adsabs/FOCAL huggingface dataset:
CMEs are known for large-scale expulsion of magnetized plasma structures from closed magnetic field regions on the Sun. They were first detected in the coronagraphic images taken in 1971 by NASA’s OSO-7 spacecraft (Tousey 1973). However, some definite inferences for the solar wind (Eddington 1910; Birkeland 1916; Biermann 1951) as well as CMEs from the Sun (Chapman & Ferraro 1931; Eddy 1974) were made decades before their formal discovery. Following OSO-7, a series of spacecraft (Skylab, Helios, P78-1 Solwind, SOHO, Coriolis, and STEREO, etc.) have observed thousands of CMEs leading to a vast literature (Munro et al. 1979; Howard et al. 1985; Gosling 1993; Hundhausen 1999; Gopalswamy et al. 2000; Schwenn 2006; Vourlidas et al. 2010; Chen 2011; Wang et al. 2011; Webb & Howard 2012; Mishra & Srivastava 2013; Mishra et al. 2017; Harrison et al. 2018). CMEs have been observed to occur often having spatial and temporal relation with solar flares, eruptive prominences (Munro et al. 1979; Webb & Hundhausen 1987; Zhang et al. 2001; Gopalswamy et al. 2003) and with helmet streamer disruptions (Dryer 1996). Unlike CMEs from the Sun, to observe stellar CMEs are challenging because the close stellar environment cannot be spatially resolved. Although stellar CMEs have not yet been directly detected in Thomson-scattered optical light from other stars, it is believed that the extreme X-ray flares observed on stars may be in conjunction with extreme stellar CMEs (Houdebine, Foing & Rodono 1990; Wheatley 1998; Leitzinger et al. 2011; Aarnio, Matt & Stassun 2012; Osten & Wolk 2015; Vida et al. 2016). Indeed, the stellar X-ray flare, helmet streamers, and prominences observed on T Tauri Stars have shown similarities with those observed on the Sun (Haisch, Antunes & Schmitt 1995; Massi et al. 2008). The CMEs and flares themselves may not be causally related, they both seem to be involved with the reconfiguration of complex magnetic field lines within the corona caused by the same underlying physical processes, e.g. magnetic reconnection (Priest & Forbes 2002; Compagnino, Romano & Zuccarello 2017). But, even for the sun, it has been noted that not all flares are accompanied by CMEs and not all CMEs by flares (Munro et al. 1979; Harrison 1995; Yashiro et al. 2008b; Wang & Zhang 2008).
Citation: Zhang et al. 2001
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The 1D SDSS spectrum of SDSS J124754.95-033738.6 (Fig. 1) is dominated by A-type stars and shows strong Balmer absorption lines, which is a clear signature of post starburst E+A galaxies. We used the 1D SDSS spectrum to measure the equivalent width (EW) of the Hδ absorption line and found EW(Hδ) = 6.7 Å, which is above the typical 5  Å threshold used to select post-starburst E+A galaxies (e.g. Goto 2007; Alatalo et al. 2016). We then fitted a stellar population synthesis model using the python implementation of Penalized Pixel-Fitting stellar kinematics extraction code (pPXF; Cappellari 2012). pPXF is a public code for extraction of the stellar kinematics and stellar population from absorption line spectra of galaxies (Cappellari & Emsellem 2004). Its output includes the best-fitting stellar model, the relative contribution of stars with different ages, the stellar velocity dispersion, and the dust reddening towards the stars (assuming a Calzetti et al. 2000 extinction law). The code uses the MILES library, which contains single stellar population synthesis models that cover the entire optical wavelength range with an FWHM resolution of 2.3 Å  (Vazdekis et al. 2010). We used models produced with the Padova 2000 stellar isochrones assuming a Chabrier initial mass function (IMF; Chabrier 2003). The stellar ages range from 0.03 to 14 Gyr, thus allowing the analysis of systems with different star formation histories. The best-fitting stellar model is marked with red in Fig. 1. Its stellar age distribution consists of two star formation episodes, with a recent short episode that started 70 Myr ago and was quenched 30 Myr ago, and an older long episode that started 14 Gyr ago and ended 6 Gyr ago. The older episode is poorly constrained and we find similarly reasonable fits when forcing the code to use templates with different ages within the range 3–10 Gyr. According to the best-fitting model, the stellar velocity dispersion is 185 km sec−1 and the dust reddening towards the stars is EB–V = 0.188 mag. The total stellar mass is $\mathrm{M_{*}} = 10^{10.8}\, M_{\odot }$, which is consistent with other estimates (e.g. Chen et al. 2012). About ∼2 per cent of this mass was formed during the recent burst.
