adsabs/FOCAL huggingface dataset:
The task of estimating stellar ages has been addressed by several authors and lots of different methods are found in the literature. For instance, there are (i) empirical methods, which use a deterministic relation between a given parameter and the age of a star (first proposed by Skumanich 1972). This is the case of gyrochronology (e.g. Barnes 2003, 2007; Mamajek & Hillenbrand 2008; Collier Cameron et al. 2009), decay of chromospheric activity (e.g. Soderblom, Duncan & Johnson 1991; Rocha-Pinto & Maciel 1998; Rocha-Pinto et al. 2000; Pace & Pasquini 2004; Lyra & Porto de Mello 2005; Pace et al. 2009; Zhao et al. 2011; Pace 2013), lithium depletion (Sestito & Randich 2005; Jackson & Jeffries 2014; Carlos, Nissen & Melendez 2016), and ‘magnetochronology’ (proposed by Vidotto et al. 2014). (ii) Model-dependent methods, which are based on the comparison between measurable physical quantities and the ones expected from stellar structure models that use age as one of its parameters. Isochrone fitting (Edvardsson et al. 1993; Nordström et al. 2004; Pont & Eyer 2004; Jørgensen & Lindegren 2005; Silaj & Landstreet 2014; Maxted, Serenelli & Southworth 2015) and asteroseismology (Cunha et al. 2007; Vauclair 2009; Metcalfe et al. 2010; Silva Aguirre et al. 2017) are classified in this category. (iii) Semifundamental methods, those that are based on well-known fundamental physics and employ only few assumptions. These are the cases for the method of cluster expansion (e.g. Makarov 2007) and nucleocosmocronology, known to predict unreliable ages (Ludwig et al. 2010). (iv) Statistical methods, which use statistical relations, like the age–metallicity relation (AMR) and the age–velocity dispersion relation (AVR), between a given property and the age. These relations have not been much explored in the literature as a direct tool to estimate stellar ages. Some few examples of its usage are found in Lachaume et al. (1999) and Maciel, Rodrigues & Costa (2011) (for the AVR) and Spina et al. (2016) (for the AMR, especially [Y/Mg] × age and [Y/Al] × age).
Citation: Rocha-Pinto et al. 2000
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The use of N-body simulations that include fragmentation allows us to perform a more detailed study of the final composition of the planets formed. In particular, we can study the water loss and/or accretion of the final planets more realistically than in the classic models of accretion. Marcus et al. (2010) presented two empirical models for the mantle stripping in differentiated planetary embryos after a collision. The authors set a simple planet structure of two layers, assuming differentiation in core and mantle, where the mantle could be composed by silicate or ice. In this work, the authors concluded that the more energetic the collision, the more mass from the mantle is lost. Therefore, for violent collisions, water could be more easily removed. Dvorak et al. (2015) performed SPH (smoothed particle hydrodynamics) simulations and studied water loss in planetary embryos and water retained in significant fragments after a collision. They concluded that the impact velocity and the impact angle play a key role in the water loss of a planetary embryo after a collision. The investigations developed by Marcus et al. (2010) and Dvorak et al. (2015) suggest that incorporating a realistic model of volatile transport and removal in an N-body code, may lead to reduced water contents on the resulting terrestrial-like planets, in comparison with those derived from classical models that assume perfect mergers. Burger et al. (2018) studied the volatile loss and transfer. The authors focused on hit-and-run encounters using SPH simulations. They concluded that the cumulative effect of several hit-and-run collisions could efficiently strip off volatile layers of protoplanets. Driven by this, Dugaro et al. (2019) studied the water delivery in planets formed in the habitable zone (HZ), using the mantle stripping models derived by Marcus et al. (2010) in their N-body simulationswith fragmentation. The authors showed that fragmentation is not a barrier for the surviving of water worlds in the HZ, and fragments may be important in the final water content of the potentially habitable terrestrial planets formed in situ.
