By comparing our results with the numerical studies of Wyper et al. (2017, 2018), we propose a compound eruption model of circular-ribbon flares consisting of two sets of successively formed ribbons and eruptions of multiple filaments in a fan-spine-type magnetic configuration. A simple schematic picture is shown in Figure 6. First, the null-point reconnection between the outermost flux of the filament F1 (blue curves) and the ambient open field occurs (panel (a)), which transfers partial flux of F1 to the closed field under the far side of the dome and to the open field exterior to the near side of the dome (dashed cyan lines in panel (a)). Meanwhile, the circular ribbon CR1 and inner ribbon IR1 (orange curves) are generated due to the flow of reconnection-accelerated particles from the null along the fan plane and the spine field into the lower atmosphere. The null-point reconnection is likely of the breakout nature (Antiochos et al. 1999; Wyper et al. 2017, 2018). Then, the F1 undergoes the slipping magnetic reconnection along the QSL binding the F1, which induces the far flux of F1 reaching the null point (panel (b)). The continuous null-point reconnection causes the sequential opening of F1, and thus leads to the significant shifts of the brightenings of CR1 and IR1 (orange regions in panel (b)). In the first episode, partial flux is transferred from under the separatrix dome via the null-point reconnection, which effectively alleviates the constraint of the nearby filament F2 (green curves). Later on, the stability of F2 is disrupted and the second episode of the flare is initiated. The continuous null-point reconnection between F2 and open field is at work and generates the sequential brightenings of CR2 and IR2 (panels (c)–(d)), similar to the evolution of the first episode. Meanwhile, the blowout jet is formed at the same time as filament material below the separatrix is ejected along field lines outside the separatrix.


In order to separate the role of different physical mechanisms in galaxy evolution, a number of studies have constrained stellar-to-halo mass (SHM) relations and ratios as a function of time using the abundance matching technique (e.g. Behroozi, Conroy & Wechsler 2010a; Moster et al. 2010; Behroozi, Conroy & Wechsler 2010b), the conditional luminosity function technique proposed by Yang, Mo & Van Den Bosch (2003), the halo occupation distribution (HOD) formalism (e.g. Berlind & Weinberg 2002; Kravtsov et al. 2004; Moster et al. 2010), and by combining the HOD, N-body simulations, galaxy clustering, and galaxy–galaxy lensing techniques (e.g. Leauthaud et al. 2012; Coupon et al. 2015). Distinguishing the properties of central galaxies from those of satellite galaxies in studies based only on the distribution of luminosity or stellar mass is challenging (e.g. George et al. 2011). By combining several observables and techniques (e.g. HOD, galaxy–galaxy lensing, and galaxy clustering) one can probe a global SHM relation for central galaxies and satellite galaxies (e.g. Leauthaud et al. 2012; Coupon et al. 2015). Coupon et al. (2015), for example, used multiwavelength data of ∼60 000 galaxies with spectroscopic redshifts in the Canada France Hawaii Telescope Lensing Survey (CFHTLenS) and Vimos Public Extragalactic Redshift Survey (VIPERS) field to constrain the relationship between central/satellite mass and halo mass, characterizing the contributions from central and satellite galaxies in the SHM relation. In this paper, we directly identify the BGGs using their precise redshifts and estimate stellar masses using the broad-band spectral energy distribution (SED) fitting technique (Ilbert et al. 2010) as used by Coupon et al. (2015). We utilize the advantages of the X-ray selection of galaxy groups and a wealth of multiwavelength, high signal-to-noise ratio observations such as the UltraVISTA survey in the COSMOS field (Laigle, Capak & Scoville 2016) to investigate the SHM relation for the central galaxies over 9 billion years. We aim to quantify the intrinsic (lognormal) scatter in stellar mass at fixed redshift in observations and compare them to the recently implemented semi-analytic model (SAM) by Henriques et al. (2015).


The choice of κ has some bearing on the value of Mej as calculated in Eq. (2). Although taken as a constant in various model light curves, the actual optical opacity varies with time (e.g. Chugai 2000; Nagy 2018), but tests have shown that that a constant opacity can be a reasonable assumption at early times (see Mazzali et al. 2000; Taddia et al. 2018). SN 2019bkc is a H/He-deficient SN, so to select an appropriate value for κ, we search the literature literature and consider only SNe of this type. For SNe Ia, where the large abundance of Fe-group elements is a source of significant opacity, Cappellaro et al. (1997) used κ = 0.15 cm2 g−1, while Arnett (1982) used κ = 0.08 cm2 g−1. The light curve of the broad lined SNe Ic 1997ef was modelled in Mazzali et al. (2000) using the same code as Cappellaro et al. (1997), this time a lower constant opacity of 0.08 cm2 g−1 was used owing to the lower Fe abundance in this SN type. The average opacity of model CC-SNe light curves was investigated by Nagy (2018), where it was found that κ = 0.1 cm2 g−1 was suitable for their H/He-deficient models. Taddia et al. (2018) demonstrated that fitting the light curves of H-deficient CC-SNe with a simple analytical model and a constant opacity κ = 0.07 cm2 g−1 returned physical parameters consistent with more complex hydrodynamic light curve models. Prentice et al. (2019) also found that using κ = 0.07 cm2 g−1 gave comparable ejecta masses to both photospheric phase and nebular phase spectroscopic modelling of H-deficient CC-SNe, with the exception of some gamma-ray burst SNe. From Sect. 5 we find that the outer ejecta is not rich in Fe-group elements, and there is no indication of helium. From the early-nebular spectra in Sect. 4.2 we see no indication of strong Fe II or Fe III line emission, demonstrating that the ejecta is poor in Fe-group elements relative to normal SNe Ia and is more like H/He-deficient CC-SNe. This justifies the use of κ = 0.07 cm2 g−1, but to show the range of possible Mej, we consider the range 0.07–0.1 cm2 g−1.


