adsabs/FOCAL huggingface dataset:
For LLAGNs, there are two competing components for the emission at optical/UV wavebands. One component is the thermal emission from the outer truncated SSD, which peaks in optical or UV bands, depending on the location of the truncated radius. The other component is the Compton scattering of synchrotron emission from the inner hot accretion flow (Manmoto et al. 1997; Yuan & Narayan 2014). Since our sample is limited to sources whose λ  10−3, we argue that the emission at 2500 Å mainly comes from the inner hot accretion flow.3 Interestingly, for hot accretion flows around supermassive BHs (the LLAGN case), the optical/UV emission usually is the first Compton up-scattered bump (Manmoto et al. 1997; Yuan & Narayan 2014). The emission from such a process has a positive correlation with $\dot{m}$, as $\dot{m}$ will mainly determine the optical depth (surface density), a quantity that controls the probability of Compton scattering (Sunyaev & Titarchuk 1980; Dermer, Liang & Canfield 1991). On the other hand, the first Compton bump is even more sensitive to the energy of electrons (a.k.a. the electron temperature), as it determines the location (in wavebands) of the peak. For a given $\dot{m}$, larger α means lower density, or equivalently lower radiative cooling to the electrons. Consequently, the electrons will be more energetic at higher temperatures (Xie & Yuan 2012). The dependence of emission at optical/UV band on the parameter α relies on detailed numerical calculations, where Manmoto et al. (1997) reported that the emission at 2500 Å has a positive correlation with α. For the above reasons, we simply write LUV as
(6)
\begin{equation}
L_{\rm UV}\sim (\dot{m} \alpha )^b,
\end{equation}
where b ∼ 2. The estimation of b comes from the fact that the first-order Compton scattering (responsible for the optical/UV emission) depends on the product of the seed photon flux (synchrotron emission, $\propto \dot{m}^{0.5-1}$; cf. Mahadevan 1997; Yuan et al. 2015; note that electron temperature also depends on $\dot{m}$ for the expression in Mahadevan 1997) and optical depth in a vertical direction ($\propto \dot{m}^{1-2}$).
Citation: Sunyaev & Titarchuk 1980
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It is obviously of fundamental importance in this process to provide a very accurate absolute calibration of the Cepheid PL relation. This can be achieved in different ways, using Cepheids in our own Galaxy that have accurate parallax measurements, or using extragalactic Cepheids for which the distances of their host galaxies have been very accurately determined with some Cepheid-independent method. A critical aspect of the calibration of the PL relation is a precise determination of its possible dependence on the metallicity of the Cepheid variables. Without an accurate knowledge of this “metallicity effect” a distance measurement to a galaxy accurate to 1% with a Cepheid PL relation is clearly not possible. In the past a lot of work was done with a variety of methods to determine the metallicity dependence of the Cepheid PL relation. Early work includes the studies of Gould (1994), Kennicutt et al. (1998), and Sakai et al. (2004). More recent studies on the metallicity effect are those of Shappee & Stanek (2011), Mager et al. (2013), and Fausnaugh et al. (2015), among others. A very detailed compilation of metallicity effect determinations prior to 2008 can be found in Table 1 of Romaniello et al. (2008). These studies seem to indicate that the metallicity effect in the near-infrared JHK bands is small, perhaps even vanishing, while there is a significant effect in optical and mid-infrared photometric bands (e.g., Freedman & Madore 2011). While most studies yielded a negative sign of the metallicity effect in optical bands meaning that more metal-rich Cepheids are intrinsically brighter than their more metal-poor counterparts of the same pulsation period, the work of Romaniello et al. (2008) has yielded the opposite sign for the effect in the V band, meaning that metal-poor Cepheids are intrinsically brighter than their more metal-rich counterparts of the same pulsation period. Theoretical studies (e.g., Caputo et al. 2000; Bono et al. 2008) appear to support Romaniello’s results, but the uncertainty on these determinations of the metallicity effect from pulsation theory still seems to be rather substantial. In the most recent work on the subject, Wielgórski et al. (2017), using the extremely well-established Cepheid PL relations in the Magellanic Clouds in optical and near-infrared bands combined with the accurate distance determinations to the LMC (Pietrzyński et al. 2013) and SMC (Graczyk et al. 2014) from late-type eclipsing binaries, found a metallicity effect compatible with zero in all bands. As a conclusion, there is still no consensus about the true effect of metallicity on Cepheid absolute magnitudes in different spectral regions. It is especially important to obtain a truly accurate determination of the metallicity effect in the near-infrared bands since these have been used, due to their much lower sensitivity to extinction, in the space-based work on H0 with the Hubble Space Telescope over the last two decades, and will be used in the near future with the James Webb Space Telescope.