Citation: Dvorak et al. (2015)
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Citation: Dvorak et al. (2015)
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Diffusive shock acceleration (DSA) operating at expanding shock waves of supernova remnants (SNRs) is widely believed to be the mechanism converting the kinetic energy released by supernova explosions into the energy of cosmic rays (CRs) (e.g., Malkov & Drury 2001). In the DSA theory, CRs being accelerated at shocks must be scattered by self-generated magnetic turbulence. Since the highest-energy CRs in the shock precursor are prone to lack self-generated turbulence, they are expected to escape the shock. The DSA theory generally predicts that a substantial fraction of the shock energy is carried away by escaping CRs. In the presence of molecular clouds surrounding the SNR, escaping CRs can illuminate the clouds through pp interactions, producing gamma-ray emission with a flux depending on the amount of nuclear CRs released by an SNR and the diffusion coefficient in the interstellar medium (ISM; Aharonian & Atoyan 1996; Aharonian et al. 2004; Rodriguez Marrero et al. 2008; Gabici et al. 2009). High Energy Stereoscopic System (H.E.S.S.) observations reveal a complex of sources (HESS J1800-240A, B, and C) ∼0.5° south of the SNR W28, coincident with molecular clouds in the field, and the Large Area Telescope (LAT) on board the Fermi satellite reveals a similar structure in gigaelectronvolt energies (Abdo et al. 2010; Hanabata et al. 2014). The gigaelectronvolt–teraelectronvolt gamma-ray emission around W28 can be regarded as a realization of this scenario (Aharonian et al. 2008). Another example is the detection of two extended gamma-ray structures located at two opposite edges of SNR W44 by Fermi-LAT (Uchiyama et al. 2012; Peron et al. 2020). The gamma-ray emission coincides with the molecular cloud complex that surrounds SNR W44. The gamma-ray emission that appears to come from the surrounding molecular cloud complex can be ascribed to the CRs that have escaped from W44. The total kinetic energy channeled into the escaping CRs is estimated to be larger than a few 1049 erg in both W28 and W44, although the exact number depends on the value of the diffusion coefficient of escaping CRs.
Citation: Gabici et al. 2009
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Our spectroscopic coverage includes the damped Lyα absorption (DLA) feature from neutral hydrogen. Analysis of this feature is complicated by blending between the host and the companion, as well as uncertainties in the continuum modeling, and it is difficult to constrain the individual contributions of the two component systems to the overall line. Modeling the line as two separate, blended Voigt profiles, we can robustly constrain the total column density of the two systems together to 5 × 1019 cm−2 ≤ N(H i) ≤ 9 × 1019 cm−2; our best-fit estimate is (6.7 ± 1.2) × 1019 cm−2, making the system technically a sub-DLA (Péroux et al. 2003). This spread in N(H i) is due to uncertainties in the relative contributions of the two systems and continuum placement. The derived N(H i) is an order of magnitude less than a typical value through a disk of a spiral galaxy with stellar mass >1010 M⊙, measured by The H i Nearby Galaxy Survey (THINGS; Walter et al. 2008; Leroy et al. 2008). This result has two implications. One is that SN2017egm may have exploded on the near side of the galaxy, where there is less neutral H i material along the line of sight. One may argue for the second possibility that UV fluxes from the SN explosion could photoionize a large fraction of neutral H i in the disk of NGC 3191, and SN2017egm could be anywhere in the disk. To validate this hypothesis, we calculate the time required, tphot, to photoionize N(H i) ∼ 1021 cm−2 over a scale height R of an H i disk. H i-ionizing flux, JUV, at the time of SN explosion is poorly constrained by observation. Let us take JUV as a fraction of fUV of the peak bolometric luminosity (Lbol); thus we have 





. The Milky Way thin disk (stellar) has a scale height of 100 pc.7

7
The H i gas can be more extended (Marasco & Fraternali 2011).
 As the most conservative assumption, let us take R = 50 pc if the SN is at the mid-plane; thus we have 





 cm−2 s−1. In this equation, without any knowledge of the early-time UV fluxes from SN 2017egm, we assume it is only 10% of the estimated bolometric luminosity (fUV = 0.01). Here, the maximum Lbol is 2 × 1044 erg s−1. To photoionize a column of 1021 cm−2 H i atoms, we need the same number of H i-ionizing photons, thus, over a timescale of tphot, we have JUVtphot ≃ 1021 cm−2, leading to tphot = 3 × 109 s. This is two orders of magnitude longer than the time lag between the explosion and the HST spectroscopy date for SN2017egm. Since 





, a larger fUV value will shorten the photoionization timescale tphot by a factor of a few, but not enough to change our conclusion. This result suggests that photoionization due to the SN explosion is probably localized within a 5 pc region.