As regards the modeling of BGK modes, there are two main theoretical approaches: the integral solution or BGK methodology and the differential (or Schamel) technique. In the former method (BGK), one assumes that the initial particle distribution function and the electrostatic potential profiles are known, so these are substituted into the Poisson equation and the integral equation is solved to obtain the trapped particle distribution function (Bernstein et al. 1957; Aravindakshan et al. 2018a, 2018b, and the references therein). In Schamel’s approach, the form of the trapped particle distribution function and of the passing (i.e., free, nontrapped) particle distribution function is assumed and substituted in Poisson’s equation, leading to a differential equation that is then solved to obtain the form of the potential (Schamel 1986; Luque & Schamel 2005, and the references therein). A distinguishing factor in the former (BGK) approach is that it involves a condition in the form of an inequality to be satisfied by the potential parameters (width and amplitude) in order for a BGK mode to be sustained. The BGK approach will be adopted in this work. The above models tacitly assume a collisionless electron-ion plasma. These assumptions are acceptable in the Earth’s magnetosphere. However, as we move farther from near-Earth plasma environments, the presence of charged dust in the plasma cannot be neglected. In the case of Saturn, there are observations of streaming ions by the Cassini spacecraft (Badman et al. 2012a, 2012b). We know that these streaming ion flows can lead to the generation of ion holes. Electrostatic solitary waves have been observed in Saturn’s magnetosphere (Williams et al. 2006) and in the dusty environment near its moon Enceladus (Pickett et al. 2015). Williams et al. (2006) reported observations of solitary structures in the vicinity of Saturn’s magnetosphere. They detected a series of bipolar pulses and speculated that these could be either electron holes or ion holes (Williams et al. 2006). Later on, Pickett et al. (2015) observed solitary wave pulses within 10 Rs (Rs is the Saturn radius) and near Enceladus. Near the Enceladus plume, they discussed how dust impacts affected the observed solitary waves. In fact, Pickett et al. (2015) pointed out that some of the bipolar electric field pulses associated with the solitary waves observed had an inverse polarity (i.e., a positive pulse first, followed by a negative pulse in a short time period) and suggested that this might be due to either an inverse direction of propagation or to a true inverse potential pulse polarity (sign). Moreover, Farrell et al. (2017) examined the conditions that allow low-energy ions, such as those produced in the Enceladus plume, to be attracted and trapped within the sheath of negatively charged dust grains. Using particle-in-cell simulations, they showed that with dust in the system, the large electric field from the grain charge disrupts pickup and leads to ion trapping. Their simulation results also reveal that the bipolar pulses reported in the Enceladus plume by Williams et al. (2006) and Pickett et al. (2015) could most probably be ion holes. In the light of the above information, we may suggest that the formation of ion holes is highly likely in the dusty plasma of environments such as the one found in Saturn. Importantly, the instrument on board Cassini, the Radio Plasma Wave Science instrument, does not have the ability to determine the polarity of the electric fields associated with the ESWs observed with 100% certainty as it lacks the ability to perform interferometry (Williams et al. 2006).

Williams et al. (2006)
Williams et al. 2006


The stellar initial mass function (IMF) of stars (i.e., the distribution of the masses of stars at their birth) is of fundamental importance in astrophysics. The IMF controls the efficiency of star formation in molecular clouds (Dib et al. 2011, 2013; Hony et al. 2015), the radiative and mechanical feedback from stars into the large-scale interstellar medium (Dib et al. 2006, 2021; Martizzi et al. 2016; Silich & Tenorio-Tagle 2017), and the dynamical and chemical evolution of galaxies (Côté et al. 2016). Significant efforts have been devoted to the determination of the shape of the IMF in a variety of environments, including the Galactic field (Salpeter 1955; Bochanski et al. 2010; Rybizki & Just 2015; Mor et al. 2019; Sollima 2019), the Galactic bulge (Zoccali et al. 2000; Wegg et al. 2017), and globular clusters (GCs; Da Costa & Freeman 1976; De Marchi & Paresce 1997; Covino & Ortolani 1997; Marconi et al. 1998; Paresce & De Marchi 2000; Sollima et al. 2007; Balbinot et al. 2009; Sollima & Baumgardt 2017; Cadelano et al. 2020), as well as in many young open clusters and associations (Dib 2014; Weisz et al. 2015; Maia et al. 2016; Dib et al. 2017; Jose et al. 2017; Madaan et al. 2020; Bisht et al. 2021; Damian et al. 2021; Elsanhoury et al. 2022). The existence of IMF variations in clusters has significant consequences for the galaxy-wide IMF and for galactic evolution (Dib & Basu 2018; Dib 2022). In the galactic ecosystem, GCs stand out as relics of early star formation with ages that span the range ≈11 Gyr to ≈13.2 Gyr (Salaris et al. 1997; VandenBerg et al. 2013; Pfeffer et al. 2018; Usher et al. 2019; Oliveira et al. 2020), and it is well established that GCs in the Milky Way and in the Magellanic clouds harbor two or more stellar populations (D’Antona & Caloi 2008; Milone et al. 2010; Sbordone et al. 2011; Gratton et al. 2012; Cummings et al. 2014; Piotto et al. 2015; Lee 2015; Oldham & Auger 2016; Mucciarelli et al. 2016; Massari et al. 2016; Dalessandro et al. 2016; Bowman et al. 2017; Carretta & Bragaglia 2018; Latour et al. 2019; Gilligan et al. 2020; Dondoglio et al. 2021; Jang et al. 2021; D’Antona et al. 2022; Kapse et al. 2022).


With a mass of Mb = 37.1 ± 5.6 M⊕ and a radius of Rb = 7.50 ± 0.44 R⊕, K2-280 b joins the group of sub-Saturns planets – defined as planets having radii between 4 and 8 R⊕ (Petigura et al. 2017) – whose masses and radii have been measured. The basic physical parameters of a sample of 23 sub-Saturns with densities measured with a precision better than 50 per cent have been presented and discussed by Petigura et al. (2017). We here extend this sample by adding K2-280 b alongside 6 additional sub-Saturns that have densities measured with a precision better than 50 per cent, as described below. WASP-156 b (Demangeon et al. 2018), an ∼0.5 $\mathrm{R_\mathrm{Jup}}$ planet with a Jupiter-like density was discovered by the ground-based SuperWASP transit survey (Pollacco et al. 2006; Smith & WASP Consortium 2014). Kepler-1656 b, a dense sub-Saturn with a high eccentricity of e = 0.84 transiting a relatively bright (V = 11.6 mag) solar-type star, was recently reported by Brady et al. (2018). Three sub-Saturns were discovered and characterized by the KESPRINT consortium, two of them in K2 campaign 3 (K2-60 b, Eigmüller et al. 2017) and campaign 14 (HD 89345 b, aka K2-234 b, Van Eylen et al. 2018; Yu et al. 2018b), and HD 219666 b (Esposito et al. 2019) in TESS Sector 1. One sub-Saturn, GJ 3470 b (Bonfils et al. 2012), orbiting an M1.5 dwarf was not included by Petigura et al. (2017), but we add it to the current sample, adopting the parameters from Awiphan et al. (2016). All of these new sub-Saturns, including K2-280 b, reside in apparently single systems. Fig. 6 shows the mass–radius and mass–density diagrams for this extended sample of 30 planets. Sub-Saturns found to be in multiplanet systems are marked with green filled circles, whereas those in single systems are marked with blue filled circles. The position of K2-280 b is indicated with a red-rimmed circle. Sub-Saturns whose density has been measured with a precision slightly worse than 50 per cent are marked with green and blue open circles. All the remaining transiting planets with measured radii and masses are marked with open grey circles.12 According to the Fortney, Marley & Barnes (2007)’s models – also shown in the mass–radius diagram (Fig. 6, upper panel) – K2-280 b has a core of about 10–25 M⊕, accounting for ∼25–65 per cent of its total mass.


