The calculation of mass outflow rates, especially in the ionized gas phase, have often come from measurements using integrated fibre or long-slit spectra, where several assumptions are invoked in the outflow modelling. These assumptions, briefly described here, result in ‘time-averaged global mass outflow rate’ with large systematic uncertainties. First, due to the limitations of the current instruments even on large telescopes, an accurate modelling of the outflow geometry is not possible. This is especially true for high redshift galaxies (z∼2) where, with currently available adaptive optics (AO) technology, one can at best achieve a spatial resolution of ∼2 kpc where the bulk of the outflow might reside (e.g. Brusa et al. 2016; Davies et al. 2020b). Therefore, the outflow geometry is either assumed to be a uniformly filled conical, bi-conical, or spherical thin shells (e.g. Veilleux, Shopbell & Miller 2001; Fischer et al. 2013; Riffel, Storchi-Bergmann & Winge 2013; Ishibashi & Fabian 2015; Thompson et al. 2015; Bae & Woo 2016; Husemann et al. 2019; Mingozzi et al. 2019). Secondly, if the data are obtained from fibre and single-slit spectroscopy, the size of the outflow is largely unconstrained. For long-slit observations, as an example, the outflow size depends on whether the slit is oriented along the outflow direction. This can be mitigated by using integral field spectroscopy (IFS) which is being increasingly used for extragalactic studies (e.g. Liu et al. 2013; Rupke & Veilleux 2013; Harrison et al. 2014; Maiolino et al. 2017; Husemann et al. 2019; Schönell et al. 2019; Rupke, Thomas & Dopita 2021), although there could still be projection effects with the IFS data. Thirdly, accurate determination of electron density and electron temperature is required for the ionized mass outflow rate calculations. Electron density is usually derived from emission lines that arise out of two closely spaced ‘metastable’ energy levels such as [S ii]λλ6716,6731 ([S ii] doublet hereafter). Density measured from the [S ii] doublet is sensitive to values between ∼10 and 5000 cm−3, typical in the Narrow Line Region (NLR) of AGN host galaxies (e.g. Osterbrock & Ferland 2006; Perna et al. 2017; Baron & Netzer 2019; Davies et al. 2020a). The [S ii] doublet is significantly weaker than the lines used to trace ionized outflows such as the [O iii]λ5007 and H α. In high redshift galaxies, it is extremely challenging to detect these doublet lines, despite hours of observations on a single target. Therefore, nominal density values are often assumed in mass outflow rate calculations, resulting in systematic uncertainties of up to 2–3 orders of magnitude. Furthermore, the density structure within the outflowing medium is often non-uniform, when resolved in low redshift galaxies (e.g. Kakkad et al. 2018). Therefore assuming a constant density within the outflowing medium often leads to inaccurate outflow rate and kinetic energy values. Collectively, these assumptions result in a systematic uncertainty of approximately 3–4 orders of magnitude (e.g. Harrison et al. 2018). This implies that the quoted values of coupling efficiency in the literature have a wide range, with the actual efficiency still an unknown in most of the studies.


To check for the validity of this idea, the case of some PACWBs already investigated in X-rays deserves to be examined. Some systems, such as WR 140 (Williams et al. 1990; Pollock et al. 2005) or Cyg OB2 #8A (Harnden et al. 1979; De Becker et al. 2006), are indeed known to be both well-studied PACWBs and bright thermal X-ray emitters, due to their colliding winds. However, other examples should be commented. The first is HD 167971. It consists of a hierarchical triple system with a 3.3-day O-type binary and a third later-type companion evolving on a 21-yr orbit (De Becker et al. 2012; Ibanoglu et al. 2013). Recently, it has been demonstrated that its thermal X-ray spectrum is dominated by the colliding-wind region in the close binary, with only a weak/moderate contribution coming from the wind-wind interaction in the wide orbit (De Becker 2015). However, it has also been demonstrated that HD 167971 presents a non-thermal radio emission modulated with a period of 21 yr, thus providing compelling evidence for a colliding-wind region origin (Blomme et al. 2007). In addition, HD 167971 is the brightest O-type synchrotron radio emitter included to date in the catalogue of PACWB. Another relevant example is HD 93129A. It is known as an early O-type wide binary with undetermined period (probably more than a century), with non-thermal radio emission recently imaged in Long Baseline Array observations (Benaglia et al. 2015). The direct imaging of this emission region points to a clear and significant synchrotron radio emission coincident with the colliding-wind region. However, the investigation in X-rays by Gagné et al. (2011) did not point to any strong over-luminosity attributable to an X-ray bright wind-wind interaction region. These examples demonstrate that the association between bright thermal X-ray emission and bright non-thermal radio emission is not necessarily clear. As a result, the quest for new members of the catalogue should by no means be restricted to objects known to display a bright thermal soft X-ray spectrum.


Both the magnitude and slope of nuclear symmetry energy contribute to the pressure of NS matter. For example, the pressure of npe matter in NSs at β equilibrium at density ρ and isospin asymmetry δ is explicitly
2

The first term is the SNM pressure

, while the last two terms are the isospin-asymmetric pressure

 from nucleons and electrons, separately. At the saturation density ρ0, P0 vanishes, and the electron contribution is also negligible, leaving the total pressure completely determined by the slope of the symmetry energy. Both P0 and Pasy increase with density with rates determined separately by the respective density dependences of the SNM EOS and the symmetry energy. In the region around ρ0 ∼ 2.5ρ0, Pasy dominates over P0 using most EOSs available. At higher densities, the SNM pressure P0 dominates, while Pasy also plays an important role, depending on the high-density behaviors of nuclear symmetry energy (Li & Steiner 2006). The exact transition of dominance from Pasy to P0 depends on the stiffnesses of both the SNM EOS and the symmetry energy. It is also well known that the radius R1.4 of canonical NSs is essentially determined by the pressure at densities around ρ0 ∼ 2.5ρ0 (Lattimer & Prakash 2000), while the maximum mass of NSs is determined by the pressure at higher densities reached in the core. Thus, knowledge of the density dependence of nuclear symmetry energy is important for understanding measurements of the masses and especially the radii of NSs. Moreover, the critical densities for forming hyperons (Sumiyoshi & Toki 1994; Lee 1996; Kubis & Kutschera 2003; Providência et al. 2019), Δ(1232) resonances (Drago et al. 2014; Cai et al. 2015; Zhu et al. 2016; Sahoo et al.2018; Ribes et al. 2019), kaon condensation (Odrzywolek & Kutschera 2009), and the quark phase (Di Toro et al. 2010; Wu & Shen 2019) are also known to depend sensitively on the high-density nuclear symmetry energy. Information about the latter is thus a prerequisite for exploring the evolution of the NS matter phase diagram in the isospin dimension. Once Esym(ρ) is better determined and, hopefully, with more astrophysical data, it will be interesting to introduce extra model parameters characterizing the physics associated with the exotic particles and/or new phases predicted to appear in superdense neutron-rich matter. With the very limited data available and the expensive computational costs of simultaneously inferring a lot more than the six EOS parameters we already have in the minimum NS model consisting of only nucleons and two leptons, our goals in this work are conservative and practical. However, inferring new physics parameters associated with the exotic degrees of freedom and new phases in superdense neutron-rich matter from astrophysical data by extending the model used in the present work are high on our working agenda.


We have studied a sample of 263 LSB galaxies observed by Green Bank Telescope (Schneider et al. 1992) which are in overlap with the SDSS footprint. We have performed two-component bulge-disc decomposition of 263 galaxies in the SDSS g, r and, i bands and investigated their structural properties in detail. We have found that $60\hbox{ per cent}$ LSBs in our specific sample are bulgeless, while $40\hbox{ per cent}$ are with bulges. Some of the LSBs are associated with significant bulge component with B/T> 0.1. Since LSBs are known to be dwelling in less-dense environment (Rosenbaum & Bomans 2004), mergers and interactions are unlikely to have led the bulge formation. We also have $15 \hbox{ per cent}$ barred galaxies in our sample. Our findings of bulges and bars suggest a considerable on-going evolution in the local LSB galaxies and the bars might as well be playing a role in the bulge growth (Laurikainen et al. 2007; Gadotti 2011; Cheung et al. 2013). The interesting fact about our sample is that they are not the class of giant LSB galaxies, in fact, most of our LSBs are faint blue and gas-rich and roughly half of them are hosting bars and bulges. Since LSB galaxies are dark matter-dominated, discs are known to be stable against bar formation (Ostriker & Peebles 1973; Efstathiou, Lake & Negroponte 1982; Christodoulou, Shlosman & Tohline 1995; Cervantes Sodi, Li & Park 2015; Algorry et al. 2017), as shown in numerical simulations of stellar discs with dark matter dominance at all radii (Saha 2014). Question arises how these faint blue LSBs are making bars and bulges. One possibility is that LSB discs are embedded in dark matter haloes that are spinning (Jimenez et al. 1998; Vitvitska et al. 2002; Kim & Lee 2013) which might be promoting bar formation provided spin parameter is not too high (Saha & Naab 2013; Cervantes-Sodi et al. 2013; Long, Shlosman & Heller 2014; Collier, Shlosman & Heller 2018). Whether these bars lead to the formation of bulges or other processes such as minor mergers being involved, needs further and detailed investigation.


