adsabs/FOCAL huggingface dataset:
The GMC associated with G305 is one of the most massive and luminous clouds in the Milky Way (Fig. 1). It is located in the Galactic plane at l ~ 305°, b ~ 0° and at a kinematic distance of 4 kpc (derived from a combinationof radio and Hα observationsby Clark & Porter (2004); Davies et al. (2012) measured its spectrophotometric distance to be 3.8 ± 0.6 kpc and most recently Borissova et al. (2019) measured the Gaia DR2 average distance to be 3.7 ± 1.2 kpc); this places it in the Scutum-Crux spiral arm. Given this distance, the complex has a diameter of ~ 30 pc (Clark & Porter 2004) and a molecular mass of ~6 × 105 M⊙ (Hindson et al. 2010). The G305 complex consists of a large central cavity that has been cleared by the winds from massive stars belonging to two visible central clusters (Danks 1 and 2) and the Wolf-Rayet star (WR48a; Clark & Porter 2004; Davies et al. 2012). The cavity is surrounded by a thick layer of molecular gas (traced by CO and NH3 emission; Hindson et al. 2010, 2013). Radio continuum observations by Hindson et al. (2012) have revealed that the cavity is filled with ionized gas and identified six ultra-compact HII (UC HII) regions and also one bright rimmed cloud (BRC) at the periphery of the cavity, indicating molecular gas irradiated by UV radiation (Sugitani & Ogura 1994; Thompson et al. 2004), which may cause implosion (Bertoldi 1989) or evaporation. A number of studies havereported star formation tracers (water and methanol masers, HII regions and massive young stellar objects, MYSOs; Clark & Porter 2004; Lumsden et al. 2013; Urquhart et al. 2014; Green et al. 2009, 2012). Furthermore, Hindson et al. (2010) found the concentration of star formation tracers to be enhanced inside a clump of NH3 bearing molecular gas that faces the ionizing sources, which is consistent with the hypothesis that the star formation has been triggered. Analysis of the stellar clusters in the complex reveals them to have ages of 1.5 Myr for Danks 1 and 3 Myr for Danks 2,with the former possibly being triggered by the latter (Davies et al. 2012). Additionally, a diffuse population of evolved massive stars was also found to exist within the confines of the G305 complex that had formed around the same time as the two clusters (Leistra et al. 2005; Shara et al. 2009; Mauerhan et al. 2011; Davies et al. 2012; Faimali et al. 2012; Borissova et al. 2019).
Citation: Davies et al. 2012
Citation function: Background
Cometary activity is driven by the gas pressure P(s), which does not depend on the ice abundance, but only on the gas temperature: also minor species can drive cometary activity, provided that heat transfer inside a pebble is faster than ice depletion. This condition fixes an upper limit for the refractory-to-ice mass ratio δi (Fulle 2021)
(8)$$\begin{eqnarray*}
\delta _i \lt {\lambda _s \over {3 ~Q ~R ~c_p}} - 1
,
\end{eqnarray*}$$where cp ≈ 103 J kg−1 K−1 is the heat capacity of the pebbles (Blum et al. 2017). In order to fulfil equation (2) during the whole inbound orbit, cometary activity is driven by at least the five ices listed in Table 2, reporting the nucleus and gas coma parameters computed by means of the activity model (Fulle et al. 2020b). Thus, the less abundant the ice, the shorter the rh-range where it can drive cometary activity (e.g. ethane in Table 2). The upper limit of each water-to-ice mass ratio is δi/δw, and in the protoplanetary disc δw ≈ 5 (Cambianica et al. 2020). The probable activity due to further ices not listed in Table 2 and the decrease of cp with the temperature (Takahashi & Westrum 1970; Shulman 2004; Bouziani & Jewitt 2022) significantly increase the upper limits of δi. However, e.g. formaldehyde has unknown thermodynamical parameters (Fray & Schmitt 2009), and e.g. ethylene and nitric oxide were not detected in 67P (Rubin et al. 2020), thus preventing a realistic computation of e.g. evolving cp values. According to the activity model, the distribution of water-ice is very inhomogeneous in the nucleus (Ciarniello et al. 2022), with water-rich pebbles, depleted of supervolatiles, embedded in a matrix of water-poor pebbles, which are rich of the ices listed in Table 2. Therefore, at rh > 3.8 au, dust is ejected from water-poor pebbles only, characterized by δw ≈ 50 (Fulle 2021), so that equation (2) is surely verified. In water-poor pebbles the water ice is less abundant than all other ices (excluded ethane, Table 2), so that these ices cannot be trapped inside a less abundant water ice. The observed activity of C/2017K2 at rh = 23.7 au (Jewitt et al. 2017) excludes also that ices may be trapped inside CO2-ice, because the CO2-driven activity onsets at rh = 13 au (Table 2).