Citation: Leroy et al. 2008
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Among the several features, the distribution of chemical elements across the Galactic disc historically constitutes the most important constraint to chemo-dynamical models of our Milky Way. A number of studies (e.g. Tosi 1988; Hayden et al. 2014, 2015; Anders et al. 2017) have shown the spatial distributions of chemical abundances and their ratios across the Galactic disc. However, these studies are mainly based on field stars, which also include very old populations that had time to migrate significantly and redistribute the chemical elements across the Galaxy (e.g. Sellwood & Binney 2002; Roškar et al. 2012; Martinez-Medina et al. 2016). Open clusters are a valuable alternative, being on average younger (Magrini et al. 2017), and therefore a better tracer of the gradients in the disc out of which the most recent stars formed. Since the work of Janes (1979), much observational evidence has established that the metallicity distribution (often abbreviated by the iron-to-hydrogen ratio [Fe/H]) traced by clusters throughout the Milky Way disc shows a significant decrease with increasing distance from the Galactic Centre. This ‘radial metallicity gradient’ – in its apparent simplicity – reflects a complex interplay between several processes that are driving the evolution of our Galaxy, including star formation, stellar evolution, stellar migration, gas flows, and cluster disruption (Cunha & Lambert 1992, 1994; Friel 1995; Stahler & Palla 2004; Carraro et al. 2006; Boesgaard, Jensen & Deliyannis 2009; Magrini et al. 2009; Frinchaboy et al. 2013; Netopil et al. 2016; Anders et al. 2017; Spina et al. 2017; Bertelli Motta et al. 2018; Quillen et al. 2018). Complementary to the study of the overall metallicity distribution, the abundance ratios of several other elements, such as α-elements, iron peak, odd-z, and neutron capture, can provide deep insight into the variety of nucleosynthesis processes, with their production sites and time-scales (e.g. Carrera & Pancino 2011; Ting et al. 2012; Reddy, Lambert & Giridhar 2016; Duffau et al. 2017; Magrini et al. 2017, 2018; Donor et al. 2020; Casamiquela et al. 2020). Therefore, understanding the distribution of metals traced by clusters across the Galactic disc is fundamental for explaining the birth, life, and death of both stars and clusters, the recent evolution of our own Milky Way, and the evolution of other spiral galaxies (Boissier & Prantzos 2000; Bresolin 2019).
Citation: Magrini et al. 2017
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Citation: Magrini et al. 2017
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Many studies often have environmental classes simply divided into (relaxed) ‘clusters’ or ‘fields’. However, in a Λ cold dark matter (ΛCDM) Universe, most clusters are expected to be the result of group/smaller cluster mergers – some of which can be extremely violent. Little is known about the role of cluster and group mergers in galaxy formation and evolution, and whether they could be important in setting the environmental trends which have now been robustly measured and described. It is particularly important to understand if cluster mergers trigger star formation (e.g. Miller & Owen 2003; Ferrari et al. 2005; Owen et al. 2005; Hwang & Lee 2009; Wegner, Chu & Hwang 2015), if they quench it (e.g. Poggianti et al. 2004), or, alternatively, if they have no direct effect (e.g. Chung et al. 2010). Results from Umeda et al. (2004), studying a merging cluster at z ∼ 0.2 (Abell 521) found tentative evidence that merging clusters could perhaps trigger star formation. More recently, Stroe et al. (2014a) conducted a wide field Hα narrow-band survey over two merging clusters with a simple geometry, with the merger happening in the plane of the sky. Stroe et al. (2014a) find a strong boost in the normalization of the Hα luminosity function of the CIZA J2242.8+5301 (‘Sausage’) cluster, several times above the field and other clusters. The authors suggest that they may be witnessing star formation enhancement or triggered due to the passage of the shock wave seen in the radio and X-rays. Interestingly, Stroe et al. (2014a) do not find this effect on the other similar merging cluster studied (‘Toothbrush’), likely because it is a significantly older merger (about 1 Gyr older; cf. Stroe et al. 2014a, 2015), and thus displays only the final result (an excess of post-starburst galaxies instead of Hα emitters). The results are in very good agreement with simulations by Roediger et al. (2014) and recent observational results by Pranger et al. (2014).