Citation: Cappellari & Emsellem 2004
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The ability both to rapidly quench and maintain low levels of star formation in red-sequence massive galaxies has often been attributed to the impact of active galactic nuclei (AGN). Radiatively-driven winds, mechanical energy, and/or thermal pressure release from the AGN are physical processes routinely incorporated into numerical simulations of galaxy evolution to solve the overcooling problem (e.g., Vogelsberger et al. 2014a; Schaye et al. 2015; Pillepich et al. 2018; Bassini et al. 2019; Wittor & Gaspari 2020), so that the characteristics of the observed galaxy population can be reproduced (e.g., Vogelsberger et al. 2014b; Nelson et al. 2018). Often two types of the AGN feedback mode are being distinguished, which are called the quasar mode or radiative mode (e.g., Di Matteo et al. 2005; Hopkins et al. 2008; Hopkins & Elvis 2010) and the radio mode also known as kinetic or maintenance mode (e.g., Bower et al. 2006; Croton et al. 2006; Fabian 2012; Gaspari et al. 2020). The quasar mode is thought to initially quench star formation through powerful radiatively driven winds that remove the gas from the galaxy (e.g., Nesvadba et al. 2008; Feruglio et al. 2010; Maiolino et al. 2012) and thereby suppress star formation. The radio mode is a heating mechanism affecting the gaseous halo that prevents continuous condensation of cold and warm gas, thereby quenching star formation over long timescales and maintaining a low level of star formation in red sequence galaxies (e.g., Brüggen & Kaiser 2002; McNamara et al. 2005; Gaspari et al. 2019; McDonald et al. 2021). Strong observational evidence for radio mode feedback has been collected from galaxy clusters hosting powerful radio galaxies (e.g., Fabian et al. 2006; McNamara & Nulsen 2007). The role of quasar mode feedback is much more controversial from an observational perspective. Various studies have reported negative (Ho 2005; Nandra et al. 2007; Schawinski et al. 2009; Farrah et al. 2012; Page et al. 2012; Mullaney et al. 2015; Shimizu et al. 2015; Wylezalek & Zakamska 2016; Kakkad et al. 2017; Catalán-Torrecilla et al. 2017; Bing et al. 2019; Bluck et al. 2020; Ramos Padilla et al. 2020; Brownson et al. 2020; Smith et al. 2020), positive (Kim et al. 2006; Cresci et al. 2015a,b; Bernhard et al. 2016; Santoro et al. 2016; Maiolino et al. 2017; Koss et al. 2021), or no effect from feedback (Elbaz et al. 2011; Bongiorno et al. 2012; Harrison et al. 2012; Husemann et al. 2014; Balmaverde et al. 2016; Leung et al. 2017; Woo et al. 2017; Shangguan et al. 2018; Scholtz et al. 2020) on the star formation rates of observed AGN host galaxies.
Citation: Gaspari et al. 2020
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Unveiling the transport properties of charged particles in the presence of turbulent magnetic fields represents the key to understanding the propagation and acceleration of energetic particles in many space and astrophysical plasmas. Several parameters can influence the particle transport, like the turbulence level, the turbulence anisotropy, the spectral shape, and the particle energy, and many different regimes are considered in the literature (Zimbardo 2005; Pommois et al. 2007; Shalchi 2010, 2015; Zimbardo et al. 2012; Lazarian & Yan 2014; Litvinenko et al. 2017). Besides the ballistic and diffusive regimes, many observations suggest that intermediate, so-called superdiffusive regimes for which 