At quasi-perpendicular shocks, the average shock structure is dominated by a foot of reflected ions, which is upstream of the shock ramp where the major thermalization and deceleration occurs. Non-stationarity in the form of rippling of the surface or steepened whistler waves (Moullard et al. 2006; Lobzin et al. 2007) is an intrinsic feature of the shock, but this is generally manifest as minor perturbations on top of an otherwise stationary shock ramp. Simulations have predicted that if the fraction of ions reflected by the shock front becomes sufficiently high, the quasi-perpendicular shock can become periodically reforming on timescales of the ion gyroperiod. Various theories have been suggested for such non-stationarity, including self-reformation where a new shock ramp grows at the edge of the foot (Biskamp & Welter 1972a; Lembège & Dawson 1987), whistler-induced reformation (Biskamp & Welter 1972b; Scholer & Burgess 2007), kinetic instabilities such as the Buneman and modified two-stream instability (e.g., Cargill & Papadopoulos 1988; Matsukiyo & Scholer 2003, 2006b; Scholer et al. 2003; Scholer & Burgess 2007; Matsumoto et al. 2013), and gradient catastrophe of nonlinear whistler waves due to steepening (Krasnoselskikh et al. 2002). However, it has not been until recently that such non-stationarity has been confirmed with in situ spacecraft observations. In a survey of Cassini shock crossings at Saturn, Sulaiman et al. (2015) found evidence of a periodically reforming shock, pulsating at a period near 0.3 of the ion gyroperiod in the unperturbed upstream medium. This period agrees with the time taken for a specularly reflected proton to gyrate across the foot and return to the main shock ramp. Sulaiman et al. (2015) also report that these periodic non-stationary shocks are primarily found in the very high Mach number regime, which gives evidence for a relation between Mach number and reformation. The main processes behind the non-stationary behavior of these very high Mach number shocks, such as the details of the ion- and electron-scale processes acting within the shock transition, remain elusive.


Set II: we now focus on the observational constraints on the model parameters after the inclusion of the local measurement of H0 by Riess et al. (2018) with the previous data sets (CMB, Pantheon, and CC) in order to see how the parameters could be improved with the inclusion of this data point. Since for this present UM, the estimation of H0 from CMB alone is compatible with the local estimation of H0 by Riess et al. (2018), thus, we can safely add both the data sets to see whether we could have something interesting. Following this, we perform another couple of tests after the inclusion of R18. The observational results on the model parameters are summarized in Table 4. However, comparing the observational constraints reported in Table 3 (without R18 data) and Table 4 (with R18), one can see that the inclusion of R18 data (Riess et al. 2018) does not seem to improve the constraints on the model parameters. In fact, the estimation of the Hubble constant H0 remains almost similar to what we found in Table 3. In order to be more elaborate in this issue, we have compared the observational constraints on the model parameters before and after the inclusion of R18 to other data sets. In Figs 7 (CMB versus CMB+R18), 8 (CMB+CC versus CMB+CC+R18), 9 (CMB+Pantheon versus CMB+Pantheon+R18), and 10 (CMB+Pantheon+CC versus CMB+Pantheon+CC+R18), we have shown the comparisons which prove our claim. One can further point out that the strong correlation between the parameters μ and H0 as observed in Fig. 5 still remains after the inclusion of R18 [see specifically the (μ, H0) planes in Figs 7–10]. The physical nature of μ does not alter at all. That means the correlation between H0 and μ is still existing after the inclusion of R18 to the previous data sets, such as CMB, Pantheon, and CC. In addition to that since μ ≲ 0.9 according to all the observational data sets, thus, the transition from past decelerating era to current accelerating era occurs to be around z ≲ 0.6, similar to what we have found with previous data sets (Table 3).


Since for this present UM, the estimation of H0 from CMB alone is compatible with the local estimation of H0 by

, thus, we can safely add both the data sets to see whether we could have something interesting.


Molecular line ratio diagrams for NGC 4710, NGC 5866 and a variety of other galaxies. Our data for NGC 4710 and NGC 5866 are shown as filled circles and squares, respectively, while our data for the nuclear discs and inner rings are shown in blue and red, respectively (black for the intermediate region). Upper and lower limits are represented by arrows. Other lenticular galaxies are indicated by magenta filled stars (Krips et al. 2010; Crocker et al. 2012), starburst nuclei by dark green filled stars, Seyferts by brown filled stars, spiral arm GMCs by black circles with an X (see Baan et al. 2008; table 3 in Krips et al. 2010 and references therein), NGC 6946 (starburst) GMCs by black circles with a cross (Topal et al. 2014), and M31 GMCs by turquoise circles with an X (Brouillet et al. 2005). The data for NGC 1266 (a lenticular galaxy with a molecular outflow) are shown by magenta squares with a filled star (Alatalo et al. 2011). The green shaded region in panel a indicates the typical range of 12CO(1–0)/HCN(1–0) ratios in starbursts with LFIR > 1011 L⊙ (see table B2 in Baan et al. 2008). The range of R11 ratios in the nuclear disc and inner ring of NGC 5866 (this work) are indicated by respectively the blue and red horizontal lines in panel b, while the typical range in spirals with LFIR  1011 L⊙ (Paglione et al. 2001) is indicated by the pale grey shaded region. In panels a and b, Crocker et al.'s (2012) single-dish observations of NGC 4710 and NGC 5866 are shown as an open black circle and an open black square, respectively (see table 4 of Crocker et al. 2012). The HCN(1–0)/HCO+ ratios for M31 GMCs (Brouillet et al. 2005) are indicated by the turquoise shaded region in panels c and d. The green shaded region in panel d indicates the typical range of 13CO(1–0)/HCO+(1–0) ratios in the disc of M82 (starburst; Tan et al. 2011). The 12CO(1–0)/HCN(1–0) ratios in spirals (Gao & Solomon 2004a) are indicated by the dark grey shaded region in panels a, e and f, respectively. The black solid lines in a number of panels show the 1 : 1 relation and are there to guide the eye. Similarly, the black dashed lines show a ratio of 1 in panels c, d and f.


The two LSST observing programs are complementary in the SN samples they will provide. The main survey will obtain light curves in six bands and photometric redshifts of about 400,000 photometrically classified SNe Ia that can be used for cosmological distance measurements, with further spectroscopic follow-up of a subsample of their host galaxies. Such a sample will not only provide larger statistics for the study of the Type Ia population in the universe but also be spread across the full 18,000 deg2 LSST main survey footprint, allowing different probes of the large-scale structure of the low-redshift universe. This sample of SNe can be used as a tracer of large-scale structure by directly probing the gravitational potential of structure through inferences of their peculiar velocities (Gordon et al. 2007; Bhattacharya et al. 2011; Howlett et al. 2017), WL of SN brightnesses (Dodelson & Vallinotto 2006; Quartin et al. 2014; Macaulay et al. 2017; Scovacricchi et al. 2017), and the local bulk flow (Riess 2000; Dai et al. 2011; Turnbull et al. 2012; Feindt et al. 2013; Huterer et al. 2015), as well as low-redshift constraints on the isotropy of the universe (Antoniou & Perivolaropoulos 2010; Campanelli et al. 2011; Colin et al. 2011; Cai et al. 2013; Javanmardi et al. 2015). The rapidly sampled Deep Drilling Fields, possibly co-added over short timescales, will yield well-sampled light curves of tens of thousands of SNe to redshifts peaking around z ∼ 0.7 and reaching beyond a redshift of 1.0, limited by the systematics related to the limits of our astrophysical understanding of SN populations and relative photometric calibration. In addition to the usual use of SNe Ia to probe the redshift–distance relation to high redshift, the luminosities will be magnified by lensing from foreground structure, a correlation that can be probed with these data. The ultimate promise of such SN surveys will be linked to the observing strategy employed by the LSST.