Citation: Fulle et al. 2020b
Citation function: Uses
TYC 9486-927-1 was observed by Torres et al. (2006) as part of the Search for Associations Containing Young stars (SACY) programme (Torres et al. 2008). They assigned a spectral type of M1 and measured a radial velocity of vrad = 8.7 ± 4.6 km s−1 from 10 observations. The large uncertainty is likely due to the star's high rotational velocity (vsin i = 43.5 ± 1.2 km s−1); suggesting it is either a single rapid rotator or a spectroscopic binary with blended lines. TYC 9486-927-1 also shows signs of activity in X-ray (Thomas et al. 1998), H α emission (Torres et al. 2006) and the UV (using GALEX data from Martin et al. 2005 we find log FFUV/FJ = −2.49, log FNUV/FJ = −2.11). 2MASS J2126−8140 is an L3 first identified by Reid et al. (2008, although referencing Cruz, Kirkpatrick & Burgasser 2009 as the discovery paper). Subsequently Faherty et al. (2013) classified it as a low gravity L3γ (using the gravity classification system of Cruz et al. 2009). Recent VLT/ISAAC observations by Manjavacas et al. (2014) find it is a good match to the young, L3 companion CD-35 2722B (Wahhaj et al. 2011). These authors also used the spectral indices of Allers & Liu (2013) to confirm that the 2MASS J2126−8140 is an L3 and shows low gravity spectral features. Manjavacas et al. (2014) also used the BT-Settl-2013 atmospheric models (Allard, Homeier & Freytag 2012) to derive Teff = 1800 ± 100 K, log g = 4.0 ± 0.5 dex, albeit with better fits to supersolar metallicity models. Filippazzo et al. (2015) use photometry, a trigonometric parallax of 31.3 ± 2.6 mas (referenced to Faherty et al., in preparation) and evolutionary models to derive an effective temperature of 1663 ± 35 K. They also derived a mass of 23.80 ±1 5.19 MJ assuming a broad young age range of 10–150 Myr. Gagné et al. (2014) listed 2MASS J2126−8140 as a high probability candidate member of Tucana–Horologium association (TucHor) but noted that its photometric distance would be in better agreement with its TucHor kinematic distance if it were an equal mass binary.
Citation: Martin et al. 2005
Citation function: Uses; Uses
Despite the differences of the dust analogues retained in previous studies (Mennella et al. 1998; Boudet et al. 2005; Coupeaud et al. 2011) and in the present one, the spectroscopic properties and temperature dependent behavior of all these analogues remain qualitatively similar: the MAC value is correlated with the dust temperature and has a complex spectral shape differing from a simple asymptotic behavior in λ-2. At the same time, because of these differences between the samples in terms of internal structure, composition, porosity, homogeneity, the shape of the MAC in the FIR varies. Consequently, the MAC value at a given wavelength of all samples from this study and from previous studies spans a large range of values (see Table 1 for the MAC value of the samples studied here and Table 1 from Demyk et al. 2013, for previous studies at 1 mm). It must be noted that the MAC in Boudet et al. (2005) has been corrected for grain shape effect whereas in Coupeaud et al. (2011) and Mennella et al. (1998) and in the present study this correction was not applied (see Sect. 2.3). This partly explains why the MAC value are smaller in Boudet’s study, together with the effect of differences in the samples in terms of composition and structure. At 100 μm, the MAC values of all the samples from this study and from previous work are similar at 300 and 10 K (50–300 cm2 g-1 at 300 K and 40–260 cm2 g-1 at 10 K). At 500 μm, the MAC is greater at 300 K than at 10 K (2–20 cm2 g-1 at 300 K and 0.7–13 cm2 g-1 at 10 K). This is also the case at 1 mm where the MAC is in the range 0.1–11 cm2 g-1 at 300 K and 0.12–7 cm2 g-1 at 10 K. We note that for each sample the MAC at 300 K is always greater than at 10 K. Furthermore, the fact that the range of values of the MAC at 300 K and 10 K overlaps results from the dispersion of the measured spectra. This diversity of the MAC value and spectral shape that vary as a function of the materials studied can be problematic for astrophysical applications since one has to decide what analog is the most relevant and should be used in the modeling. This is considered in more detail in Sect. 5.