 with α > 1, may exist. Here, r is the distance from the starting point, t is the time, and α is the anomalous diffusion exponent. These observations range from the analysis of nonrelativistic electrons accelerated in solar energetic events (Lin 1974), to the anomalously large parallel mean free paths inferred for solar energetic protons (Reames 1999) and for termination shock accelerated ions (Giacalone 2013). On a larger, astrophysical scale, Ragot & Kirk (1997) showed, by studying the spectral index evolution of diffuse radio emission from synchrotron emitting electrons in the Coma cluster of galaxies, that this can be interpreted in terms of superdiffusive transport. The transport properties can also be deduced by studying the energetic particle profiles upstream of shock waves, where particles are thought to be accelerated. In particular, the observations of power-law energetic particle profiles upstream of shock waves in the heliosphere (Perri & Zimbardo 2007, 2008, 2009, 2015; Sugiyama & Shiota 2011; Zimbardo et al. 2012) and in the supernova remnant shock precursors (Perri et al. 2016; Perri 2018) are an indication of superdiffusive transport. Further, superdiffusive transport also influences processes like diffusive shock acceleration (Kirk et al. 1996; Ragot & Kirk 1997; Perri & Zimbardo 2012a; Zimbardo & Perri 2013; Bykov et al. 2017) and stochastic Fermi acceleration (Sioulas et al. 2020), leading to modifications of the energy spectral index and of the acceleration time. As an application of superdiffusive shock acceleration (Perri & Zimbardo 2012a), we may mention that a discrepancy is found in the Mach numbers derived by X-rays and by radio observations of galaxy clusters’ merger shocks (Akamatsu et al. 2017; Colafrancesco et al. 2017; Van Weeren et al. 2017); this discrepancy could be explained by the modification of the energy spectral index implied by superdiffusive shock acceleration (Zimbardo & Perri 2017, 2018).
Citation: Giacalone 2013
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The recoiling supermassive black hole (rSMBH) carries it the broad-line region (BLR) along with it and leaves the stellar nucleus behind; it can be observable for tens of Myr as an offset AGN (Madau & Quataert 2004; Loeb 2007, Blecha et al. 2011, 2016). We therefore expect two observational characteristics: (i) the rSMBH could be observed spatially offset with respect to the stellar center of the host galaxy, and (ii) the broad emission lines could have a measurable velocity offset with respect to the systemic velocity. So far, there have been more than a dozen reports of rSMBH candidates. Some examples of rSMBH candidates are SDSS J092712.65+294344.0 (Komossa et al. 2008), SDSS J105041.35+345631.3 (Shields et al. 2009), M87 (Batcheldor et al. 2010), QSO E1821+643 (Robinson et al. 2010), CXOC J100043.1+020637 (Civano et al. 2010), CXO J122518.6+144545 (Jonker et al. 2010), a half-dozen SDSS QSOs (Eracleous et al. 2012), 10 nearby core elliptical galaxies (Lena et al. 2014), NGC 3115 (Menezes et al. 2014), 5 SDSS AGNs (Comerford et al. 2015), and 26 SDSS QSOs (Kim et al. 2016). Except for CXOC J100043.1+020637, most of the rSMBH candidates described to date either have a spatial offset or a velocity offset, but not both. The source CXOC J100043.1+020637 has two compact sources separated by ∼2.5 kpc and has a velocity offset of ∼1200 km s−1 (Civano et al. 2010). Chandra observations find that the southeastern source, which has a point-like morphology typical of a bright AGN, is responsible for the whole X-ray emission in this system (Civano et al. 2012). The northwestern source has a more extended profile in the optical band, with a scale length of ∼0.5 kpc. Recent 3 GHz Karl G. Jansky Very Large Array (VLA) observations find that the entire observed 3 GHz radio emission can be associated with the southeastern nucleus (Novak et al. 2015). The observations favored an explanation within the rSMBH picture, but the presence of an obscured and radio-quiet SMBH in the northwestern source is not ruled out (i.e., Blecha et al. 2013; Wrobel et al. 2014).
Citation: Eracleous et al. 2012
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The non-gravitational interaction in the dark sector, precisely between dark matter and dark energy is a phenomenological concept that was originally thought to explain the different values of the time-independent cosmological constant (Wetterich 1995), but later on, such concept was found to be very useful to explain the cosmic coincidence problem (Amendola 2000; Chimento et al. 2003; Cai & Wang 2005; Hu & Ling 2006; del Campo, Herrera & Pavón 2008, 2009). Certainly, this led to a large amount of investigations towards this direction where the dark sectors have direct interaction (Billyard & Coley 2000; Barrow & Mota 2003; Barrow & Clifton 2006; Skordis et al. 2006; Koivisto & Mota 2008b; Quartin et al. 2008; Chimento 2010; Valiviita, Maartens & Majerotto 2010; Koivisto, Mota & Zumalacarregui 2012; Thorsrud, Mota & Hervik 