adsabs/FOCAL huggingface dataset:
Many studies have been done to understand the dynamics and origin of such systems since the discovery of the first binary asteroid system, Dactyl orbiting around (243) Ida in 1993 (Chapman et al. 1995). Based on the structure of ‘rubble pile’ asteroids (a collection of gravitationally bound boulders with a distribution of size scales and very little tensile strength between them), a model for how they can disrupt due to close flybys of a planet was developed. However, close encounters with the planets proved not to be enough for creation of the current population of binary systems (Margot et al. 2002; Walsh & Richardson 2008). Another model for their formation is by increasing their spin rates due to incident and remitted solar photons, known as the Yarkovsky–O'Keefe–Radzievskii–Paddack (YORP) effect. The YORP effect on contact binary asteroids has been studied (Bottke et al. 2002; Merline et al. 2002; Scheeres 2002; Walsh & Richardson 2006). Using a model with an ellipsoid and a sphere in a planar case, Scheeres (2007) studied fission limits (spin limit to occur a fission) and the stability of that kind of system for different initial conditions. After that, the stability of a binary system was analysed using a two-ellipsoid model (Scheeres 2009). Pravec et al. (2010) made a complete study about formation of asteroid pairs through rotation fission. Jacobson & Scheeres (2011) studied the creation of binaries and other observed near-Earth asteroid (NEA) systems, including doubly synchronous binaries, high-e binaries, ternary systems and contact binaries. That study analysed the dynamics of a binary system just after rotational fission. Using a two-ellipsoid model taking into account mutual gravitational interactions and tidal dissipation, they analysed the dynamics for different mass ratios of the system under a planar assumption. The current work follows from these results, but looks at more likely, non-planar initial configurations. This extension is significant, as non-planar cases must take into account the complete rotational motion (rotation, precession and nutation) of each body. Our results are compared with the results obtained by Jacobson & Scheeres (2011).
Citation: Merline et al. 2002
Citation function: Background
In this paper, we use a legacy value data set covering the inner star-forming disc of NGC 300 taken with the VLT/MUSE instrument (Bacon et al. 2010), consisting of a contiguous 7 arcmin × 5 arcmin mosaic (∼4 kpc × 3 kpc) and covering the galaxy out to galactocentric radii of about 0.45R25 (with R25 ∼ 5.33 kpc being the optical radius; Paturel et al. 2003). NGC 300 is an ideal target to study stellar feedback: it is the closest (D ∼ 2 Mpc; Dalcanton et al. 2009), non-interacting, star-forming disc galaxy that can be mapped at the necessary spatial resolution [i.e. 1 arcsec, which corresponds to ∼10 pc, resolving individual star-forming regions and supernova remnants (SNRs)]. The large spatial coverage (to cover most of the star-forming disc) available not only in the optical with MUSE but throughout the electromagnetic spectrum (e.g. Helou et al. 2004; Westmeier, Braun & Koribalski 2011; Riener et al. 2018; Kruijssen et al. 2019; Schruba, Kruijssen & Leroy 2019) makes NGC 300 the ideal target for simultaneous resolved feedback, stellar population, and ISM studies. Closer galaxies like the Magellanic Clouds, M31, or M33 do not allow similar large-scale multiwavelength mapping due to their large angular sizes, while more distant galaxies (beyond a few Mpc) do not allow multiwavelength studies with similar spatial resolution across the optical, infrared, mm/sub-mm, and radio. NGC 300 perfectly bridges between ∼100 pc resolution IFU surveys of nearby galaxies like PHANGS, and upcoming (sub-) pc scale resolution IFU surveys of the Milky Way and the Magellanic Clouds like SDSS-V/LVM (Kollmeier et al. 2017). Further, NGC 300 offers a favourable inclination of ∼40° (Puche, Carignan & Bosma 1990), it is actively forming stars at a rate between ∼0.08 and ∼0.30 M⊙ yr−1 (Kang et al. 2016, and references therein), and has a well-studied population of ${\rm H\, \small {II}}$ regions (e.g. Deharveng et al. 1988; Bresolin et al. 2009; Faesi et al. 2014), planetary nebulae (PNe; e.g. Soffner et al. 1996; Peña et al. 2012; Stasińska et al. 2013), and SNRs (e.g. Blair & Long 1997; Millar, White & Filipovic 2012; Vučetić, Arbutina & Urošević 2015).
