the transition to the nebular phase (Leonard et al. 2006; Chornock et al. 2010), perhaps suggesting that the core of the SN is more aspherical than the early-time photosphere (Chugai et al. 2005; Chugai 2006). However, as demonstrated by the modelling of Dessart & Hillier (2011), it is also possible that even large asymmetries during the plateau phase will produce very little polarization, owing to the high optical depth to electron scattering and the fact that geometric information is lost due to multiple scatters. The ‘spike’ that is sometimes seen during the drop off of the plateau may, therefore, be more of an optical-depth effect (i.e. the ‘spike’ occurs when $\tau _{e^-}$ has decreased to unity) than a demonstration of increasing asphericity with depth in the atmosphere (Leonard et al. 2012). The picture for SNe IIn, on the other hand, is not as well understood. The primary reason for this is that an effective model for a SN IIn must not only account for the geometry of the SN ejecta, but also the geometry of the CSM interaction region (Chugai 2001). In such cases, the temporal evolution that multi-epoch spectropolarimetry provides becomes particularly important in establishing a physical model. | [
"Leonard et al. 2001"
] | [
"The initially low polarization levels often rise during the plateau phase",
"with a polarization angle that typically remains nearly fixed throughout (e.g."
] | [
"Background",
"Background"
] | [
[
1036,
1055
]
] | [
[
855,
928
],
[
957,
1035
]
] |
2020MNRAS.499.5230F__Tripp,_Savage_&_Jenkins_2000_Instance_1 | Different methods have been proposed to detect the hot, highly ionized WHIM gas: detection in galaxy groups with Sunyaev–Zeldovich effect (Hill et al. 2016; de Graaff et al. 2019; Lim et al. 2020; Tanimura et al. 2020) using autocorrelation function measurements (Galeazzi et al. 2010), with absorption lines in quasar sightline (Kovács et al. 2019) and using CMB as a backlight (Ho, Dedeo & Spergel 2009). Given the challenges of X-ray data, observations at longer wavelengths (UV and optical) benefit from higher instrumental throughout, enhanced spectral resolution. By reverting to ground-based facilities, longer exposure times and larger number of targets become possible. Nevertheless, the UV lines have so far mostly been used to detect absorbing gas with temperature range $10^5\, \mathrm{K} \lt T \lt 10^6\, \mathrm{K}$ from either O vi (Tripp, Savage & Jenkins 2000; Danforth & Shull 2005; Danforth & Shull 2008; Tripp et al. 2008; Savage et al. 2014; Werk et al. 2014; Danforth et al. 2016; Sanchez, Morisset & Delgado-Inglada et al. 2016) or BLAs (Lehner et al. 2007; Danforth, Stocke & Shull 2010). Recently, Zastrocky et al. (2018) have constrained the Milky Way’s hot (T = 2 × 106 K) coronal gas using the forbidden 5302 Å transition of Fe xiv. Only recently, some highly ionized iron UV lines detected in emission have been used as diagnostics of gas at temperatures of T = 107 K. Out of several forbidden lines in the UV that could trace this gas temperature range, and from various species of highly ionized iron, the emission of [Fe xxi] is the brightest (Anderson & Sunyaev 2016). Anderson & Sunyaev (2018) report the discovery of [Fe xxi] in emission in a filament projected 1.9 kpc from the nucleus of M87. Theoretically, the highly ionized iron UV lines can be observed in absorption as well. The forbidden line of [Fe xxi], in particular, has the largest effective cross-section for absorption and a rest wavelength λ1354 Å, conveniently close to Ly α λ1215 Å. | [
"Tripp, Savage & Jenkins 2000"
] | [
"Nevertheless, the UV lines have so far mostly been used to detect absorbing gas with temperature range $10^5\\, \\mathrm{K} \\lt T \\lt 10^6\\, \\mathrm{K}$ from either O vi"
] | [
"Background"
] | [
[
848,
876
]
] | [
[
679,
846
]
] |
2017AandA...602A..29B__Shepherd_1997_Instance_1 | The MOJAVE survey provides access to excellent Very Long Baseline Array (VLBA) data taken at 15 GHz. This is of great value for investigating AGN properties on a statistical basis (e.g., Lister et al. 2016; Homan et al. 2015). Whereas the MOJAVE team is providing a statistical analysis of the complete sample, our approach is to select and focus on specific sources which appear to be special due to unique or rare properties. Although a statistical analysis of large numbers of sources is certainly of utmost importance and great value, a detailed analysis concentrating on peculiar properties – that are not necessarily common to the AGN population – can produce complementary results. We re-modeled fifty VLBA observations of 1308+326 obtained at 15 GHz (taken from the online MOJAVE archive webpage) between 1995.05 and 2014.07 with Gaussian components within the difmap-modelfit program (Shepherd 1997). The modelfit program fits image-plane model components to the visibilities in the uv plane. We did not apply self-calibration but used the calibration as provided by the MOJAVE team. Only circular components were used. The use of exclusively circular Gaussian components proved to be the most efficient way to parameterize the component properties. It reduces the number of free parameters, compared to the use of elliptical Gaussians, and allows a more secure identification of components across the epochs. Although it might have advantages to model the data of some of the epochs with elliptical components, our experience is that circular component modeling allows a more homogeneous analysis of all the epochs and more trustworthy identification of individual components in their long-term motion and evolution. Every epoch was modeled independently starting from a point source model. The errors were estimated from deviations in all parameters derived by calculating fits to models with ±1 component. All the images with model-fits superimposed are displayed in Figs. A.1–A.13. The parameters and corresponding uncertainties of the model-fits are listed in Table A.1. Components labeled with an “x” denote the presence of features that could not be reliably traced across the epochs. In addition we analyzed single-dish total intensity and polarization radio monitoring data at three radio frequencies, which was observed by the UMRAO monitoring program. | [
"Shepherd 1997"
] | [
"We re-modeled fifty VLBA observations of 1308+326 obtained at 15 GHz (taken from the online MOJAVE archive webpage) between 1995.05 and 2014.07 with Gaussian components within the difmap-modelfit program",
"The modelfit program fits image-plane model components to the visibilities in the uv plane.",
"We did not apply self-calibration but used the calibration as provided by the MOJAVE team. Only circular components were used. The use of exclusively circular Gaussian components proved to be the most efficient way to parameterize the component properties. It reduces the number of free parameters, compared to the use of elliptical Gaussians, and allows a more secure identification of components across the epochs. Although it might have advantages to model the data of some of the epochs with elliptical components, our experience is that circular component modeling allows a more homogeneous analysis of all the epochs and more trustworthy identification of individual components in their long-term motion and evolution."
] | [
"Uses",
"Background",
"Compare/Contrast"
] | [
[
894,
907
]
] | [
[
689,
892
],
[
910,
1001
],
[
1002,
1726
]
] |
2016AandA...586A.156K__Osorio_et_al._(2011)_Instance_1 | In this study, we use a model atom of Li i which was originally developed and tested by Cayrel et al. (2007) and Sbordone et al. (2010). For the purposes of the current work, the model atom was updated and now consists of 26 levels and 123 (96 of which are radiative) bound-bound transitions of Li i and the ground level of Li ii, with each level of Li i coupled to the continuum via bound-free transitions. (The ground state of Li ii in the current model atom is always in LTE, since lithium is mostly fully ionized throughout the model atmospheres studied in this work.) This renders the model atom complete up to the principal quantum number n = 6 and spectroscopic term \hbox{$^2{\rm F}^{\rm o}$}Fo2, with additional energy levels up to n = 9 and term 2D (Fig. 1). Data concerning atomic energy levels and transitions (level energies and statistical weights; wavelengths and Einstein coefficients of the bound-bound transitions) were taken from the NIST database. We used electron collisional excitation and ionization rates from the quantum mechanical computations of Osorio et al. (2011) for the energy levels of up to 5s (2S). Elsewhere, collisional excitation by electrons for radiatively permitted transitions was accounted for by using the classical formula of van Regemorter (1962), while the formula of Seaton (1962) was used to compute collisional electron ionization rates. To account for the collisional excitation by hydrogen, we used collisional excitation rates computed by Barklem et al. (2003), while the classical formula of Drawin (in the formulation of Lambert 1993) was used for radiatively permitted transitions when no quantum mechanical data were available. Hydrogen H–Li charge transfer rates were taken from Barklem et al. (2003) for the atomic levels up to 4p inclusive. Bound-free transitions resulting from collisions with hydrogen were expected to be inefficient and thus were ignored. Photoionization cross sections were taken from TOPBASE (Cunto et al. 1993). No scaling of collisional rates was applied in the calculations of bound-free and bound-bound transitions. Information about the energy levels and bound-bound radiative transitions, included in the present version of the Li i model atom, are provided in Tables A.1 and A.2, respectively. Twenty-seven transitions in the model atom are purely collisional. Collisional radiatively-forbidden transitions involving Li i levels beyond 5s were not accounted for since reliable quantum-mechanical data for these transitions are not available. We note that the role of the omitted transitions between the higher levels is minor: when they are taken into account using the formula of Allen (1973), collision strength Ω = 1, the change in the estimated abundance (which directly applies to abundance corrections, too) is always less than 0.05 dex, with typical values being significantly smaller. | [
"Osorio et al. (2011)"
] | [
"We used electron collisional excitation and ionization rates from the quantum mechanical computations of",
"for the energy levels of up to 5s (2S)."
] | [
"Uses",
"Uses"
] | [
[
1073,
1093
]
] | [
[
968,
1072
],
[
1094,
1133
]
] |
2016MNRAS.462.2275K__Porubcan,_Kornos_&_Williams_2004_Instance_1 | Currently, the concept of the existence of genetic relations between comets and meteoroid streams as well as near-Earth asteroids (NEAs) is generally accepted. As a consequence, a new definition, the ‘comet–asteroid–meteoroid complex’, was introduced for the indication of the families of objects with a common origin. The certainty of the existence of such associations has been proved by numerous studies of the dynamical properties of some small bodies. For instance, the association of comet 2P/Encke with the Taurid meteoroid stream was confirmed by a number of investigations and does not raise any doubts. Furthermore, it was shown that more than 40 asteroids belong to the Taurid complex, i.e. they move on orbits close to those of the comet Encke and the Taurid stream. A cometary nature of these NEAs was suggested and a conclusion was made that they are either extinct fragments of comet Encke or represent (together with comet Encke) the remnants of a larger comet-progenitor of the stream (Asher, Clube & Steel 1993a; Babadzhanov 2001; Porubcan, Kornos & Williams 2004, 2006; Babadzhanov, Williams & Kokhirova 2008a; Rudawska, Vaubaillon & Jenniskens 2012a,b; Madiedo et al. 2013). This family of near-Earth objects with a common origin is named the Taurid comet–asteroid–meteoroid complex. The Quadrantid comet–asteroid–meteoroid complex is another well-known set of related NEOs that very probably includes comet 96P/Machholz 1 and certainly NEA 2003EH1 and the Quadrantid meteoroid stream, producing eight meteor showers observable on the Earth. It was shown that asteroid 2003EH1 is in fact the extinct fragment of a parent comet of the Quadrantid stream (Jenniskens 2004; Williams et al. 2004; Babadzhanov, Williams & Kokhirova 2008b; Neslusan, Hajdukova & Jakubik 2013). It turned out that the Piscid meteoroid stream contains three related NEAs moving within the stream and representing the extinct debris of a larger comet-progenitor of this complex (Babadzhanov & Williams 2007; Babadzhanov, Williams & Kokhirova 2008c). Based on investigation of the dynamical properties, it was found that three NEAs with similar comet-like orbits are associated with the ι Aquariid meteoroid stream and this asteroid–meteoroid complex is the result of the break-up of a parent comet (Babadzhanov, Williams & Kokhirova 2009). | [
"Porubcan, Kornos & Williams 2004"
] | [
"A cometary nature of these NEAs was suggested and a conclusion was made that they are either extinct fragments of comet Encke or represent (together with comet Encke) the remnants of a larger comet-progenitor of the stream"
] | [
"Background"
] | [
[
1049,
1081
]
] | [
[
779,
1001
]
] |
2016ApJ...822...22O__Orlando_et_al._2015_Instance_1 | We used the FLASH code (Fryxell et al. 2000) to perform the calculations. In particular we solved the equations for compressible gas dynamics with the FLASH implementation of the piecewise-parabolic method (Colella & Woodward 1984). The radiative losses Λ in Equation (2) are calculated through a table lookup/interpolation method. Also we extended the code by additional computational modules to calculate the deviations from electron-proton temperature-equilibration and the deviations from equilibrium of ionization of the most abundant ions. For the former, we calculated the ion and electron temperatures in each cell of the post-shock medium, taking into account the effects of Coulomb collisions (see Orlando et al. 2015 for the details of the implementation). According to Ghavamian et al. (2007), first the electrons are assumed to be heated at the shock front almost istantaneously up to kT ∼ 0.3 keV by lower hybrid waves. This istantaneous heating does not depend on the shock Mach number and is expected for fast shocks (i.e., >103 km s−1) as those simulated here. Then we considered the effects of the Coulomb collisions to calculate the evolution of ion and electron temperatures in each cell of the post-shock medium in the time Δtj = t − tshj, where tshj is the time when the plasma in the jth domain cell was shocked and t is the current time. The time tshj is stored in an additional passive tracer added to the model equations. To estimate the deviations from equilibrium of ionization of the most abundant ions, we adopted the approach suggested by Dwarkadas et al. (2010). In fact, this approach ensures high efficiency in the calculation (expecially in the case of 3D simulations as in our case) as well as a reasonable accuracy in the evaluation of the non-equilibrium of ionization effects. The approach consists of the computation of the maximum ionization age in each cell of the spatial domain τj = nejΔtj, where nej is the electron density in the jth cell and Δtj is the time since when the plasma in the cell was shocked (see above). | [
"Orlando et al. 2015"
] | [
"For the former, we calculated the ion and electron temperatures in each cell of the post-shock medium, taking into account the effects of Coulomb collisions (see",
"for the details of the implementation)."