2012; Akrami et al. 2013; Faraoni, Dent & Saridakis 2014; Yang & Xu 2014a,b,c; Duniya, Bertacca & Maartens 2015; Pan, Bhattacharya & Chakraborty 2015; Valiviita & Palmgren 2015; Mukherjee & Banerjee 2017; Pan & Sharov 2017; Santos et al. 2017; Sharov et al. 2017; Pan, Mukherjee & Banerjee 2018; also see Pan & Chakraborty 2013; Chen et al. 2014; Pan & Chakraborty 2014; Shahalam et al. 2015, 2017; Cai, Tamanini & Yang 2017; Kumar & Nunes 2017a; Odintsov, Oikonomou & Tretyakov 2017). Such interacting scenarios have good motivation if the particle physics theory is considered because from the particle physics view, mutual interaction between any two fields is a natural phenomenon, irrespective of the nature of the fields. Although the interacting dynamics is complicated and a generalized cosmic scenario, it recovers the non-interaction cosmology as a special case. Thus, the theory of non-gravitational interaction between dark matter and dark energy is a generalized version of the non-interacting dark matter and dark energy cosmologies. Interestingly enough, the observational data at recent time found that the direct interaction between dark matter and dark energy cannot be excluded (Salvatelli et al. 2014; Kumar & Nunes 2016; Nunes, Pan & Saridakis 2016; Yang et al. 2016; Kumar & Nunes 2017b; van de Bruck, Mifsud & Morrice 2017; Yang, Banerjee & Pan 2017a; Yang, Pan & Mota 2017b; Yang, Pan & Barrow 2018). Moreover, very recently, it has been reported that the current tension on the local Hubble constant can be alleviated with the introduction of dark matter and dark energy interactions (Kumar & Nunes 2016; Di Valentino, Melchiorri & Mena 2017). Additionally, the crossing of phantom barrier has also been found to be an easy consequence of the non-gravitational interaction. Thus, the theory of interacting dark energy might be considered to be an appealing field of research and indeed a hot topic for the next generation of the astronomical surveys.
Citation: Sharov et al. 2017
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The comparison with other hot corinos is not easy since we have a limited number of lines, in contrast to well-known sources that have been more extensively observed with ALMA and NOEMA, such as IRAS 16293-2422 (Jørgensen et al. 2016), NGC1333 IRAS 2A and 4A (Taquet et al. 2015; López-Sepulcre et al. 2017). In general, we find a similar inventory ofCOMs but with lower abundances in B1b-S. We are going to discuss only some trends and ratios between them. For example, one similarity with hot corinos are the higher abundances of O-bearing COMs with respect to N-bearing COMs. We observe a similar trend in B1b-S, where the highest abundances are obtained for CH3OCOH, CH3OCH3, and CH3CHO, while NH2CN and NH2CHO show the lowest abundances. Cyanamide has been recently detected towards the low-mass protostars IRAS 16293-2422 and NGC 1333 IRAS2A (Coutens et al. 2018), with observed NH2CN to NH2CHO ratios of 0.2and 0.02, respectively. These values are in the range of those observed towards the molecular clouds in the Galactic centre but lower than in Orion KL (Coutens et al. 2018). We obtain in B1b-S anabundance ratio of 0.25, similar to IRAS 16293-2422. Of the three possible isomers of C2 H4O2, we have detected CH3OCOH and CH2OHCHO. The observed CH3OCOH to CH2OHCHO ratio in B1b-S, ~20, is similar to that observed in the low-mass protostars in NGC 1333 and IRAS 16293-2422 (Taquet et al. 2015; Jørgensen et al. 2012). Acetic acid (CH3COOH) is the most stable but the least abundant of the three isomers (Lattelais et al. 2010). It has been observed in IRAS 16293-2422 with a ratio with respect to glycolaldehyde of ~11 (Jørgensen et al. 2016), consistent with the 5–15 upper limits in B1b-S. Glycolaldehyde and its corresponding alcohol, ethylene glycol, show similar abundances in B1b-S, slightly higher for CH2OHCHO. This is in contrast to other hot cores and hot corinos (Fuente et al. 2014; Jørgensen et al. 2016; Favre et al. 2017). However, since detections of these species are based on just a few lines, in particular for glycolaldehyde, column densities may be not well constrained and it is difficult to make definite conclusions. We have detected CH3CH2OCOH for the first time in a low-mass protostar, with a relatively high abundance of 10−11. This detection shows that the molecular complexity is high in young hot corinos and other species with a larger number of atoms could be present. It is noteworthy that this species has not been previously observed in the well-known hot corinos IRAS 16293-2422 and NGC 133IRAS4A. We have checked in the ALMA spectral line survey of IRAS 16293-2422 (PILS, Jørgensen et al. 2016), and no clear features are seen, although the observed frequencies are different. It is possible that the high level of line confusion and wide linewidths prevent the detection of weak lines in these more evolved sources.
Citation: Coutens et al. 2018
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The filtered MHD equations read
11







