adsabs/FOCAL huggingface dataset:
Numerous investigations of tidal activity on extrasolar planets have been conducted, with a range of topics from the behavior of gas giants (e.g., Běhounková et al. 2010, 2011; Remus et al. 2012a, 2012b; Storch & Lai 2014), to tidal alterations of system dynamics (e.g., Lecoanet et al. 2009; Matsumura et al. 2010; Cébron et al. 2011; Bolmont et al. 2015; Turbet et al. 2017), to tidal alterations of habitability (Barnes et al. 2008, 2013; Jackson et al. 2008a, 2008b; Heller & Armstrong 2014; Kopparapu et al. 2014), issues of spin dynamics (Correia et al. 2008; Ferraz-Mello et al. 2008; Efroimsky 2012b; Cunha et al. 2015), and the role of tides on exomoons (Namouni 2010; Heller & Barnes 2013). Many such studies naturally begin with frequency-independent internal models, but an increasing number consider viscoelastic models (Henning et al. 2009; Běhounková et al. 2010, 2011; Remus et al. 2012a, 2012b; Auclair-Desrotour et al. 2014; Correia et al. 2014; Henning & Hurford 2014; Makarov & Efroimsky 2014; Shoji & Kurita 2014; Driscoll & Barnes 2015; Makarov 2015). Countless more studies rely upon reasonable selections of tidal dissipation terms in order to inform simulations of system dynamics. For solid planetary objects, a detailed study is eventually needed to constrain which rheological models are best under the stress, pressure, and compositional conditions that are applicable to exoplanets and exomoons. Indeed, studies of the Earth tell us that multiple rheological models may be needed as one goes deeper into an exoplanet’s interior. Higher pressures will surely change the microphysical mechanisms that govern the rheological response (Karato & Spetzler 1990). We currently must rely mainly on analytical and numerical modeling when exploring the interiors of extrasolar planets, particularly worlds in the super-Earth category not represented in our solar system (Valencia et al. 2007). It is not yet known how well laboratory results on the viscosity of peridotite can extend to high-pressure phases such as post-perovskite (Murakami 2004), which may play a large role in super-Earths.
Citation: Ferraz-Mello et al. 2008
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Cygnus A, at z = 0.0562, is 10 times closer than the next radio galaxy of similar radio luminosity.4