] | [
"Uses",
"Uses"
] | [
[
708,
727
]
] | [
[
546,
707
],
[
728,
767
]
] |
2022AandA...660A.135V__Spina_et_al._2016_Instance_1 | The first study, to our knowledge, to notice the net increase in the abundance of slow (s) neutron capture elements in young stellar populations is D’Orazi et al. (2009), in which the abundance of barium in young star clusters was seen to be higher than in the older ones. Maiorca et al. (2011, 2012) added a few more elements with important s-process contributions (yttrium, zirconium, lanthanum, and cerium), confirming the increasing trend towards younger ages. Subsequently, a number of works have attempted to both clarify the origin of this increase (see, e.g., Bisterzo et al. 2014; Mishenina et al. 2015; Trippella et al. 2016; Magrini et al. 2018; Spina et al. 2018; Busso et al. 2021) and to use their abundances to estimate the ages of stars, often using neutron capture s-process elements in combination with other elements with opposite behaviours, such as α elements – that we indicate as chemical clocks – and thus maximising the dependence of the relationship with age (see, e.g., Tucci Maia et al. 2016; Nissen 2016; Feltzing et al. 2017; Fuhrmann et al. 2017; Slumstrup et al. 2017; Titarenko et al. 2019). Once the existence of a relationship between age and chemical clocks was established (see, e.g., Spina et al. 2016; Delgado Mena et al. 2019; Jofré et al. 2020), the next steps were the following: (i) to clarify the applicability of these relationships with luminosity class (dwarf or giant) (see, e.g., Tucci Maia et al. 2016; Slumstrup et al. 2017; Casamiquela et al. 2021), metallicity (see, e.g., Feltzing et al. 2017; Delgado Mena et al. 2019; Casali et al. 2020), and population type (thin disc, thick disc, halo) (see, e.g., Titarenko et al. 2019; Nissen et al. 2020; Tautvaišienė et al. 2021), or even in dwarf galaxies (Skúladóttir et al. 2019; ii) to calibrate them with a sample of stars with reliable age determination, which are usually open star clusters (OCs), solar twins, or targets with asteroseismic observations. Finally, it is essential to understand whether these relationships are valid throughout the Galactic disc, or whether they are necessarily position-dependent. For the first time, Casali et al. (2020) applied the relations derived from a large sample of solar-like stars located in the solar neighbourhood and noted that they fail to reproduce the ages of star clusters in the inner disc. They concluded that the relationship between age and chemical clocks is not universal and that it varies with galactocentric position. Later, Magrini et al. (2021b) suggested that the differences in the relationships between age and chemical clocks in different parts of the Galactic disc are due to the strong dependence on the metallicity of the yields of low-mass stars, which produce s-process elements during the final stages of their evolution. Casamiquela et al. (2021) used red clump stars in open clusters to investigate the age dependence of several abundance ratios, including those that contain s-process and α elements. They found that the relationship between [Y/Mg] and ages outlined by open clusters is similar to the one found using solar twins in the solar neighbourhood. They also found that the abundance ratios involving Ba are those with the highest correlation with age. However, they also note that as one moves away from the solar neighbourhood, the dispersion increases and is in agreement with the findings of Casali et al. (2020), which attributed this to the spatial variation of the star formation history along the galactocentric radius. | [
"Spina et al. 2016"
] | [
"Once the existence of a relationship between age and chemical clocks was established (see, e.g.,"
] | [
"Background"
] | [
[
1222,
1239
]
] | [
[
1125,
1221
]
] |
2021MNRAS.505.5833F__Lesgourgues_2011_Instance_1 | Besides the Patchy and the LN mocks, we also model the multipoles of the BOSS CMASS two-point correlation function using an analytic approach, which is required to run the Monte Carlo analysis (see Section 5). The 2PCF can be obtained from the Fourier transform of the matter power spectrum, P(k), for which we assume the template from Padmanabhan & White (2008):
(10)$$\begin{eqnarray*}
P(k)=\left[P_{\rm {lin}}(k)-P_{\rm {dw}}(k)\right]e^{-k^2\Sigma _{\rm {nl}}^2/2}+P_{\rm {dw}}(k) .
\end{eqnarray*}$$In the equation above, Plin(k) is the linear matter power spectrum computed using the Boltzmann code CLASS (Lesgourgues 2011), assuming the Planck 2015 (Ade et al. 2016) fiducial cosmology. The Pdw(k) term is the de-wiggled power spectrum (Eisenstein & Hu 1998), while the Σnl parameter encodes the smoothing of the BAO peak due to non-linear effects (Crocce & Scoccimarro 2006). The multipoles of the analytic 2PCF are defined as
(11)$$\begin{eqnarray*}
\xi _l(s) = \frac{i^l}{2\pi ^2}\int _0^{\infty } P_l(k)j_l(ks)k^2{\rm d}k ,
\end{eqnarray*}$$from which we recover the monopole (l = 0) and the quadrupole (l = 2). In equation (11), jl(x) represents the spherical Bessel function of first kind and order l, while Pl(k) are the multipoles of the power spectrum defined as
(12)$$\begin{eqnarray*}
P_l(k)=\frac{2l+1}{2}\int ^1_{-1}\left(1+f\mu ^2\right)^2P(k)L_l(\mu){\rm d}\mu ,
\end{eqnarray*}$$where Ll(x) is the Legendre polynomial of order l and P(k) is the template given in equation (10). By replacing equation (12) in equation (11), the analytic expressions for monopole (l = 0) and quadrupole (l = 2) are respectively (Xu et al. 2012):
(13)$$\begin{eqnarray*}
\xi _{\rm {model}}^{(0)}(s) = B_0\xi _0(\alpha s)+a_0^{(0)}+\frac{a_1^{(0)}}{s}+\frac{a_2^{(0)}}{s^2} ,
\end{eqnarray*}$$(14)$$\begin{eqnarray*}
\xi _{\rm {model}}^{(2)}(s) = B_2\xi _2(\alpha s)+a_0^{(2)}+\frac{a_1^{(2)}}{s}+\frac{a_2^{(2)}}{s^2} ,
\end{eqnarray*}$$where α is the shift parameter, while $(a_1^{(i)},a_2^{(i)},a_3^{(i)})$ are linear nuisance parameters. | [
"Lesgourgues 2011"
] | [
"In the equation above, Plin(k) is the linear matter power spectrum computed using the Boltzmann code CLASS",
"assuming the Planck 2015 (Ade et al. 2016) fiducial cosmology."
] | [
"Uses",
"Uses"
] | [
[
614,
630
]
] | [
[
506,
612
],
[
633,
695
]
] |
2019ApJ...875...63M__Stern_et_al._2019_Instance_1 | The technique of weak lensing offers direct measurement of the total matter distribution of a galaxy cluster (baryonic and dark matter), and can thus provide an unbiased mass calibration. Weak lensing manifests itself as small but coherent distortions of distant galaxies that result from the gravitational deflection of light due to foreground structures (e.g., Kaiser 1992). Cluster weak lensing appears as a tangential shear of background galaxy shapes around a cluster. Numerous attempts to calibrate SZ masses have been made in the literature using ACT clusters (Miyatake et al. 2013; Jee et al. 2014; Battaglia et al. 2016), SPT clusters (McInnes et al. 2009; High et al. 2012; Schrabback et al. 2018; Stern et al. 2019; Dietrich et al. 2019), Planck clusters (von der Linden et al. 2014b; Hoekstra et al. 2015; Penna-Lima et al. 2017; Sereno et al. 2017; Medezinski et al. 2018a), Planck and SPT clusters (Gruen et al. 2014), and other massive cluster samples (Marrone et al. 2009, 2012; Hoekstra et al. 2012; Smith et al. 2016). The mass calibration is often parameterized as
1
where MSZ is the SZ mass and Mtrue is the true cluster mass, which for this paper we take to be the weak-lensing mass MWL. This ratio can be taken for individual clusters or for an ensemble average and these values will be consistent as long as the appropriate weights are used (Medezinski et al. 2018a). Recently, Planck Collaboration et al. (2016d) reported a disagreement between 1−b obtained by weak-lensing calibrations of Planck SZ cluster masses (e.g., von der Linden et al. 2014b; Hoekstra et al. 2015) and that inferred from reconciling the Planck primary CMB parameters with the Planck SZ cluster counts. This disagreement is not statistically significant (∼2σ) and will decrease after accounting for additional bias corrections, like Eddington bias (Battaglia et al. 2016) and new optical depth measurements (Planck Collaboration et al. 2016e). However, if such a disagreement persists as the precision of cluster measurements improves, then it could reveal the need for extensions to the standard cosmological model (Planck Collaboration et al. 2016c), like a non-minimal sum of neutrino masses (e.g., Wang et al. 2005; Shimon et al. 2011; Carbone et al. 2012; Mak & Pierpaoli 2013; Louis & Alonso 2017; Madhavacheril et al. 2017), or illuminate additional systematic effects in cluster abundance measurements. | [
"Stern et al. 2019"
] | [
"Numerous attempts to calibrate SZ masses have been made in the literature using",
"SPT clusters"
] | [
"Background",
"Background"
] | [
[
708,
725
]
] | [
[
474,
553
],
[
631,
643
]
] |
2019AandA...625A.148D__Li_et_al._2011_Instance_1 | With a stellar mass of 5 × 1010 M⊙ (Viaene et al. 2014), Andromeda belongs to the transition regime between the active blue-sequence galaxies and passive red-sequence galaxies (e.g. Bower et al. 2017; Baldry et al. 2006), which happens around the stellar mass of 3 × 1010 M⊙ (e.g. Kauffmann et al. 2003). This galaxy is a prototype galaxy from the Local Group where the star formation has been quenched in the central part. Andromeda hosts both very little gas and very little star formation, while the black hole is basically quiet and has some murmurs (Li et al. 2011). In a previous study about M 31 nucleus, Melchior & Combes (2017) have shown that there is no gas within the sphere of influence of the black hole. Indeed, the gas has been exhausted. Most scenarios of the past of evolution of Andromeda reproduce the large scale distribution and show evidence of a past activity rich in collisions (Ibata et al. 2001, 2014; Thilker et al. 2004; Gordon et al. 2006; McConnachie et al. 2009; Miki et al. 2016; Hammer et al. 2018). However, the exact mechanism quenching the activity in the central kiloparsec is still unknown (Tenjes et al. 2017). Block et al. (2006) proposed a frontal collision with M 32, which could account for the two ring structures observed in the dust distribution. Melchior & Combes (2011, 2016) showed the presence of gas along the minor axis and support the scenario of the superimposition of an inner 1 kpc ring with an inner disc. Melchior & Combes (2013) estimated a minimum total mass of 4.2 × 104 M⊙ of molecular gas within a (projected) distance to the black hole of 100 pc. This is several orders of magnitude smaller than the molecular gas present in the central molecular zone of the Milky Way (Pierce-Price et al. 2000; Molinari et al. 2011). In the Galaxy, while large amounts of dense gas are present in the central region, Kruijssen et al. (2014) discussed the different processes that combine to inhibit star formation, which was observed to be a factor ten times weaker than expected (e.g. Leroy et al. 2008). | [
"Li et al. 2011"
] | [
"Andromeda hosts both very little gas and very little star formation, while the black hole is basically quiet and has some murmurs"
] | [
"Background"
] | [
[
555,
569
]
] | [
[
424,
553
]
] |
2021MNRAS.502..915C__Cisneros-Parra_1970_Instance_1 | Under the Applegate model, the change in orbital period is directly related to the change in the companion star’s gravitational quadrupole moment Q (Applegate & Patterson 1987),
(8)$$\begin{eqnarray*}
\frac{\Delta P_{\rm orb}}{P_{\rm orb}} = -9\frac{\Delta Q}{M_{\rm c} A^2},
\end{eqnarray*}$$where A = x(1 + q)/sin i is the orbital separation. For comparison, the total quadrupole moment induced by the spin of the companion star and the tidal distortion in the pulsar’s gravitational field is (Voisin, Breton & Summers 2020a)
(9)$$\begin{eqnarray*}
\frac{Q}{M_{\rm c} A^2} = -\frac{2}{9} k_2 \left(\frac{R_{\rm c}}{A}\right)^5 \left(4 q + 1\right),
\end{eqnarray*}$$where Rc is the radius of the companion star and k2 is the apsidal motion constant, a parameter describing the deformability of the companion star (Sterne 1939). For solar-type stars k2 ∼ 0.035 (Ogilvie 2014), while if we assume that redback companions are akin to the companions in CV systems whose outer envelopes have also been stripped through accretion, then we may expect a smaller value k2 ∼ 10−3 (Cisneros-Parra 1970). For J2039, the hyperparameter $h = 3.9^{+2.2}_{-1.2}$ s corresponds to the typical fractional amplitude for the variations in orbital phase. Taking the simpler squared exponential covariance function of equation (4) corresponding to n → ∞, then the deviations in orbital period have covariance function,
(10)$$\begin{eqnarray*}
K_{\Delta P_{\rm orb}/P_{\rm orb}}(t_1,t_2) &=& \frac{\partial ^2 K}{\partial t_1 \partial t_2} \nonumber\\
&=& \frac{h^2}{l^2} \exp \left(\!-\frac{(t_1 - t_2)^2}{2\ell ^2}\!\right) \left(\!1 - \frac{(t_1 - t_2)^2}{\ell ^4}\!\right).