Citation: Shappee & Stanek (2011)
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With the results from Gaia and the large number of stars collected from dedicated surveys, a plethora of Galactic mass estimates have recently been made using using different methods and data samples. We summarize these most recent results in Fig. 8. Grouping together the works applying a distribution function method (Callingham et al. 2019; Eadie & Jurić 2019; Posti & Helmi 2019; Vasiliev 2019; Li et al. 2020; Deason et al. 2021; Hattori et al. 2021; Correa Magnus & Vasiliev 2022; Shen et al. 2022; Slizewski et al. 2022; Wang et al. 2022) the weighted mean mass estimate is ∼0.93 ± 0.047 × 1012 M⊙. The methods using high velocity stars with full 6D phase-space information have been used to estimate the mass of the Milky Way (Monari et al. 2018; Deason et al. 2019; Grand et al. 2019; Koppelman & Helmi 2021; Necib & Lin 2022) have a weighted mean mass of ∼0.93 ± 0.099 × 1012 M⊙. Two recent works using either the Sagittarius or Magellanic Steams (Craig et al. 2021; Vasiliev et al. 2021) give a weighted mean mass of ∼0.98 ± 0.15 × 1012 M⊙. The lightest mass measurements have come from rotation curve based methods (de Salas et al. 2019; Eilers et al. 2019; Ablimit et al. 2020; Cautun et al. 2020; Karukes et al. 2020; Jiao et al. 2021) with a weighted mean of ∼0.76 ± 0.023 × 1012 M⊙. The works which use 6D satellite phenomenology compared to Milky Way-type simulations (Patel et al. 2018; Villanueva-Domingo et al. 2021) infer a weighted mean Galactic mass of ∼0.97 ± 0.0091 × 1012 M⊙ and Rodriguez Wimberly et al. (2022) find their results are consistent with a Galactic mass in the range of 1–1.2 × 1012 M⊙. Zaritsky et al. (2020) apply the timing argument to distant Milky Way halo stars to derive a lower limit to the Milky Way mass of 0.91 × 1012 M⊙. Within the uncertainty, our BHB mass estimates are in agreement with Zaritsky et al. (2020), although our KG mass estimates and a few of the recent mass estimates which we plot in Fig. 8 are lower than this limit.
Citation: Wang et al. 2022
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Detailed IBEX results also showed that (1) the ∼0.5–6 keV ENA spectral indices in the GDF are ordered in latitude, with those observed near mid- and low latitudes between ±45° being significantly steeper compared with those observed at higher latitudes (Funsten et al. 2009b; McComas et al. 2009b), and (2) the corresponding ENA fluxes exhibit temporal variations on an annual scale that reflect the decreasing output of the SW, which resulted in a general decrease and flattening of the SW dynamic pressure during 2007–2010 (McComas et al. 2012, 2014). Desai et al. (2015, 2016; see also Dayeh et al. 2012) studied the energy dependence and latitudinal ordering of the ∼0.5–6 keV ENA spectral indices γ in the GDF between 2009 and 2013 and showed that the latitudinal (θ) dependence of γ is energy dependent and well represented by the cosine function
1





with different offsets, amplitudes, and phase angles. Desai et al. (2016) further reported that the general decrease in the >1 keV ena fluxes from 2009–2011 to 2012–2013 occurred at all latitudes and that this decrease was not accompanied by corresponding changes in the spectral indices. Indeed, over the first five years of the IBEX mission, the ENA spectral indices in the GDF exhibited a strong and persistent energy-dependent, latitudinal ordering that reflected the solar minimum latitudinal profile of the fast and slow SW speeds in the inner heliosphere (e.g., Funsten et al. 2009b; Dayeh et al. 2011; Livadiotis et al. 2011; Schwadron et al. 2014; Desai et al. 2015, 2016; Zirnstein et al. 2017). Based on the reconstructed latitudinal and temporal profiles of SW parameters from 2011 to 2014 (Sokół et al. 2013, 2015), i.e., during the ascending phase of solar cycle 24 and following the predictions of McComas et al. (2012, 2014), Desai et al. (2016) further suggested that the GDF in 2014–2017 would either stabilize or increase, and that the latitudinal ordering of the corresponding spectral indices would most likely be disrupted.