4
Radio luminosity >1045 erg s−1.
 The nuclear regions in Cygnus A have been observed extensively at radio through X-ray wavelengths (Carilli & Barthel 1996). The inner few arcseconds is a complex mix of optically obscuring dust clouds (Vestergaard & Barthel 1993; Whysong & Antonucci 2004; Lopez-Rodriguez et al. 2014; Merlo et al. 2014), atomic gas seen in narrow line emission (Stockton et al. 1994; Taylor et al. 2003), H i 21 cm absorption toward the inner radio jets, with a neutral atomic column density >1023 cm−2, depending on H i excitation temperature (Struve & Conway 2010), polarized, broad optical emission lines due to scattering by dust (Antonnuci et al. 1994; Ogle et al. 1997), and a highly absorbed hard X-ray spectrum with a total gas column density of ∼3 × 1023 cm−2 (Ueno et al. 1994; Reynolds et al. 2015). VLBI radio observations at 0.05 mas resolution reveal highly collimated jets originating on scales ∼200 times the Schwarzschild radius (Boccardi et al. 2016). Tadhunter et al. (2003), derive a black hole mass of 2.5 ± 0.7 × 109 M⊙ from HST and Keck spectroscopy of Pa-α and [O iii], and conclude that Cygnus A contains an AGN with a bolometric luminosity of order 1046 erg s−1, comparable to high redshift quasars (Runnoe et al. 2012). This AGN is highly obscured in the optical due to dust along our line of sight, with Av > 50 magnitudes, based on near-IR spectroscopy (Imanishi & Ueno 2000). Studies of the mid- to far-IR spectral and polarization properties have led to a model of a clumpy, dusty torus obscuring the AGN in Cygnus A, with a radius of at least 130 pc, although these conclusions are based on spatially integrated properties; these observations did not have the spatial resolution to resolve the torus, and hence are partially contaminated by emission from the radio core-jet (Privon et al. 2012; Lopez-Rodriguez et al. 2018).
Citation: Ogle et al. 1997
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A significant limitation of the model is that it ignores the well-established hydrodynamic evolution of the loop during the cooling process, involving the substantial transfer of mass between the chromosphere and the corona. For large downward heat fluxes, the transition region is unable to radiate the supplied energy, resulting in the deposition of thermal energy in the dense chromosphere. The resulting two to three orders-of-magnitude temperature enhancements create a large pressure gradient that drives an upward enthalpy flux of “evaporating” plasma. However, as the loop cools, the decreased heat flux becomes insufficient to sustain the radiation emitted in the now-dense transition region and hence an inverse process of downward enthalpy flux starts to occur. It has been suggested (Klimchuk et al. 2008) that the enthalpy fluxes associated with both evaporating and condensing plasma are at all times in approximate balance with the excess or deficit of the heat flux relative to the transition region radiation loss rate. This basic idea has allowed the development of global “Enthalpy-Based Thermal Evolution of Loops” (EBTEL) models that describe the evolution of the average temperature and density in the coronal part of the loops; these models are generally in good agreement with one-dimensional hydrodynamic simulations (Klimchuk et al. 2008; Cargill et al. 2012a, 2012b). It is, in principle, possible to include the effects of a turbulence-controlled heat flux in EBTEL (or 1D hydrodynamic) models. If this heat flux is reduced sufficiently relative to its collisional value, then, for the reasons explained above, there will be a significant impact on the thermal evolution of the loop. Doing so, however, would still require a numerical treatment, which is beyond the scope of the present work (but which it is our intention to carry out in a future work). Instead, we adopt a simpler approach that allows a systematic and fairly transparent quantitative analysis of the impact of turbulence on the thermodynamics of post-flare loops.
Citation: Klimchuk et al. 2008
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Citation: Klimchuk et al. 2008
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The first step in searching for dynamically correlated minor bodies, particularly those resulting from break-ups, is to get a clear characterization of what the expectations may be. The outcome of cometary disruption is well documented through two well-studied examples, those of the comets 73P/Schwassmann-Wachmann 3 and D/1993 F2 (Shoemaker-Levy 9). For reasons that still remain unclear, comet 73P started to break apart in 1995 and dozens of fragments were observed in 2006 and 2007 (see e.g. Crovisier et al. 1996; Weaver et al. 2006; Reach et al. 2009; Hadamcik & Levasseur-Regourd 2016). Some of these fragments have been recovered in 2010–2011 (Harker et al. 2011, 2017; Sitko et al. 2011) and 2016–2017 (e.g. Kadota et al. 2017;1 Williams 2017); it may consist of hundreds of pieces now (68 of them have orbit determinations). This fragmentation process can be described as gentle and progressive. In striking contrast, comet Shoemaker-Levy 9 experienced a sudden, violent fragmentation event triggered by strong tidal forces during a close encounter with Jupiter in 1992 July (see e.g. Sekanina, Chodas & Yeomans 1994, 1998; Asphaug & Benz 1996; Sekanina 1997). Most fragments collided with Jupiter over a period of a week (1994 July 16–22); 21 of them have orbit determinations. Quite different may have been the collisional event that led to the formation of the Haumea family (Brown et al. 2007; Schlichting & Sari 2009; Leinhardt, Marcus & Stewart 2010; Lykawka et al. 2012; Ortiz et al. 2012) perhaps more than 1 Gyr ago (Ragozzine & Brown 2007; Volk & Malhotra 2012). Fragments of recently disrupted minor bodies must have very similar values of their semimajor axis, a, eccentricity, e, inclination, i, longitude of the ascending node, $\mathit {\Omega }$, argument of perihelion, ω, and time of perihelion passage, τq, but $\mathit {\Omega }$, ω and τq tend to become increasingly randomized over time. In contrast, recently unbound pairs resulting from binary dissociation events might have relatively different values of a and e, but very similar values of i, $\mathit {\Omega }$ and ω, the difference in τq may initially range from weeks to centuries, but grows rapidly over time (see e.g. de León, de la Fuente Marcos & de la Fuente Marcos 2017; de la Fuente Marcos, de la Fuente Marcos & Aarseth 2017).
Citation: Kadota et al. 2017
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A spatial coincidence of the radio jet morphology and velocity dispersion of the ionised gas has already been reported for spatially-resolved spectroscopy of more luminous radio-quiet AGN (e.g. Husemann et al. 2013; Villar-Martín et al. 2017) and powerful compact radio sources (e.g. Roche et al. 2016), but it has been correctly proposed that the fast moving plasma itself can lead to radio emission that mimics jet activity (Zakamska & Greene 2014; Hwang et al. 2018). In the case of HE 1353−1917 we can rule out that the ionised plasma is creating the radio emission because the high-velocity ionised gas traced by [O III] is significantly displaced compared to the observed jet-like radio emission. Hence, we think that the radio jet is transferring its energy and momentum to the ambient medium through an extended shock front, which creates turbulence in a dense clumpy ISM. Such a great impact of the radio jet has been observationally shown in many cases (e.g. Villar-Martín et al. 1999, 2014; O’Dea et al. 2002; Nesvadba et al. 2006; Holt et al. 2008; Guillard et al. 2012; Harrison et al. 2015; Santoro et al. 2018; Tremblay et al. 2018; Jarvis et al. 2019) and theoretically supported through detailed hydrodynamic simulations (e.g. Krause & Alexander 2007; Sutherland & Bicknell 2007; Wagner & Bicknell 2011; Wagner et al. 2012; Cielo et al. 2018; Mukherjee et al. 2018). As we discussed in Sect. 3.6, the jet power alone is sufficient to energetically drive the outflow because only a small fraction of the AGN luminosity would impact the thin disc of the galaxy implying conversion efficiencies of more than 10% of Lbol. Hopkins & Elvis (2010) proposed a two-stage process for efficient radiation-driven outflows. They describe a scenario in which an initial weak wind in the hot gas phase, possibly initiated by an accretion disc wind or a radio jet, creates additional turbulence in the surrounding medium so that massive gas clouds will subsequently expand and disperse. This expansion of gas clouds would significantly increase their apparent cross-section with respect to incident radiation field of the AGN. Such a two-stage process may increase the coupling efficiency by an order of magnitude. While we cannot directly confirm this process with our observations, the close alignment of the jet axis and the ionisation cone greatly suggest that the outflow is driven jointly by both mechanical and radiative energy with an unknown ratio of the two. The open question is whether the same powerful outflow could have developed without the fast radio jet impacting the cold gas directly given its unique orientation.
Citation: Sutherland & Bicknell 2007
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Citation: Villar-Martín et al. 1999
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The best-fit parameters are shown in Table 3. We find that the uncertainties in M* and 