Vela X-1 (4U 0900−40) is an eclipsing high-mass X-ray binary (HMXB) discovered during rocket borne X-ray observations in 1967 (Chodil et al. 1967). It is located at a distance of ∼2.0 kpc (Sadakane et al. 1985; Nagase 1989) in the Vela constellation. Recent estimates using Gaia data infer distance of $2.42^{+0.19}_{-0.17}$ kpc (Bailer-Jones et al. 2018). The system consists of a massive B0.5Ib supergiant HD 77581 (Brucato & Kristian 1972; Hiltner, Werner & Osmer 1972; Jones & Liller 1973; Vidal, Wickramasinghe & Peterson 1973) having mass of about ∼23 $\rm {M_\odot }$ and radius of ∼34 $\rm {R_\odot }$ (Van Paradijs et al. 1976; Joss & Rappaport 1984; Nagase 1989; van Kerkwijk et al. 1995) and a neutron star with mass ∼1.8 $\rm {M_\odot }$ (Van Paradijs et al. 1976; Nagase 1989; Barziv et al. 2001; Rawls et al. 2011). The orbital period of the binary system is about 9 d (Hiltner et al. 1972; Forman et al. 1973; Vidal et al. 1973; Watson & Griffiths 1977; van Kerkwijk et al. 1995). Due to the close proximity of about 1.7 $\rm {R_\star }$ (Conti 1978; Quaintrell et al. 2003) between the neutron star and its companion, the neutron star is immersed in the dense stellar wind of the donor star having typical mass-loss rate of about $\dot{M} \mathrm{\sim 10^{-6} ~{M_\odot } \, yr^{-1}}$ (Hutchings 1974; Dupree et al. 1980; Nagase et al. 1986; Sako et al. 1999). A fraction of the stellar wind is captured and channelled along the strong magnetic field (∼2.7 × 1012 G; Kretschmar et al. 1996; Coburn et al. 2002; Kreykenbohm et al. 2002) of the neutron star on to the magnetic poles, producing regular X-ray pulsations caused by the spin period ∼283 s (Rappaport & McClintock 1975; McClintock et al. 1976) of the neutron star. Although Vela X-1 is known to be a persistent source having luminosity of about 4 × 1036 erg s−1 (McCray et al. 1984; Sadakane et al. 1985; Nagase et al. 1986; Kreykenbohm et al. 2002), it shows a plethora of X-ray variabilities such as sudden flares lasting a few minutes to several hours wherein the luminosity increases by several folds within very short time-scales of a few tens of seconds (Lapshov et al. 1992; Staubert et al. 2004; Kreykenbohm et al. 2008). Occurrence of sudden flares in this system are not so well understood and is believed to be due to enhanced accretion rate due to variabilities in the stellar wind from the companion star (Nagase et al. 1983; Haberl & White 1990) or accretion of clumpy stellar wind (Staubert et al. 2004; Ducci et al. 2009; Fürst et al. 2010; Odaka et al. 2013). Some studies suggest that sudden flares might be related to formation of transient accretion disc (Inoue et al. 1984; Taam & Fryxell 1989; Haberl & White 1990; Kreykenbohm et al. 2008). Another bizarre manifestation seen in Vela X-1 is occurrence of abrupt ‘off-states’ wherein X-ray pulsations cessation (within less than the pulse period) is observed for several tens of minutes at a time (Inoue et al. 1984; Lapshov et al. 1992; Kreykenbohm et al. 1999, 2008; Doroshenko, Santangelo & Suleimanov 2011; Sidoli et al. 2015). These states are poorly understood and might be caused by changes in the accretion rate due to variabilities in the stellar wind (Lapshov et al. 1992; Coburn et al. 2002). Some earlier studies also suggest that ‘off-states’ might be associated with formation of transient accretion discs (Inoue et al. 1984) or the accretion is choked due to the sudden onset of propeller effect (Kreykenbohm et al. 2008). It has also been suggested that the onset of these ‘off-states’ can be caused due to transition from the higher luminosity Compton cooling regime to the lower luminosity radiative cooling regime (Shakura, Postnov & Hjalmarsdotter 2013) or due to unstable hydrodynamic flows in the vicinity of the neutron star (Manousakis & Walter 2015a). Recent numerical studies suggest formation of temporary accretion discs in wind-fed X-ray pulsars (Karino, Nakamura & Taani 2019; El Mellah, Sundqvist & Keppens 2019a; El Mellah et al. 2019b) but conclusive evidence of their existence has been elusive. Interestingly, Liao et al. (2020) infer presence of temporary accretion disc in Vela X-1 during an extended low state lasting at least 30 ks that was accompanied by unusual spin-up event and similar Fe Kα fluxes compared to the preceding flaring period.


Over the past decade, many attempts to address this issue have been carried out, such as from the perspective of conventional nuclear physics and even exotic physics beyond the standard BBN framework (Angulo et al. 2005; Cyburt et al. 2008, 2016; Boyd et al. 2010; Pospelov & Pradler 2010; Fields 2011; Kirsebom & Davids 2011; Wang et al. 2011; Broggini et al. 2012; Coc et al. 2012, 2013, 2014; Cyburt & Pospelov 2012; Kang et al. 2012; Voronchev et al. 2012; Bertulani et al. 2013; Hammache et al. 2013; He et al. 2013; Kusakabe et al. 2014; Pizzone et al. 2014; Yamazaki et al. 2014; Hou et al. 2015, 2017; Famiano et al. 2016; Damone et al. 2018; Hartos et al. 2018; Luo et al. 2019; Rijal et al. 2019; Clara & Martins 2020). However, despite the fact some solutions using exotic physics have succeeded in resolving this issue, it appears there is still no universally accepted solution in the academic community since validations of these mysterious exotic physics are beyond the capabilities of current science. Conversely, it seems more worthwhile to exclude any potential possibility of resolving the 7Li discrepancy from the perspective of nuclear physics. It is known that the majority of the primordial 7Li production arises from the decay of 7Be by electron capture during the 2 months after BBN stops. Thus, for the solution of the Li problem, reactions involving 7Be could be more significant than those involving 7Li. Therefore, many reactions that potentially destroy 7Be were investigated to solve this discrepancy over past 10 yr (Kirsebom & Davids 2011; Broggini et al. 2012; Hammache et al. 2013; Hou et al. 2015; Hartos et al. 2018). Meanwhile, enormous efforts have been made to refine the reaction rates of key BBN reactions in the past 20 yr (Smith et al. 1993; Descouvemont et al. 2004; Serpico et al. 2004; Cyburt & Davids 2008; Neff 2011; Pizzone et al. 2014; Tumino et al. 2014; Hou et al. 2015; Barbagallo et al. 2016; Iliadis et al. 2016; Kawabata et al. 2017; Lamia et al. 2017, 2019; Damone et al. 2018; Rijal et al. 2019; Mossa et al. 2020), but the probability of solving or alleviating the 7Li problem by improving our knowledge of relevant nuclear reaction rates still cannot be eliminated. Recent experiments for key nuclear reactions like 7Be(n,p)7Li and 7Be(d,p)24He allow for a reduction of the 7Li production by about 12% (Damone et al. 2018; Rijal et al. 2019) compared to previous calculations. At present, nuclear uncertainties cannot rule out that some of the reactions destroying 7Li are indeed more efficient than those currently used (Boyd et al. 2010; Chakraborty et al. 2011).


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.


Our group is addressing this problem by combining a variety of complementary perspectives: (i) by constructing a new generation of high-quality star density profiles derived from star counts instead of surface brightness (see Lanzoni et al. 2007a, 2010, 2019; Miocchi et al. 2013; Pallanca et al. 2021); (ii) by investigating the population of stellar exotica (Ferraro et al. 2001, 2003, 2015, 2016; Pallanca et al. 2010, 2013,2014, 2017; Cadelano et al. 2017, 2018, 2020) and their connection with the dynamical evolution of the parent cluster (see Ferraro et al. 2009, 2012, 2018a, 2019; Lanzoni et al. 2016); (iii) by characterizing the three-dimensional (3D) global velocity space through the analysis of the velocity dispersion profile and rotation curve from resolved star spectroscopy (Lanzoni et al. 2013, 2018a, 2018b; Ferraro et al. 2018b) and proper motions (PMs; see Raso et al. 2020). The determination of GGC internal kinematics from resolved star velocities is particularly relevant and challenging. In this context we promoted the ESO-VLT Multi-Instrument Kinematic Survey (hereafter the MIKiS survey; Ferraro et al. 2018b, 2018c), a project specifically designed to characterize the kinematical properties of a sample of GGCs in different dynamical evolutionary stages from the radial velocities (RVs) of hundreds of individual stars distributed over the entire radial range of each stellar system. To this end, the survey fully exploits the spectroscopic capabilities of different instruments currently available at the ESO Very Large Telescope (VLT): originally designed to use the adaptive optics (AO) assisted integral-field spectrograph SINFONI, the multiobject integral-field spectrograph KMOS, and the multiobject fiber-fed spectrograph FLAMES/GIRAFFE, it has been recently complemented with individual projects and an ongoing large program (PI: Ferraro) fully exploiting the remarkable performances of the AO-assisted integral-field spectrograph MUSE.


It is interesting that the tracers of atomic and molecular hydrogen become maximum at distances ∼0.85 kpc, where no dust cloud is inferred from the Swift/XRT data (see Fig. 5). A fiducial dust cloud at the distance of ∼0.85 kpc would produce an X-ray ring with angular size ∼9 arcmin on MJD 57205.5. As this would fall well within the Swift/XRT FOV (see Fig. 2), its absence should be related to the dust properties of the respective cloud. We estimated therefore that the maximum grain size should be ≫ 0.2 μm. A dust cloud composed by large grains ( ∼ 1 μm) would suppress the scattered intensity even at 1 keV, while it would significantly attenuate X-rays at ≤0.5 keV (e.g. Smith & Dwek 1998; Corrales & Paerels 2015). Alternatively, the absence of the X-ray ring might indicate a much smaller number of grains per hydrogen atom at ∼0.85 kpc compared to the other clouds. The analysis presented so far, as in most studies, does not take into account possible variations of the radial profiles in the azimuthal direction. We remind that the profiles shown in Figs 3 and B1 were created by summing the counts of each annulus, i.e. integrating over the azimuthal angle. Although this method is sufficient for probing the average properties of the dust clouds, such as position and average column density, it cannot provide information about the spatial inhomogeneity of the dust clouds and/or their inclination with respect to the LOS. The photon statistics of the Swift/XRT observations are sufficient for quantifying the azimuthal variations of the ring intensity (see also Fig. 2). Fig. 12 shows the azimuthal variation of the scattered photons for Swift/XRT observation 2. There are three important features that need to be mentioned: (i) the radial profile of ring 5 is highly variable along the azimuthal direction, with the peak number of counts changing by a factor of ∼5 above the background level (see sub-panels for 180°–216° and 252°–288°); (ii) azimuthal variations are also present in the rings 3 and 4, yet the variability amplitude is lower when compared to the ring 5. The peak number of counts of the fourth ring is for all azimuth angles larger compared to that of the third ring; (iii) the azimuthal behaviour of the rings 1 and 2 is the most intriguing, as the second peak (corresponding to the ring 2) becomes prominent for azimuth angles 0°–36° and 324°–360° while the first peak dominates for azimuth angles of 216°–324°. Obviously, this information is lost from the azimuthal integrated radial profiles shown in Fig. 3. Similar features appear in all Swift/XRT observations with their significance varying according to the photon statistics of the observation.


One of the main uncertainties in elemental abundances is the quality of the adopted atomic data used in spectral synthesis calculations (Bigot & Thevenin 2008). The Belgian repository of fundamental atomic data and stellar spectra (BRASS) aims to provide astronomers with quality information for the large amount of atomic data available for high-resolution optical spectroscopy, in an attempt to help reduce systematic input errors in quantitative spectroscopy from atomic data and line selection (Lobel et al. 2017). Previously, we retrieved and cross-matched a large quantity of atomic data from several major atomic databases such as the Vienna Atomic Line Database (VALD3; Ryabchikova et al. 2015), the National Institute of Standards and Technology Atomic Spectra Database (NIST ASD; Kramida et al. 2018), and providers within the Virtual Atomic and Molecular Data Centre (VAMDC; Dubernet et al. 2016), in preparation for quality assessment work (Laverick et al. 2018; hereafter Paper 1). In this work the atomic data of seemingly “unblended” spectral lines are quality assessed against several benchmark dwarf stars, including the Sun, spanning late F-type to early K-type stars, for the spectral range 4200–6800 Å1. Unblended spectral lines for stars of ∼G2V spectral type are identified in a homogeneous manner using both the observed benchmark spectra, and the theoretical input line list of Paper I. Astrophysical oscillator strengths2 are derived for these unblended lines, using two commonly utilised methods, to gauge the reliability of the spectral line for quantitative spectroscopy and to produce “benchmark” log(g f) values for quality assessment of atomic data. The literature log(g f) values are then compared against these benchmark log(g f) values to determine which literature values reliably reproduce the stellar spectra of cool dwarf stars, and thus whether the values can be recommended for spectroscopic modelling. This paper presents three main sets of results:


Relativistic jets are the manifestation of the extreme processes that occur within the central regions of galaxies (see Blandford et al. 2019 for a review). Active galactic nuclei (AGNs) hosting relativistic jets closely aligned to the line of sight are called blazars. Due to their peculiar orientation, the relativistic amplification of the nonthermal jetted radiation (Doppler boosting; see, e.g., Rybicki & Lightman 1979) leads to the observation of a number of interesting phenomena. A few examples are detection at all accessible frequencies (e.g., Abdo et al. 2011), observation of temporal and spectral variability (Gaidos et al. 1996; Acciari et al. 2011; Fuhrmann et al. 2014; Paliya et al. 2017b), and superluminal motion and high brightness temperature (Scheuer & Readhead 1979; Lister et al. 2019). The optical and radio emissions detected from blazars are found to be significantly polarized (e.g., Fan et al. 2008; Itoh et al. 2016). The flux enhancement also makes blazars a dominating class of γ-ray emitters in the extragalactic high-energy sky (Ajello et al. 2020) and one of the very few astrophysical source classes detected at cosmic distances (e.g., Romani et al. 2004; Sbarrato et al. 2013). Blazars are classified as flat-spectrum radio quasars (FSRQs) and BL Lac objects based on their optical spectroscopic properties. FSRQs are characterized by broad emission lines (rest-frame equivalent width >5 Å), whereas BL Lac sources exhibit weak or no emission lines in their optical spectra, thereby making it challenging to detect their redshift (Stickel et al. 1991). BL Lac objects are known to exhibit a negative or mildly positive evolution compared to the strong positive evolution noticed in FSRQs (Ajello et al. 2012, 2014). Altogether, FSRQs dominate the known population of high-redshift (z ≳ 3) blazars and are found to be much more luminous than the BL Lac population (e.g., Ajello et al. 2009; Ackermann et al. 2017; Paliya et al. 2019d).


Recently, polarized (sub)millimetre emission has been detected in an increasing number of discs by Atacama Large Millimeter/submillimeter Array (ALMA) with its high sensitivity and angular resolution. However, the origin of disc polarization remains uncertain, since grains do not have to be aligned with just the magnetic field (Kataoka et al. 2017; Yang et al. 2019). They may also be aligned in the direction of the radiative anisotropy (Lazarian & Hoang 2007a; Tazaki, Lazarian & Nomura 2017) or the drift velocity of the grains relative to the ambient gas (Gold 1952; Lazarian 1995; Lazarian & Hoang 2007b). Furthermore, even spherical grains can produce polarized emission by self-scattering of large grains in an anisotropic radiation field (Kataoka et al. 2015; Yang et al. 2016, 2017; Stephens et al. 2019). The scattering interpretation of the disc polarization is favoured in several targets (e.g. Stephens et al. 2014, 2017; Kataoka et al. 2016; Bacciotti et al. 2018; Dent et al. 2019; Girart et al. 2018; Harris et al. 2018; Hull et al. 2018; Lee et al. 2018). One way to gauge the effects of scattering and identify polarization from aligned grains would be to observe at multiple wavelengths since the efficiency for scattering for grains of given sizes decreases rapidly with the wavelength in the optically thin and small-particle (or Rayleigh scattering) limit. Indeed, in the disc of Class I protostar BHB 07-11, Alves et al. (2018) detected polarization with ALMA at three wavebands (Bands 3, 6, and 7 or ∼ 3, 1.3, and 0.87 mm, respectively) with consistent polarization orientations across three bands and increasing polarization fraction with wavelength, which is generally not expected for scattering-induced polarization. The rather high mean polarization fractions (∼7.9, 5.3, and 3.5 ${{\ \rm per\ cent}}$ for Bands 3, 6, and 7 respectively) are also higher than those typically produced in models of scattering-induced disc polarization ($\sim \!1 {{\ \rm per\ cent}}$). At least for this well-studied source, scattering is unlikely the main mechanism for producing the observed multiwavelength disc polarization and aligned grains are favoured.


Galaxies seem to retain a memory of their spin orientation with respect to the cosmic web filaments and walls, as suggested by the results from large-scale cosmological hydrodynamical simulations (Dubois et al. 2014; Codis et al. 2018; Wang et al. 2018; Ganeshaiah Veena et al. 2019; Kraljic, Davé & Pichon 2020b). The mass dependence of the spin alignment signal is however debated. While some works confirmed the existence of a galaxy spin transition from parallel to perpendicular with respect to the filament’s direction (Dubois et al. 2014; Codis et al. 2018; Kraljic et al. 2020b), and analogously with respect to walls (Codis et al. 2018; Kraljic et al. 2020b), others (Ganeshaiah Veena et al. 2019; Krolewski et al. 2019) found preferential perpendicular orientation with respect to filaments at all masses with no sign of a spin transition. A possible interpretation of this lack of detection of a clear transition is the nature of the filaments, with galaxies in thinner filaments having their spins more likely perpendicular to the filament’s axis, compared to galaxies of similar mass in thicker filaments (Ganeshaiah Veena et al. 2019). This can be in turn understood recalling the multiscale nature of the problem and the conditional TTT (Codis et al. 2015) predicting larger transition mass for denser, thus thicker, filaments. Further support for this interpretation was provided by the findings of stronger impact of large-scale tides on the galaxy spin orientation in denser filaments (Kraljic et al. 2020b, using filament density as a proxy for the thickness of filaments). In addition to the stellar mass, the spin-filament alignment was shown to depend on other internal properties of galaxies. Blue or rotation-supported galaxies were found to dominate the alignment signal at low stellar mass, while red or dispersion-dominated galaxies tend to show a preferential perpendicular alignment (Codis et al. 2018; Wang et al. 2018; Kraljic et al. 2020b).


One might hope that these global observations would strongly constrain the SFHs of individual galaxies, but this connection is not easily established. For example, average SFHs can be inferred by integrating the main sequence SFR over time (e.g., Leitner 2012), but this approach leads to inconsistencies (Leja et al. 2015). Instead, the most successful theoretical models link the growth of stellar mass to the growth of the dark matter halos that galaxies inhabit, for example, via subhalo abundance matching (e.g., Kravtsov et al. 2004; Conroy et al. 2006; Behroozi et al. 2013b; Moster et al. 2013), halo occupation distributions (e.g., Peacock & Smith 2000; Seljak 2000; Hearin et al. 2016), semi-analytic models (Kauffmann et al. 1993; Somerville et al. 2001; Guo et al. 2011), or other assumptions (Bouché et al. 2010; Davé et al. 2012; Lilly et al. 2013; Tacchella et al. 2013; Mitra et al. 2017). One important conclusion from these models is that there has to be significant scatter between halo and galaxy masses (and thus growth histories) in order to explain observations (More et al. 2009; Behroozi et al. 2013b; Reddick et al. 2013; Gu et al. 2016). As a result, even models that agree on global constraints can lead to orthogonal interpretations of the evolution of individual galaxies. A good example for such disagreement is the “rapid quenching”7

7
The term “quenching” is somewhat ambiguous. In this paper, we use it to mean the cessation of star formation, without any presumption as to whether the decrease happens quickly or slowly, and whether it happens due to a diminishing gas supply or other physical processes.
 framework where galaxies follow the main sequence until they sharply fall below the main sequence (Peng et al. 2012; Wetzel et al. 2013; Tacchella et al. 2016b; Tinker et al. 2016) and the “stochastic” framework where correlated scatter and the central limit theorem lead to the main sequence (Kelson 2014; Kelson et al. 2016).


To explore magma effects on sub-Neptune atmospheres, we assume the atmosphere equilibrates with a well-stirred magma ocean. Our model makes the following simplifications: (a) we consider only the elements Fe, Mg, Si, O, and H. Chemically reduced carbon compounds may also contain H; for simplicity, we omit consideration of them here. We also restrict ourselves to the range of magma elemental compositions for which SiO2 is a major constituent. (b) We set 2000 K ≤ Tmai ≤ 3000 K, so that the magma–atmosphere interface is molten but the vapor pressure of the magma is small relative to the total atmospheric pressure (Fegley et al. 2016; Sossi & Fegley 2018). This Tmai is at the low end of the Tmai output by thermal evolution models for multi-Gyr-old sub-Neptunes (e.g., Bodenheimer & Lissauer 2014; Howe & Burrows 2015; Vazan et al. 2018a). We consider lower Tmai in Section 4.4. (c) We ignore Fe3+ (i.e., Fe2O3). We expect Fe3+ will be a minor constituent of a magma ocean equilibrated with a H2-dominated atmosphere. Equal thermodynamic activities of FeO and Fe2O3 in magma at 3000 K require fO2 = 28 bar, much higher than expected from thermal dissociation of steam at any P and T below 1 kilobar and 3500 K. (d) We assume that metal (if present) is pure Fe for these calculations; in reality, the metal will be an Fe-dominated alloy. We may be (slightly) underestimating fO2 by doing this. (e) We track nonideal behavior of both H2 and H2O (Appendix C), but we assume ideal mixing of H2 and H2O. This is a valid assumption both under mineral-free conditions in the atmosphere for T > 650 K, and also at the magma–atmosphere interface given our model assumptions (Seward & Franck 2019; Bali et al. 2013; Soubiran & Militzer 2015). We ignore joint-solubility effects. (f) We use a single value of gravitational acceleration g, corresponding to 1.2× the bare-rock radius, to convert from bottom-of-atmosphere pressure to atmosphere column mass. (g) We ignore the effect of dissolved volatiles on core mass.


In Figure 2, we show the Chandra 0.3–8 keV images with SDSS contours overlaid for the six mergers in our sample. In Table 4 we list the number of counts detected in the 0.3–8 keV and 2–8 keV bands, and list the detection threshold, PB, associated with each position. There are a number of PB thresholds employed in the literature to define source detection significance. Based on weak sources in Chandra deep field images, the threshold for PB adopted based on a balance between reliability and completeness varies from 0.002 to 0.007 (Xue et al. 2011, 2016; Luo et al. 2017). Based on even the lowest of all these thresholds, all sources are detected. Note that the detection thresholds adopted in the literature for sources at known locations are often PB  0.01, which corresponds to

 (e.g., Lansbury et al. 2014). We note that due to insufficient counts, coupled with the fact the exact location of the galaxy nuclei is uncertain in the advanced mergers in our sample (see SDSS images in Figure 1), it is impossible to quantify any possible spatial offsets between the positions of the detected Chandra sources and the actual galactic nuclei. It is therefore not possible to determine using these observations alone if some of the mergers host offset AGNs, another unambiguous signature of a galaxy merger that can probe AGN triggering through galaxy interactions (Barrows et al. 2016, 2017). We note that for sources within the 2′ of the boresight, the absolute accuracy of source locations on the ACIS-S chip has a 90% uncertainty radius of

,18

18

http://cxc.cfa.harvard.edu/proposer/POG/pdf/MPOG.pdf

 indicating that the positions of all detected targets are consistent with the locations of the SDSS knots, suggesting that the detected sources likely correspond to the nuclei of the mergers. J1036+0221, J1045+3519 Gal 1, J1221+1137 Gal 1, and J1306+0735 Gal 2 were detected in the hard band using the same detection threshold PB  0.002 using the 2–8 keV source counts. Note that there are insufficient counts to perform a spectral analysis or to obtain reliable HRs for our targets. We therefore list in Table 6 the observed X-ray luminosity, assuming a simple power-law model with

, corrected for Galactic absorption.