However, a significant outstanding problem of using red giants is that modeling their individual frequencies is too time consuming for the analysis of tens of thousands of stars. We therefore rely on using asteroseismic scaling relations,

ν

max

∝

gT

eff

−
1

/

2

 and

Δ
ν
∝
ρ

 (Brown et al. 1991; Kjeldsen & Bedding 1995), to estimate their radius and mass (and hence age). Here,

ν

max

 is the frequency of maximum amplitude and

Δ
ν

 the average large frequency separation. These relations assume that the structure of a red giant star is homologous with respect to the Sun. In reality this assumption is not strictly correct and verification of the relations is ongoing. However, the independent high-precision estimates of mass and radius required for this verification are difficult to obtain. For subgiants and dwarfs, the

ν

max

 scaling relation has been shown to work well (Bedding 2014) and recently, Coelho et al. (2015) found the proportionality

ν

max

∝

gT

eff

−
1

/

2

 to be accurate to within 1.5%. Using Hipparcos parallaxes and/or interferometry, the asteroseismic radii calculated from scaling relations have been found to be accurate to within 5% (Bruntt et al. 2010; Huber et al. 2012; Silva Aguirre et al. 2012). For giants we generally do not have accurate parallaxes, so such studies are awaiting results from Gaia (Perryman 2002). Open clusters have been used to test the scaling relations for giants (Brogaard et al. 2012; Miglio et al. 2012; Sandquist et al. 2013). Miglio et al. (2012) found agreement to within 5% for scaling relation-based radii. Testing of masses is more challenging. For a few cases where such verification have been performed, the scaling relation-based masses seem to be overestimated for giants (Miglio et al. 2012; Frandsen et al. 2013; Epstein et al. 2014). For two lower red giant branch stars (Epstein et al. 2014) find evidence that the mass estimated by using only

Δ
ν

 (but with additional

ν

max

 independent quantities) is lower compared to using both

Δ
ν

 and

ν

max

. Based on this they suggested that a modification to the

ν

max

 scaling relation might be required. Theoretical modeling has suggested corrections to the

Δ
ν

 scaling relation (Stello et al. 2009; White et al. 2011; Miglio et al. 2013a), but there has been no comprehensive study to verify the corrections. In relation to

ν

max

, Houdek et al. (1999) and Chaplin et al. (2008) had suggested theoretically that

ν

max

 coincides with the plateau of the damping rate with frequency. Belkacem et al. (2011) confirmed this for the Sun using SoHO GOLF observations. Balmforth (1992) suggested that this is caused by a resonance between the thermal adjustment time of the superadiabatic boundary layer and the mode frequency, which was also confirmed by the theoretical study of Belkacem et al. (2011; see also Belkacem 2012; Belkacem et al. 2013). However, there is currently no way to accurately predict

ν

max

 from theory.


We wish to add to the work of Zhou et al. (2014) by deriving Ṁacc for LkCa15 b. To this end we use the upper limit on the flux from the Hα, Paγ and Paβ lines to estimate the accretion luminosity (Lacc) in each line. The equation Ṁacc = 1.25 (LaccR∗)/(GM∗) is used (Gullbring et al. 1998; Hartmann et al. 1998) and the results of Alcalá et al. (2014) are used to convert the luminosity of each line (Lline) to Lacc. Rpl is taken as 0.22 R⊙ and 0.34 R⊙ for masses of 6 MJup  and 15 MJup respectively. Rpl was estimated using the SETTL evolutionary models for 1 Myr (Allard et al. 2003). Our method is analogous to studies which use various accretion tracers to derive Ṁacc in low-mass stars and BDs (Alcalá et al. 2014; Whelan et al. 2014a), and therefore it is assumed here that the correlation between Lline and Ṁacc for low-mass pre-main sequence stars is applicable for planetary mass objects. Studies of Ṁacc using Lacc estimated from Lline have shown that the optimum way to estimate Ṁacc is to use several accretion tracers found in different wavelength regimes (Rigliaco et al. 2011, 2012). In this way any spread in Ṁacc due to different tracers probing different regimes of accretion or having a jet/wind component can be overcome. This is our reason for using more than one accretion tracer here. However, as many of the accretion tracers found in the spectrum of LkCa 15 show strong variability (refer to Fig. 2) we chose to limit our calculations to the lines with the least variability namely Hα, Paγ and Paβ. Here we are specifically referring to the presence of variable absorption features. For example in E1 the He I 1.083 μm line is double peaked but in E2 and E3 it is single peaked with a deep red-shifted absorption. The Hγ and Hβ lines also show red-shifted absorption in E2. Additionally, Hα is the line in which we are most likely to see a contribution from the planetary companion Close et al. (2014). It is found that for the 3σ upper limit on the flux, log (Ṁacc [ Hα ] ) = −9.0 to −9.2, log (Ṁacc [ Paγ ] ) = −9.1 to −9.3 and log (Ṁacc [ Paβ ] ) = −8.9 to −9.1. The range in Ṁacc for the individual lines comes from the estimated range in the mass of the companion. These estimates are in agreement with predictions for mass accretion rates from circumplanetary disks, which place Ṁacc for a 1−10 MJup planet in the range 10-9 to 10-8+M⊙/yr (Zhu 2015).