\end{eqnarray*}$$The typical (fractional) amplitude of the orbital period variations is therefore ΔPorb/Porb ∼ h/ℓ = (3 ± 1) × 10−7, corresponding to $\Delta Q / Q \sim 3\times 10^{-5} k_2^{-1}$. The time-varying component to the gravitational quadrupole moment is therefore required to be of order a few per cent of the total expected quadrupole moment at most to explain the observed orbital period variations. From this, it seems plausible that the observed period variations can be powered by quadrupole moment changes, without requiring that a large fraction of the star be involved in the process. The required fractional quadrupole moment changes are very similar to those recently calculated for the companion to the black widow PSR J2051–0827 by Voisin et al. (2020b), despite the large difference in their masses. | [
"Cisneros-Parra 1970"
] | [
"while if we assume that redback companions are akin to the companions in CV systems whose outer envelopes have also been stripped through accretion, then we may expect a smaller value k2 ∼ 10−3"
] | [
"Uses"
] | [
[
1077,
1096
]
] | [
[
882,
1075
]
] |
2018MNRAS.478...69A__Borucki_2016_Instance_1 | The complexity of non-adiabatic pulsations and their coupling to the convection has posed many problems since the field’s inception and still does. The main problem lies in our, so far, limited understanding of the interaction between convection and pulsations. However, several important steps forward have already been taken, and several recent reviews on the topic exist (see for example Houdek & Dupret 2015; Samadi, Belkacem & Sonoi 2015). The case of solar pulsational stability has been studied in detail both theoretically (Balmforth 1992) and observationally (Chaplin et al. 1997; Komm, Howe & Hill 2000), while the space missions CoRoT (Baglin et al. 2006) and Kepler (Borucki et al. 2010; Borucki 2016) have provided high-quality seismic data for stars of different flavours against which we can test models and further our understanding of stellar pulsations. Appourchaux et al. (2014) analysed oscillation mode linewidths for a number of Kepler main-sequence solar-like stars and found interesting relationships between linewidths, frequencies, and effective temperatures. Using CoRoT observations Samadi et al. (2012) showed that non-adiabatic effects are present and non-negligible in red giant stars. Houdek & Gough (2002) modelled damping rates and velocity amplitudes of the red giant ξ Hydrae, while Dupret et al. (2009) computed theoretical amplitudes, lifetimes, and heights in the frequency power spectrum of oscillation modes at different stages of red giant evolution, including the phase of core helium burning, and Grosjean et al. (2014) computed synthetic power spectra for mixed modes in red giants. Belkacem et al. (2012) were able to reproduce observed Γ versus Teff across the HR-diagram including both main-sequence and red giant stars. However, calculations of frequency-dependent damping rates for red giant stars have so far not been able to survive comparisons with observations. Handberg et al. (2017), hereafter referred to as H17, obtained precise frequencies and linewidths for a sample of red giants in NGC 6819 by means of extensive, careful peakbagging. Here, we compute frequency-dependent damping rates for a selection of red giant branch (RGB) stars in the H17 sample. This is done via a non-adiabatic stability calculation (Houdek et al. 1999) for which we obtain the convective fluxes from a non-local, time-dependent convection model (Gough 1977a,b) partly calibrated through 3D convection simulations (Trampedach et al. 2013). | [
"Borucki 2016"
] | [
"The case of solar pulsational stability has been studied in detail",
"while the space missions",
"and Kepler",
"have provided high-quality seismic data for stars of different flavours against which we can test models and further our understanding of stellar pulsations."
] | [
"Background",
"Background",
"Background",
"Background"
] | [
[
700,
712
]
] | [
[
445,
511
],
[
615,
639
],
[
667,
677
],
[
714,
871
]
] |
2020AandA...635A.121M__Stolker_et_al._2016_Instance_1 | As scattered light imaging is sensitive to the stellar irradiation, it allows one to search for misalignments between various disk regions. While studying the morphology of the innermost disk region is challenging due to its very small radial extent, often marginally resolvable by optical interferometry (Lazareff et al. 2017), scattered light imaging of the outer disk can indirectly reveal the presence of a misaligned inner disk. In this scenario, depending on the misalignment angle, the outer disk image will show narrow shadow lanes (e.g., Pinilla et al. 2015; Stolker et al. 2016; Benisty et al. 2017; Casassus et al. 2018), broad extended shadows (Benisty et al. 2018) or low-amplitude azimuthal variations (Debes et al. 2017; Poteet et al. 2018). In some cases, studies of the CO line kinematics support a misalignment between inner and outer disk regions (Loomis et al. 2017; Pérez et al. 2018). The exact origin of such a misalignment is still unclear. In the case of T Tauri stars, if the stellar magnetic field is inclined, it can warp the innermost edge of the disk, which would then rotate at the stellar period (AA Tau; Bouvier et al. 2007). Alternatively, inner and outer disk regions can have different orientations if the primordial envelope had a different angular momentum vector orientation at the time of the inner/outer disk formation (Bate 2018). Other scenarios involve the presence of a massive companion/planet that is inclined with respect to the disk. If the companion is massive enough, the disk can break into two separate inner and outer disk regions, that can then precess differently and result in a significant misalignment between each other (e.g., Nixon et al. 2012; Facchini et al. 2013; Nealon et al. 2018; Zhu 2019). A clear example of such a scenario is the disk around HD 142527, in which an M-star companion was detected (Biller et al. 2012), likely on an inclined and eccentric orbit (Lacour et al. 2016; Claudi et al. 2019). Dedicated hydrodynamical simulations successfully reproduce most of the observed features in this disk (eccentric cavity, spiral arms, misaligned inner disk and shadows; Price et al. 2018). | [
"Stolker et al. 2016"
] | [
"In this scenario, depending on the misalignment angle, the outer disk image will show narrow shadow lanes (e.g.,"
] | [
"Background"
] | [
[
568,
587
]
] | [
[
434,
546
]
] |
2020ApJ...897...73M__Dugair_et_al._2013_Instance_1 | Many Be-binary systems were observed during their outbursts, which offered interesting results (Bildsten et al. 1997; Reig 2011). Bright X-ray outbursts are observed in Be binaries, most likely during the periastron passage of its neutron star through the circumstellar disk of its companion. Depending on the amount of matter released from its companion and the geometry of the binary system, rare as well as regular outbursts are observed during its binary orbit (Okazaki & Negueruela 2001; Okazaki et al. 2002; Okazaki 2016). The pulse characteristics of some of these, such as EXO 2030+375 (Parmar et al. 1989), Cepheus X-4 (Mukerjee et al. 2000), and XTE J1946+274 (Paul et al. 2001), were studied in detail during their outburst activities. Studies on pulse characteristics offer information on the pulsar geometry and the mechanism underlying its emitted pulse profile. The shape of the emitted pulse depends on modes of accretion inflows, source luminosity, geometry of accretion column, and the configuration of its magnetic field with respect to an observer’s line of sight (Parmar et al. 1989). Therefore, such studies offer understanding of pulsars in binary system and disk–magnetosphere interaction during the process of mass accretion, which affects its emitted radiation. Quasi-periodic oscillations (QPOs) have been detected from many Be binaries, such as A0535+262 (Finger et al. 1996; Finger 1998), EXO 2030+375 (Angelini et al. 1989), 4U 0115+63 (Soong & Swank 1989; Heindl et al. 1999; Dugair et al. 2013), and V0032+53 (Qu et al. 2005). Studies of QPOs offer rich information about the accretion torque onto the neutron star, thermodynamic properties of the inner accretion disk, and electrodynamics of the disk–magnetosphere interaction of the neutron star. Details on sources with observed QPOs, their frequencies, and other features along with pulsar spin frequencies, etc. have been given in tabular form by Devasia et al. (2011), Ghosh (1998), and Mukerjee et al. (2001). Some of these transient Be-binary pulsars such as A0535+26 (50 mHz, 9.7 mHz), 1A 1118–61 (92 mHz, 2.5 mHz), XTE J1858+034 (110 mHz, 4.53 mHz), EXO 2030+375 (200 mHz, 24 mHz), SWIFT J1626.6–5156 (1000 mHz, 65 mHz), XTE J0111.2–7317 (1270 mHz, 32 mHz), as well as a persistent Be binary, X Per (54 mHz, 1.2 mHz), and an OB-type binary, 4U 1907+09 (69 mHz, 2.27 mHz), showed higher QPO frequency compared to their respective spin frequency as mentioned in order inside parentheses (Devasia et al. 2011). These cover an interestingly wide range of QPO frequencies between 50 and 1270 mHz for these pulsars. Studies of cyclotron absorption features, if present in the spectrum, enable us to determine the strength of the surface magnetic field of the neutron star and offer insight into the line-producing region and the structure of the accretion column and its geometry (Staubert et al. 2019). Cyclotron absorption features thus have provided an important diagnostic probe for detailed studies of neutron star binaries since their discovery in the spectrum of Her X-1 (Truemper et al. 1978). There are several reports on the detection of cyclotron absorption features in the spectrum of many Be binaries, starting at a lower energy, from ∼10 keV (Jun et al. 2012; DeCesar et al. 2013), to a higher energy, at ∼100 keV (La Barbera et al. 2001). A detailed compilation of such sources and studies is given in Staubert et al. (2019) and Maitra (2016). It has been observed in detailed studies that some sources show a wide variation in their cyclotron line energy with respect to their pulse phase and source luminosity, and time, such as Vela X-1, Cen X-3, and Her X-1 (Staubert et al. 2019). These interesting properties help in understanding the nature of these sources and also offer insight into their underlying physical properties governing such changes. | [
"Dugair et al. 2013"
] | [
"Quasi-periodic oscillations (QPOs) have been detected from many Be binaries, such as",
"4U 0115+63"
] | [
"Background",
"Background"
] | [
[
1507,
1525
]
] | [
[
1288,
1372
],
[
1455,
1465
]
] |
2021ApJ...921...25C__Way_et_al._2017_Instance_1 | Only a few GCM studies have previously considered isolated examples of higher-order spin–orbit resonance effects on climate (Wordsworth et al. 2010; Yang et al. 2013, 2020; Turbet et al. 2016; Boutle et al. 2017; Del Genio et al. 2019b). To our knowledge, no previous work has incorporated geothermal heating into a 3D GCM in the context of evaluating IHZ limits. Haqq-Misra & Kopparapu (2014) did report the impact of a 2 W m−2 surface heating in a highly idealized GCM for a synchronous rotation planet, while Haqq-Misra & Heller (2018) conducted idealized GCM simulations of tidally heated exomoons in synchronous rotation with the host planet. Yang et al. (2013) showed that at 2:1 and 6:1 resonances with a static/slab ocean (see Section 2.2.2 of Way et al. 2017), Bond albedo is lower than it is for synchronous rotation and decreases rather than increases with incident stellar flux, thus destabilizing the climate as the planet approaches the IHZ. Turbet et al. (2016) considered a 3:2 resonance state and static ocean for Proxima Centauri b, assuming zero eccentricity. Boutle et al. (2017) simulated the same planet in 3:2 resonance and 0.3 eccentricity; that study uses a thin static ocean surface, which produced a longitudinal double-eyeball pattern of surface liquid water roughly coincident with the maxima in stellar heating. Wang et al. (2014) found zonally symmetric temperatures for 3:2 and 5:2 resonances with a static ocean, but Dobrovolskis (2015) showed that this was the result of an incorrect spatial pattern of instellation. Del Genio et al. (2019b) performed the first dynamic ocean simulation of a planet in a higher-order resonance, showing that despite the double maximum in instellation at 3:2 resonance, the resulting climate has a tropical liquid waterbelt spanning the planet because of the ocean thermal inertia and heat transport. Yang et al. (2020) used a dynamic ocean and focused on the outer edge of the habitable zone by considering the effect of sea ice drift on snowball transitions for nine exoplanets, including a sampling of the 3:2 resonance, also with zero eccentricity. | [
"Way et al. 2017"
] | [
"Yang et al. (2013) showed that at 2:1 and 6:1 resonances with a static/slab ocean (see Section 2.2.2 of",
"), Bond albedo is lower than it is for synchronous rotation and decreases rather than increases with incident stellar flux, thus destabilizing the climate as the planet approaches the IHZ."