Multiwavelength observations of the GC indicate that the number of pulsars in the central few parsecs should be high (Wharton et al. 2012) and conditions are highly favourable for relativistic binaries (Faucher-Giguère & Loeb 2011). The dense nuclear star cluster surrounding Sgr A* (see e.g. Genzel, Eisenhauer & Gillessen 2010, for a review) contains a majority of older late-type stars, but contrary to expectations, massive young main-sequence stars (Ghez et al. 2003) and possible neutron star progenitors such as Wolf–Rayet stars (Paumard et al. 2001). The presence of neutron stars is further indicated by large numbers of X-ray binaries, possible pulsar wind nebulae, X-ray features such as the ‘cannonball’ and compact radio variables (Muno et al. 2005; Wang, Lu & Gotthelf 2006; Zhao, Morris & Goss 2013, 2020). Despite this only six radio pulsars have been discovered within half a degree of Sgr A* (Johnston et al. 2006; Deneva, Cordes & Lazio 2009; Eatough et al. 2013c; Shannon & Johnston 2013) even after many dedicated searches at multiple wavelengths (Kramer et al. 1996a, 2000; Klein et al. 2004; Klein 2005; Deneva 2010; Macquart et al. 2010; Eatough et al. 2013a; Siemion et al. 2013). Hyperstrong scattering of radio waves in the GC has been the principal explanation for the scarcity of detected pulsars (Cordes & Lazio 1997, 2002; Lazio & Cordes 1998a,b), however, scatter broadening measurements of PSR J1745−2900 in Spitler et al. (2014) and Bower et al. (2014) appear to contest this.1 Other authors have noted that the lack of GC pulsars is expected under a certain set of conditions and considering the sensitivity limits of existing pulsar surveys (Chennamangalam & Lorimer 2014; Liu & Eatough 2017; Rajwade, Lorimer & Anderson 2017). Alternatively, the scarcity of detected pulsars might be caused by a more complex scattering structure towards the GC (Cordes & Lazio 1997; Lazio & Cordes 1998a, b; Johnston et al. 2006; Schnitzeler et al. 2016; Dexter et al. 2017).


In order to see whether the CN- and HK′-strong stars in our study are also enhanced in Fe and s-process elements, we have compared our results with high-resolution spectroscopy by M15. In Figure 4, our δCN and δHK′ indices are plotted with [Na/Fe] and [Ca/Fe] abundances, respectively, for 33 common stars. In general, the strength of the CN band is correlated with the N and Na abundances, while the CH band is affected by C abundance (Sneden et al. 1992; Smith et al. 1996; Marino et al. 2008). The upper panel of Figure 4 also shows a strong correlation between [Na/Fe] and the δCN index, which is in good agreement with previous studies (Sneden et al. 1992; Lim et al. 2016).4

4
Careful inspection of the upper panel of Figure 4 also shows the possibility that the s-poor and s-rich groups are probably separated on this diagram, with the s-rich stars more enhanced in both [Na/Fe] and δCN. This would imply that the variations in light elements would be present in each group with different s-process elements abundances, which has already been found in other GCs with s-process element and Fe variations, such as M2 and M22 (Marino et al. 2011; Yong et al. 2014). More samples of stars, however, are needed to confirm this trend in NGC 5286.
 The CN-weak (blue) and CN-strong (red) subpopulations are almost identical to the s-poor (triangles) and s-rich (squares) groups, respectively. In addition, the δHK′ index is understandably correlated with the [Ca/Fe] abundance with a few exceptions (see the lower panel of Figure 4). According to this comparison, the difference in δHK′ index between CN-weak and CN-strong stars (∼0.094) is equivalent to 0.09 dex in Δ[Ca/Fe] and 0.15 dex in Δ[Fe/H]. These comparisons confirm that our results from low-resolution spectroscopy are consistent with those from high-resolution spectroscopy by M15. Consequently, the later-generation stars in NGC 5286 show the enhancements not only in light elements (CN) but also in heavy elements (Fe and Ca) and s-process elements, although the presence of Fe spread requires further investigations (see Mucciarelli et al. 2015; Lee 2016).


Although, the standard form of Press–Schechter mass function with $f(\nu)=\sqrt{{2}/{\pi }} \nu \mathrm{ e}^{-\frac{\nu }{2}}$ which discussed in Press & Schechter (1974) and Bond et al. (1991) can provide a good approximation of the predicted number density of haloes, it fails by predicting approximation too many low-mass haloes and too few high-mass ones (Sheth & Tormen 1999, 2002; Lima & Marassi 2004). Thus, in this study we apply another well-known fitting formula which first proposed in Sheth & Tormen (1999):
(24)
\begin{eqnarray*}
f(\nu)=0.2709\sqrt{\dfrac{2}{\pi }}(1+1.1096\nu ^{0.6})\mathrm{ exp}(-\dfrac{0.707 \nu ^2}{2})\,\, .
\end{eqnarray*}
In a Gaussian density field, σ is given by
(25)
\begin{eqnarray*}
\sigma ^2(R)=\dfrac{1}{2 \pi ^2}{\int _0}^\infty k^2 P(k) W^2(kR) \, {\rm d}k\,\, ,
\end{eqnarray*}
where R = (3M/4πρm0)1/3 is the radius of the spherical overdense region, W(kR) is the Fourier transform of a spherical top-hat profile with radius R and P(k) is the linear power spectrum of density fluctuations (Peebles 1993). To obtain the value of σ, we follow the procedure presented in Abramo et al. (2007a). Following on Ade et al. (2016), we use the normalization of matter power spectrum σ8 = 0.815 for ΛCDM cosmology. The number density of virialized haloes above a certain value of mass M at zc, the collapse redshift obtained by
(26)
\begin{eqnarray*}
N(\: M,z)={\int _0}^\infty \dfrac{{\rm d}n(z)}{{\rm d}M^{\prime }}\, {\rm d}M^{\prime }\,\,.
\end{eqnarray*}
The above limit of integration in equation (26) is $M=10^{18}\, \mathrm{ M}_{\rm \odot}\, \mathrm{ h}^{-1}$ which such gigantic structures could not in practice be observed. Now we can calculate the number density of virialized haloes in both homogeneous and clustered DE scenarios using equations (23) and (26). In this way the total mass of a halo is equal to the mass of pressureless matter perturbations. However, the virialization of dark matter perturbations in the non-linear regime cannot be independent from the properties of DE (Lahav et al. 1991; Maor & Lahav 2005; Creminelli et al. 2010; Basse, Bjlde & Wong 2011). Thus, in clustered DE scenarios, we should consider the contribution of perturbated DE components to the total mass of the haloes (Creminelli et al. 2010; Basse et al. 2011; Batista & Pace 2013). Based on the behaviour of wde(z), DE can reduce or enhance the total mass of the virialized halo. One can obtain ϵ(z), the ratio of DE mass to be taken into account with respect to the mass of dark matter, from:
(27)
\begin{eqnarray*}
\epsilon (z)=\dfrac{m_{\rm DE}}{m_{\rm DM}}\,\, ,
\end{eqnarray*}
where the value of mDE depends on what we consider as the mass of DE component. When one only considers the contribution of the perturbations of DE, the mDE takes the form
(28)
\begin{eqnarray*}
{m_{\rm DE}}^{\mathrm{ Perturbed}}=4 \pi \bar{\rho }_{\rm DE}{\int _0}^{R_{\rm vir}} \, {\rm d}R R^2 \delta _{\rm DE}(1+3{c_{\rm eff}}^2)\,\,.
\end{eqnarray*}
In the other hand, if we assume both DE contributions of perturbation and background level, the total mass of DE in virialized haloes takes this new form
(29)
\begin{eqnarray*}
{m_{\rm DE}}^{\mathrm{ Total}}=4 \pi \bar{\rho }_{\rm DE}{\int _0}^{R_{\rm vir}} {\rm d}R R^2 [(1+3 w_{\rm DE})+ \delta _{\rm DE}(1+3{c_{\rm eff}}^2)].
\end{eqnarray*}
The quantities inside a spherical collapsing region in the framework of the top-hat profile, evolve only with cosmic time. Thus from equation (28) one can find
(30)
\begin{eqnarray*}
\epsilon (z)=\dfrac{\Omega _{\rm DE}}{\Omega _{\rm DM}}\dfrac{\delta _{\rm DE}}{1+\delta _{\rm DM}}\,\,
\end{eqnarray*}
and from equation (29) we can obtain
(31)
\begin{eqnarray*}
\epsilon (z)=\dfrac{\Omega _{\rm DE}}{\Omega _{\rm DM}}\dfrac{1+3 w_{\rm DE}+\delta _{\rm DE}}{1+\delta _{\rm DM}}\,\, .
\end{eqnarray*}
The mass of dark matter also is obtained from (see also Batista & Pace 2013):
(32)
\begin{eqnarray*}
{m_{\rm DM}}=4 \pi \bar{\rho }_{\rm DM}{\int _0}^{R_{\rm vir}} \, {\rm d}R R^2 (1+ \delta _{\rm DM})\,\,.
\end{eqnarray*}
In Fig. 5 we plot the evolution of ϵ(z) using equation (30) as the definition of DE mass. We observe that, at high redshift, where the role of DE is less important, ϵ for both of parametrizations becomes negligible. This parameter has a greater value in the case of parametrization (2).


To constrain the size of outflows that we could have missed, we performed simple simulations. We placed artificial, unipolar secondary sources next to a primary point source model representing Sgr A* and compared the closure phases obtained from the resulting artificial visibility data with the observations. We considered two geometries: a single-point source and a jet composed of ten equally spaced point sources (knots) with equal fluxes. We probed four orientations for the simulated outflows (see Fig. 2): along the major axis, along the minor axis of the beam, the jet direction claimed by Li et al. (2013), and the jet direction claimed by Yusef-Zadeh et al. (2012). We used total fluxes of 0.2 Jy and 0.55 Jy for the artificial sources; these values ensure that our simulated outflows are sufficiently faint to not violate the constraints given by the known recent brightness evolution of Sgr A* (0.2 Jy from the mean variability of ≈15% from June 2013 to February 2014 at 41 GHz, with 0.55 Jy corresponding to the strongest variation in the same period, Chandler & Sjouwerman 2014). For each simulation setup, we measured the average of absolute values of the closure phases for each triangle. We varied the distances of the model sources (for the jet model: the largest distance) from Sgr A* until we found a critical distance at which the absolute values of the simulated closure phases exceeded those of the observations by more than the 1σ error at all triangles. We summarize our results in Table 1. As expected, the critical distances are smaller for brighter outflows. Jet-like structures lead to larger critical distances than equally luminous single, compact sources. As a consequence of the very elongated beam, the critical distances for sources located along the major axis of the beam are larger by a factor of ≈7 than for those located along the minor axis. In a few cases (denoted “N/A” in Table 1), the absolute values of the simulated closure phases were similar to those of the observations for all distances of the model sources, meaning that we were unable to identify a critical distance. Overall, our observations limit the extension of asymmetric (in the observer frame) jet-like outflows from Sgr A* to projected distances of ≈2.5 mas along the major axis and ≈0.4 mas along the minor axis.