Citation: Schruba, Kruijssen & Leroy 2019
Citation function: Motivation; Motivation
Parameter  is likely different for each AGN and may depend on the accretion rate. We have 0.3 for Mrk 110 (see Fig.1). The lines parallel to the best-fitting line to Mrk 110 cannot connect two points of Mrk 493 or IRAS 04416 even considering the corresponding errors. Mrk 110, Mrk 493 and IRAS 04416 have $\dot{\mathscr{M}}_{f=1}=$ 5.89, 75.9 and 426.6 or $\dot{\mathscr{M}}_{\rm {f}}=$ 0.49, 1.04 and 7.27, respectively. Mrk 493 and IRAS 04416 have larger accretion rates than Mrk 110 and it is possible that  depends on the accretion rate, but the present data do not allow us to test this hypothesis. There is a strong positive correlation between f and $\dot{\mathscr{M}}_{f=1}$, $f=6.8(\pm 1.6)\dot{\mathscr{M}}_{f=1}^{0.4\pm 0.1}$ (see Fig.3), which is consistent with f being dominated by the radiation pressure. This correlation supports the explanation of $f=5.4 r_{\rm {BLR}}^{0.3}$ in Mrk 110 arising due to the radiation pressure from the accretion disc. Thus, the relation $f=6.8\dot{\mathscr{M}}_{f=1}^{0.4}$ reflects the physical essence of relations like $f=5.4 r_{\rm {BLR}}^{0.3}$. The radiation pressure will produce more obvious effects on the BLR clouds as  increases. As the radiation pressure vanishes,  vanishes. The larger values of f  816 make MRM increase for Mrk 110. In like manner, larger f values may exist in quasars. Quasar J0100+2802 at z6.30, the most luminous quasar known at z6, has MRM(f1)1.21010M and Lbol1.621048ergs1 (Wu et al. 2015). It has LEdd  1.5  1038M/M  1.8  1048 erg s1 for solar composition gas and Lbol/LEdd0.9. $\dot{\mathscr{M}}_{f=1}= L_{\rm {bol}}/L_{\rm {Edd}}/\eta$ (Du etal.2014), where  is the efficiency of converting rest-mass energy to radiation (Thorne1974) and in general,  is of the order of 0.1. Thus $\dot{\mathscr{M}}_{f=1}\sim 9$ and f16 for J0100+2802. As f16, MRM1.91011M and Lbol/LEdd0.06. The larger black hole mass further gives rise to the most significant challenge to the Eddington limit growth of black holes in the early Universe (Willott etal.2010; Volonteri2012). A high f value is suggested for PG 1247+267 by the ultraviolet RM of carbon lines (Trevese etal.2014). PG 1247+267 has L(1350)3.91047ergs1 and ionization stratification like low-luminosity AGNs. The broad H has a redward shift of 0.008 with respect to [Oiii] 5007 (McIntosh etal.1999b), and has vFWHM7460kms1 (McIntosh etal.1999a). If zg0.008, f  13, consistent with the high f value suggested in Trevese etal. (2014). Thus, the new method is capable of estimating f in quasars. For the Eddington ratio Lbol/LEdd(f)Lbol/fLEdd(f1)1, we have $\dot{\mathscr{M}}_{f=1}=1133$, f113 and $\dot{\mathscr{M}}_{f}= 10$ for 0.1. Then, we have Lbol/LEdd113 when assuming f1. That we do not often see sources with such (apparent) Eddington ratios may suggest that the Thomson cross-section typically used in the radiation pressure calculation underestimates the coupling between the radiation and the BLR gas. On considering the line-driven radiation pressure (Castor, Abbott  Klein1975), the radiation pressure due to the gas opacity will be 103 times that due to the electron scattering opacity (Ferland etal.2009).