The equations are evolved from 1 to 550 Myr for models M1 and M2 and from 13 to 550 Myr for model M3. All the results are compared to data of the ONC (Davies et al. 2014; Cieza & Baliber 2007), Cyg OB2 (Roquette et al. 2017), Upper Sco (Rebull et al. 2018), h Per (Moraux et al. 2013), the Pleiades (Rebull et al. 2016; Lodieu et al. 2019) and M37 (Hartman et al. 2009). The selection criteria applied to the observational data are shown in Table 2. The Cyg OB2 sample only contains stars with periods longer than 2 days because they are free from contaminants (for more details, see Roquette et al. 2017). For the Pleiades, we have cross matched the samples from Lodieu et al. (2019) and Rebull et al. (2016). In this work, we adopt solar metallicity stellar evolutionary models (Baraffe et al. 1998). Most of the samples analyzed here have solar metallicity. The ONC (Padgett 1996; D’Orazi et al. 2009; Biazzo, Randich & Palla 2011), U Sco (Viana Almeida et al. 2009) and the Pleiades (Takeda, Hashimoto & Honda 2017) present solar metallicity. Although Cyg OB2 does not have determinations of abundance, Wright et al. (2010), Guarcello et al. (2013) and Roquette et al. (2017) all use solar metallicity stellar models. Berlanas et al. (2018) find no evidence of self-enrichment in Cyg OB2. There are some works showing that the metallicity of h Per is sub solar (Z  = 0.01 - Southworth, Maxted & Smalley 2004; Tamajo, Pavlovski & Southworth 2011). However, Dufton et al. (1990) and Smartt & Rolleston (1997) obtained solar abundances for the same cluster. For M37 (NGC 2099), Casamiquela et al. (2017) obtained Z  = + 0.08 while Netopil et al. (2016) obtained Z  = + 0.02. There are several uncertainties related to age determination particularly for young clusters (see, for example Soderblom et al. 2014). The ages and corresponding references adopted in this work are shown in the 2nd and 3rd columns of Table 2. For NGC 2362, Mayne & Naylor (2008) suggest an age range between 4 and 5 Myr. We choose the age of 5 Myr because this is in better agreement with our models. For Cyg OB2, Wright, Drew & Mohr-Smith (2015) observe an age spread consistent with an extended stellar formation phase of 6 Myr with a peak between 4 and 5 Myr. We assume an age of 5 Myr for the cluster, as suggested by Wright et al. (2010). Among the clusters studied in this work, the age attributed to U Sco exhibits the greatest variation, from 5 Myr (Slesnick, Hillenbrand & Carpenter 2008; Herczeg & Hillenbrand 2015) to 11 Myr (Pecaut et al. 2012). Rebull et al. (2018) adopt 8 Myr for it but an 11 Myr old rotational period distribution returns a better value in the KS tests performed in this work.

and the Pleiades
present solar metallicity.


The present HST-COS data were taken 20 days after the last XMM-Newton pointing (Kaastra et al. 2011) as the closing measurements of the campaign, which lasted in total about 100 days. Spectral coverage simultaneous to HST-COS was provided instead by both Chandra-LETGS (Ebrero et al. 2011) and Swift-XRT (Mehdipour et al. 2011). We used the average SED recorded by the XMM-Newton instruments 20–60 days before the HST-COS observation. The choice of SED is very important in the BLR modeling, as different lines respond to the continuum variations on different time scales (Korista & Goad 2000; Peterson et al. 2004). Reverberation mapping studies of Mrk 509 report that the delay of the Hβ with respect to the continuum is very long (about 80 days for Hβ, Carone et al. 1996; Peterson et al. 2004). However, higher ionization lines respond more quickly to the continuum variations. Taking as a reference the average Hβ/C iv delay ratio for NGC 5548 (Peterson et al. 2004), for which – contrary to Mrk 509 – a large set of line measurements is available, we obtain that the C iv line in Mrk 509 should respond in approximately 40 days. A similar (but shorter) time delay should apply to the Lyα line (Korista & Goad 2000). This delay falls in the time interval covered by the XMM-Newton data. Therefore, our choice of SED should be appropriate for the modeling of at least the main UV lines. Variability of the X-ray broad lines has been reported on time scales of years (Costantini et al. 2010); however, no short-term studies are available. We expect that the X-ray broad lines should respond promptly to the continuum variations, as they may be located up to three times closer to the black hole with respect to the UV lines (C07). During the XMM-Newton campaign the flux changed by 30% at most, with a minimal change in spectral shape (Sect. 3.1). The used SED should therefore represent what the BLR gas sees for the X-ray band. However, for the optical lines the used SED might be too luminous as we observed an increase in luminosity of about 30% during the XMM-Newton campaign and, as seen above, the time-delay of the optical lines may be large.


Without knowledge of nucleus shape and spin parameters (pole orientation and shape), a thermophysical model is pointless, and we instead adopted a NEATM (Near Earth Asteroid Thermal Model) model, used extensively for asteroids (Harris 1998) and TNOs (Müller et al. 2020, and references therein). NEATM is based on the asteroid standard thermal model (STM; Lebofsky et al. 1989) but accounts for phase angle effects; additionally, the temperature distribution is modified by an adjustable η−1/4 factor, which represents the combined and opposed effects of roughness (η  1) and thermal inertia (η > 1). For fixed surface (thermal inertia, roughness) and spin properties, η is also a function of the subsolar temperature, and, therefore, of the heliocentric distance (e.g., Spencer et al. 1989; Lellouch et al. 2013). Given the rh = 20 au distance of our measurements (and the expected large size of 2014 UN271), we adopted a beaming factor η = 1.175 ± 0.42, based on measurements of 85 Centaurs and TNOs (Lellouch et al. 2013, 2017). We also specified a bolometric emissivity ϵb = 0.90 ± 0.06 and a relative radio emissivity ϵr = ϵmm/ϵb = 0.70 ± 0.13, as inferred from combined Spitzer/Herschel/ALMA measurements of nine objects (Brown & Butler 2017; Lellouch et al. 2017). The lower-than-unity relative radio emissivity is interpreted as resulting from (i) the sounding of a colder dayside subsurface and (ii) the loss of outgoing thermal radiation due to volume scattering in the subsurface and/or Fresnel reflection at the surface. The few available radio observations of cometary nuclei also generally indicate radio emissivities lower than 1, for example ∼0.5 for Hale-Bopp (Fernández 2002) and  0.8 for 8P/Tuttle (Boissier et al. 2011). Comets are also found to have low thermal inertias (e.g.,  10,  30, and  45 MKS for 8P/Tuttle, 22P/Kopff, and 9P/Tempel 1, respectively; Boissier et al. 2011; Groussin et al. 2009, 2013), consistent with a beaming factor, η, of order unity. Based on NEATM analysis of a large sample of comet nuclei observed with Spitzer at rh = 3.5–6 au, Fernández et al. (2013) find a mean η of 1.03 ± 0.11. The large 29P/Schwassmann-Wachmann nucleus (D = 65 km) has η = 1.1 ± 0.2 (Schambeau et al. 2021). These numbers are fully consistent with our choice of η. Given the values of rh, η, and ϵb, NEATM calculations indicate that the object’s spectral index over 224–242 GHz is 1.93, slightly lower than the Rayleigh-Jeans limit of 2.