] | [
"Background",
"Background"
] | [
[
752,
767
]
] | [
[
648,
751
],
[
767,
955
]
] |
2021MNRAS.503..354G__Cantat-Gaudin_et_al._2020_Instance_1 | The spatial distribution of OB stars and associations, young long-period Cepheids and open clusters, star-forming regions, H ii regions, interstellar dust, and giant molecular and neutral gas clouds in the solar vicinity that have been in existence generally τ ≲ 108 yr is known to correlate with the location of the inner Sagittarius, the closest Orion, and outer Perseus spiral arm segments. (The distances for the vast majority of these spiral tracers have been determined in the literature with trigonometric or photometric methods.) The Sun is situated at the inner edge of the Orion arm (Levine et al. 2006; Hou & Han 2014; Nakanishi & Sofue 2016; Xu et al. 2018, 2021; Lallement et al. 2019; Reid et al. 2019; Skowron et al. 2019; Cantat-Gaudin et al. 2020; Fig. 2 above).3 These three spatial features nearby to the Sun appear to form part of the global spiral structure in the Galaxy. Contrary, the objects of older population with larger random velocities, for instance, main-sequence A–K stars or the oldest Cepheids and open clusters, do not currently follow the exact location of those arms (e.g. Cantat-Gaudin et al. 2020, fig. 8 therein; Griv et al. 2020, fig. 7 therein). The latter can be explained by the difference in rotation velocity between the spiral density waves and the objects. Investigating the velocity field of Xu et al.’s (2018) O and early B-type stars in the framework of the Lin–Shu density-wave proposal, we also found that the Sun lies within the Orion arm, at the inner edge of this spiral. The radial distance from the Sun to the centre of the Orion arm is ≈0.2 kpc in the direction of the Galactic anticentre, the centre of the Sagittarius arm is ≈1.8 kpc from the Sun in the direction of the GC, and the width of the arms is ≈0.5 kpc. The radial distance between the centres of the Orion and Sagittarius arms near the Sun is λrad ≈ 2 kpc (cf. Hou & Han 2014; Wu et al. 2014; Bovy et al. 2015). As for us, the nearest Orion spiral arm forms part of the dominant density-wave structure of the system. | [
"Cantat-Gaudin et al. 2020"
] | [
"The Sun is situated at the inner edge of the Orion arm"
] | [
"Background"
] | [
[
738,
763
]
] | [
[
538,
592
]
] |
2018MNRAS.476.4510P__Hobbs,_Edwards_&_Manchester_2006_Instance_1 | The modulation of an extra-solar signal can, if working in terms of signal phase, be expressed as a time modulation, e.g. for a phase evolution given by
(1)
\begin{eqnarray}
\phi (t) = \phi _0 + 2\pi f_0\left( t - t_0 + \Delta \tau (t) \right),
\end{eqnarray}
where t is the time of arrival of the signal at the observer, and ϕ0 and f0 are an initial phase and frequency at the epoch t0 in a reference frame at rest with respect to the source, the time modulation term is Δτ(t). Assuming, for now, that the source is at rest with respect to the SSB, the time modulation can be expressed as a combination of terms
(2)
\begin{eqnarray}
\Delta \tau = \Delta _{\rm R} + \Delta _{\rm E} - \Delta _{\rm S},
\end{eqnarray}
where ΔR (the Roemer delay) is a geometric retardation term, ΔE (the Einstein delay) is a relativistic frame transformation term taking into account relativistic time dilation, and ΔS (the Shapiro delay) is the delay due to passing through curved space–time. These terms are discussed in, for example, chapter 5 of Lyne & Graham-Smith (1998), while Edwards, Hobbs & Manchester (2006) provide more detailed discussion of time delays accounting for more effects with particular relevance to pulsar observations. Here, for each of the terms we use the sign conventions given in the source code for the pulsar timing software tempo21 (Hobbs, Edwards & Manchester 2006) and in the LALSuite gravitational wave software library functions (LIGO Scientific Collaboration 2017), rather than those used in the equation of Edwards et al. (2006).2 The Roemer delay is given by
(3)
\begin{eqnarray}
\Delta _{\rm R} = \frac{\boldsymbol {r}\cdot \hat{\boldsymbol {s}}}{c},
\end{eqnarray}
where $\boldsymbol {r}$ is a vector giving the position of the observer with respect to the SSB, and $\hat{\boldsymbol {s}}$ is a unit vector pointing from the observer to the source. The Einstein delay (see e.g. equations 9 and 10 of Edwards et al. 2006) converts to a new time coordinate frame, and depends on the choice of frame you want, i.e. Barycentric Coordinate Time (TCB), in which the effect of the presence of the Sun's gravitational potential is removed. The Shapiro delay (for which we will only consider the contribution from the Sun) is to first order given by
(4)
\begin{eqnarray}
\Delta _{\rm S} \equiv \Delta _{\rm S_{\odot }} = -\frac{2G {\rm M}_{\odot }}{c^3}\ln {\left({\boldsymbol {r}}_{\rm se}\cdot \hat{\boldsymbol {s}} + |\boldsymbol {r}_{\rm se}| \right)}
\end{eqnarray}
for waves passing around the Sun, where $\boldsymbol {r}_{\rm se} = \boldsymbol {r}_{{\oplus}} - \boldsymbol {r}_{\odot }$ is the vector from the centre of the Sun to the geocentre.3 Unlike electromagnetic waves, gravitational waves will pass through matter, and therefore a different term is required for a wave passing through the Sun, i.e. when $\left|\boldsymbol {r}_{\rm se}\right|^2 - \left(\boldsymbol {r}_{\rm se}\cdot \hat{\boldsymbol {s}}\right)^2 < R_{\odot }^2$ and $\boldsymbol {r}_{\rm se}\cdot \hat{\boldsymbol {s}} < 0$, giving
(5)
\begin{eqnarray}
\Delta _{\rm S_{\odot }} &=& -\frac{2G {\rm M}_{\odot }}{c^3}\Bigg [\ln {\left(\boldsymbol {r}_{\rm se}\cdot \hat{\boldsymbol {s}} + \sqrt{R_{\odot }^2 + \left(\boldsymbol {r}_{\rm se}\cdot \hat{\boldsymbol {s}}\right)^2} \right)} \nonumber \\
&&- \,2\left(1 - \frac{\sqrt{\left|\boldsymbol {r}_{\rm se}\right|^2 - \left(\boldsymbol {r}_{\rm se}\cdot \hat{\boldsymbol {s}}\right)^2}}{R_{\odot }}\right)\Bigg]\!,
\end{eqnarray}
where R⊙ is the radius of the Sun. | [
"Hobbs, Edwards & Manchester 2006"
] | [
"Here, for each of the terms we use the sign conventions given in the source code for the pulsar timing software tempo21"
] | [
"Uses"
] | [
[
1355,
1387
]
] | [
[
1234,
1353
]
] |
2022ApJ...937...76W__Verdini_et_al._2015_Instance_1 | Direct measures of cascade rates in turbulent systems often employ theoretical formulations related to Kolmogorov’s “4/5” law (Kolmogorov 1941b; Frisch 1995) and its variants, in which the inertial range cascade rate is related to a signed third-order structure function. This so-called exact law is derived from the fluid equations without appeal to dimensional analysis, assumptions about scaling behavior, or any ansatz concerning timescales; however, this law does require time stationarity, spatial homogeneity, the existence of an inertial range, and a finite dissipation rate. The original formulation for isotropic incompressible hydrodynamics has been extended to magnetohydrodynamics (MHD; Politano & Pouquet 1998a,1998b) and related models. The MHD version is frequently applied to in situ observations of plasma turbulence in the solar wind (Sorriso-Valvo et al. 2007; MacBride et al. 2008; Bandyopadhyay et al. 2020) to obtain cascade rates that inform theories of heating and acceleration of the solar wind (Osman et al. 2011), providing ground truth for related approximations in space physics (Vasquez et al. 2007). Frequently a major issue in these applications is the use of formulations derived assuming isotropy in turbulence that is actually anisotropic (Verdini et al. 2015), this being the typical case for solar wind and magnetosheath turbulence. Usually this potential inconsistency is disregarded in favor of extensive averaging, whenever possible. Another more practical limitation is the challenging requirement of a sufficient volume of data (Podesta et al. 2009), a kinematic and statistical issue further complicated by potential sensitivity to the tails of the probability distribution of the fluctuations (Dudok de Wit 2004). Taking these challenges into account, we note that the ability to extract cascade rates from observational data is of increasing importance due to the centrality of fundamental questions relating to heating and dissipation in space and astrophysical plasmas (e.g., Kiyani et al. 2015). Therefore, in the present study we revisit several related issues that are pertinent to the evaluation of third-order laws using single-point or multi-point measurements. We reexamine the issue of averaging by focusing on conditions for obtaining accurate results in both isotropic and anisotropic turbulence. The strategies we examine are implemented using data from three-dimensional (3D) MHD turbulence simulations. A motivation for this approach is that for such cases we have an unambiguous determination of the underlying turbulence symmetry as well as a straightforward method to quantify the absolute dissipation rate. | [
"Verdini et al. 2015"
] | [
"Frequently a major issue in these applications is the use of formulations derived assuming isotropy in turbulence that is actually anisotropic",
", this being the typical case for solar wind and magnetosheath turbulence."