Citation: Wu et al. 2015
Citation function: Uses
The results of this first exploratory work pave the way to a series of future investigations in which we will broaden the range of initial conditions and study their impact on the empirical parameters defined here. By changing the initial structural properties of the simulated clusters, we will compare the three parameters determined in stellar systems that, after one Hubble time of evolution, have reached different dynamical states. We will also include populations of primordial binaries, which are known to halt the core contraction earlier in the cluster evolution and at lower concentrations (see, e.g., Vesperini & Chernoff 1994; Trenti et al. 2007; Chatterjee et al. 2010). The main differences between the values of A
5, P
5, and S
2.5 in simulations with and without primordial binaries are expected during the advanced phases of the evolution, toward CC and post-CC, when the milder contraction of the clusters with primordial binaries might lead to a different and/or less extreme evolution of these parameters. The study presented here will also be further extended to explore the effects of different retention fractions of dark remnants (neutron stars and black holes; see, e.g., Alessandrini et al. 2016; Giersz et al. 2019; Kremer et al. 2020, 2021; Gieles et al. 2021, for some studies on the dynamical effects of dark remnants). Finally, a forthcoming paper will be dedicated to building nCRDs and determining the three parameters here defined in a sample of observed star clusters. This requires photometric observations (i) with a high enough angular resolution to resolve individual stars even in the innermost cluster regions, (ii) sampling each system at least out to 0.5 × r

h
, and (iii) deep enough to reach a few magnitudes below the MSTO. These requirements are achieved by most HST and adaptive-optics-assisted observations currently available for many GCs, thus making the determination of the three parameters from observations relatively straightforward, although particular care is needed to deal with typical observational difficulties such as photometric incompleteness, differential reddening, and Galactic field contamination. We will discuss the relation between these parameters and other dynamical indicators (in particular, the A
+ parameter measured from BSSs; see the Introduction), thus providing quantitative assessments of the operational ability of the three nCRD diagnostics to distinguish dynamically young GCs from systems in advanced states of dynamical evolution.
Citation: Chatterjee et al. 2010
Citation function: Uses
Citation: Giersz et al. 2019
Citation function: Future Work
Another way of obtaining information about the nucleosynthesis processes involved in producing carbon is to compare it with other elements that are characterised by a well-known source of production, as in the case of oxygen. In Fig. 5, we show the variation of [C/O] as a function of [Fe/H], which serves as a first-order approximation to the evolution with time. To calculate the [C/O] ratios, two oxygen abundance indicators are used independently. At subsolar metallicities, the abundance ratios with both oxygen indicators are mostly negative and show an increasing trend towards higher metallicity. This is explained by the fact that oxygen is entirely produced by SNe Type II from massive progenitors, which started to release theiryields at earlier ages in the Galaxy and, hence, at lower metallicities (e.g. Woosley & Weaver 1995). The massive stars producing carbon at low metallicities might be less massive than those producing oxygen (i.e. having a longer life), explaining a delayed contribution of carbon, hence, the negative [C/O] ratios. Alternatively, this could be explained by increasing O/C yields for more massive progenitors of SNeII. Once metallicity starts to increase, low- and intermediate-mass stars release carbon and massive stars start to eject more carbon than oxygen (Carigi et al. 2005). The [C/O] ratio seems to have a constant rise towards higher metallicities when using the forbidden oxygen line. However, in the case when the O I 6158 Å line is employed, we do observe that the maximum in [C/O] takes places close to solar metallicity to then become flat or decrease. This suggests that low-mass stars mostly contribute to carbon around solar metallicity, whereas at super-solar metallicities, massive stars produce carbon together with oxygen, thereby flattening or even decreasing the [C/O] ratio. This trend is in agreement with the metallicity dependent yields from Carigi et al. (2005), which provide higher carbon as [Fe/H] increases from massive stars (i.e. also increasing the O production) but lower carbon from low and intermediate mass stars as [Fe/H] increases (i.e. less production of C). The turning point of increased relative production of carbon from massive stars takes place at A(O) ~ 8.7 dex (see Fig. 2 of Carigi et al. 2005) which equals to [O/H] ~ 0.0 dex. This observed behaviour of [C/O] is in contrast to the steady increase of [C/O] up to [Fe/H] ~ 0.3 dex found, for example, by Franchini et al. (2021). Nevertheless, the general trend we find when using the [O I ] 6300 Å line is similar to the reported by Franchini et al. (2021), who use also that oxygen indicator. All thick-disk stars present negative [C/O] ratios and when using the oxygen line at 6158 Å thin-disk stars with [Fe/H] ≲ –0.2 have [C/O]  0 as well. Thick-disk stars and low-metallicity thin-disk stars at the same metallicity have similar [C/O] ratios, meaning that the balance between different production sites for oxygen and carbon is the same among both populations, despite [C/Fe] and [O/Fe] being systematically higher for thick-disk stars at a given metallicity.