Citation: McComas et al.; 2014
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Several physical processes affect galaxies inside clusters in a simultaneous way. One of these mechanisms is the ram pressure stripping (e.g. Gunn & Gott 1972; Abadi, Moore & Bower 1999; Book & Benson 2010; Steinhauser, Schindler & Springel 2016). This process can remove an important fraction of the cold gas from galaxies, resulting in the inhibition of star formation. Although this mechanism is more effective at the central regions of massive clusters, it has been reported in less massive systems (e.g. Rasmussen, Ponman & Mulchaey 2006; Jaffé et al. 2012; Hess & Wilcots 2013). Ram pressure stripping occurs as galaxies move at high speeds through the hot ionized gas of the intracluster medium, which collides with the cold gas of the galaxies and removes it. The warm gas from the galactic halo can also be removed by the gas of the intracluster medium, a process known as starvation (e.g. Larson, Tinsley & Caldwell 1980; Balogh, Navarro & Morris 2000; McCarthy et al. 2008; Bekki 2009; Bahé et al. 2013; Vijayaraghavan & Ricker 2015). This process can cut-off further gas cooling from the galaxy’s halo gas that fuels future star formation. Kawata & Mulchaey (2008) predicted that starvation can act in galaxy groups as well. Another physical process that works on galaxies in their passage through the deep potential well of the cluster is tidal stripping (e.g. Zwicky 1951; Gnedin 2003a; Villalobos, De Lucia & Murante 2014). It can induce a central star formation burst (Byrd & Valtonen 2001), bar instabilities (Łokas et al. 2016), changes in the pattern of the spiral arms (Semczuk, Łokas & del Pino 2017), and truncate dark matter haloes (e.g. Gao et al. 2004; Limousin et al. 2009). In the outskirts of clusters, mechanisms like galaxy–galaxy interaction, known as harassment, are more effective (e.g. Moore et al. 1996; Moore, Lake & Katz 1998; Gnedin 2003b; Smith et al. 2015). Most of the processes mentioned above tend to decrease or to completely suppress the star formation in galaxies. As a consequence, galaxies in clusters are typically red, early-type, with an old stellar population, and have little or none star formation at all.
Citation: Jaffé et al. 2012
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Citation: Larson, Tinsley & Caldwell 1980
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Within the framework of the fireball shock model, Pe'er etÂ al. (2007) proposed a method to infer central engine parameters using observed data. With the measured temperature and flux of an identified thermal component in the spectrum, along with a flux ratio between thermal and non-thermal components, one may infer the size of the jet at the base of the outflow, r0, and the dimensionless entropy of the outflow,  (which is also the bulk Lorentz factor of the outflow, if the photosphere radius is greater than the fireball coasting radius). Some authors have applied this method to some Fermi GRBs (Iyyani etÂ al. 2013; Preece etÂ al. 2014; Ghirlanda etÂ al. 2013). The derived central engine parameters are sometimes ad hoc or inconsistent. For instance, the analyses for GRB 110721A (Iyyani etÂ al. 2013) and for GRB 130427A (Preece etÂ al. 2014) led to a curious conclusion that the bulk Lorentz factor of the outflow of different layers are decreasing with time. This would lead to no, or at most very inefficient, internal shock emission. Yet both bursts have dominant non-thermal emission. More curiously, the data of GRB 110721A (Iyyani etÂ al. 2013) require that r0 is rapidly varying with time by 2â3 orders of magnitudes. This is hard to imagine given the well-believed paradigm of the GRB central engine: If the engine is naked, the size of the engine (a hyper-accreting black hole or a millisecond magnetar) is around r0 â¼ 107âcm; if an extended envelope of a collapsar progenitor is considered, the fireball may be âre-born,â with r0 â¼ R*Î¸j â¼ 109R*, 10Î¸j, â1âcm (where R* is the size of the progenitor star, and Î¸j is the jet opening angle). If one considers the depletion of the envelope, r0 should decrease with time. However, Iyyani etÂ al. (2013) showed that r0 increases from 106âcm to 108âcm early on, and then decreases mildly after 2Â s. These absurd conclusions suggest that the starting point of the analysis, i.e., the assumption of a pure fireball model, might not be valid. It is interesting to see whether a hybrid ejecta photosphere model may solve the problem. Incidentally, Ghirlanda etÂ al. (2013) analyzed another burst, GRB 100507, using the fireball framework (Pe'er etÂ al. 2007), but found that the derived r0 remains constant and reasonable. The jet composition of that burst may be more close to a fireball. It would be interesting to see whether a general theoretical framework can be established, which may be reduced to the standard fireball framework when Ï0  1.