 are considerably large due to a degeneracy between the two parameters when all parameters are variable. Plotted in Figure 1 is the faint-end slope α as a function of redshift. Our results indicate that the best-fit values of α are about −2 at 





 to 10, which are steeper than those at lower redshift (e.g., 





 at 





 in Bouwens et al. 2015). We show the fitting results at 





, 8, 9, and 10 in Figures 2, 3, 4, and 5, respectively. The top and bottom panels present the observed number densities and the best-fit luminosity functions in the image plane and the source plane, respectively. We also plot the results of previous blank-field surveys (Ouchi et al. 2009; Bradley et al. 2012; McLure et al. 2013; Oesch et al. 2013; Schenker et al. 2013; Bowler et al. 2014; Bouwens et al. 2015; Finkelstein et al. 2015; Calvi et al. 2016) and recent HFF results in other studies (Atek et al. 2015a; Laporte et al. 2016; McLeod et al. 2016). The best-fit parameters are consistent with those in previous studies. In the top panel of Figure 2, there may be an excess in the observed surface number density at 





. The reason for this excess is not clear, although using a size–luminosity relation that gives smaller sizes at faint magnitudes may reduce this excess. At 





, the observed number densities at the bright end are slightly larger than the number densities in the simulation. This is probably due to the existence of an overdense region of 





 dropouts in the Abell 2744 cluster field. We discussed the properties of the overdensity in Ishigaki et al. (2016; see also Zheng et al. 2014 and Atek et al. 2015b). At 





, although we detect no galaxies, we can place a constraint on the luminosity function from the non-detection. Based on the best-fit parameters where only 