Citation: Coupeaud et al. (2011)
Citation function: Similarities; Similarities
The QBOs are also found in the local wavelet power spectra of the Bx, By, and Bz that are displayed in the left panel of Figure 2. As this figure shows, the significant regions of above 95% confidence level in the range of 256–512 days (peak at 1.01 yr) for Bx intermittently appear during 1975–2000, and those in the range of 256–600 days (peak at 1.02 yr) for By are also intermittently found during 1975–2000. The QBOs for Bz only appear in solar cycle 22, which corresponds to the significant period of 0.90 yr, and also peak at 1.58 and 2.77 yr. The possible period of 3.45 yr for Bx does not show the corresponding significant region in the local wavelet power spectrum. The significant region that corresponds to the possible period of 2.37 yr for By appears near 1992. Early study proved that the solar QBOs can be transmitted into interplanetary space by the open magnetic flux (Lockwood 2001; Bazilevskaya et al. 2014); thus, the QBOs found in the Bx, By, and Bz components should be related to the solar QBOs. On the other hand, the annual variation in the IMF polarity in the band of 256–512 days, which is referred to the Rosenberg–Coleman effect (Rosenberg & Coleman 1969), only appears in the ascending phase of solar cycles by studying the IMF polarity date for the years 1927–2002 through the wavelet analysis method (Echer & Svalgaard 2004). The authors indicated that such a result should be attributed to a more stable and flat heliospheric current sheet that only appears in the ascending phase of solar cycles and strong disturbance of the heliospheric current sheet that is present in the declining phase and minimum time of solar cycles, and the Rosenberg–Coleman effect had been confirmed by the IMF Bx component during 1964–2002. The wavelet power spectra of the IMF Bx and By components in Figure 2 show that the annual variation in two time series can also be found in some, but not all, ascending phases of solar cycles, which is partly similar to the wavelet map of the IMF polarity in Echer & Svalgaard (2004). Thus, the annual variation in the IMF Bx and By components is also modulated by the stability or strong disturbance of the heliospheric current sheet. However, the wavelet power spectra of the IMF Bz show a different result, which indicates that the annual variation in this time series should not be related to the heliospheric current sheet.
Citation: Rosenberg & Coleman 1969
Citation function: Uses; Compare/Contrast
Magnetohydrodynamic (MHD) shallow water equations are an alternative to complete system of MHD equations for plasma. In this approximation, a thin layer of plasma with a free boundary in a gravity field is studied (Gilman 2000). Shallow water flows with rotation are usually considered in case of large-scale flows in plasma astrophysics (Gilman 1967) and play an important role in understanding of various astrophysical objects. Such a model is used to study large-scale flows of the solar tachocline (a thin layer inside the Sun, located above the convective zone) (Gilman 2000; Dikpati & Gilman 2001; Miesch & Gilman 2004; Hughes, Rosner & Weiss 2007), flows of accreting matter in neutron stars (Inogamov & Sunyaev 1999, 2010; Spitkovsky, Levin & Ushomirsky 2002), dynamics of the atmospheres of neutron stars (Heng & Spitkovsky 2009), and magnetoactive tidally locked atmospheres of exoplanets (Cho 2008; Heng & Showman 2015; Batygin, Stanley & Stevenson 2017; Pierrehumbert & Hammond 2019). MHD shallow water equations are obtained by depth-averaging three-dimensional MHD equations of plasma layer with respect to pressure being hydrostatic and the height of the layer being much smaller than characteristic horizontal scale of motion. However, the depth-averaging procedure does not always lead to shallow water equations. Although the equations obtained by integrating over the height of the studied layer of the liquid will have a form similar to the equations of shallow water (Klimachkov & Petrosyan 2017b).1 Equations obtained in this paper are similar to MHD shallow water equations, but they have additional terms and equations referred to vertical magnetic field (Klimachkov & Petrosyan 2017a; Fedotova, Klimachkov & Petrosyan 2020). These new equations transform into common MHD shallow water equations (Gilman 2000) in case of zero vertical magnetic field. Due to this, hereinafter we name our approximation as quasi-two-dimensional MHD approximation and equations are named as quasi-two-dimensional equations for rotating astrophysical plasma with vertical magnetic field.2 Detailed review of wave processes in magnetohydrodynamics of astrophysical plasma with vertical magnetic field is presented in Petrosyan et al. (2020). Extensions of magnetohydrodynamics in plasma astrophysics for vertically stratified flows with vertical magnetic field can be found in Fedotova, Klimachkov & Petrosyan (2021).