Citation: Preece etÂ al. 2014
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In Sifón et al. (2013), we used the σ–M200 scaling relation of Evrard et al. (2008) to estimate dynamical masses. As discussed in Section 1, the scaling relation of Evrard et al. (2008) was calibrated from a suite of N-body simulations using DM particles to estimate velocity dispersions. However, the galaxies, from which velocity measurements are made in reality do not sample the same velocity distribution as the DM particles. They feel dynamical friction and some are tidally disrupted, which distorts their velocity distribution and biases their dispersion (e.g. Carlberg 1994; Colín et al. 2000). Recent high-resolution hydrodynamical simulations of ‘zoomed’ cosmological haloes have shown that there is a significant difference between the velocity distributions of DM particles and galaxies themselves; whether galaxies (i.e. overdensities of stars in hydrodynamical simulations) or DM subhaloes are used makes comparatively little difference (Munari et al. 2013). Results from state-of-the art numerical simulations depend on the exact definition of a galaxy and the member selection applied, but the current consensus is that galaxies are biased high (i.e. at a given mass the velocity dispersion of galaxies or subhaloes is larger than that of DM particles) by 5–10 per cent with respect to DM particles (Lau et al. 2010; Munari et al. 2013; Wu et al. 2013), translating into a positive 15–20 per cent bias in dynamical masses when using DM particles. This is illustrated in Fig. 5: DM particles are not significantly impacted by either dynamical friction or baryonic physics; therefore, the scaling relations for DM particles are essentially the same for all simulations. In contrast, DM subhaloes are affected by baryons in such a way that including baryonic feedback (most importantly feedback from active galactic nuclei – AGN, but also from cooling and star formation) makes their velocity dispersions much more similar to those of simulated galaxies. This means we can rely on our analysis of the previous section, based on DM subhaloes, to correct the velocity dispersions measured for ACT clusters, and then estimate dynamical masses using predictions obtained either from galaxies or subhaloes. The difference between the Saro et al. (2013) and Munari et al. (2013) galaxy scaling relations depends on the details of the semi-analytic and hydrodynamical implementations used in Saro et al. (2013) and Munari et al. (2013), respectively. The different cosmologies used in the Millenium simulation (in particular, σ8 = 0.9; Springel et al. 2005) by Saro et al. (2013) and the simulations by (Munari et al. 2013, σ8 = 0.8) may also play a role.