] | [
"Compare/Contrast",
"Compare/Contrast"
] | [
[
1276,
1295
]
] | [
[
1132,
1274
],
[
1296,
1370
]
] |
2017MNRAS.470.3882T__Breen_et_al._2015_Instance_1 | A sample of 17 starless clump candidates has been selected from the Traficante et al. (2015a) as objects with Σ ≥ 0.05 g cm−2, mass ${{{M}}}\ge 300$ M⊙, bolometric luminosity over envelope mass ratio L/M ≤ 0.3 and very low dust temperature (T 15 K), indicative of very young stage of evolution (see Section 4), no (or faint) emission at 70 μm after visual inspection of each source and no counterparts in the MSX and WISE catalogues in correspondence of the Herschel dust column density peak. In addition, we checked for different masers emission associated with these clumps, as they are an indication of on-going star formation activity. We searched in the methanol multibeam survey (MMB; Green et al. 2009) and found no Class II CH3OH masers in the sources of our sample (Breen et al. 2015); from the MMB survey we also searched for hydroxyl (OH) masers at 6035 MHz (Avison et al. 2016), a transition often associated with high-mass star-forming regions, and also found no associations. We searched for CH3OH and OH masers using also the Arecibo surveys of Olmi et al. (2014), which is more sensitive than the MMB survey and it is targeted to identify weak masers associated with Hi-GAL high-mass objects. We found no CH3OH masers at distances less than 100 arcsec from the source centroids. We found one source, 34.131 + 0.075, with a weak OH maser (peak emission of 20 mJy, ≃3σ above the rms of the observations made with the Arecibo telescope, Olmi et al. 2014). Finally, we checked several surveys of water masers in the first quadrant (Merello et al., in preparation, and references therein) and found that only one source, 23.271 − 0.263, has a H2O maser association (at ≃3 arcsec from the source centroid), identified in the survey of Svoboda et al. (2016). Note that the source 18.787−0.286 is classified as starless in Traficante et al. (2015a) catalogue and has no maser associations, although it shows a 70 μm counterpart. The 70 μm source however is faint, with a peak emission of ≃60 mJy pixel−1 compared to a background of ≃130 mJy pixel−1. The clump follows all the other selection criteria and has very low dust temperature (T = 10.6 K, see Section 4), so we include it in the analysis. The clump embedded in the cloud SDC19.281−0.387, which follows the same criteria but it is not in the Traficante et al. (2015a) catalogue, was also included in our selection. The final sample of 18 clumps presented here contains some of the most massive 70 μm quiet clumps observed in the Galaxy. | [
"Breen et al. 2015"
] | [
"and found no Class II CH3OH masers in the sources of our sample"
] | [
"Uses"
] | [
[
776,
793
]
] | [
[
711,
774
]
] |
2022MNRAS.515.2633P__Blandford_&_Königl_1979_Instance_1 | Active galactic nuclei (AGN) have been discovered a century ago and still remain a hot topic of research. The theoretical predictions and the observational results suggest that the AGN have three main components namely, a central supermassive black hole (SMBH), an accretion disc around the SMBH, bipolar high relativistic jets of particles. The launching of the jets perpendicular to the accretion disc plane remains a long-standing puzzle to the astronomers. The GRMHD simulations have made some progress in understanding the launching of the jets and it is suggested to be the interplay between the accretion flow, magnetic field lines, and the SMBH (Mościbrodzka & Falcke 2013; Mościbrodzka et al. 2014). Simulations and theory together suggest that the magnetic field plays an important role in collimating the particles and giving them a jet like shape (Blandford & Königl 1979; Blandford & Payne 1982; Koide, Shibata & Kudoh 1998; Mościbrodzka, Falcke & Shiokawa 2016). The jets are believed to be highly relativistic and the process of particle acceleration inside the jets are still unclear. The AGNs are classified in various types under the AGN unification scheme developed by Urry & Padovani (1995). According to this scheme, the observer’s viewing angle with respect to jet axis divides the sources in various class such as quasars, seyfert galaxies, blazars, etc. In the case of blazars, the jet axis is within few degrees to the observer’s line of sight. Due to the direct view of the jet and because of the superluminal motion, blazars are among the brightest sources in the Universe. Blazars are classified in two main types namely flat-spectrum radio quasars (FSRQs) and the BL Lacertae (BL Lac) objects depending upon the presence or absence of optical emission lines in their spectra (Stickel et al. 1991; Weymann et al. 1991). Based on the location of the synchrotron peak, the BL Lac objects are further divided into three parts known as low BL Lac (LBL), intermediate BL Lac (IBL), and high BL Lac (HBL) by Padovani & Giommi (1995). | [
"Blandford & Königl 1979"
] | [
"Simulations and theory together suggest that the magnetic field plays an important role in collimating the particles and giving them a jet like shape"
] | [
"Background"
] | [
[
860,
883
]
] | [
[
709,
858
]
] |
2022MNRAS.516.5874W__Haasteren_2017_Instance_1 | An outlier is defined to be an anomalous event or observation that arises from a process that differs from the majority of the data generation. Outlier detection has always been an indispensable part of data analysis; contaminated data sets without proper outlier treatment can increase modelling uncertainties and produce misleading results. A common mitigation strategy is to model the data as a Gaussian mixture of inlier and outlier distributions with differing variance (Hogg, Bovy & Lang 2010; Vallisneri & van Haasteren 2017). For example, assume a model with an inlier data model, yi = μi + ϵi, where yi is the i-th observation, μi is the mean, and ϵi is Gaussian random noise with variance $\sigma _i^2$. We can then account for possible outlier contamination in the data collection by modelling such fluctuations with $\epsilon _\mathrm{out}\sim \mathcal {N}(0, \sigma _\mathrm{out}^{2})$, where our full data model now includes a latent outlier indicator zi for each observation, where zi = 1 for an outlier and 0 otherwise. This indicator is modelled with a certain prior outlier probability, θ, e.g. zi ∼ Bernoulli(θ). This data model is a mixture of two Gaussians with different mean and different variances, which can be expressed in the form
(1)$$\begin{eqnarray}
y_i = (1-z_i) \mu _i +(1-z_i) \epsilon _i + z_i \epsilon _\mathrm{out}.
\end{eqnarray}$$Incorporating the outlier indication parameter zi allows us to assess the possibility of an individual measurement being an outlier and to formulate the likelihood as a mixture of two Gaussians that respectively model the inlier and outlier distributions:
(2)$$\begin{eqnarray}
p \left(y_{i} \mid \mu _{i}, z_{i}, \sigma _{i}, \sigma _{\mathrm{out }}\right)=\left\lbrace \begin{array}{l{@}{\quad}l}\mathrm{e}^{-\left(y_{i}- \mu _{i}\right)^{2} /\big(2 \sigma _{i}^{2}\big)} / \sqrt{2 \mathrm{\pi} \sigma _{i}^{2}}, & \text{for } z_{i}=0 \\
\mathrm{e}^{-y_{i}^{2} /\big(2 \sigma _{\mathrm{out }}^{2}\big)} / \sqrt{2 \mathrm{\pi} \sigma _{\mathrm{out }}^{2}}, & \text{for } z_{i}=1 .\end{array}\right. \\
\end{eqnarray}$$We use this model for the toy sine wave example in Section 2.3. | [
"Vallisneri & van Haasteren 2017"
] | [
"A common mitigation strategy is to model the data as a Gaussian mixture of inlier and outlier distributions with differing variance"
] | [
"Uses"
] | [
[
500,
531
]
] | [
[
343,
474
]
] |
2020AandA...639A..88C__Chatzistergos_et_al._2019b_Instance_2 | To overcome these limitations, in our previous paper (Chatzistergos et al. 2018b, Paper I, hereafter) we introduced a novel approach to process the historical and modern Ca II K observations, to perform their photometric calibration, to compensate for the intensity centre-to-limb variation (CLV, hereafter), and to account for various artefacts. By using synthetic data, we also showed that our method can perform the photometric calibration and account for image artefacts with higher accuracy than other methods presented in the literature. More importantly, we showed that, as long as the archives are consistent with each other, for example, they are centred at the same wavelength and employing the same bandwidth for the observations, the method can be used to derive accurate information on the evolution of plage areas without the need of any adjustments in the processing of the various archives (Chatzistergos et al. 2019b, Paper II, hereafter). In Paper II, we applied our method to 85 972 images from 9 Ca II K archives to derive plage areas and produce the first composite of plage areas over the entire 20th century. In particular, we analysed the Ca II K archives from the Arcetri, Kodaikanal (8-bit digitisation), McMath-Hulbert, Meudon, Mitaka, Mt Wilson, Rome/PSPT, Schauinsland, and Wendelstein sites. Five out of the nine analysed archives were amongst the most studied and prominent ones, while the remaining archives were from less studied data sources. There are, however, many other Ca II K archives that are available and still remain largely unexplored. These archives harbour the potential to fill gaps in the available plage series as well as to address inconsistencies among the various archives and within individual archives (e.g. change in data quality, or in the measuring instrument with time). Moreover, since the work presented in Paper II, more data from various historical and modern archives became available in digital form. In particular, historical data that have been made available in the meantime include those from the latest 16-bit digitisation of the Kodaikanal archive, Catania, Coimbra, Kenwood, Kharkiv, Kyoto, Manila, Rome, Sacramento Peak, and Yerkes observatories, as well as additional data from the Meudon and Mt Wilson archives. In this light, here we present results from the most comprehensive analysis to date of historical and modern Ca II K observations taken between 1892 and 2019 from 43 different datasets for the purposes of producing a composite plage area series. | [
"Paper II"
] | [
"In",
", we applied our method to 85 972 images from 9 Ca II K archives to derive plage areas and produce the first composite of plage areas over the entire 20th century. In particular, we analysed the Ca II K archives from the Arcetri, Kodaikanal (8-bit digitisation), McMath-Hulbert, Meudon, Mitaka, Mt Wilson, Rome/PSPT, Schauinsland, and Wendelstein sites. Five out of the nine analysed archives were amongst the most studied and prominent ones, while the remaining archives were from less studied data sources."
] | [
"Background",
"Background"
] | [
[
960,
968
]
] | [
[
957,
959
],
[
968,
1476
]
] |
2018AandA...616A..96R__Haardt_&_Madau_(2012)_Instance_1 | As expected, the final luminosity (LV) of our model dwarfs strongly correlates with the shape of their formation histories. We divide our models into three categories dependent on their LV range. In the following, we will refer to them as sustained, extended and quenched. A few representative cases of each of these three categories are shown in Fig. 9. The strength of the UV-background heating is indicated by the dotted black curve. It represents the hydrogen photo-heating rate due to the UV-background photons following the model of Haardt & Madau (2012).
(a)LV > 108 L⊙, sustained: the star formation rate of those massive and luminous dwarfs increases over 1 to 2 Gyr. This period is followed by a rather constant SFR plateau. These systems are massive enough to resist the UV-background heating and, once formed, to form stars continuously. This sustained star formation activity that lasts up to z = 0 results from the self-regulation between stellar feedback and gas cooling (Revaz et al. 2009; Revaz & Jablonka 2012).
(b)106 L⊙ LV 108 L⊙, extended: in this luminosity range, the star formation is clearly affected by the UV-background. After a rapid increase, the star formation activity is damped owing to the increase of the strength of the UV-heating. However, at the exception of the h070 halo which is definitively quenched after 6.5 Gyr, the potential well of those dwarfs is sufficiently deep to avoid a complete quenching. The star formation activity extends to z = 0, however, at a much lower rate than the original one.