The Vela Molecular Ridge Cloud-D (hereafter VMR-D) (260Â° â² â â² 264Â°; |b| â² 1Â°) is part of a giant molecular complex located along the Galactic plane (260Â° â² â â² 272Â°; |b| â² 3Â°; Murphy & May 1991) and is then well suited to represent a typical star-forming region (SFR) of our Galaxy. For this reason a subregion of this cloud has been the subject of many previous papers, dealing with different observational aspects of the star formation (SF), such as the presence of outflows (Wouterloot & Brand 1999; Elia etÂ al. 2007), jets (Lorenzetti etÂ al. 2002; Giannini etÂ al. 2005, 2013), and clustering (Massi etÂ al. 2000). The continuum submillimeter emission in the VMR-D cloud was surveyed by Massi etÂ al. (2007), who catalogued 29 resolved dust cores and also obtained a further list of 26 unresolved candidate cores. More recently, thanks to the opportunity offered by the Spitzer Space Telescope, the VMR-D region was observed with the IRAC (Î» = 3.6, 4.5, 5.8, 8.0âÎ¼m) and MIPS (Î» = 24, 70âÎ¼m) focal-plane instruments, obtaining in this way six mosaics, covering about 1.2Â deg2, which have been analyzed to produce a merged photometric Spitzer-IRAC point-source catalog (hereinafter Spitzer-PSC) complemented with MIPS photometry (Strafella etÂ al. 2010, hereinafter PaperÂ I). Further observational progress was made when the BLAST experiment (Pascale etÂ al. 2008) mapped the whole Vela Molecular Ridge in the far-IR (FIR) spectral region (Î» = 250, 350, 500âÎ¼m), complementing in this way the Spitzer spectral coverage toward long wavelengths. These observations were discussed by Olmi etÂ al. (2009), who obtained a catalog of dense cores/clumps in the VMR-D cloud. The last important observational progress was made with the Herschel Space Observatory, which, surveying the Galactic plane in the framework of the Hi-GAL key project, partially mapped the VMR-D region in the FIR spectral range (Î» = 70, 160, 250, 350, 500âÎ¼m) with a spatial resolution and sensitivity almost twice that of BLAST. Here we also analyze these observations for the first time, thanks to the support of the Hi-GAL collaboration that provided us with the corresponding calibrated maps. These have been used to extract five single-band photometries that constitute another important spectral extension of our information about this region.


Nitrogen chemistry mainly consists of three competing processes: (i) the conversion of atomic N to N2 in the gas phase, (ii) destruction of N2, for instance, via photodissociation and reaction with He+, and (iii) freeze-out of atomic N and N2 onto dust grains followed by surface reactions (e.g., Daranlot et al. 2012; Li et al. 2013). The conversion of atomic N into N2 has been proposed to occur by slow neutral-neutral reactions, such as NO + N and CN + N (Herbst & Klemperer 1973; Daranlot et al. 2012). According to the pseudo-time-dependent gas-phase astrochemical model under dense cloud conditions (104 cm−3, 10 K, 10 mag) by Le Gal et al. (2014), the conversion of atomic N into N2 takes an order of Myr, depending on assumed elemental abundances. In the gas-ice model of Daranlot et al. (2012), under the similar physical conditions, the conversion of atomic N to N2 takes ~5 × 105 yr, and it occurs after the significant fraction of nitrogen is frozen out. On the other hand, N2 mainly forms via the reactions NH2 + N and NH + N around the transition from atomic to molecular nitrogen in the models of Furuya & Aikawa (2018) and Furuya & Persson (2018), in which the dynamical evolution of molecular clouds is considered. NH2 and NH are mainly formed via photodesorption of NH3 ice, followed by photodissociation in the gas phase. In this case, the formation rate of N2 from atomic N is, roughly speaking, similar to the freeze-out rate of atomic N. Considering that interstellar ices, at least water ice, are already abundant in molecular clouds with relatively low line-of-sight visual extinction (e.g., ~3 mag for the Taurus dark clouds, Whittet 1993), it may not be surprising that the transition from atomic to molecular nitrogen occurs in the parent cloud of L1544 or in the outer regions of L1544. It should be noted that the N2-dominant region could be larger than the regions traced by N2H+ and NH3 emission, since their abundances are controlled not only by N2, but also by CO; the catastrophic CO freeze-out, which occurs in the late stage of the interstellar ice formation at high densities (≳105 cm−3; e.g., Pontoppidan 2006), causes their abundances to be enhanced (e.g., Aikawa et al. 2005).


To mitigate this problem, several studies have suggested to use the width of the [O iii]λ5007 Å emission line (hereafter [O iii]) originating in the narrow-line region (NLR) as a surrogate for σ⋆, assuming that the NLR is gravitationally bound to the bulge and thus, that the gas kinematics follows the bulge potential (e.g. Terlevich, Diaz & Terlevich 1990; Whittle 1992; Nelson & Whittle 1996; Nelson 2000; Boroson 2003; Shields et al. 2003; Greene & Ho 2005; Netzer & Trakhtenbrot 2007; Salviander et al. 2007; Salviander & Shields 2013). However, while the [O iii] emission line is a prominent line that can be easily measured in AGNs out to large distances, it is also known to often have asymmetric line profiles due to non-gravitational gas kinematics such as outflows, infalls, or interaction with radio jets. In particular, it is known to often display a blue wing (e.g. Heckman et al. 1981; De Robertis & Osterbrock 1984; Whittle 1985; Wilson & Heckman 1985; Mullaney et al. 2013; Woo et al. 2016), generally interpreted as a signature of outflows with dust preferentially hiding one cone behind the stellar disc. For that reason, some studies have excluded the [O iii] blue wing, as well as any radio sources and galaxies undergoing tidal interactions. The MBH was found to scale with the width of the [O iii] line (σ[O iii]), albeit with a large scatter (e.g. Nelson & Whittle 1996; Greene & Ho 2005). Other studies have suggested the use of different emission lines, such as [S ii]λλ6716, 6731 (e.g. Komossa & Xu 2007; Ho 2009) that have a lower ionization potential and do not suffer from substantial asymmetries, or mid-infrared lines (e.g. Dasyra et al. 2008, 2011), but the scatter is comparable to that of the core of the [O iii] line. While all studies confirm the original findings by Nelson & Whittle (1996), i.e. a moderately strong correlation between σ⋆ and σ[O iii] but with real scatter, the origin of the scatter remains unclear. No dependencies have been found with AGN luminosity, host-galaxy morphology, star formation rate, or local environment (Greene & Ho 2005; Rice et al. 2006).


The SFG sample was constructed using the Great Observatories All-Sky LIRG Survey (GOALS sample, Armus et al. 2009), from which we extracted 158 galaxies, with data from Inami et al. (2013), who report the fine-structure lines at high resolution in the 10 − 36 μm interval, and Stierwalt et al. (2014), who include the detections of the H2 molecular lines and the PAH features at low spectral resolution. For those galaxies in the GOALS sample that have a single IRAS counterpart, but more than one source detected in the emission lines, we have added together the line or feature fluxes of all components, to consistently associate the correct line or feature emission to the total IR luminosity computed from the IRAS fluxes. To also cover lower luminosity galaxies, as the GOALS sample only includes luminous IR galaxies (LIRGs) and ultra-luminous IR galaxies (ULIRGs), we included 38 galaxies from Bernard-Salas et al. (2009) and Goulding & Alexander (2009), to reach the total sample of 196 galaxies with IR line fluxes in the 5.5 − 35 μm interval in which an AGN component is not detected. For the Bernard-Salas et al. (2009), Goulding & Alexander (2009), and the GOALS samples, we excluded all the composite starburst-AGN objects identified as those with a detection of [NeV] either at 14.3 or 24.3 μm. It is worth noting that the original samples from Goulding & Alexander (2009) and Bernard-Salas et al. (2009) have spectra solely covering the central region of the galaxies. To estimate the global SFR, we corrected the published line fluxes of the Spitzer spectra by multiplying them by the ratio of the continuum reported in the IRAS point source catalogue to the continuum measured on the Spitzer spectra extracted from the CASSIS database (Lebouteiller et al. 2015). We assumed here that the line emission scales (at first order) with the IR brightness distribution. In particular, we considered the continuum at 12 μm for the [NeII]12.8 μm and [NeIII]15.6 μm lines, and the continuum at 25 μm for the [OIV]25.9 μm, [FeII]26 μm, [SIII]33.5 μm, and [SiII]34.8 μm lines. This correction was not needed for the AGN sample and the GOALS sample because of the greater average redshift of the galaxies in the 12MGS and GOALS samples. In particular, the 12MGS active galaxy sample has a mean redshift of 0.028 (Rush et al. 1993), while the GOALS sample has a mean redshift of 0.026. The galaxies presented by Bernard-Salas et al. (2009) have instead an average redshift of 0.0074, while the sample by Goulding & Alexander (2009) has an average redshift of 0.0044. For the other lines in the 10 − 36 μm interval, Goulding & Alexander (2009) did not report a detection, and we used the data presented in Bernard-Salas et al. (2009) for a total of 15 objects. Both Bernard-Salas et al. (2009) and Goulding & Alexander (2009) reported data from the high-resolution Spitzer-IRS spectra. Data in the 50 − 205 μm interval were taken from Díaz-Santos et al. (2017). For the GOALS sample, 20 starburst galaxies were taken from Fernández-Ontiveros et al. (2016), and 23 objects were taken from the ISO-LWS observations of Negishi et al. (2001). As a result, we obtained a total sample of 193 objects. Lastly, the PAH features’ fluxes were measured from the low-resolution Spitzer-IRS spectra by Brandl et al. (2006), including 12 objects from the sample of Bernard-Salas et al. (2009) and 179 objects from Stierwalt et al. (2014).


The number counts of the most massive clusters have the potential to constrain cosmological parameters. Unfortunately, these systems also tend to be most affected by the effects described above. Massive systems will produce the greatest gravitational lensing shear, and in our hierarchical universe, they are also commonly disrupted by recent merging activity. In this work, we aim to better understand how these considerations affect the observed SZE signals using high-resolution submillimeter and radio imaging of a representative sample of SZE-selected clusters.We present new observations at 345 GHz (19 2 resolution) with the Large APEX Bolometer Camera (LABOCA; Siringo et al. 2009) on the Atacama Pathfinder EXperiment (APEX; Güsten et al. 2006) telescope25

25
This publication is based on data acquired with the Atacama Pathfinder Experiment (APEX). APEX is a collaboration between the Max-Planck-Institut für Radioastronomie, the European Southern Observatory, and the Onsala Space Observatory.
 and at 2.1 GHz (5″ resolution) with the Australia Telescope Compact Array (ATCA) of a sample of massive SZE-selected galaxy clusters. We call the project “LASCAR,” the LABOCA/ACT Survey of Clusters at All Redshifts, in honor of the Lascar volcano near the ACT site in northern Chile. We use these data to measure the properties of the clusters’ spatially resolved SZE increment signals, and quantify the degree of background and foreground radio and infrared galaxy contamination. Section 2 describes our cluster sample. Section 3 presents observations and data reduction techniques. Section 4 assesses the SZE contamination by point sources. Section 5 uses the point-source subtracted multi-wavelength SZE maps to place constraints on cluster peculiar velocities. In Section 6 we discuss our results in the context of previous work, and in Section 7, we conclude. In our calculations, we assume a flat ΛCDM cosmology with

,

, and

 (Komatsu et al. 2011).