Citation: Spitkovsky, Levin & Ushomirsky 2002
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The formation and evolution of S0 galaxies are very important for understanding the formation and evolution of galaxies, but they are still an open question (e.g., the recent review by D’Onofrio et al. 2015). Currently, there are two possible scenarios on the origin of S0 galaxies. One is that S0 galaxies are transformed from spiral galaxies, where spirals lose their gas and star formation is rapidly quenched. The other is that S0 galaxies are intrinsically different from spiral galaxies since their formation (Kormendy & Kennicutt 2004; Barway et al. 2009; van den Bergh 2009). The transformation origin may be associated with intra-cluster medium and neighboring galaxies, via minor mergers, slow encounters, galaxy harassments (Moore et al. 1996), or tidal effects in the dense environment (Gunn & Gott 1972; Larson et al. 1980; Dressler & Sandage 1983; Mihos & Hernquist 1994; Moore et al. 1998, 1999; Neistein et al. 1999; Shioya et al. 2002). A lot of studies have discussed the environmental dependence of galaxy evolution. Generally speaking, early-type galaxies tend to be in dense environments and have low star-formation rates (SFRs; Dressler 1980; Balogh et al. 1997, 1998, 2000; Poggianti et al. 1999; Treu et al. 2003). The fraction of S0 galaxies in the field is only about 15%, while spirals are the majority (Naim et al. 1995). Within the group environment, spirals and S0s are both about 40%–45% (Postman & Geller 1984). Furthermore, S0s become dominant in dense environments, the fraction grows up to 60% in clusters (Dressler 1980; Postman & Geller 1984). Dressler et al. (1997), Fasano et al. (2000), and Desai et al. (2007) also found that the galaxy morphological distributions change abruptly in clusters at 





, about 50 ∼ 70% of spirals at high redshift (z > 0.4) are transformed into S0s, while a fraction of ellipticals, about 25%, remains nearly constant between z = 0.8 and z = 0.0. However, Wilman et al. (2009) showed that the fraction of S0s in groups is the same as in clusters but it is much higher than in the field at z = 0.4, which might suggest that S0s are formed in groups or subgroups.
Citation: van den Bergh 2009
Citation function: Background; Background
Extended radio emission in galaxies is associated with both radio jets and lobes and with outflows, seen often as aligned radio sources in the opposite directions with respect to the central compact radio core. Giant radio galaxies (GRG) are extreme cases of this phenomenology with jets and lobes extending on ∼ Mpc scales suggesting that they are either very powerful or very old site for electron acceleration. In this respect, GRGs have a crucial role in the acceleration of cosmic rays over large cosmic scales (e.g. Kronberg et al. 2004), in the feedback mechanism of AGNs into the intergalactic and intracluster medium (e.g. Subrahmanyan et al. 2008) and in the seeding of large-scale magnetic fields in the universe (e.g. Kronberg et al. 2004) and they are excellent sites to determine the total jet/lobe energetics in AGN-dominated structures (see e.g. Colafrancesco 2008, Colafrancesco & Marchegiani 2011). To date our knowledge of GRGs (see e.g. Ishwara-Chandra & Saikia 1999, 2002; Lara et al. 2001; Machalski, Jamrozy & Zola 2001; Schoenmakers et al. 2001; Kronberg et al. 2004; Saripalli et al. 2005; Malarecki et al. 2013; Butenko et al. 2014) is limited by their sparse numbers and by the difficulty of detecting them over large areas of the sky. Low-frequency radio observations have an enhanced capacity to detect the extended old electron population in these objects (see e.g. the recent Low Frequency Array – LOFAR – observation of the GRG UGC095551), but high-frequency radio observations are less efficient in this task due to the steep-spectra of giant radio lobes. In this context these sources will be ideal targets for the next coming deep, wide-field surveys like, e.g. the ATLAS survey of the Australia Telescope Network Facility (ATNF; see Norris et al. 2009) or the Square Kilometre Array (SKA) deep surveys that will have the potential to study their population evolution up to high redshifts and thus clarifying their role on the feedback for the evolution of non-thermal processes in large-scale structures.