(c)LV 106 L⊙, quenched: the potential well of those galaxies is so shallow that the gas heated by the UV - photons escape the systems. Star formation is generally rapidly quenched after 2 or 3 Gyr. Only halo h064 shows signs of activity up to 4 Gyr. Those galaxies may be considered as true fossils of the re-ionization in the nomenclature of Ricotti & Gnedin (2005). They are all faint objects with only old stellar populations.
| [
"Haardt & Madau (2012)"
] | [
"The strength of the UV-background heating is indicated by the dotted black curve. It represents the hydrogen photo-heating rate due to the UV-background photons following the model of"
] | [
"Uses"
] | [
[
539,
560
]
] | [
[
355,
538
]
] |
2020AandA...638A..16T__Barnes_(2017)_Instance_2 | Figure 12 shows the results of our tidal evolution calculations. The left panel of Fig. 12 shows the planetary rotational evolution of GJ 1148 b due to star–planet tides. After ~850 Myr, GJ 1148 b reaches a rotation period that is 2∕3 of the orbital period, and remains there with Prot = 27.5 d. During the integration the planetary semi-major axis and eccentricity are mostly unaffected. An asymptotic rotation period that is shorter than synchronous and 2/3 of the orbital period is expected for eb ≳0.24 in the constant Q tidal model (Goldreich & Peale 1966; Cheng et al. 2014). The time for GJ 1148 b to reach asymptotic rotation is inversely proportional to the initial Prot, as long as the initial Prot is much less than 27.5 d, and it depends on the other parameters of GJ 1148 b according to Eq. (3) of Barnes (2017) and Eq. (15) of Cheng et al. (2014). The rotational period of GJ 1148 b is thus very likely much longer than the orbital periods of the hypothetical exomoons, which could be dynamically stable only with orbital periods between 0.7 and 2 d. The right panel of Fig. 12 shows that the longer rotational period of GJ 1148 b (Prot = 27.5 d) leadsto strong orbital decay of the stable exomoon orbits due to tidal interactions with the planet. An exomoon eventually reaches the Roche limit where it is tidally disrupted by the gas giant. Not even one hypothetical “stable” exomoon in the context of Sect. 5.3.1 had survived this test. The maximum time a Mars-like exomoon could survive is ~55 M yr, while for Titan-like moons the maximum survival time is longer, ~255 M yr. The latter is longer by roughly the mass ratio of Mars to Titan, which can be understood from Eq. (2) of Barnes (2017) and Eq. (16) of Cheng et al. (2014). These timescales are optimistic since the orbital decay would start before the planet reaches the asymptotic spin state. In both cases the survival times are much shorter than the age of the system. Therefore, given the relatively fast orbital decay in the small stable region around the planet, we conclude that exomoons around GJ 1148 b are unlikely to exist. | [
"Barnes (2017)"
] | [
"The latter is longer by roughly the mass ratio of Mars to Titan, which can be understood from Eq. (2) of"
] | [
"Uses"
] | [
[
1697,
1710
]
] | [
[
1592,
1696
]
] |
2015MNRAS.454.2691M__Leitherer_et_al._1999_Instance_1 | In order for simulations to play a role in improving our understanding of the formation and dynamics of the CGM, particularly given the complex, multiphase picture emerging from the latest observations (Tumlinson et al. 2011; Werk et al. 2014), the level of detail and sophistication in stellar feedback models must improve. In this work, we analyse the outflowing (and infalling) gas seen in the galaxies and CGM of the Feedback in Realistic Environments (FIRE) simulations,1 first presented in Hopkins et al. (2014). Unlike the subgrid recipes which involve kinetically prescribed decoupled winds and cooling-suppressed blastwaves, the FIRE simulations solve the ‘overcooling’ problem by explicitly modelling the radiation pressure, stellar winds, and ionizing feedback from young stars as taken directly from the population synthesis code starburst99 (Leitherer et al. 1999). These ‘early feedback’ mechanisms act before SNe, heating and stirring the surrounding ISM which is necessary to match conditions in star-forming regions such as Carina (Harper-Clark & Murray 2009) and 30 Dor (Lopez et al. 2011; Pellegrini, Baldwin & Ferland 2011). SNe are implemented by taking into account their energy and momentum input. When the cooling radius of SNe is resolved, SN energy injected is free to expand and generate momentum in the ISM before too much energy is radiated away. When this scale is poorly resolved, momentum accumulation from SN remnant evolution below the resolution scale is added to the surrounding gas. This model is physically realistic when it is applied on the scale of giant molecular clouds, meaning that a resolution of several to tens of parsecs is required. The physical feedback implementation in FIRE successfully regulates mass accumulation in galaxies and provides a physical explanation for the inefficiency of star formation in galactic discs (Kennicutt 1983, 1998; Genzel et al. 2010). We stress that we allow hydrodynamical interactions and cooling of all gas at all times, unlike in typical subgrid models. This is critical to make meaningful predictions for the phase structure of circumgalactic gas. | [
"Leitherer et al. 1999"
] | [
"Unlike the subgrid recipes which involve kinetically prescribed decoupled winds and cooling-suppressed blastwaves, the FIRE simulations solve the ‘overcooling’ problem by explicitly modelling the radiation pressure, stellar winds, and ionizing feedback from young stars as taken directly from the population synthesis code starburst99"
] | [
"Uses"
] | [
[
855,
876
]
] | [
[
519,
853
]
] |
2021AandA...653A..36M__Goulding_&_Alexander_(2009)_Instance_4 | The SFG sample was constructed using the Great Observatories All-Sky LIRG Survey (GOALS sample, Armus et al. 2009), from which we extracted 158 galaxies, with data from Inami et al. (2013), who report the fine-structure lines at high resolution in the 10 − 36 μm interval, and Stierwalt et al. (2014), who include the detections of the H2 molecular lines and the PAH features at low spectral resolution. For those galaxies in the GOALS sample that have a single IRAS counterpart, but more than one source detected in the emission lines, we have added together the line or feature fluxes of all components, to consistently associate the correct line or feature emission to the total IR luminosity computed from the IRAS fluxes. To also cover lower luminosity galaxies, as the GOALS sample only includes luminous IR galaxies (LIRGs) and ultra-luminous IR galaxies (ULIRGs), we included 38 galaxies from Bernard-Salas et al. (2009) and Goulding & Alexander (2009), to reach the total sample of 196 galaxies with IR line fluxes in the 5.5 − 35 μm interval in which an AGN component is not detected. For the Bernard-Salas et al. (2009), Goulding & Alexander (2009), and the GOALS samples, we excluded all the composite starburst-AGN objects identified as those with a detection of [NeV] either at 14.3 or 24.3 μm. It is worth noting that the original samples from Goulding & Alexander (2009) and Bernard-Salas et al. (2009) have spectra solely covering the central region of the galaxies. To estimate the global SFR, we corrected the published line fluxes of the Spitzer spectra by multiplying them by the ratio of the continuum reported in the IRAS point source catalogue to the continuum measured on the Spitzer spectra extracted from the CASSIS database (Lebouteiller et al. 2015). We assumed here that the line emission scales (at first order) with the IR brightness distribution. In particular, we considered the continuum at 12 μm for the [NeII]12.8 μm and [NeIII]15.6 μm lines, and the continuum at 25 μm for the [OIV]25.9 μm, [FeII]26 μm, [SIII]33.5 μm, and [SiII]34.8 μm lines. This correction was not needed for the AGN sample and the GOALS sample because of the greater average redshift of the galaxies in the 12MGS and GOALS samples. In particular, the 12MGS active galaxy sample has a mean redshift of 0.028 (Rush et al. 1993), while the GOALS sample has a mean redshift of 0.026. The galaxies presented by Bernard-Salas et al. (2009) have instead an average redshift of 0.0074, while the sample by Goulding & Alexander (2009) has an average redshift of 0.0044. For the other lines in the 10 − 36 μm interval, Goulding & Alexander (2009) did not report a detection, and we used the data presented in Bernard-Salas et al. (2009) for a total of 15 objects. Both Bernard-Salas et al. (2009) and Goulding & Alexander (2009) reported data from the high-resolution Spitzer-IRS spectra. Data in the 50 − 205 μm interval were taken from Díaz-Santos et al. (2017). For the GOALS sample, 20 starburst galaxies were taken from Fernández-Ontiveros et al. (2016), and 23 objects were taken from the ISO-LWS observations of Negishi et al. (2001). As a result, we obtained a total sample of 193 objects. Lastly, the PAH features’ fluxes were measured from the low-resolution Spitzer-IRS spectra by Brandl et al. (2006), including 12 objects from the sample of Bernard-Salas et al. (2009) and 179 objects from Stierwalt et al. (2014). | [
"Goulding & Alexander (2009)"
] | [
"The galaxies presented by Bernard-Salas et al. (2009) have instead an average redshift of 0.0074, while the sample by",
"has an average redshift of 0.0044."