If we consider for the bulk density the value 4500 kg m−3, which is one of the highest measured in the asteroid population out of those asteroids with good quality of data (see Carry 2012), it will strengthen the hypothesis that Psyche could be an exposed metal core of a differentiated asteroid (Elkins-Tanton et al. 2017). According to the models of asteroid differentiation, the process that led to the formation of Psyche happened very early. Considering Psyche's current diameter, Deff = 226 km (Shepard et al. 2017), the Psyche parent body (PPB) was supposed to be ∼500 km in diameter and have suffered severe ‘hit-and-run’ impact events capable of removing all crust and mantle, exposing the core (Elkins-Tanton et al. 2016). In addition, Psyche should have ∼40 per cent macroporosity, if we assume that it is made of blocks of iron/nickel with a density around 7500 kg m−3. In that case, the core itself was possibly destroyed and re-accumulated, implying a severe collisional history. When an asteroid is disrupted catastrophically, with a remaining mass ≤50 per cent of the initial one, after a collision with another body, an asteroid family is formed. If the collision happened in the Main Belt, a family of asteroid fragments should be in the region of Psyche; however, no family related to Psyche has been found yet (Davis, Farinella & Marzari 1999). One possibility to solve this issue is that the potential Psyche asteroid family was created at an early time, e.g. within the first 500 Myr of Solar system history (Davis et al. 1999). This would allow the family fragments to be ground down by collisional evolution and be unobservable today. The same models show that, even in this case, today there should be several surviving fragments having diameters around 20 km and above the detection limit. There is a lack of primordial asteroid families in the Main Belt (Brož et al. 2013; Spoto, Milani & Knežević 2015), very likely due to the classical methods that are used to identify them. The hierarchical clustering method (HCM) is not sensitive enough to find old and dispersed families, as it searches for asteroids forming compact groups in orbital element space (semi-major axis, eccentricity and inclination). A new approach has been proposed and implemented with success (Walsh et al. 2013; Delbo’ et al. 2017), as it is able to distinguish very old families, having eccentricities and inclinations dispersed in space. Therefore the possibility of the absence of a Psyche family could be due to searching biases. However, this may be an unlikely hypothesis, because A-type asteroids that could represent mantle material (almost pure olivine) from differentiated bodies do not exist extensively in the orbital space related to Psyche, but instead are distributed randomly in the Main Belt (Davis et al. 1999; DeMeo et al. 2015). In order to study this puzzling small body further, NASA is sending a new Discovery Mission to Psyche. The main goal is to get insight into whether it is a core of a parent body and understand the procedures of differentiation, making all the above questions more valid than ever. The alternative theory is that Psyche is a planetesimal that bears primitive unmelted material (Elkins-Tanton et al. 2016).


Magnetars are possibly the most exotic objects of all the classes of neutron stars. High magnetic fields (≳1014 G) and intense X-ray/soft γ-ray emission combined with erratic spin-down behaviour makes them unique amongst the neutron star population. The soft gamma-ray repeater (SGR) J1935+2154 was discovered when the Swift-Burst Alert Telescope detected an X-ray burst on 2014 July 5 (Lien et al. 2014; Stamatikos et al. 2014). This initial burst was then followed by a number of other short bursts (Cummings 2014). Following this, the sky location of SGR J1935+2154 was quickly recognized to place it coincident with the supernova remnant (SNR) G57.2+0.8, strongly suggesting an association (Gaensler 2014). Follow-up radio observations with the Very Large Array (VLA) at 6 GHz revealed no persistent radio emission down to 41 $\mathrm{\mu Jy}$ (3σ; Fong & Berger 2014). Subsequent observations with the Chandra X-ray telescope detected X-ray pulsations with a period of 3.24 s (Israel et al. 2014). Searches with the Giant Metrewave Radio Telescope (GMRT), Ooty, and Parkes telescopes failed to detect any pulsed radio emission (Burgay et al. 2014; Surnis et al. 2014). Since the initial X-ray outburst the source has undergone further outbursts in 2015 February, 2016 May, and 2019 November. It is noteworthy that sporadic X-ray bursts are seen (Kozlova et al. 2016; Younes et al. 2017a) even between these periods of activity, making it one of the most active magnetars known (Lin et al. 2020b). As well as the single pulse and periodicity searches, searches for continuum radio emission, which might be associated with a new pulsar wind nebula activated by the bursting activity, were carried out just after the discovery of the source, with the GMRT (Surnis et al. 2016). They report 3σ upper limits of 1.2 and 4.5 mJy at frequencies of 362.5 and 610 MHz, respectively. Searches for continuum emission associated with this most recent burst have been undertaken by a wide range of telescopes and we summarize these in Table 1. In spite of deep searches, no continuum emission has been detected at the best known position of SGR J1935+2154. A detection of pulsar-wind nebula emission from the magnetar would have significant implications on the emission physics of the magnetar and its association with G57.2+0.8, although a pulsar-wind nebula has been detected around only one magnetar to date (Younes et al. 2016).


The extended star-forming region S235 is known to be a part of the giant molecular cloud G174+2.5 in the Perseus Spiral Arm (e.g., Heyer et al. 1996) and contains two known sites: the S235 complex and the S235AB region (see Figure 1 in Dewangan & Anandarao 2011 and also Figure 1 in Kirsanova et al. 2014). The present work is focused on the S235 complex and does not include the S235AB region. Different values of the distance (1.36, 1.59, 1.8, 2.1, and 2.5 kpc) to the extended star-forming region S235 have been reported in the literature (e.g., Georgelin et al. 1973; Israel & Felli 1978; Evans & Blair 1981; Brand & Blitz 1993; Burns et al. 2015; Foster & Brunt 2015). In the present work, we have chosen a distance of 1.8 kpc following Evans & Blair (1981), which is an intermediate value of the published distance range. The H ii region associated with the S235 complex is predominantly ionized by a single massive star, BD+35o1201, of O9.5V type (Georgelin et al. 1973). The S235 complex has been studied using multiple data sets spanning near-infrared (NIR) to radio wavelengths. The S235 complex is known as an active site of star formation, harboring young stellar clusters (e.g., Kirsanova et al. 2008; Camargo et al. 2011; Dewangan & Anandarao 2011; Chavarría et al. 2014) associated with known star-forming subregions, namely East 1, East 2, and the Central region (e.g., Kirsanova et al. 2008). In our previous work on the S235 complex using Spitzer-IRAC data (Dewangan & Anandarao 2011, hereafter Paper I) we detected several young stellar objects (YSOs) including a high mass protostellar object (HMPO) candidate as well as signatures of outflow activities. Using 13CO (1−0) line data, Kirsanova et al. (2008) found three molecular gas components (i.e., −18 km s−1

 km s−1 (red), −21 km s−1

 km s−1 (central), and −25 km s−1

 km s−1 (blue)) in the direction of the S235 complex. However, the complex is well traced in mainly two molecular gas components (central and blue). More recently, Kirsanova et al. (2014) derived physical parameters of dense gas (i.e., gas density and temperature) in subregions of the complex using ammonia (NH3) line observations. However, the properties of dense gas have not been explored with respect to the ionizing star location. Previous studies indicated that the S235 H ii region is interacting with its surrounding molecular cloud and the S235 complex has been cited as a possible site of triggered star formation (Kirsanova et al. 2008, 2014; Camargo et al. 2011).