Citation: Munari et al. 2013
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The C/O ratio varies across exoplanets’ host star populations (Delgado Mena et al. 2010; Brewer & Fischer 2016; Brewer et al. 2017), and this variation is likely to be reflected in the composition of exoplanet atmospheres, assuming that they are formed with the same materials as their stars. Moreover, various processes in the protoplanetary disks and the planet formation process can affect the exoplanet compositions and have a significant impact on the final C/O ratio (Öberg et al. 2011; Mordasini et al. 2016; Espinoza et al. 2017; Madhusudhan et al. 2017). For these reasons, it is necessary to consider the effects of the C/O ratio on the atmospheric chemistry and the formation of aerosols. Numerous studies have been performed using chemical models (Madhusudhan 2012; Moses et al. 2013; Venot et al. 2015; Tsai et al. 2017; Heng & Lyons 2016; Goyal et al. 2018; Drummond et al. 2019), but corresponding laboratory experiments are still largely nonexistent. Laboratory investigations can provide essential insight into the effects of the C/O ratio on the atmospheric photochemistry and the formation of aerosols. In a previous work, we performed the first laboratory experiments dedicated to the study of the chemistry in hot Jupiter atmospheres (Fleury et al. 2019). This work focused on the chemistry in atmospheres with T > 1000 K and a C/O ratio of 1 (representing C enhancement compared to the solar value of 0.54), because chemical models predict that the abundances of hydrocarbon and nitrile species increase by several orders of magnitude in these atmospheres compared to atmospheres with a low C/O ratio (Venot et al. 2015). Therefore, they can be considered as better candidates for the formation of complex organic molecules with longer carbon chains. This first study revealed that photochemical aerosols could be produced at temperatures as high as 1500 K and that water could be efficiently formed through photochemical channels. In the present work, we performed new experiments to study the chemistry in hot Jupiter atmospheres at similar temperatures (1173–1473 K) but with lower C/O ratios. We used a gas mixture of H2, H2O, and CO that represents the simplest plausible atmosphere for a hot Jupiter with a C/O ratio  1. This new study, compared with our previous work, allows us to assess the evolution of the chemistry in hot Jupiter atmospheres as a function of the C/O ratio and atmospheric composition.
Citation: Tsai et al. 2017
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Also, by studying different ratios we can get information about the masses of the progenitors enriching the ISM at the formation time of our stars. The work by Travaglio et al. (1999) showed that the best progenitors for reproducing the r-process contribution to the enrichment of the Galaxy are SNe II from stars with masses 8–10 M⊙. On the other hand, more massive SNe II of M > 15 M⊙ enriched the ISM with oxygen at earlier times since those massive stars evolve faster. As a consequence we can observe that the ratios of r-process elements with respect to oxygen are negative for low metallicities. In Fig. 14 we show the ratios between Eu-Y-Ba and O using the abundances of the oxygen line at 6158 Å derived for the same sample by Bertran de Lis et al. (2015). Since we do not have very metal-poor stars we cannot observe the behaviour of Y and Ba at very low metallicities, where they are thought to be mainly produced by the r- and not the s-process. We can see how [Eu/O] has a less steep decline towards lower metallicities when compared to Ba and Y. This occurs because Eu is a pure r-process, whereas Y and Ba at [Fe/H] ~ –1 dex are mainly produced by AGB stars, which evolve more slowly than the progenitors of Eu and present an even longer delay with respect to the more massive progenitors of oxygen. At this point it is also interesting to compare our heavy elements with Mg, another α element, using the rederived abundances in this work. In Fig. 15 we can see the same decreasing trends towards lower metallicities for Y and Ba but less steep than when comparing oxygen, while [Eu/Mg] is mostly flat. This might be explained by increasing O/Mg yields for higher mass SNe progenitors (e.g. Woosley & Weaver 1995; McWilliam et al. 2008, and references therein). Thus, the production of oxygen would start earlier in the Galaxy producing higher [O/Mg] at lower [Fe/H]. Moreover, the [Eu/Mg] is mostly flat suggesting that these two elements receive an important contribution from SNe progenitors of similar masses but less massive than oxygen progenitors, as explained above. However, the study of McWilliam et al. (2008) discarded the possibility of increasing O/Mg yields for higher mass SNe progenitors since it would imply a metallicity-dependent initial mass function (IMF), that is, an increase in the fraction of low-mass SNe at higher [Fe/H]. Instead, they proposed that a metallicity-dependent modulation of the SNe O/Mg ratio can perfectly explain the behaviour of this ratio in the disc and in the bulge. In Fig. 15 it is also interesting to see the well-defined separation of thick disc and hαmr stars with respect to the thin disc group for [Y/Mg] and [Ba/Mg].
Citation: Bertran de Lis et al. (2015)
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