When energy flows from the interior of the Sun outward into the solar atmosphere, why is the Sun’s outer atmosphere, the corona, much hotter than the inner atmosphere, the underlying chromosphere and photosphere? This is the long-standing problem of the coronal heating, which is one of the eight key mysteries in modern astronomy (Kerr 2012). For about 80 yr since the discovery of the extremely hot corona around the late 1930s (Grotian 1939; Edlen 1945), people have worked hard on addressing this issue, and great advances have been made in observation and theoretical studies (Parnell & De Moortel 2012; Amari et al. 2015; Arregui 2015; Cargill et al. 2015; De Moortel & Browning 2015; Jess et al. 2015; Klimchuk 2015; Longcope & Tarr 2015; Peter 2015; Schmelz & Winebarger 2015; Velli et al. 2015; Wilmot-Smith 2015). Especially during recent decades, high-resolution observations of solar super-fine structures indicate that small spicules, minor hot jets along small-scale magnetic channels from the low atmosphere upwards to the corona, petty tornados and cyclones, and small explosive phenomena such as mini-filament eruptions and micro- and nano-flares—all of these small-scale magnetic activities contribute greatly to coronal heating (De Pontieu et al. 2011; 2018; Zhang & Liu 2011; Parnell & De Moortel 2012; Klimchuk 2015; Peter 2015; Schmelz & Winebarger 2015; Henriques et al. 2016; Li et al. 2018a). Additionally, contributions of MHD waves to heating the corona have been observationally illustrated (van Ballegooijen et al. 2011; Jess et al. 2015; Kubo et al. 2016; Morton et al. 2016; Soler et al. 2017; Morgan & Hutton 2018). Meanwhile, with the progress of observational studies, two groups of theoretical models, magnetic reconnection models and magnetohydrodynamic wave models, have traditionally attempted to explain coronal heating, but so far no models can address the key mystery perfectly (van Ballegooijen et al. 2011; Arregui 2015; Cargill et al. 2015; Peter 2015; Velli et al. 2015; Wilmot-Smith 2015). Maybe we do not need to intentionally take to heart such the classical dichotomy, because waves and reconnections may interact with each other (De Moortel & Browning 2015; Velli et al. 2015). Additionally, statistical studies may look at coronal heating from a comprehensive perspective. Li et al. (2018b) found that the long-term variation of the heated corona, which is represented by coronal spectral irradiances, and that of small-scale magnetic activity are in lockstep, indicating that the corona should statistically be effectively heated by small-scale magnetic activity. Observational and theoretical model studies through heating channels and modes, and statistical studies by means of heating effect (performance of the heated corona), both suggest that coronal heating originates from small-scale magnetic activity.


In Fig. 10, we plot the variation of the ratio of the outflow contribution to the FWHM and turbulent energy. The ratio of the outflow contribution  = 1 – ‘non-outflow contribution’/‘all contributions’. We observe that the outflow has a contribution in the FWHM: about 20 per cent in the local region at the H ii region (non-outflow contribution is about 81 per cent) and about 10 per cent even in the clumps. According to Eturb  = (3/16 ln 2)Mcloud × FWHM2, outflow has a contribution in the turbulent energy up to 35 per cent in the local region at the H ii region (1 − 0.812). It has a contribution of at least 15 per cent in the clump at early stages of massive star formation, which is lower than that reported in previous studies (e.g. Bally 2016; Drabek-Maunder et al. 2016). The outflow contribution decreases with time once the outflow action stops. This indicates that the outflows do not have a significant cumulative impact on the turbulent levels during the occurrence of several outflow actions. Thus, the outflow energy contribution to turbulent energy increases insignificantly with the evolutionary stages. Our results suggest that the outflow energy is large enough to maintain the turbulent energy in the clumps and that the outflow has some (not significant) effect on the turbulent energy. However, there is a better correlation between the outflow energy and turbulent energy (see Fig. 5). Therefore, we could not determine if the outflow significantly contributes to the turbulent energy in the clumps. This is consistent with the study conducted by Maud et al. (2015). They also reported that there is a better correlation between the outflow energy and turbulent energy, but the core turbulence is not driven by the local input from the outflows. However, Drabek-Maunder et al. (2016) and Yang et al. (2018) reported that there is no correlation between the turbulent and outflow energies. Urquhart et al. (2018) found that the clump mass and evolutionary stage are uncorrelated. For similar mass of massive star, it is likely that we can observe the obvious difference of turbulent energy between clump without and with outflow. However, for statistics, the mass parameter of turbulent energy is less constrained for each evolutionary stage. All these findings imply that the outflow action has some impact on the local environment and cloud itself, but the contribution from outflow does not mainly drive turbulence. This observation is consistent with several other studies that suggest that turbulence is mostly driven by large-scale mechanisms (Ossenkopf & Mac Low 2002; Brunt, Heyer & Mac Low 2009; Padoan et al. 2009; Arce et al. 2010; Mottram & Brunt 2012; Plunkett et al. 2015; Drabek-Maunder et al. 2016).


The wealth of precise all-sky data from the Gaia Data Release 2 (DR2) revealed a new feature in the Herzsprung–Russell diagram (HRD), namely a gap in the mid-M dwarf main sequence (Jao et al. 2018). The gap appears at a magnitude MG ∼ 10 and colour GBP – GRP ∼ 2.3−2.5 in the Gaia filter system. It is observed in optical and near-infrared colour-magnitude diagrams (CMDs), indicating that it is not specific to the Gaia photometry and not due to an atmospheric feature that would depend on the wavelength. Jao et al. (2018) suggest the feature is linked to the onset of full convection in M dwarfs. Interestingly, Mayne (2010) was the first to suggest the existence of an observational signature for the transition between fully and partly convective structures for pre-main sequence stars and predicted that it would result in a HRD gap. This author explored signatures of this transition in young clusters and linked the growth of a radiative core to rapid change in effective temperature caused by changes in the dominant energy transport mechanism and ignition of hydrogen burning. Following the announcement of the HRD gap discovery by Jao et al. (2018), MacDonald & Gizis (2018) proposed an explanation based on standard stellar evolution models. They suggest that the observed feature is due to the complex interplay between production of 3He and its transport by convection. More specifically, they predict a fast change in the luminosity over a narrow mass range of ∼0.31 M⊙−0.34 M⊙ characterised by the presence of a convective core and a convective envelope that ultimately merge. During this merging process, the central 3He abundance increases, causing an increase in luminosity and thus an observable feature in the luminosity function. In this paper, we re-examine the explanation suggested by MacDonald & Gizis (2018), since at first sight it is not clear why a sudden increase of the luminosity due to the merging of the convective zones of the core and the envelope would create a dip in the luminosity function, and thus a gap in the HRD. In this analysis, we confirm that the best explanation for the observed feature is linked to the property of 3He nuclear production and destruction, and to its mixing. We also find that a change in the energy transport from convection to radiation does not induce structural changes that could be visible. Regarding the very details of the process, however, we disagree with MacDonald & Gizis (2018) and propose an alternative explanation.


The only gas-phase process, which is predicted to efficiently lead to products, is the process involving ionized methanimine. According to the model by Vuitton et al. (2007), the amount in the upper atmosphere of Titan of ionized methanimine is small, but not negligible. The products of the reaction CH2NH + CH2NH+ all have a mass-to-charge ratio of 57, where an important contribution is given by the abundant carbocation C4H\hbox{$_{9}^{+}$}+9. In this condition, it is difficult to see if any of these species is present in small amounts in the ionosphere of Titan. Interestingly, we have also investigated the further reaction of 1+ with a third molecule of methanimine. The formation of the species (CH2NH)\hbox{$_{3}^{+}$}+3, starting from two molecules of methanimine and the ionic species CH2NH+, is a strongly exothermic reaction, being \hbox{$\Delta H_{0}^{\circ} = -305$}ΔH0◦=−305 kJ/mol at CCSD(T) level. The optimized structure of (CH2NH)\hbox{$_{3}^{+}$}+3 is shown in Fig. 10. We can conclude, therefore, that polymerization of methanimine in the gas-phase at low temperatures may well be initiated by the presence of an ionized molecule. As for the experiment on ice by Bernstein et al. (1995), it is well known that reaction barriers possibly present in gas-phase reactions are not significantly reduced when moving to ice-mediated reactions (see, for instance, Rimola et al. 2014). Normally, the tunneling effect is invoked to explain the observed reactivity, but in this case the reaction barriers are so high that it is difficult to think that a reaction sequence starting with dimerization of neutral methanimine molecules can account for the observed formation of hexamethylenetetramine or polymethylenimine. The reaction must start by involving a radical or an ionized species and not two neutral closed shell molecules. This was already noted by Vinogradoff et al. (2012), who suggested that the reaction between two neutral methanimine molecules is mediated by formic acid, which acts as a proton donor, and by Cottin et al. (2001), who irradiated mixed ice with protons. Notably, Vinogradoff et al. (2013) failed to see hexamethylenetetramine and polymethylenimine formation starting from pure CH2=NH ice. Since in the experiment by Bernstein et al. (1995) the ice was irradiated by VUV photons at the Lyman alpha wavelength, and we now know that methanimine can be efficiently ionized by those photons, we can also argue that ionization of several methanimine molecules can instead trigger the process in cold interstellar ices. This statement is in line with what is known for gas-phase polymerization of olefin (El-Shall 2008; Cottin et al. 2001). Alternatively, external strong energy sources that can induce local nonequilibrium conditions, could promote neutral-neutral dimerization. For instance, in a study by Zhou et al. (2010), in which acetylene ices were irradiated with energetic electrons, electronically excited acetylene molecules were invoked to account for the experimental observation of benzene formation.


We used the combination of models from STARBURST99 and our model for the contribution from stripped stars to represent the radiation of a full stellar population in which stripped stars are formed. We made our models publicly available on the STARBURST99 online interface2, providing the addition from stripped stars to the spectral energy distribution, the emission rates of H I-, He I-, and He II-ionizing photons, and the high-resolution UV and optical spectra. In this study, we compare the contribution from stripped stars to the version of STARBURST99 that uses the initial mass function from Kroupa (2001) with mass limits of 0.1 M⊙ and 100 M⊙, that is, the same as what we employed for the stripped stars in the population. We chose to compare to the STARBURST99 models that use non-rotating stellar evolutionary models from the Geneva grids (Levesque et al. 2012) and spectral models from WM-BASIC for OB-stars (Pauldrach et al. 2001; Leitherer et al. 2010), CMFGEN for WR stars (Hillier & Miller 1998; Smith et al. 2002), and BASEL v3.1 for later type main sequence stars, cooler stars, and red supergiants (Lejeune et al. 1997). When comparing our models of various metallicity with STARBURST99, we used the STARBURST99 models of Z = 0.014, 0.008, 0.002, and 0.001 together with our models with metallicity of Z = 0.014, 0.006, 0.002, and 0.0002, respectively (see also Table A.1). We consider that the difference in metallicity between the two model sets is small and expect that the difference when using models with exactly the same metallicity is also small. We consider that the combination of the stripped star models and STARBURST99 is a good assumption for radiation with wavelengths shorter than ∼5000 Å. For the model to be accurate at longer wavelengths, we would need to decrease the radiation from giant stars to compensate for stars that we assume have become stripped. Giant stars emit their radiation primarily at wavelengths longer than ∼5000 Å. We expect the decrement of radiation at these long wavelengths to be at maximum about 30% (as also suggested by Eldridge et al. 2017, see e.g., their Figs. 5 and 15). This is approximately the fraction of massive stars that get stripped (Sana et al. 2012) and thus the fraction of giant stars that should be missing. This topic is beyond the scope of this paper, but we hope to address it more in detail at a later stage.