In Fig. 7 we compare UGC 1378’s SFR density versus gas surface density (the Schmidt–Kennicutt relation) to data in the literature. The gas surface density corresponds to H i calculated from the 0th moment map from Mishra et al. (2017) in the same areas as SFR density. Points for the HSB and LSB discs are plotted as black and grey circles, respectively. We plot the mean SFR and H i surface density for the entire galaxy with a large open circle. The black line corresponds to the relation with an exponent of 1.4 found by Kennicutt (1998). Triangles give results for LSB galaxies published by Wyder et al. (2009), and bright and faint crosses show normal spiral galaxies from Kennicutt (1998) – total and H isurface densities. A blue line shows the best-fitting relation for the H isurface density of Bluedisk galaxies from Roychowdhury et al. (2015). We also plot the SFR in the outer regions of spiral galaxies (Bigiel et al. 2010, square symbols). In Fig. 7 the UGC 1378 measurements lie between normal spirals and LSB galaxies. The HSB disc data lie above the relation plotted for normal spirals, possibly indicating that the SFR is boosted by the bar driving gas to the star-forming rings. We cannot account for molecular gas since there are no available measurements for UGC 1378. The contribution of molecular gas would likely move the HSB disc of UGC 1378 towards the locus of normal galaxies. Because the HSB SFR of UGC 1378 is close to the predicted SFR from the Kennicutt (1998) relation obtained from H i densities (faint crosses in Fig. 7). The LSB disc of UGC 1378 lies below the correlation and accounting for molecular gas would only increase the deviation from the normal Schmidt–Kennicutt relation. Similar deviations are observed in ‘classical’ LSB galaxies, Bluedisk galaxies (Roychowdhury et al. 2015), outer parts of HSB spiral galaxies (Bigiel et al. 2010), and H idiscs in early-type galaxies (Yıldız et al. 2017). These deviations for LSB galaxies are at least partially explained by their lower gas densities leading to lower SFRs (Abramova & Zasov 2011). A recent episode of gas accretion on to the disc of UGC 1378 may also contribute to a lower SFR if the gas is not yet fully participating in the star formation. Lutz et al. (2017) studied a sample of very H i rich galaxies and proposed that very high specific angular momentum in H irich galaxies prevents the accreted gas from being transported to the mid-plane of the disc and being converted into stars. This mechanism may act to preserve giant gaseous discs.


Applied to massive stars, one can expect the presence of a tertiary companion to enrich the variety of evolutionary pathways in the inner binary by driving it to close stellar interactions (Toonen, Hamers & Portegies Zwart 2016; Toonen et al. 2020). Yet, simulating the evolution of massive stellar triples poses a difficult challenge since the stellar physics of each individual star and the gravitational three-body dynamics have to be combined in a self-consistent way. Concerning massive stars, both of these aspects are closely intertwined. For instance, kicks experienced in the supernova (SN) explosions modify and potentially disrupt the three-body configuration. Likewise, massive stars at high metallicity suffer significant mass-loss through stellar winds that loosen the inner and outer orbits (Castor, Abbott & Klein 1975; Vanbeveren 1991; Vink, de Koter & Lamers 2001; Schneider et al. 2015; Mapelli 2016). It has been shown that mass-loss in the inner binary due to winds or at compact object formation could induce or strengthen the LK effect (Shappee & Thompson 2013; Michaely & Perets 2014). In addition, massive stars attain large radii as they evolve off the main sequence and beyond, so that Roche lobe overflow and mergers are expected to occur frequently in isolated massive binaries (Bonnell & Bate 2005; Eldridge, Izzard & Tout 2008; Sana et al. 2012; Schneider, Podsiadlowski & Müller 2021). For example, more than $\sim 70\, {{\ \rm per\ cent}}$ of Galactic massive O-type stars are expected to undergo at least one mass-transfer episode with their binary companion (Sana et al. 2012). A tertiary companion could facilitate these types of close stellar interaction via the LK mechanism by driving the inner binary to smaller pericentre distances. Previous studies of stellar triples have shown that these may give rise to X-ray binaries (Naoz et al. 2016) or even trigger a stellar merger (Perets & Kratter 2012; Stegmann et al. 2022) leading to the formation of Blue stragglers (Perets & Fabrycky 2009; Naoz & Fabrycky 2014; Antonini et al. 2016) and type Ia SN (Iben & Tutukov 1999; Thompson 2011). Moreover, an expanded tertiary star could itself overflow its Roche lobe and initiate a mass transfer phase on to the inner binary (de Vries, Portegies Zwart & Figueira 2014; Portegies Zwart & Leigh 2019; Di Stefano 2020a, b; Hamers et al. 2021).


Our free chemistry retrieval suite results are further at odds with equilibrium chemistry due to the potential presence of an overabundance of H− in many retrievals across our suite. Across our free chemistry retrieval suite, the increasing abundance of H− is driven by the downturn in the final four WFC3/G141 data points, as seen, for example, in retrievals A and C in Figs 11 and 12. Here, H− acts like a uniform opacity source in the optical, which turns off at around 1.6 $\rm{\mu m}$ coinciding with these data points. Under equilibrium chemistry conditions, the abundances of H− retrieved in our suite would be possible only at temperatures ≳2500 K (Kitzmann & Heng 2018). However, the production of appreciable quantities of H− could be possible under disequilibrium processes. As described by Lewis et al. (2020), enhanced e-, H, and H2 mixing ratios (Lavvas, Koskinen & Yelle 2014) with production of H− by H2 dissociative electron attachment and destruction by atomic H collisional detachment can enable mixing ratios of H−, which are at the orders of magnitude of the retrieved abundances, even for the temperatures expected within the atmosphere of WASP-17b. The conditions required for these processes are likely for hot Jupiters orbiting F-type stars such as WASP-17, making the abundances of H− seen in our retrieval suite plausible outside of equilibrium conditions. While the downturn at 1.6 $\rm{\mu m}$, which seems to drive the inclusion of H−, could be explained by patchy clouds (e.g. Line & Parmentier 2016; MacDonald & Madhusudhan 2017), our explorations of the cloud parametrization found patchy clouds to be statistically disfavoured for the measured transmission spectrum (see Section 6.1). Additional IR observations around 1.6 $\rm{\mu m}$, which overlap with the existing G141 data, would help to corroborate the shape of the transmission spectrum in this region, shedding light as to whether H− is indeed present within the atmosphere of WASP-17b.


Theoretically, the production, propagation, and escape of LyC photons are related to the physical properties of the galaxies. Firstly, the production of LyC radiation implies the presence of young, massive stars, and therefore of on-going star formation. Because of the fast recombination timescale of the HI atoms, previous episodes of star formation have no significant impact on the production of ionizing photons eventually escaping the galaxy (e.g. Paardekooper et al. 2015). Secondly, the propagation of LyC photons within the ISM is favoured by a negligible amount of dust and low column density of HI (N(HI) ≤ 1018 cm-2) in a 10-pc scale region around the emitting star clusters. This could be the case for galaxies embedded in dark-matter halos with masses less than 108 M⊙ (Yajima et al. 2011; Wise et al. 2014; Paardekooper et al. 2015). However, even galaxies residing in more massive halos can have lines of sight favourable to the propagation and the escape of LyC photons (Gnedin et al. 2008; Roy et al. 2015). Supernova explosions could have cleared their ISM, and star-formation episodes could occur in their outskirts. In addition, “runaway” OB stars up to 1 kpc away from the initial-origin regions are proposed to significantly contribute to the amount of LyC photons finally emitted into the IGM (Conroy & Kratter 2012). Thirdly, LyC photons emitted into the IGM can affect the galaxy environment, changing the ratio of neutral vs ionized gas, eventually fuelling the ISM (e.g. Martin et al. 2012, for a study of ionized-metal outflows and inflows). Simulations at intermediate redshift have shown that the LyC escape fraction (fesc(LyC)) steeply decreases as the dark-matter halo mass (Mh) increases at 3 z 6 (e.g. Yajima et al. 2011) and that the median fesc(LyC) also changes with redshift at z = 4−6 (e.g., Cen & Kimm 2015). It is worth stressing that while some authors find that the LyC escape fraction decreases with the increase in the halo mass (see also Ferrara & Loeb 2013), other works find the opposite trend: fesc(LyC) is found to range from a few percent (e.g. Gnedin et al. 2008) up to
        20−30% (e.g. Mitra et al. 2013) or even higher (e.g. Wise & Cen 2009).