] | [
"Compare/Contrast",
"Compare/Contrast"
] | [
[
2507,
2534
]
] | [
[
2389,
2506
],
[
2535,
2569
]
] |
2019MNRAS.486.1781R__Bonning_et_al._2012_Instance_1 | To check for any spectral variation in the optical/IR bands, we looked for variation in the V − J band colour against the V-band brightness. This colour variation was analysed for the epochs A, B, D, and E. During epochs A and B, the source showed a ‘redder when brighter’ (RWB) behaviour. During epoch E, a bluer when brighter behaviour was observed. During epoch D, we observed a complex behaviour. Upto a V-band brightness of around 15 mag, the source showed a ‘bluer when brighter’ behaviour, but for optical brightness fainter than 15.0 mag, a ‘redder when brighter’ behaviour was observed. The colour–magnitude diagrams for all the four epochs are shown in Fig. 10. The spectral variations shown by the source are thus complex. From studies on the optical–IR colour–magnitude diagram, it is known that FSRQs in general show an RWB trend, which is attributed to them having a luminous accretion disc (Gu et al. 2006; Bonning et al. 2012). The observed optical emission is a combination of thermal blue emission from the accretion disc and non-thermal red emission from the jet. As the source gets brighter, the non-thermal emission has a more dominant contribution to the total flux, giving rise to the RWB behaviour (Bonning et al. 2012). During epochs A and B, there is a trend of the object to become RWB, irrespective of its optical brightness. The optical flares dominated by synchrotron emission processes during A and B have corresponding γ-ray flares that are produced by EC processes. However, during epochs D and E, the colour variations were found to depend on the optical brightness. During the epochs when this complex spectral behaviour was noticed, the source showed an optical/IR flare with no or a weak corresponding flare in the γ-ray band. The source showed a much larger amplitude of variability in the optical/IR bands, while in the γ-ray band it was either faint or below the detection limit of Fermi. This definitely points to some complex physical changes and could be due to a combination of changes in the bulk Lorentz factor, electron energy density, and magnetic field as seen from our SED modelling of the multiband data. | [
"Bonning et al. 2012"
] | [
"From studies on the optical–IR colour–magnitude diagram, it is known that FSRQs in general show an RWB trend, which is attributed to them having a luminous accretion disc"
] | [
"Compare/Contrast"
] | [
[
922,
941
]
] | [
[
734,
904
]
] |
2020ApJ...898L..25K__Townsley_&_Bildsten_2003_Instance_1 | Once He core burning finishes the core contracts and hydrogen burning starts, the radius of the hot subdwarf expands beyond its Roche radius, and mass transfer starts at an orbital period close to the observed orbital period. Mass transfer will continue for ≈1 Myr at a rate exceeding 10−9 M⊙ yr−1 until hydrogen shell burning is finished and the star contracts to become a carbon–oxygen WD with a thick helium layer and a small residual layer of hydrogen. The high accretion rate will heat the accreting WD significantly (Townsley & Bildsten 2003). Models predict a Teff ≈ 50,000 K for accretion rates of 10−9 M⊙ yr−1 (Burdge et al. 2019) consistent with the high blackbody temperature of the accretor observed in ZTF J2055+4651. Accretion onto the WD companion at this rate will cause unstable hydrogen ignition after ≈10−4 M⊙ accumulates, leading to classical novae eruptions (Nomoto 1982; Nomoto et al. 2007; Wolf et al. 2013). This accretion rate predicts a recurrence time of order 105 yr for a total of approximately 10 novae. Our binary model suggests that this system is within the first ≈10% of the 1 Myr accretion phase. At the current state the orbit will shrink with
s s−1, which will be detectable after a few years of monitoring. The right panel of Figure 5 shows the evolution of the donor through this mass transfer phase. After accretion has ceased, the orbit of the system will continue to shrink due to the radiation of gravitational waves and the system will merge in ≈30 Myr. Our models predict that there is a substantial He layer of ≈0.05 M⊙ left in the former hot subdwarf and the total mass of the system is relatively high (Mtotal ≈ 1.1 M⊙). Recent models predict that such a system explodes as a subluminous thermonuclear supernova (Perets et al. 2019; Zenati et al. 2019). If the system avoids a thermonuclear supernova it will merge and could evolve into a rapidly rotating single high-mass carbon–oxygen WD (Saio 2008; Clayton 2012; Schwab 2019). | [
"Townsley & Bildsten 2003"
] | [
"Mass transfer will continue for ≈1 Myr at a rate exceeding 10−9 M⊙ yr−1 until hydrogen shell burning is finished and the star contracts to become a carbon–oxygen WD with a thick helium layer and a small residual layer of hydrogen. The high accretion rate will heat the accreting WD significantly"
] | [
"Background"
] | [
[
523,
547
]
] | [
[
226,
521
]
] |
2018ApJ...866L...1S__Pecharromán_et_al._1999_Instance_1 | It was found that the complex dielectric function from Pecharromán et al. (1999) for the sample obtained by heating bayerite at 1273 K, assuming a spheroid with depolarization parameters of (0.35, 0.003), produced an opacity with 11, 20, 28, and 32 μm features, so this component was included in the models. However, with only this component, the observed 20 μm features in the residual spectra were found to be wider than those in the models. By adding the opacity of the sample obtained by heating boehmite at 1173 K, the width of the 20 μm feature could be matched. This was done using the complex dielectric function for the sample obtained by heating boehmite at 1173 K from Pecharromán et al. (1999), assuming a spheroid with depolarization parameters of (0.35, 0.035). The complex dielectric functions of the samples obtained by heating bayerite and boehmite to various temperatures (Pecharromán et al. 1999) were derived by modeling the reflectance spectra of pellets obtained by pressing powders of these materials under great pressure. This method required Pecharromán et al. (1999) to assume an effective medium theory, such that a pellet is a mixture of one of their samples with a matrix of air. Pecharromán et al. (1999) noted that heating bayerite at 500°C eliminates the XRD pattern of bayerite, and they note that at 700°C, the infrared reflectance spectrum of the boehmite sample no longer shows OH− stretching bands. This must mean that the samples obtained from heating bayerite at 1273 K and from heating boehmite at 1173 K are no longer bayerite or boehmite, respectively. XRD performed by Pecharromán et al. (1999) of the sample of bayerite prepared at 1273 K suggests only θ-alumina was present, and their infrared and NMR spectroscopy confirms this. XRD of their sample obtained from heating boehmite to 1173 K (Pecharromán et al. 1999) suggests δ-alumina to be present, though some amounts of θ-alumina and α-alumina are present, as they deduce from XRD and infrared and NMR spectroscopy. | [
"Pecharromán et al. (1999)"
] | [
"It was found that the complex dielectric function from",
"for the sample obtained by heating bayerite at 1273 K, assuming a spheroid with depolarization parameters of (0.35, 0.003), produced an opacity with 11, 20, 28, and 32 μm features, so this component was included in the models."
] | [
"Uses",
"Uses"
] | [
[
55,
80
]
] | [
[
0,
54
],
[
81,
307
]
] |
2018MNRAS.479.3254V__Schneider_et_al._2018_Instance_1 | The lifetime of molecular clouds (MCs) remains an active research topic in the study of the interstellar medium and star formation, and most recent studies, both observational and theoretical, place this lifetime at a few times 107 yr for clouds in the 105–106M⊙ mass range (e.g. Blitz & Shu 1980; Kawamura et al. 2009; Zamora-Avilés, Vázquez-Semadeni & Colín 2012; Zamora-Avilés & Vázquez-Semadeni 2014; Lee, Miville-Deschênes & Murray 2016). In addition, several observational studies have suggested that the star formation rate (SFR) of the clouds appears to increase over their lifetimes. For example, studies of young clusters embedded in moderate-mass MCs (∼104M⊙) (e.g. Palla & Stahler 1999, 2000; Da Rio et al. 2010) have shown that their age histograms contain a large majority of young (1–2 Myr) objects, but also a tail of older (up to several Myr) ones suggesting an accelerating star formation activity, sometimes followed by a subsequent decline (see also Povich et al. 2016; Schneider et al. 2018). In addition, Kawamura et al. (2009) reported a clear evolutionary process over the lifetime of giant molecular clouds (GMCs; of masses ∼105–106M⊙) in the Large Magellanic Cloud, evidenced by the increasing number of massive stars across the sequence of GMC ‘classes’ proposed by those authors. Finally, on the basis of the large scatter in the observed star formation efficiency (SFE) in Milky Way GMCs, Lee et al. (2016) have concluded that the SFR in those clouds must also be time variable. Numerical simulations of MC formation and evolution also exhibit time varying, increasing SFRs during their early stages (e.g. Vázquez-Semadeni et al. 2007; Hartmann, Ballesteros-Paredes & Heitsch 2012). Also, in the presence of stellar feedback, at late times the SFRs reach a maximum and begin to decrease again (e.g. Vázquez-Semadeni et al. 2010; Colín, Vázquez-Semadeni & Gómez 2013). Vázquez-Semadeni, González-Samaniego & Colín (2017) have recently shown that the simulations of Colín et al. (2013) in fact produce stellar age histograms highly resemblant of the observed ones (Palla & Stahler 1999, 2000; Da Rio et al. 2010), and reproduce observed radial age gradients in clusters (Getman et al. 2014) as well as bottom-heavy stellar initial mass functions (IMFs) in scattered regions of massive star formation (Povich et al. 2016). | [
"Schneider et al. 2018"
] | [
"For example, studies of young clusters embedded in moderate-mass MCs (∼104M⊙)",
"have shown that their age histograms contain a large majority of young (1–2 Myr) objects, but also a tail of older (up to several Myr) ones suggesting an accelerating star formation activity, sometimes followed by a subsequent decline (see also"
] | [
"Background",
"Background"
] | [
[
990,
1011
]
] | [
[
593,
670
],
[
725,
969
]
] |
2019MNRAS.483..971V__al_2002_Instance_1 | We have also considered early radio emission from gamma-ray bursts (GRBs), which can have higher brightness temperatures at early times than blazars, owing to their ultrarelativistic velocities. They can therefore be brighter and easier to measure while still at small angular sizes, and are consequently observed to show interstellar scintillation in their first days at ${\sim } 5\, \mbox{GHz}$ (Granot & van der Horst 2014). Before deceleration to Lorentz factor Γ 1/θj (before the ‘jet break’ for a jet of opening half-angle θj), the projected source angular size θ at (earth) time T after explosion of a GRB at redshift $z$ is θ ∼ 2cT Γ/DM($z$), where DM($z$) = DA($z$)(1 + $z$) is the proper motion distance, and DA($z$) the angular diameter distance. The Blandford–McKee blast wave of the ultrarelativistic shock moving into a medium of uniform external density ρ0 has radius R ≃ 2cT Γ2/(1 + $z$) and explosion energy per unit solid angle E/Ω ≃ ρ0R3Γ2c2, which gives Γ ≃ 9(Eiso, 53/n0)1/8(T/[(1 + $z$)day])−3/8, where $E=10^{53}\, \mbox{erg}(\Omega /4\pi)E_{iso,53}$ and n0 is the external density in cm−3 (Granot et al 2002, cf.). At DM($z$ = 1) = 3.3 Gpc, $\theta = [0.2,\, 1,\, 4]\, \mu \mbox{as}$ at $T=[0.1,\, 1,\, 10]\, \mbox{d}$. Thus at $\lambda \lt 4\, \mbox{cm}$ (the transition wavelength below which Milky Way scintillation becomes unimportant), the GRB will be smaller than our fiducial scattering angle $\theta =20\,\mu \mbox{as}(\lambda /30\, \mbox{cm})^{11/5}\lt 0.25\,\mu \mbox{as}$ for less than 0.1 d. During this time, the scintillation time-scale will be set by the rapidly expanding source, expanding across the refractive screen at a projected speed of ∼ΓcDl/Ds. This is many times c for our cosmological lenses with Dl ∼ 0.5Ds (but less than $1\, \mbox{km s}^{-1}$ for Milky Way interstellar plasma at $D_l\sim 100\, \mbox{pc}$, so Milky Way scintillation time-scales are dominated by gas motions in the Milky Way, not the apparent source expansion). The refractive scintillation time-scale is thus the same as the time-scale for the source to expand to a size larger than the refractive scale – i.e. the source will have only about 1 speckle before becoming too large to display refractive scintillation. This would be difficult to convincingly detect in a GRB. | [
"Granot et al 2002"
] | [
"The Blandford–McKee blast wave of the ultrarelativistic shock moving into a medium of uniform external density ρ0 has radius R ≃ 2cT Γ2/(1 + $z$) and explosion energy per unit solid angle E/Ω ≃ ρ0R3Γ2c2, which gives Γ ≃ 9(Eiso, 53/n0)1/8(T/[(1 + $z$)day])−3/8, where $E=10^{53}\\, \\mbox{erg}(\\Omega /4\\pi)E_{iso,53}$ and n0 is the external density in cm−3"
] | [
"Uses"
] | [
[
1115,
1132
]
] | [
[
759,
1113
]
] |