Coming back to the flux values given in Table 1, it is tempting to explain the deficiency of the measured fluxes at energies ∼68 and ∼78 keV compared to the fluxes measured at 1.157 MeV as a consequence of an additional component of the flux at 1.157 MeV, which is generated by the interaction of low-energy cosmic rays (LECR) with abundant circumstellar species like Fe, Mn, and Cr in the environment of Cas A. Siegert et al. (2015) attempted to interpret these discrepant line fluxes of ${}^{44}_{}\mathrm{Ti}$  at different energies exactly in this way. However, considering that little or nothing is known about the LECR fluxes in the Cas A SNR and uncertainties in the generally small cross-sections for the relevant reactions to produce either ${}^{44}_{}\mathrm{Ti}$  or excited ${}^{44}_{}\mathrm{Ca}^{*}$ (Silberberg, Tsao & Barghouty 1998; Tsao, Silberberg & Barghouty 1998), the validity of such an interpretation of the discrepant measurements of ${}^{44}_{}\mathrm{Ti}$  fluxes at 68 and 78 keV and at 1.157 MeV by different instruments and by the same instrument (SPI) may be doubted. Additionally, if one assumes that the production of the 1.157 MeV line emission is supported in Cas A by the enhanced flux of LECRs, then immediately a problem arises related to the absence of other lines emission from much more abundant elements like oxygen, carbon, and nitrogen with very large, well-measured cross-sections for excitation. Indeed, simulations of the excitation emission lines produced by LECRs in Cas A have shown that lines at 4.43, 6.13, 6.9, and 7.1 MeV are expected to be strongest (Summa et al. 2011) for the expected spectrum of LECR (Berezhko et al. 2003) that are interacting with the CSM near the Cas A SNR. However, because no gamma-ray line emission at 4.43, 6.13, 6.9, and 7.1 MeV is observed from the Cas A SNR, we consider this explanation of the excitation origin of the high 1.157 MeV ${}^{44}_{}\mathrm{Ti}$  line flux compared to that at 68 and 78 keV as very problematic.


The initialization of solar flares remains an unsolved problem. Early ideas on how the initialization might occur were described by Norman & Smith (1978). They argued that flare process cannot start in the entire flare volume at one instant, and proposed that the flare onset was localized in a small part of an active region, from which the energy release extends as dissipation spreading process throughout the flare volume. Two types of agents that may lead to this kind of a dissipation process were addressed: electron beams and shock waves. These agents can trigger flares at large distances from their initial locations, causing sympathetic (simultaneous) flares or leading to a sequential flare energy release in one active region (Liu et al. 2009; Zuccarello et al. 2009). These triggering processes were numerically studied by Karlický & Jungwirth (1989) and Odstrčil & Karlický (1997). Karlický & Jungwirth (1989) assumed that electron beams, penetrating into the current sheet in the magnetic reconnection region, generate Langmuir waves. Then, using the particle-in-cell model, the authors studied the effects of these electrostatic waves on the plasma system. Sufficiently strong Langmuir waves were found to be able to generate ion-sound waves through the three-wave decay process (Bárta & Karlický 2000). These ion-sound waves increase electrical resistivity in the current sheet system, which results in the onset of the energy dissipation. Thus, the electron beams are able to cause magnetic reconnection. Odstrčil & Karlický (1997) studied the mechanism for the flare trigger by shock waves. They used a 2D magnetohydrodynamic model with the MHD shock wave propagating towards the current sheet. A portion of the shock wave passed through the sheet, and the rest was reflected. Nothing occurred at the very beginning of the wave-current sheet interaction. However, after some time, specific plasma flows around the current sheet were formed, which led to the start of magnetic reconnection. This shows that for reconnection to be triggered, the enhanced electrical resistivity as well as the plasma flows are important.


Several evolutionary channels have been proposed that lead to a SNIa explosion. For a comprehensive review, see Livio & Mazzali (2018) and Wang (2018). Among these, the two classical scenarios are the single- and the double-degenerate channels. In the single-degenerate channel a white dwarf (WD) in a binary system accretes mass from a non-degenerate donor until it grows near the Chandrasekhar limit (Whelan & Iben 1973; Han & Podsiadlowski 2004; Nomoto & Leung 2018). In the double-degenerate channel two WDs in a close binary system merge due to angular momentum loss caused by the emission of gravitational waves (GWs) and the resulting merger has a mass near the Chandrasekhar limit (Whelan & Iben 1973; Iben & Tutukov 1984; Liu, Wang & Han 2018). Additional evolutionary channels for SNIa include the double-detonation mechanism (Woosley & Weaver 1986; Livne & Arnett 1995; Shen et al. 2012), the violent merger model (Pakmor et al. 2010; Sato et al. 2016), the core-degenerate channel (Sparks & Stecher 1974; Livio & Riess 2003; Kashi & Soker 2011; Wang et al. 2017) and a mechanism which involves the collision of two WDs (Benz, Thielemann & Hills 1989; Aznar-Siguán et al. 2013; Kushnir et al. 2013). In the double-detonation scenario a WD accumulates helium-rich material on its surface, which is compressed and ultimately detonates. The compression wave propagates towards the centre of the WD and a second detonation occurs near the centre of its carbon--oxygen core. In the violent merger model, the detonation of the WD core is initiated during the early stages of the merger. This can happen, for example, due to compressional heating by accretion from the disrupted secondary or due to a preceeding detonation of accreted helium (alike the double-detonation scenario) that is ignited dynamically (Guillochon et al. 2010; Pakmor et al. 2010, 2011, 2012, 2013; Kashyap et al. 2015; Sato et al. 2015, 2016). In the core-degenerate scenario a WD merges with the hot core of an asymptotic giant branch star during (or after) a common envelope (CE) phase. Finally, the evolutionary phase involving the collision of two WDs requires a tertiary star which brings the two WDs to collide due to the Kozai--Lidov mechanism, or dynamical interactions in a dense stellar system, where this kind of interaction is more likely to happen.


Application of linear theory to investigate IGWs has been done extensively in the field of oceanography (Sutherland 2010). The general idea is to linearize hydrodynamical equations and introduce a wave-like ansatz to solve the linearized equations. In the context of stellar parameters, one of the earliest works was done by Press (1981), which focused on solar-like stars. In our work, we follow similar steps, starting with the linearized hydrodynamical equations in the anelastic approximation:
(8)$$\begin{eqnarray*}
\nabla \cdot \overline{\rho } \boldsymbol {v} = 0,
\end{eqnarray*}$$(9)$$\begin{eqnarray*}
\frac{\partial \boldsymbol {v}}{\partial t} = - \nabla \left(\frac{P}{\overline{\rho }}\right) - C \overline{g} \boldsymbol {\hat{r}}
\end{eqnarray*}$$(10)$$\begin{eqnarray*}
\frac{\partial T}{\partial t} = - v_\mathrm{ r} \left(\frac{\partial \overline{T}}{\partial r} - (\gamma - 1) \overline{T} h_\rho \right)
\end{eqnarray*}$$We ignore the pressure term in equation (4), which leads to a set of equations that conserve energy (Brown, Vasil & Zweibel 2012). We also do not consider rotational, thermal diffusion, or viscous effects. In cylindrical coordinates, this 2D analysis allows us to set the z-derivatives to zero. The three equations shown above can then be reduced to one second-order differential equation with vr(r) as the evolving term:
(11)$$\begin{eqnarray*}
0 &=& \frac{\partial ^2 \alpha }{\partial r^2} + \left(\frac{N^2}{\omega ^2} - 1 \right) \frac{m^2}{r^2} \alpha + \left[ -\overline{\rho }^{-1/2}\frac{\partial ^2 \left(\overline{\rho }^{1/2}\right)}{\partial r^2} + \frac{\partial h_{\rho }}{\partial r} \right]\alpha \nonumber \\
&&+\, \frac{1}{4r^2} \alpha,
\end{eqnarray*}$$where $\alpha = v_\mathrm{ r} \overline{\rho }^{1/2} r^{3/2}$. We have used a wave ansatz of the form vr(r, θ, z) ∝ vr(r)eimθe−iωt, where m is the horizontal wavenumber,1 ω is the angular frequency, and θ is the angular coordinate in the equatorial plane. Generally, in the radiation zone, there will be regions where the oscillatory term (OT), (N2/ω2 − 1)m2/r2, dominates and regions where the density term (DT), $[ -\overline{\rho }^{-1/2}\partial ^2 (\overline{\rho }^{1/2})/\partial r^2 + \partial h_{\rho }/\partial r]$, dominates. When the ratio of OT to DT is less than 1, an IGW loses its wave-like behaviour and the approximate radius where this ratio is exactly equal to 1 is called the turning point. The importance of this will be discussed in Section 4.


Figure 6(a) shows the 1.3 mm continuum and C18O(J = 2–1) distribution around the Papillon Nebula. The extended 1.3 mm continuum emission around the Papillon Nebula YSO roughly agrees with the distribution of Hα emission and has no counterparts of molecular gas, indicating that the continuum emission seems to be dominated by free–free emission from the ionized gas (see also Paper I). On the other hand, the filamentary dust clumps along the C18O emission, a tracer of cold/dense molecular gas, are considered to be dominated by thermal dust emission. Two major local maxima, hereafter MMS-1 and MMS-2, are found in the 1.3 mm continuum image in Figures 6(a)–(c). Because we detected extended emission in 1.3 mm and C18O along the north–south direction, the two sources are considered to be dense cores embedded in the filamentary cloud. The peak column densities and total masses of both sources deduced from the 1.3 mm continuum emission are ∼1 × 1024 cm−2, and ∼2 × 102 M⊙, respectively, with an assumption of the dust emissivity,