Citation: Chung et al. 2010
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The possible presence of dust in the habitable zones of nearby main-sequence stars is considered a major threat for the direct imaging and characterization of Earth-like extrasolar planets (exo-Earths) with future dedicated space-based telescopes. Several independent studies have addressed this issue and concluded that visible to mid-infrared direct detection of exo-Earths would be seriously hampered in the presence of dust disks 10 to 20Â times brighter than the solar zodiacal cloud assuming a smooth brightness distribution (e.g., Beichman et al. 2006; DefrÃ¨re et al. 2010; Roberge et al. 2012). The prevalence of exozodiacal dust at such a level in the terrestrial planet region of nearby planetary systems is currently poorly constrained and must be determined to design these future space-based instruments. So far, only the bright end of the exozodi luminosity function has been measured on a statistically meaningful sample of stars (Lawler et al. 2009; Kennedy & Wyatt 2013). Based on WISE observations and extrapolating over many orders of magnitude, Kennedy & Wyatt (2013) suggest that at least 10% of gigayear-old main-sequence stars may have sufficient exozodiacal dust to cause problems for future exo-Earth imaging missions. To determine the prevalence of exozodiacal dust at the faint end of the luminosity function, NASA has funded the Keck Interferometer Nuller (KIN) and the Large Binocular Telescope Interferometer (LBTI) to carry out surveys of nearby main-sequence stars. Science observations with the KIN started in 2008 and the results were reported recently (Millan-Gabet et al. 2011; Mennesson et al. 2014). One of their analyses focused on a sample of 20 solar-type stars with no far infrared excess previously detected (i.e., no outer dust reservoir). Assuming a log-normal luminosity distribution, they derived the median level of exozodiacal dust around such stars to be below 60Â times the solar value with high confidence (95%). Yet, the state-of-the-art exozodi sensitivity achieved per object by the KIN is approximately one order of magnitude larger than that required to prepare future exo-Earth imaging instruments.
Citation: Roberge et al. 2012
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The binary characteristics of early-type magnetic stars may provide crucial clues, allowing one to test alternative fossil field hypotheses. The non-magnetic chemically peculiar stars of Am (A-type stars with enhanced lines of Fe-peak elements) and HgMn (late-B stars identified by strong lines of Hg and/or Mn) types are frequently found in close binaries (Gerbaldi, Floquet & Hauck 1985; Ryabchikova 1998; Carquillat & Prieur 2007), including eclipsing systems (Nordstrom & Johansen 1994; Strassmeier et al. 2017; Takeda et al. 2019). In contrast, only about ten close (Porb  20 d) spectroscopic binaries containing at least one magnetic ApBp star are known (Landstreet et al. 2017). The overall incidence rate of magnetic upper main sequence stars in close binaries is less than 2 per cent (Alecian et al. 2015), although this fraction is significantly higher if one includes wide long-period systems (Mathys 2017). This low incidence of magnetic ApBp stars in close binaries is frequently considered as an argument in favour of the stellar merger origin of fossil fields (de Mink et al. 2014; Schneider et al. 2016). In this context, confirmation of magnetic ApBp stars in short-period binary systems gives support to alternative theories or, at least, demonstrates that early-type stars may acquire magnetic fields through different channels. In addition, detached close binary stars, particularly those showing eclipses, are valuable astrophysical laboratories that provide model-independent stellar parameters and allow one to study pairs of co-evolving stars formed in the same environment. Until recently, no early-type magnetic stars in eclipsing binaries were known. The first such system, HD 66051, was identified by Kochukhov et al. (2018). The second system, HD 62658 containing twin components of which only one is magnetic, was found by Shultz et al. (2019). Several other eclipsing binaries containing candidate ApBp stars were proposed (Hensberge et al. 2007; González, Hubrig & Castelli 2010; Skarka et al. 2019), but the magnetic nature of these stars has not been verified by direct detections of their fields using the Zeeman effect. In this paper, we put a spotlight on another candidate eclipsing magnetic Bp star, which received little attention prior to our work despite being significantly brighter than the confirmed magnetic eclipsing systems HD 62658 and HD 66051.