 is variable, ∼1.4 galaxies are expected to be detected in the HFF fields. The middle panels of Figures 2–5 show histograms of the number of the dropouts. It is seen that our samples push the magnitude limits of the luminosity functions significantly by up to ∼3 magnitude. The correlations between M* and α at z ∼6–7 and 8 are presented in Figure 6.
Citation: Schenker et al. 2013
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Citation: Bowler et al. 2014
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The Gibbs free energy of the system, and thus the composition of the solids formed depends on the pressure and temperature at which condensation occurs. In order to consider reasonable pressures and temperatures for the inner regions of the PPD, and in order to convert these temperatures and pressures into radial locations within the disc and formation times for the solid condensates, we consider the simplest possible PPD model. We use the theoretical model derived in Chambers (2009), which models the viscous accretion of gas heated by the star. This model has been previously used for the modelling of planetesimal formation in PPDs (Moriarty et al. 2014; Harrison et al. 2018) and super-Earths (Alessi, Pudritz & Cridland 2017). This model ignores any vertical or radial mixing, and as will be discussed further later, any radial drift. All of these processes may be of critical importance in a realistic PPD. The Chambers model is a disc model with an alpha parameterization that divides the disc into three sections; an inner viscous evaporating region, an intermediate viscous region, and an outer irradiated region. For the calculations in this work, we have assumed disc parameters of $s_{0} = 33\, \mathrm{au}$, $\kappa _{0} = 0.3\, \mathrm{m^{2}\, kg}^{-1}$, α = 0.01, γ = 1.7, μ = 2.4, and $M_{*}=0.78\, \mathrm{M}_{\odot }$ following Chambers (2009) and Motalebi et al. (2015). We also assume that the mass of the PPD is directly proportional to the mass of the host star according to M0 = 0.1M* (Chambers 2009; Andrews et al. 2013). The temperature and radius of the star in the PPD phase are assumed to be functions of the stellar mass in the form derived in Siess, Dufour & Forestini (2000). The relations used in this work to calculate the PPD mass, the initial stellar radius, and the initial stellar temperature as a function of stellar mass are consistent with the values given in Stepinski (1998) and Chambers (2009) for a solar mass star. The analytical expressions for the pressure and temperature of the mid-plane of the PPD as a function of radial location (a) and time (tdisc) are presented in Appendix C. The temperature–radial location curves for the model disc around a star similar to HD 219134 are plotted as a function of time in Fig. 2. The pressure–temperature space mapped out by the model disc for the case of a star similar to HD 219134 is displayed in the Appendix in Fig. C1. The pressure–temperature space for the model disc of a solar mass star shows negligible differences compared to the HD 219134 case.
Citation: Moriarty et al. 2014
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This conclusion can be quantified by the number of catastrophic collisions per comet (Rickman et al. 2015)
(6)
\begin{equation}
N_{{\rm coll}} = N_{\rm p} A_{\rm p} u T / V,
\end{equation}
where Np is the number of comets in the disc, Ap and u are the collision cross-section and speed, respectively, T ≈ 0.4 Gyr is the time spent from accretion to scattering beyond Neptune and V is the disc volume. A cumulative size distribution of comets with a power index of −2.0 and u ≈ 0.6 km s−1 provides Ncoll ≈ 3, assuming that ≈5 Earth masses are distributed in comets of diameters from 1 to 100 km (Rickman et al. 2015). The size distribution is probably shallower (Johansen et al. 2015), as confirmed by the shallowing size distribution of craters of diameter 10 km observed on Pluto and Charon (Singer et al. 2016; Robbins et al. 2017). We simulate the impacts on Pluto and Charon by means of Holsapple’s model (http://keith.aa.washington.edu/craterdata/scaling/index.htm) with the following target parameters: cold ice as geological type, lunar gravity, zero atmospheric pressure; and with the following projectile parameters: bulk density of 500 kg m−3, diameter of 0.1 km and impact speed of 1 km s−1. Tests performed assuming numerical values around those just listed provide craters always a factor 2 larger than the projectiles, so that the number of projectiles of 0.1 km radius is a factor from (0.1/2.5)2.4 − 3 = 7 to (0.1/2.5)1.6 − 3 = 90 below previous estimates (Morbidelli & Rickman 2015; Jutzi & Benz 2017; Jutzi et al. 2017), according to Charon’s and Pluto’s crater size distributions, respectively (Robbins et al. 2017). The same computations performed by Rickman et al. (2015), changing only the cumulative power index from −2.0 to −1.4, i.e. Charon’s crater size distribution (Robbins et al. 2017), provide Ncoll ≈ 0.5, and Ncoll ≈ 0.05 with a cumulative power index of −0.6, i.e. Pluto’s crater size distribution (Robbins et al. 2017), which make equation (6) consistent with the observed flux of 67P fractal particles. This conclusion is confirmed by the craters observed on Nix (Robbins et al. 2017), with a cumulative power index of −0.8, close to Pluto’s one, a measured cumulative crater density of 0.01 km−2 at diameters >3 km (smaller projectiles would not destroy a parent comet, according to equation (5)) and an extrapolated cumulative crater density 0.1 km−2 at diameters >0.1 km, matching that extrapolated for Charon with a steeper cumulative index (Robbins et al. 2017). Nix and Charon are less affected than Pluto by a possible significant resurfacing and their crater density suggests a negligible number of catastrophic impacts during the Solar system lifetime on bodies of cross-section 10 km2.