2016MNRAS.463L..26B__Ackermann_et_al._2014_Instance_1 | We calculate the corresponding γ-ray spectrum constructed from the photons arriving at the observer within the observation time of MAGIC and plot it in the bottom panel of Fig. 5. Although it is possible to explain the very fast variability of the emission even with a moderate Lorentz factor of the blob, strong constraints are put by the level of the observed flux. If the emission region has a radius of Rb = 3 × 1014 cm, and is moving with a Lorentz factor of γb = 100, we require an energy density of ρE = 20 erg cm−3 (measured in the blob's frame of reference) to reproduce the flux observed by MAGIC and Fermi-LAT (see the bottom panel of Fig. 5). Note that such large values of the Lorentz factor of the emission region in the jet have been already postulated in terms of other models in order to explain extremely short flares observed in this source (Ackermann et al. 2014) or in the other sources, e.g. PKS 2155−304 (Aharonian et al. 2007). Such large Lorentz factors of the blob find also some observational support from the observations of the superluminal motion in PKS 1510−089 which represents similar type of blazar (Jorstad et al. 2005). We can estimate the power of the blob in the observer's reference frame on $L_{\rm blob} = \pi R_{\rm b}^2c\rho _E \gamma _{\rm b}^2\approx 1.7\times 10^{45}$ erg s−1. On the other hand, the Eddington luminosity of the black hole in PKS 1222+21, with the mass 6–8 × 108 M⊙, is LEdd = 1.3 × 1047M9 ≈ 8–10 × 1046 erg s−1. Therefore, the blob has to contain about ∼2 per cent of the Eddington power. This is quite demanding but seems not to be excluded, especially if Rb ≈ R⊥. Lower values of γb require a much higher energy density in the blob (e.g. ρE = 340 erg cm−3 for γb = 50 and Rb = 3 × 1014 cm). The strong dependence on the γb is a combined result of the transformation of the energy density to the reference frame of the observer and the beaming of the emission in a narrower cone. Note that a larger radius of the blob will lower the energy density constraint, e.g. for Rb = 1015 cm we obtain ρE = 4.9 erg cm−3 for γb = 100 and ρE = 80 erg cm−3 for γb = 50, at the assumption that there is no competing energy loss process of the electrons at such a large distance from the star. | [
"Ackermann et al. 2014"
] | [
"Note that such large values of the Lorentz factor of the emission region in the jet have been already postulated in terms of other models in order to explain extremely short flares observed in this source"
] | [
"Similarities"
] | [
[
861,
882
]
] | [
[
655,
859
]
] |
2015ApJ...799...55G__Klassen_et_al._2000_Instance_1 | While the angular extent of IP shocks can be directly investigated using multi-point in situ measurements, the size of coronal shocks can only be indirectly inferred via remote-sensing observations of the electromagnetic emissions associated with them. According to Nelson & Robinson (1975), the average angle subtended at the solar surface by fundamental metric type II radio emission sources is 43°. Aurass et al. (1994) found particular cases with larger, double type II source structures covering a separation angle beyond 90°. Type II radio sources often show non-radial propagation trajectories (see Mann et al. 2003, and references therein). Wave-like large-scale disturbances propagating over the solar disk in extreme ultraviolet observations (usually referred to as âEIT wavesâ or âEUV wavesâ) are in close empirical correlation with type II radio bursts (Klassen et al. 2000). Most EIT waves are accompanied by CMEs, and observations and MHD modeling suggest that they are driven by the lateral expansion of CMEs, while the ultimate nature of the phenomenon remains under debate and could consist of true waves, pseudo waves (e.g., reconnection fronts), or a combination of both (Patsourakos & Vourlidas 2012; Nitta et al. 2013b, and references therein). According to Patsourakos & Vourlidas (2012), EIT waves can reach distances up to 1.3 R (850 Mm) from the source. Single-case studies reported some EIT waves covering a whole solar hemisphere (Klassen et al. 2000; Kienreich et al. 2009; Thompson & Myers 2009). Connections between EIT waves and SEP events have been often suggested (e.g., Bothmer et al. 1997; Krucker et al. 1999), and recently Rouillard et al. (2012) hypothesized that the EIT wave can be used to track the expansion of a coronal shock responsible for particle acceleration. Other authors question the EIT wave acceleration scenario for SEPs, with many EIT waves being observed at well-connected positions having no associated SEP increase (Miteva et al. 2014). | [
"Klassen et al. 2000"
] | [
"Type II radio sources often show non-radial propagation trajectories (see Mann et al. 2003, and references therein). Wave-like large-scale disturbances propagating over the solar disk in extreme ultraviolet observations (usually referred to as âEIT wavesâ or âEUV wavesâ) are in close empirical correlation with type II radio bursts"
] | [
"Background"
] | [
[
876,
895
]
] | [
[
534,
874
]
] |
2015AandA...582A.104R__Stix_2002_Instance_1 | Thermal motions of atoms produce a Doppler broadening of spectral lines with a Gaussian profile. Other unresolved velocities of a random nature are usually described as a turbulence broadening with a Gaussian or Lorentzian profile (see Rutten 2003, for a detailed description). The instrumental broadening encompasses the broadening caused by the finite spectral resolution of the instrument and is commonly approximated by a Gaussian. When other line broadening mechanisms are negligible, the total line broadening is the convolution of the line broadening profiles for the thermal and turbulence motions as well as the instrumental profile (Sect. 10.5 in Böhm-Vitense 1989). In other words, the velocity equivalent of the observed line width, Wobs = c × Δλ/λ, at 1/e of the peak intensity results from instrumental, Doppler, and turbulence (non-thermal) broadenings by (1)\begin{equation} W_{\rm{obs}}^2 = \left(c\times \frac{\Delta\lambda}{\lambda}\right)^2 = W_{\rm{instrumental}}^2 + W_{\rm{Doppler}}^2 + W_{\rm{turbulence}}^2, \end{equation}Wobs2=c×Δλλ2=Winstrumental2+WDoppler2+Wturbulence2,assuming that all three line broadening components have a Gaussian profile (Eq. (4.17) of Stix 2002). The POLIS instrumental width is less than 2 km s-1 (Beck 2006; Rezaei 2008; Beck et al. 2013a), while that of the Echelle spectrograph is of the same order. Assuming a generic chromospheric temperature of 104 K, we estimate a turbulence velocity using Eq. (2), (2)\begin{equation} \label{eq:one} \Delta\lambda=\frac{\lambda}{c}\sqrt{2\,k_{\rm B}\,T/m+ W_{\rm{turbulence}}^2\,\,+\,\,W_{\rm{instrumental}}^2 }, \end{equation}Δλ=λc2 kB T/m+Wturbulence2 + Winstrumental2,where Δλ is the observed line width, m is mass of the calcium atom, c the speed of light, and kB is the Boltzmann constant (Tandberg-Hanssen 1960). Using the measured width of Ca ii H & IR lines of 1.0 and 0.7 Å, respectively (Sect. 4), we estimate a turbulence velocity of about 45 km s-1 for Ca ii H and 24 km s-1 for Ca ii IR lines (we also note that the H1 minima of the EB profile is about 1 Å wider than in the quiet Sun profile). The width of the emission peaks on either side of the Hα line (1 Å) amounts to a turbulence velocity of 15 km s-1. Attributing the line width to the temperature and the instrumental profiles (omitting the turbulence broadening), we get a temperature of about 5 × 105 K, which is too hot for chromospheric heights. An increased turbulence velocity as a function of height in the chromosphere is part of standard models, either in the quiet Sun or sunspots (Kneer & Mattig 1978; Vernazza et al. 1981; Lites & Skumanich 1982). Our measured values, however, are larger than the turbulence velocity in an average atmosphere. The estimated turbulence velocity changes from one profile to another, but the general result remains the same: the observed width of the emission peaks is far in excess of any instrumental or thermal Doppler profile and to the first order has to have a turbulent nature. The Doppler width of a calcium line at 1–2 × 104 K is only about 2–3 km s-1, far from the observed widths of >20 km s-1. | [
"Stix 2002"
] | [
"In other words, the velocity equivalent of the observed line width, Wobs = c × Δλ/λ, at 1/e of the peak intensity results from instrumental, Doppler, and turbulence (non-thermal) broadenings by (1)\\begin{equation} W_{\\rm{obs}}^2 = \\left(c\\times \\frac{\\Delta\\lambda}{\\lambda}\\right)^2 = W_{\\rm{instrumental}}^2 + W_{\\rm{Doppler}}^2 + W_{\\rm{turbulence}}^2, \\end{equation}Wobs2=c×Δλλ2=Winstrumental2+WDoppler2+Wturbulence2,assuming that all three line broadening components have a Gaussian profile (Eq. (4.17) of"
] | [
"Uses"
] | [
[
1190,
1199
]
] | [
[
678,
1188
]
] |
2017AandA...605A..20C__Lattanzi_et_al._(2015)_Instance_1 | As mentioned above, molecular oxygen was used to calibrate the magnetic field applied. A total of 155 Zeeman components (for the three transitions considered) was measured, with the magnetic field varied from B = 2.3 G (Itot = 0.2 Amp) to B = 113.5 G (Itot = 10 Amp). Figure 5 shows the Zeeman spectrum for the N,J = 3, 2 ← 1, 2 transition when a magnetic field of 5.7 G is applied. The fit was carried out with the program described in the previous section, with the spectroscopic parameters and g factors fixed at the values of Yu et al. (2012) and Christensen & Veseth (1978), Evenson & Mizushima (1972), respectively; the only free parameter was the correction factor to be applied to the theoretical magnetic field (see Eq. (1)). The fit reproduces in a satisfactory manner the measured Zeeman components, with a standard deviation of 73 kHz (the uncertainty for the measured frequencies was in most cases set to 70 kHz). Moving to SO, for the seven transitions considered, a total of 353 Zeeman components were measured, with the magnetic field varied from B = 5.7 Gauss (Itot = 0.5 Amp) to B = 124.8 Gauss (Itot = 11 Amp), and fitted as described above. In the fitting procedure the spectroscopic parameters (i.e., the rotational, centrifugal distortion, and fine structure constants) were kept fixed at the values derived by Lattanzi et al. (2015). The g factors resulting from the fit are given in Table 4 together with the best-estimated values discussed above, while the complete set of the measured Zeeman components is available in the Supplementary Material. Alternative fits were carried out: In the first fit, the three g factors, gs, gl, and gr, were fitted. In a second step, three different fits were carried out by fixing one of the three g factors and fitting the other two. In the last fit, only gs was determined. We note that in the first fit, based on the comparison with theory, the gs value is overestimated and the gl value is underestimated; the two terms therefore seem to be correlated. For this reason, we performed the additional fits described above. We note that in all cases, gr is determined with a limited accuracy, that is, with a relative uncertainty of ~20%. We also note that, if we fix gs at the best computed value, a gl value in good agreement with theory is obtained. However, by fixing gl at the best estimate, the resulting gs is still slightly overestimated. Simulations using values of gs in the 2.0020−2.0030 range show that the Zeeman splittings only change by a few tens of kHz, that is, in most cases within the typical uncertainty affecting the frequency measurements. The last comment concerns the standard deviation of the fits that, in all cases, is about 50 kHz. | [
"Lattanzi et al. (2015)"
] | [
"In the fitting procedure the spectroscopic parameters (i.e., the rotational, centrifugal distortion, and fine structure constants) were kept fixed at the values derived by"
] | [
"Uses"
] | [
[
1333,
1355
]
] | [
[
1161,
1332
]
] |
End of preview. Expand
in Dataset Viewer.
Function Of Citation in Astrophysics Literature (FOCAL): Dataset and Task
Can you explain why the authors made a given citation?
This dataset was created as a shared task for WIESP @ AACL-IJCNLP 2023.
Dataset Description
Datasets are in JSON Lines format (each line is a json dictionary).
Each entry consists of a dictionary with the following keys:
"Identifier": unique string to identify the entry"Paragraph": text string from an astrophysics paper"Citation Text": list of strings forming the citation (most often a single string, but sometimes the citation text is split up)"Citation Start End": list of integer pairs denoting where the citation starts and end in"Paragraph"(most often a single pair, sometimes the citation text is split up, if so follows the order in"Citation Text")"Functions Text": list of strings highlighting parts of the paragraph that explain the function of the citation"Functions Label": list of strings with the label for each text element in"Functions Text"(in same order)"Functions Start End": list of integer pairs denoting where the elements in"Functions Text"start and end in"Paragraph"(in same order)
start and end are defined by the character position in the "Paragraph" string.
Instructions for Workshop Participants:
How to load the data using the Huggingface library:
from datasets import load_dataset
dataset = load_dataset("adsabs/FOCAL")
How to load the data if you cloned the repository locally:
(assuming ./FOCAL-TRAINING.jsonl is in the current directory, change as needed)
- python (as list of dictionaries):
import json
with open("./FOCAL-TRAINING.jsonl", 'r') as f:
focal_training_from_json = [json.loads(l) for l in list(f)]
- into Huggingface (as a Huggingface Dataset):
from datasets import Dataset
focal_training_from_json = Dataset.from_json(path_or_paths="./FOCAL-TRAINING.jsonl")
File List
├── FOCAL-TRAINING.jsonl (2421 samples for training)
├── FOCAL-VALIDATION.jsonl (606 samples for validating your training methods)
├── FOCAL-TESTING.jsonl (821 samples for testing)
├── FOCAL-VALIDATION-NO-LABELS.jsonl (606 samples for validation without the labels. Used during the shared task of [WIESP-2023](https://ui.adsabs.harvard.edu/WIESP/2023/)
├── FOCAL-TESTING-NO-LABELS.jsonl (821 samples for testing without the labels. Used during the shared task of [WIESP-2023](https://ui.adsabs.harvard.edu/WIESP/2023/)
├── /scoring_scripts/score_focal_seqeval.py (scoring scripts used during the shared task of [WIESP-2023](https://ui.adsabs.harvard.edu/WIESP/2023/)
├── /scoring_scripts/score_focal_labels_only.py (scoring scripts used during the shared task of [WIESP-2023](https://ui.adsabs.harvard.edu/WIESP/2023/)
├── /data/*.parquet (files used when loading the dataset through Huggingface's API)
├── README.MD (this file)
└──
Maintainer: Felix Grezes (ORCID: 0000-0001-8714-7774)
Data annotator: Tom Allen (ORCID: 0000-0002-5532-4809)
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