Citation: Mathys 2017
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Below, we describe a simple emission model that can explain most of the key emission features of the pulsars presented in this paper. It draws significantly from the model proposed in Timokhin (2010) that explains nulling and mode changing in pulsars by shrinking and expanding the magnetosphere of the neutron star. The model assumes a dipole magnetic field line structure and a schematic diagram is shown in Fig. 10. The emission beam is assumed to be a ‘fan beam’ with multiple flux tubes along the open field lines (Karastergiou & Johnston 2007; Oswald, Karastergiou & Johnston 2019). We assume the fan beam to be “patchy” and partially filled meaning that only a portion of the tube is emitting radiation. The patchy beam scenario is one of the common beam models that has been used to explain the emission properties of pulsars (see Lyne & Manchester 1988; Manchester et al. 2010). As shown in Fig. 10, it is assumed that the emission patch is fixed within the polar cap region, i.e. the region consists of open magnetic field lines with respect to the boundary of the comoving magnetosphere (known as the light cylinder). When the magnetosphere shrinks the polar cap region expands accordingly with the dipole field lines and changes the orientation of the emission flux tube produced from the patchy region (see Fig. 10b). Due to these changes, our line of sight (LoS) encounters a different part of the flux tube, resulting in variation in the observed pulse profile shape, switching the pulsar from the normal to swoosh emission. It has been postulated that low-frequency radio emission is produced at a higher altitude compared to the high-frequency emission in the magnetosphere (i.e. – RFM, Cordes 1978; Oswald et al. 2019). Therefore, due to the curvature of the dipole magnetic field lines, the flux tube of the patchy beam at a lower frequency can be oriented in a direction that is out of our LoS (see Fig. 10b). This results in apparent nulls at low frequencies, which is consistent with the observations of PSR B0919+06 (see Fig. 1, and also Shaifullah et al. 2018).
Citation: Lyne & Manchester 1988
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The difficulty resides in the definition of ‘group’ itself. If on the simulation side, groups are well defined thanks to an access to the entire three-dimensional information, on the observational side, calling an ensemble of galaxies a group constitutes a great challenge because of a restricted access to the information. In observations, knowing precisely the fraction of collapsed material becomes quite problematic. Still several schemes have been developed to define groups within galaxy catalogues. They mainly invoke Friends of Friends (FoF) like algorithms based on projected separation, radial velocities and even luminosities to identify what are called ‘groups’ of galaxies (e.g. Huchra & Geller 1982; Geller & Huchra 1983; Ramella et al. 2002; Eke et al. 2004; Yang et al. 2005; Crook et al. 2007; Lavaux & Hudson 2011; Makarov & Karachentsev 2011; Old et al. 2014; Tempel et al. 2014; Old et al. 2015). This paper does not aim at scrutinizing in detail the methods used to group catalogues. It aims at testing two recently released versions of groups for galaxies in the local Universe to understand the differences in the reconstructions generated by two various grouping schemes as described below:
Tempel et al. (2016) introduced a new grouping method (hereafter Tempel Grouping scheme). This method is based on a widely used FoF percolation method, where different linking lengths in radial (along the line of sight) and in transversal (in the plane of the sky) directions are used but the conventional FoF groups are refined using multimodality analysis. More precisely, Tempel et al. (2016) use a model-based clustering analysis to check the multimodality of groups found by the FoF algorithm and they separate nearby/merging systems. In the current paper, we use published catalogues of groups detected using this new method.Tully Grouping scheme is based on literature groups and in that respect is not a systematic scheme. Within 30 Mpc, groups are those identified by Tully (1987), further away groups are those given in the literature like Abell’s catalogue (Abell, Corwin & Olowin 1989). Recently, Tully (2015a,b) published a more systematic way of deriving groups based on radii of second turn around and iterations. After comparisons, we find that the catalogue grouped with this last scheme is an intermediate between the catalogues obtained with Tully and Tempel Grouping schemes and as such will result in more mitigated conclusions would we compare it to Tempel Grouping scheme. In addition, Tully Grouping scheme has been used so far with the second catalogue to build constrained initial conditions. We thus stick to Tully Grouping scheme in the rest of the paper.4
Citation: Ramella et al. 2002
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