 of 1 cm2 g−1 for protostellar envelopes (e.g., Ossenkopf & Henning 1994), a dust-to-gas ratio of 3.0 × 10−3 (Herrera et al. 2013; Gordon et al. 2014), and a uniform dust temperature of 20 K, which is typically adapted/estimated for galactic high-mass star-forming dust clumps (e.g., Urquhart et al. 2014; Yuan et al. 2017). Note that the core boundaries deriving their total masses were set as the 30% intensity level of each continuum peak to avoid contaminations from the parental filamentary clouds. Although these sources were not cataloged as point sources in the infrared observations (e.g., Chen et al. 2010; Carlson et al. 2012), their detection in the 1.3 mm is strongly suggestive of their protostellar nature. We have identified outflow wings that have a velocity span of ∼30 km s−1 in 12CO(J = 2–1) toward MMS-1 and MMS-2. Figures 6(b)–(e) show the distributions and the line profiles of the outflow wings. We extracted the spectra and chose the velocity ranges using the following procedure. We defined the outer boundaries of the outflow spectra (i.e., maximum relative velocity) above the 2σ level of the velocity-smoothed spectra with a smoothing kernel of 9 ch (=1.8 km s−1). We extracted the spectra at positions ∼1″ away from the millimeter sources in the east direction as the references without the outflow contaminations and defined the velocities below 2σ intensity levels as the inner edge of the outflow spectra (see Figures 6(d) and (e)). The outflow and YSO properties are listed in Table 2. The size of the outflow is as small as ∼0.1 pc, and escaped detection with our lower-resolution study (Paper I). It is likely that the launching points of the outflows coincide with the 1.3 mm continuum peaks. Because the positional offsets between the blueshifted and redshifted lobes are quite small toward MMS-1 and MMS-2, the outflow orientations may be close to pole-on or very small. The dynamical time (td) of the outflows is roughly estimated to be 104 yr from a ratio of 0.1 pc/20 km s−1. We roughly estimated the mechanical forces of the outflow lobes (Fout) using the following equation: Fout = MoutVout/td (e.g., Beuther et al. 2002), where Vout and Mout are the outflow velocity and mass, respectively. The estimated Fout is ∼10−3–10−2 M⊙ km s−1 yr−1, depending on the assumption of the outflow inclination angle (i = 30°–70°). The Fout and the envelope mass derived from millimeter dust continuum observations are consistent with those of Galactic high-mass protostars (e.g., Beuther et al. 2002) and the N159W-South region (TFH19). A large amount of the surrounding gas with a mass of ∼102 M⊙ and the nondetection of infrared emission suggest that MMS-1 and MMS-2 are in an extremely young phase of high-mass star formation, with an age of ≲104 yr. We note that the Papillon Nebula YSO is more evolved than the two sources; however, the age is as young as ∼0.1 Myr (Paper I) judging from the combination of the spectral energy distribution fitting using the Spitzer/Herschel data and the compactness of the H i region (see also Chen et al. 2010). Although certain time differences are found, the three high-mass protostellar systems with separations of ∼1–2 pc are formed within the order of ∼0.1 Myr. We discuss the possible processes of high-mass star formation taking place in the N159E-Papillon region in Section 4.1.


The H i mass fraction of every gas particle in the baryonic runs is calculated based on the particle’s temperature and density and the cosmic UV background radiation flux while including a prescription for self-shielding of H2 and dust shielding in both H i and H2 (Christensen et al. 2012). This allows for the straightforward calculation of the total H i mass of each simulated galaxy. We create mock H i data cubes only for the 42 halos that contain

. Specifically, we create mock data cubes that mimic ALFALFA observations (Haynes et al. 2011). After specifying a viewing angle (see below), our code considers the line-of-sight velocity of each gas particle. The velocity of each particle is tracked in the simulation by solving Newton’s equations of motion, but any turbulent velocity of the gas is not taken into account. Velocity dispersions in dwarf galaxies can be on the order of the rotational velocity, ∼10–15 km s−1 (e.g., Stanimirović et al. 2004; Tamburro et al. 2009; Oh et al. 2015). Dispersions are thought to be driven at least partially by thermal velocities or supernovae (Tamburro et al. 2009; Stilp et al. 2013a, 2013b). In our simulations, supernovae inject thermal energy, and the thermal state of the H i gas needs to be considered in the mock H i linewidth for a realistic comparison to observations. To account for the thermal velocity, the H i mass of each gas particle is assumed to be distributed along the line-of-sight in a Gaussian distribution with a standard deviation given by the thermal velocity dispersion,

, where T is the temperature of the gas particle. After this thermal broadening is calculated, a mock H i data cube can be generated by specifying the spatial and velocity resolution. For all of our galaxies, we adopt a spatial resolution of 54 pixels across 2Rvir. In practice, this corresponds to a range of ∼1 kpc resolution in our lowest-mass galaxies up to ∼9 kpc resolution in our most massive galaxies. However, the spatial resolution plays no role in our study, since measurements of the VF are based on spatially unresolved H i data. For the velocity resolution, we match the ALFALFA specification of 11.2 km s−1 (two-channel boxcar-smoothed).


There are several different effects that have been considered to explain the observed offset in the [O iii]λ5007/Hβ vs. [N ii]λ6584/Hα BPT diagram among high-redshift galaxies. First, there are the physical parameters describing the H ii regions contributing to the integrated line ratios from galaxies. These include the ionization parameter, ionizing spectrum of the stars illuminating the H ii-region gas, and the electron density. Early work highlighting the issue of the high-redshift offset in the [O iii]λ5007/Hβ vs. [N ii]λ6584/Hα BPT diagram focused on these parameters (e.g., Shapley et al. 2005; Brinchmann et al. 2008; Liu et al. 2008), and they have been revisited more recently by Kewley et al. (2013), Steidel et al. (2014), and Masters et al. (2014). Systematically higher ionization parameters (which appear to apply in high-redshift galaxies; Nakajima et al. 2013), harder ionizing spectra, and higher electron densities (Shirazi et al. 2014), all tend to shift the locus of galaxies in the [O iii]λ5007/Hβ vs. [N ii]λ6584/Hα diagram toward higher [O iii]/Hβ and [N ii]/Hα values. Next, there is the role of different types of pressure in determining the internal structure and dynamics of H ii regions. Yeh et al. (2013) and Verdolini et al. (2013) suggest that radiation pressure is significant in high-redshift H ii regions, as compared with gas pressure associated with stellar winds, and that the effects of radiation pressure can lead to [O iii]/Hβ line ratios in excess of the “maximum starburst” limit of Kewley et al. (2001). Possible contamination by weak AGNs has also been suggested as a way to shift galaxy emission-line ratios into the “composite” region of the [O iii]λ5007/Hβ vs. [N ii]λ6584/Hα BPT diagram (e.g., Wright et al. 2010), in between the curves of Kauffmann et al. (2003) and Kewley et al. (2001). Finally, both Masters et al. (2014) and Steidel et al. (2014) consider gas-phase abundance ratios—specifically, the N/O ratio—which can affect where galaxies fall in the [O iii]λ5007/Hβ vs. [N ii]λ6584/Hα BPT diagram. If the relationship between N/O and

 evolves out to high redshift, then distant galaxies will shift relative to local ones in the [O iii]λ5007/Hβ vs. [N ii]λ6584/Hα BPT diagram.


Our simulations, despite probing quite different jet velocities and resolution levels, point to a very unstable nature of the structure resulting from the jet–wind–orbit interaction in HMMQ. Although this was already suggested, our numerical calculations strongly endorse this possibility. Our results, not being an extensive exploration but just two characteristic examples, do not settle the issue for other parameter choices. Nevertheless, the simulations probe fiducial cases and their outcomes suggest that the jet is unlikely to leave unscathed the region close to the binary, say $z\lesssim 10\, a$. Even for smaller χj values and longer Porb values than those explored here, we propose that jet–wind–orbit interaction could induce instability growth, which could produce precession–like patterns in the jets at larger scale. Even if the jets are so powerful that significant mixing and disruption does not occur on scales $\sim 1-10\, a$, and Φ is initially rather small, the growth of Kelvin–Helmholtz (KH) instabilities is expected (see also, e.g. Perucho 2019, in the context of extragalactic jets). In fact, the jet–wind interaction alone can already perturb the jet (Perucho & Bosch-Ramon 2008; Perucho et al. 2010), and stellar wind clumping, not considered in the present simulations, should also render the jet more prone to disruption (Perucho & Bosch-Ramon 2012). In addition to KH instabilities, Rayleigh–Taylor and Richtmyer–Meshkov instabilities could also develop at the dynamical jet–wind contact discontinuity, particularly due to the Coriolis force, as in the similar case studied by Bosch-Ramon et al. (2015) with a pulsar wind instead of a jet. These additional instabilities would produce non-linear perturbations that would couple to the KH instability, enhancing the disruptive effects of all these processes.5 We note that jet precession-like features caused by KH instabilities may or may not follow the orbital period, as these instabilities could span a broad range of wavelengths. Therefore, in addition to the cases explored here, χj values even smaller than θj (see Bosch-Ramon & Barkov 2016, for a discussion on the χj – θj relation) could also lead to distorted jets on scales ≫a. Interestingly, this has been observed in radio in Cyg X-3, but not yet in Cyg X-1 (see,e.g. Mioduszewski et al. 2001; Miller-Jones et al. 2004; Tudose et al. 2007, for related radio observations of Cyg X-3). Interestingly, regardless of the χj value, if the jet gets disrupted on scales $\lesssim 10\, a$, the strong pressure drop outwards of the embedding medium can make the jet–wind mixed flow turn into a collimated structure (see Bosch-Ramon & Barkov 2016; see also Millas et al. 2019 for the case of the HMMQ SS 433, a different but related situation -see Section 1-). In the case of a weaker wind-orbit effect on the jet, the jet inertia, and the density drop of the medium, may allow the jet to keep some coherence despite KH instability growth, at least until interacting with the surrounding medium on much larger scales (see, e.g. Marti et al. 1996; Gallo et al. 2005; Russell et al. 2007; Sell et al. 2015 for Cyg X-1 radio observations, and Bordas et al. 2009; Bosch-Ramon et al. 2011; Yoon et al. 2011 for simulations, of the jet-medium interaction). To properly study the evolution of orbit-affected jets at z ≫ a in HMMQ, devoted simulations are planned.


Extensive modelling efforts have been undertaken to explain observations and the formation of dust in local and high redshift SNe. While some studies use the classical nucleation theory (CNT) to describe dust formation under equilibrium conditions in shocked environments (Kozasa et al. 1989; Todini & Ferrara 2001; Nozawa et al. 2003; Schneider et al. 2004), other studies describe the formation of both molecules and dust clusters from the shocked gas by assuming a chemical kinetic approach under non-equilibrium conditions and the subsequent coalescence and coagulation of these clusters to form dust grains (Cherchneff & Lilly 2008; Cherchneff & Dwek 2009; 2010; Sarangi & Cherchneff 2013; 2015, hereafter SC15). On the other hand, the processing of dust in SNRs has received less attention. The thermal sputtering of dust by the forward shock has been studied by Nozawa et al. (2006), and sputtering by the RS in local and primitive SNe was modelled by Nozawa et al. (2007), Bianchi & Schneider (2007), and Nath et al. (2008). Sputtering by the RS in Type II-b SNe with application to the Cas A SNR was studied by Nozawa et al. (2010). Finally, Silvia et al. (2010; 2012) proposed a hydrodynamic study of an ejecta clump, which was processed by the RS, and followed thermal sputtering as the clump was crossed and gradually disrupted by the shock. All studies show that dust is strongly reprocessed in SNRs. However, the final mass of surviving dust is not well constrained because of several factors. Firstly, all studies use as initial conditions for sputtering in the SNR the dust masses and size distributions that result from applying CNT. The chemical types and masses of the dust that are used as initial conditions may consequently be in error using this formalism, as discussed by Cherchneff (2014). Furthermore, some of these studies assume a homogeneous ejecta in the SNR phase (Nozawa et al. 2007; 2010; Bianchi & Schneider 2007; Nath 2008), which implies that very harsh conditions hold in the post-shock gas for dust survival because the RS crosses and reprocesses the ejecta at very high velocities. By considering clumpy ejecta, the RS velocity will be greatly reduced in the dense clumps (Silvia et al. 2010; Biscaro & Cherchneff 2014).