12





where we sum over repeated indices, and
13







14







15







16





denote the inertial (I), Maxwell (M), advective (A), and dynamo (D) subfilter-scale stresses, respectively. Despite their common origin through the electric field in the induction equation, we here treat 





 and 





 separately, in order to disentangle the effects of magnetic-field-line advection, encoded in 





, and magnetic-field-line stretching, encoded in 





. Usually, the magnetic subscale stress refers to the difference 





 (Aluie 2017; Offermans et al. 2018). Equations (11) and (12) differ from expressions for the filtered MHD equations found elsewhere by an additional projection of the coupling terms. The latter ensures that the dynamics defined by Equations (11) and (12) are confined to the same finite-dimensional subspace Ωℓ of the original domain Ω (Buzzicotti et al. 2018; Offermans et al. 2018). At first sight, this formulation suggests that the corresponding evolution equations for kinetic and magnetic energy feature terms are not Galilean invariant, which ought to be avoided as the measured subfilter-scale energy transfers otherwise include unphysical fluctuations (Aluie & Eyink 2009a, 2009b; Buzzicotti et al. 2018). However, the energy balance equations can be expressed in an alternative way by including terms that vanish under spatial averaging and ensure Galilean invariance of all terms (Buzzicotti et al. 2018; Offermans et al. 2018). For a statistically stationary evolution, the spatiotemporally averaged energy budget can then be written as
17







18





where 





 and 





 are the filtered kinetic and magnetic dissipation rates, respectively, and 





 are terms that convert kinetic to magnetic energy 





 and vice versa 





, and
19







20







21







22





denote the four proper energy fluxes, in the sense that they vanish in the limit ℓ → 0, as can be seen from Equations (13)–(16). If positive, the inertial and Maxwell fluxes, 





 and 





 transfer kinetic energy from scales larger than or equal to ℓ to scales smaller than ℓ and vice versa if negative, while the advective and dynamo fluxes, 





 and 





, do so with magnetic energy. Note that there is no interscale energy conversion as the conversion terms 





 and 





 only involve filtered fields; as such they are known as resolved-scale conversion terms (Aluie 2017). The total energy flux is then given by the sum
23
Citation: Buzzicotti et al. 2018
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Citation: Buzzicotti et al. 2018
Citation function: Uses
So far, only one ancient and massive intruder has been identified unambiguously, with its body now nothing but an enormous cloud of tidal wreckage scattered throughout the inner Milky Way. The existence of a vast debris structure left behind by this merger event, known today as the Gaia-Sausage/Enceladus (GS/E), was suggested before Gaia (see Evans 2020, for the historical development). In particular, Deason et al. (2013) argued that the rapid transition in the Galactic stellar halo structural properties at break radius of 20–30 kpc is likely associated with the apocentric pileup of a relatively early (8–10 Gyr ago) and single massive accretion event. It is hypothesized that the progenitor dwarf galaxy was massive enough for its orbit to shrink and radialize quickly as a result of a complex interplay between dynamical deceleration, host recoiling, and self-friction (Vasiliev et al. 2022). Sinking deep in the heart of the Milky Way, the dwarf sprayed the bulk of its stars in a region enclosed by its last apocenter, i.e., some ∼30 kpc (see Deason et al. 2018). As a result, the region of the Galactic halo within this so-called break radius (see Deason et al. 2011) is inundated with the GS/E stars, consistently showing up as the most striking substructure even in relatively small volumes around the Sun (see examples of pre-Gaia hints in, e.g., Chiba & Yoshii 1998; Brook et al. 2003; Meza et al. 2005; Nissen & Schuster 2010; Hawkins et al. 2015). Subsequently, the Gaia data made crystal clear the unusually strong radial anisotropy of the relatively metal-rich GS/E debris and helped to reveal its dominance in the solar neighborhood (see Belokurov et al. 2018; Haywood et al. 2018b; Myeong et al. 2018b). The genesis of the GS/E debris cloud was also unambiguously confirmed by its unique chemical fingerprint (see, e.g., Helmi et al. 2018; Mackereth et al. 2019) and the large group of globular clusters (GCs) associated with it (see, e.g., Myeong et al. 2018c, 2019; Massari et al. 2019). Close to the Sun, the GS/E structure has been thoroughly scrutinized both kinematically and chemically (see Evans et al. 2019; Necib et al. 2019; Sahlholdt et al. 2019; Das et al. 2020; Feuillet et al. 2020, 2021; Kordopatis et al. 2020; Molaro et al. 2020; Monty et al. 2020; Aguado et al. 2021a; Buder et al. 2021a; Bonifacio et al. 2021; Carollo & Chiba 2021; Matsuno et al. 2021). Outside of the solar neighborhood, fewer studies exist; nonetheless, the global structure of the GS/E cloud is starting to come into focus (see, e.g., Iorio & Belokurov 2019; Lancaster et al. 2019; Simion et al. 2019; Naidu et al. 2020; Balbinot & Helmi 2021; Bird et al. 2021; Iorio & Belokurov 2021; Wu et al. 2022).
Citation: Deason et al. 2018
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