Citation: Kronberg et al. 2004
Citation function: Background
Citation: Kronberg et al. 2004
Citation function: Background; Background; Future Work; Future Work
Citation: Kronberg et al. 2004
Citation function: Motivation
Galaxy colour is known to be sensitive to local density. Generally, sheets are denser than fields and filaments are denser than sheets. So the dependence of red and blue fractions on the geometry of large-scale environment shown in Fig. 5 may partly arise due to dependence of galaxy colour on local density. We need to decorrelate the effect of local density in order to test the role of large-scale structures on galaxy colours. We address this issue by calculating local number density of galaxies using kth nearest neighbour method (Casertano & Hut 1985). We compute the local number density using equation (2) with k = 5. We plot the local density against the local dimension of galaxies in three different volume-limited samples in Fig. 7. The top left, middle left, and bottom left panels of Fig. 7 show the relations between local dimension and local density for the three volume-limited samples when local dimensions are computed using $R_2=10 {\, h^{-1}\, {\rm Mpc}}$. The results in these panels show that the environments with larger local dimension indeed tend to have a lower local density. However, these relationships show very large scatters. The environments with local dimension up to D = 2.5 can have a wide range of local densities and it is difficult to assign a specific density range to the environments with different local dimensions. The three panels in the middle column and three panels in the right column of Fig. 7 show the relations between local density and local dimension in these samples for $R_2=40 {\, h^{-1}\, {\rm Mpc}}$ and $R_2=70 {\, h^{-1}\, {\rm Mpc}}$. They show a similar trend as seen in the three panels in the left column of the same figure. It may be noted that galaxies with smaller local dimension are progressively absent when the geometry of environments are characterized on larger length-scales. This points out to the emergence of a homogeneous network of galaxies on larger length-scales as mentioned earlier.
Citation: Casertano & Hut 1985
Citation function: Uses
Finally, our models assume the absence of planetary magnetic fields. The early paradigm considering the evolution of terrestrial planets has implied that the planetary magnetic field is necessary to protect planetary atmospheres and reduce the atmospheric mass loss (see e.g. Dehant et al. 2007, and references therein). The later studies, however, show that this point of view is ambiguous. Thus, the effect of the magnetic field on the atmospheric escape can be considered as a result of the two concurring processes: reducing the escape by capturing the ionised atmospheric species within the closed magnetic field lines, and enhancing the escape of the atmospheric ions through the regions of the open magnetic lines (polar cusps, in the case of a dipole field) and the reconnection on the night-side (see, e.g. Khodachenko et al. 2015; Sakai et al. 2018; Carolan et al. 2021). Thus, for planets in the Solar System, it was shown both in the observations (Gunell et al. 2018; Ramstad & Barabash 2021) and by modelling (Sakai et al. 2018; Egan et al. 2019) that the presence of a weak magnetic field can intensify atmospheric escape. These results, however, should be taken with caution for young planets, and in particular those in the sub-Neptune range, because of the different atmospheric structures and the non-thermal mechanisms dominating the atmospheric mass loss in the Solar System, which are contrary to the planets considered in this study (see, e.g. Scherf & Lammer 2021, for the discussion). For hot Jupiters, Khodachenko et al. (2015) predict a significant suppression of escape for intrinsic magnetic fields larger than 0.3 G. The model with the closest setup to this study by Carolan et al. (2021) predicts, however, for the 0.7Mjup planet experiencing XUV (thermally) driven atmospheric escape, a small increase in the atmospheric mass-loss rate with increasing dipole field strength (about twice between 0 and 5 G). We therefore expect that the possible effect from the planetary intrinsic magnetic field depends largely on the strength and configuration of the planetary and stellar magnetic fields, but, according to the numbers reported in the literature, might not affect our results dramatically. The lack of studies for close-in sub-Neptune-like planets, however, holds us from making final conclusions.
Citation: Gunell et al. 2018
Citation function: Compare/Contrast; Compare/Contrast