Citation: Carigi et al. 2005
Citation function: Compare/Contrast
From the best-fitting values of the normalization at a fixed energy, we can obtain the ratios of the hydrogen column densities for different dust layers, such as:

(16)

\begin{eqnarray}
\frac{N_{\rm H,12}}{N_{\rm H, 5}} \approx \frac{\mathcal {F}_{\rm X}^{(12)}(E)}{\mathcal {F}^{(5)}_{\rm X}(E)} \frac{\left(1-\langle x \rangle _{12} \right){\langle x \rangle _{12}}}{\left(1-x_5\right){x_5}},
\end{eqnarray}

where we assumed that the number of grains per hydrogen atom is the same in all clouds and dropped by the factor of Cd, i, since this is not sensitive to the grain composition (Mauche & Gorenstein 1986) (see also Section 2). In the above, NH, 12 represents the average column density of dust clouds 1 and 2. As already mentioned in Section 4.1 and later in Section 4.3, these are most probably one dust cloud of finite width, whose average column density we are probing. Having derived the ratios at four different energies, we calculated the weighted means, namely NH, 12/NH, 5 = 0.19 ± 0.03, NH, 12/NH, 34 = 0.059 ± 0.006, and NH, 34/NH, 5 = 3.5 ± 0.6. Thus, the intermediate dust clouds have the highest column density. This is 3.5 times higher than that of the fifth dust cloud, which may also explain the approximately equal intensities of rings 3–4 and 5, given their different distances from the observer. Interestingly, the column density of the clouds located closest to V404 Cyg is ∼6 per cent NH, 34. These findings are in rough qualitative agreement with the extinction histogram shown in Fig. 5, where the lowest extinction values are found at distances ≳2 kpc, i.e. where the dust layers 1 and 2 are located. Quantitatively, we find that the ratios NH, 34/NH, 5 and NH, 34/NH, 12 as derived from the extinction maps (Sale et al. 2014) are by a factor of ∼3 smaller than our estimates, while the NH, 12/NH, 5 ratio is the same (within uncertainty values). This implies that our analysis is overestimating the NH, 34 column density by a factor of ∼3. A simple explanation for this difference is that the dust-to-hydrogen ratio is not the same for all clouds as originally assumed in our calculations (the Ai/Aj term has dropped from the l.h.s. of equation 16). In any case, the ratio of the normalizations $\mathcal {F}_{\rm X}^{(i)}$ can be directly related to the ratio of dust column densities NH, iAi without resorting to any additional assumptions.
Citation: Mauche & Gorenstein 1986
Citation function: Uses
The diffuse hot gas X-ray luminosities in the 0.3–8 keV band are taken from the work of KF15. They have carefully removed the contribution from discrete sources such as low-mass X-ray binaries (Fabbiano 2006) to the total X-ray luminosity, leaving the diffuse gas contribution LX, Gas. A correction to bolometric would increase the X-ray luminosities by 0.08 dex on average. Most of the X-ray data come from Chandra observations. However, for some high-mass galaxies, the X-ray emission is particularly extended (e.g. NGC 4374, 4486, 4649, 5846) and in those cases ROSAT data from O‘Sullivan et al. (2001), corrected to the Chandra energy band, are used. Although the contribution from discrete sources in the ROSAT data cannot be subtracted as accurately as it can for Chandra data, their contribution is only about 1 per cent of the diffuse gas luminosity for these high-mass galaxies (see O'Sullivan et al. 2001). For further details, see KF15. Here we make a very small correction to the KF15 LX,Gas luminosities for the distances used in the SLUGGS survey (Brodie et al. 2014). The KF15 compilation did not include several galaxies that appear in the Alabi et al. (in preparation) study. Here we also include the X-ray luminosities for NGC 720, NGC 1316 and NGC 3115 from Boroson et al. (2011), and for NGC 5128 from KF13. Su et al. (2014) conducted a detailed XMM and Chandra study of NGC 1400. As well as the X-ray emission centred on NGC 1400, they detected an enhanced region of X-rays to the NE of the galaxy that they associated with stripped gas. Here we use the X-ray luminosity centred on NGC 1400 with a small adjustment to our X-ray band and distance, and assume an uncertainty of 20 per cent. We note that the X-ray luminosity would double if the enhanced region were also included. Two galaxies in Alabi et al. (in preparation) but not included here are NGC 2974 (not observed by Chandra) and NGC 4474 (the Chandra observation was only 5 ks).