Citation: Johansen et al. 2015
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We show in Fig. 6 the dependence of some Ly α characteristics on absolute FUV magnitude. Our galaxies with detected LyC emission are shown by red filled circles and those with upper limits of LyC emission are represented by red open circles. All our low-mass galaxies are characterized by moderate Ly α luminosities in a narrow range between 1042.19 and 1042.74 erg s−1 (Fig. 6a), that are slightly below the values for confirmed LyC leakers (blue filled circles) by Izotov et al. (2016a,b, 2018a,b) and high-redshift galaxies (grey open circles) by Ouchi et al. (2008), Hashimoto et al. (2017), Jiang et al. (2018), Matthee et al. (2017), Matthee et al. (2018), Sobral et al. (2018), but are ∼1 order of magnitude higher than those for GPs (black asterisks; Jaskot & Oey 2014; Henry et al. 2015; Jaskot et al. 2017; Yang et al. 2017a; McKinney et al. 2019). Our low-mass galaxies have high EW(Ly α) ∼ 65–220 Å (Table 7, red symbols in Fig. 6b), similar to those in other LyC leakers (blue symbols in Fig. 6b). They are at the high end of the EW(Ly α) values for high-z LAEs by Ouchi et al. (2008), Hashimoto et al. (2017), Jiang et al. (2018), Harikane et al. (2018), Caruana et al. (2018), Pentericci et al. (2018), Matthee et al. (2017, 2018), Sobral et al. (2018) (grey open circles) and GPs (black asterisks). However, contrary to expectations for galaxies with lower stellar masses and, likely, lower masses of the neutral gas, the separation between the Ly α peaks is on average similar to that in higher mass LyC leakers (Fig. 6c), and it is higher in galaxies with upper limits of LyC emission (>400 km s−1, red open circles). Ly α escape fractions fesc(Ly α) in low-mass galaxies are also similar to those in higher mass LyC leakers, and they are lower in galaxies with upper limits of LyC emission (red open circles in Fig. 6d). We also note that the average ratio of blue and red peak fluxes of ∼25 per cent (Table 7) is somewhat lower than the value of ∼30 per cent quoted by Hayes et al. (2021) for $z\, \sim$ 0 galaxies.
Citation: McKinney et al. 2019
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An alternative approach is to map the CGM through direct imaging of the Ly α line. Theoretical models suggest that three main mechanisms should be able to generate circumgalactic Ly α emission: cooling radiation of gravitationally heated gas (e.g. Haiman, Spaans & Quataert 2000; Yang et al. 2006; Dijkstra & Loeb 2009), ultraviolet (UV) photons produced through shock mechanisms (Taniguchi & Shioya 2000; Mori, Umemura & Ferrara 2004), and recombination radiation following photoionization (often referred as fluorescence) powered by UV sources (Cantalupo et al. 2005; Geach et al. 2009; Kollmeier et al. 2010). While the fluorescent signal powered by the diffuse metagalactic UV background (Hogan & Weymann 1987; Binette et al. 1993; Gould & Weinberg 1996; Haardt & Madau 1996), with an expected surface brightness (SB) of $\rm SB_{Ly\alpha }\sim 10^{-20} \,erg \,s^{-1} \,cm^{-2} \,arcsec^{-2}$ (Cantalupo et al. 2005; Rauch et al. 2008), is still out of reach for current optical instrumentation (but see Gallego et al. 2018), Ly α fluorescence is predicted to be boosted up into the detectable regime in the vicinity of bright ionizing sources, as luminous quasars (Rees 1988; Haiman & Rees 2001; Alam & Miralda-Escudé 2002; Cantalupo et al. 2005). This theoretical prediction has been confirmed by a number of surveys targeting the fluorescent Ly α emission around luminous and radio-quiet quasars, using narrow-band (NB) filters on 8-metre class optical telescopes (e.g. Cantalupo, Lilly & Haehnelt 2012; Cantalupo et al. 2014; Martin et al. 2014; Arrigoni Battaia et al. 2016) and spectroscopic observations (e.g. Christensen et al. 2006; North et al. 2012; Herenz et al. 2015). However, these surveys have revealed giant Ly α nebulae, spanning distances from the quasar larger than 100 physical kpc (pkpc), only in less than 10 per cent of the targets (e.g. Cantalupo et al. 2014; Hennawi et al. 2015; maximum projected linear sizes >300 pkpc), and emission on smaller scales (R ≲ 50–60 pkpc) have been detected only in about 50 per cent of the cases. This 50 per cent detection rate is likely due to a combination of limits of the observational techniques, as for instance NB filter losses, spectroscopic slit losses, point spread function (PSF) losses and, most importantly, dilution of the signal of the Ly α line into the continuum flux (both background and from the host galaxy) encompassed by the width of the filter (see also Borisova et al. 2016 for a discussion).
Citation: Gallego et al. 2018
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