Citation: O‘Sullivan et al. (2001)
Citation function: Uses; Uses
Douchin & Haensel (2001; DH) formulated a unified EoS for NS on the basis of the SLy4 Skyrme nuclear effective force (Chabanat et al. 1998), where some parameters of the Skyrme interaction were adjusted to reproduce the Wiringa et al. calculation of neutron matter (Wiringa et al. 1988) above saturation density. Hence, the DH EoS contains certain microscopic input. In the DH model the inner crust was treated in the CLDM approach. More recently, unified EoSs for NS have been derived by the Brussels-Montreal group (Chamel et al. 2011; Pearson et al. 2012; Fantina et al. 2013; Potekhin et al. 2013). They are based on the BSk family of Skyrme nuclear effective forces (Goriely et al. 2010). Each force is fitted to the known masses of nuclei and adjusted among other constraints to reproduce a different microscopic EoS of neutron matter with different stiffness at high density. The inner crust is treated in the extended Thomas-Fermi approach with trial nucleon density profiles including perturbatively shell corrections for protons via the Strutinsky integral method. Analytical fits of these neutron-star EoSs have been constructed in order to facilitate their inclusion in astrophysical simulations (Potekhin et al. 2013). Quantal Hartree calculations for the NS crust have been systematically performed by (Shen et al. 2011b,a). This approach uses a virial expansion at low density and a RMF effective interaction at intermediate and high densities, and the EoS of the whole NS has been tabulated for different RMF parameter sets. Also recently, a complete EoS for supernova matter has been developed within the statistical model (Hempel & Schaffner-Bielich 2010). We shall adopt here the EoS of the BSk21 model (Chamel et al. 2011; Pearson et al. 2012; Fantina et al. 2013; Potekhin et al. 2013; Goriely et al. 2010) as a representative example of contemporary EoS for the complete NS structure, and a comparison with the other EoSs of the BSk family (Chamel et al. 2011; Pearson et al. 2012; Fantina et al. 2013; Potekhin et al. 2013) and the RMF family (Shen et al. 2011b,a) shall be left for future study.
Citation: Chamel et al. 2011
Citation function: Uses; Uses
Citation: Chamel et al. 2011
Citation function: Background
The CO emission, tracking the bulk of the gas, reveals an almost face-on one-armed spiral, of which almost two full windings can be traced. What could be the origin of this spiral structure? As the majority of AGB stars are in binary systems, and perhaps all host planets, interaction between the outflow and a sufficiently massive and nearby companion may be the explanation of the observed CO morphology. The intricate emission features in the inner 2″ of the central CO emission maps is strongly reminiscent of hydrodynamical simulations of wind–binary interaction by Mastrodemos & Morris (1998) and Mohamed & Podsiadlowski (2012), where the latter authors performed tailored simulations for the Mira AB system in which the outflow of the AGB star Mira A is perturbed by the presence of its close companion Mira B. The wind–binary interaction that ensues leads to what is known as wind Roche-lobe overflow (WRLOF), where the slow AGB wind is confined to the star’s Roche lobe, while overflowing through the L1 Lagrange point. Gravitational interaction of the overflowing material with the companion produces an intricate feedback system where the stellar outflow material is ejected into the surrounding CSE through two distinct streams (through L2 and the stagnation point3) which combine to form an annular stream. As this stream travels outwards, it creates the larger scale spiral observed in the wind. The morphology resulting from this particular type of wind–binary interaction is shown in Fig. 3 in Mohamed & Podsiadlowski (2012). In Fig. 11 we show the emission pattern seen in the central regions of the CO channel at υ*. We compare this image with the bottom left panel of Fig. 3 in Mohamed & Podsiadlowski (2012), an opacity map of the interaction zone. Though the two properties that are compared differ in nature, they likely still trace the same global morphological structure. Indeed, several of the predicted morphological features can be identified in the data of EP Aqr. The bright central region with a north and southward hook-like extension are strikingly similar, as are the eastern and western crescent-shaped “voids”, the overall shape, and the morphological properties of the small-scale instabilities.
Citation: Mohamed & Podsiadlowski (2012)
Citation function: Compare/Contrast; Compare/Contrast; Similarities
Citation: Mohamed & Podsiadlowski (2012)
Citation function: Similarities; Background