It is not clear which mechanism is operating to accelerate electrons up to relativistic energies. It could be shock acceleration, stochastic acceleration or magnetic reconnection (see Zdziarski et al. 2014, for some discussions), or shock interaction in a magnetic reconnection site (Lazarian & Vishniac 1999; de Gouveia dal Pino & Lazarian 2005). The diffusive shock acceleration involving the first-order Fermi process is often regarded as the most effective scenario in jets. However, this process requires that electrons are pre-heated up to a value comparable to the energy of thermal ions. Fortunately, a quasi-Maxwellian electron distribution with strong coupling with protons has been found in PIC simulations of collisionless relativistic (Spitkovsky 2008; Sironi & Spitkovsky 2011) and non-relativistic (Riquelme & Spitkovsky 2011) shocks. For the current study, jets are relativistic or should be at least mildly relativistic. In fact, the low-energy tail of electrons with a thermal distribution has a relatively small contribution to the SEDs. On one hand, a sharp low-energy cutoff,

, from which electrons can be energized, is assumed in Zdziarski et al. (2014) for the jets of black hole X-ray binaries in the low/hard state. On the other hand, a hard injection spectrum below

, which could approximate the Maxwellian distribution, is used to model a sample of blazars (e.g., Ghisellini & Tavecchio 2009; Zhang et al. 2012). Similarly to the latter, the relativistic electrons injected in the dissipation region are considered as
4

where

 is the break energy of relativistic electrons, and p and q are the energy spectral indices of the electrons below

 and above

, respectively. The normalization constant of the electrons,

, is determined by
5

where

 is the accretion power of the system via Roche lobe outflows of the companion star. Here,

 is the mass accretion rate. The power of relativistic electrons,

, accounts for a fraction of the jet power of

. We further consider

 to be 0.1 and

 an adjustable parameter.

 (assuming to be 1) and

 are minimum and maximum energies of the relativistic electron, respectively.


In this work, we use APOGEE calibrated atmospheric parameters and chemical abundances from the Sloan Digital Sky Survey IV (SDSS-IV; Gunn et al. 2006; Blanton et al. 2017) Data Release 14 (DR14; Abolfathi et al. 2017). The APOGEE target selection is described in Zasowski et al. (2013) and data reduction is described in Nidever et al. (2015). The atmospheric parameters and chemical abundances are determined using the APOGEE Stellar Parameters and Chemical Abundances Pipeline (ASPCAP; García Pérez et al. 2016). ASPCAP uses the code ferre (Allende Prieto et al. 2006) in combination with grids of normalized stellar synthetic spectra (see Zamora et al. 2015), as created with extensive atomic and molecular linelists (Shetrone et al. 2015), to simultaneously determine Teff, log g, [M/H], [α/M], [C/M], [N/M], and microturbulance through χ2 minimization. During this process, ASPCAP fits for the overall abundance of metals [M/H] and the relative abundance of α-elements [α/M], using O, Mg, Si, S, Ca, and Ti; the relative abundances of non-α elements (except for C and N) are set to solar ratios when inferring [M/H]. The measurements of both [M/H] and [α/M] are dominated by different elements in different temperature regimes. The abundances of the individual elements are then determined by fitting specific spectral windows containing relevant absorption lines while varying the corresponding family of elements (Holtzman et al. 2015, in preparation). The DR14 abundances have been internally calibrated to remove Teff correlations in open clusters, similar to the corrections to DR12 described in Holtzman et al. (2015); see Holtzman (in preparation) for a description of the DR14 calibrations. The APOGEE team has found that the metallicity parameter [M/H] closely correlates with the [Fe/H] measurement (Holtzman et al. 2015, in preparation). In this paper, we will assume that the ASPCAP measurements of [M/H] and [α/M] can be taken as proxies from [Fe/H] and [α/Fe], and therefore compared to literature results and theoretical models for these ratios.

Uses Background Background Background Background


In this context, MWC 758 (HD 36112) offers a unique environment to probe the existence of planetary companions and to explore the connection between disk structures and planet formation. MWC 758 is a young stellar object (3.5 ± 2 Myr, Meeus et al. 2012) at a distance of 151
$^{+9}_{-8}$

151

−9

+8

4

 pc (Gaia Collaboration 2016) close to the edge of the Taurus star forming region (stellar properties are given in Table 1). Measurements of resolved CO emission around the star determined the stellar mass to be 2.0 ± 0.2 M⊙ and the disk to have an inclination of 21° ± 2° and a position angle of the semi-major axis of 65° ± 7° (Isella et al. 2010). The mass and age estimates were based on the previously adopted hipparcos distances of 200 pc (van den Ancker et al. 1998) and 279 pc (van Leeuwen 2007). Given the revised Gaia distance, the star could be older and lighter than previously thought. In this paper, we assume a stellar mass of 1.5 ±0.2 M⊙, reflecting the scaling of the dynamical mass estimate to the new Gaia distance. Based on its SED, MWC 758 has been classified as a pre-transition disk (Grady et al. 2013). Although a cavity of 55 astronomical units (au) in radius has been inferred from dust millimeter emission (Andrews et al. 2011), infrared polarized intensity observations have found no clear evidence for a cavity in scattered light (Grady et al. 2013; Benisty et al. 2015). Using Ks-band (2.15 μm) direct imaging andH-band (1.65 μm) polarimetric imaging with the High-Contrast Instrument with Adaptive Optics (HiCIAO) at the Subaru Telescope, Grady et al. (2013) detected two spiral arms and polarized light down to 0.′′ 1 (15 au) from the star. Recent VLT Spectro-Polarimetric High-contrast Exoplanet REsearch (SPHERE) observations in the Y band (1.04 μm) have confirmed the presence of scattered light at least down to 14 au (Benisty et al. 2015). The asymmetries observed by Isella et al. (2010) in the mm-dust distribution and in CO emission suggest that the disk may be gravitationally perturbed by a low-mass companion orbiting within a radius of 23 au (assuming a distance of 151 pc). The asymmetric cm-dust distribution was shown to follow the location of the mm-dust (Marino et al. 2015a), hinting towards the hypothesis of a dust trap, which could also be created by a companion in the gap through the Rossby wave instability (e.g., Pinilla et al. 2012b). Hydrodynamical simulations of the disk indicate that the observed spirals could instead be launched by a massive planet or brown dwarf at larger separations (~ 100 au based on the revised Gaia distance, Dong et al. 2015b). The presence of stellar companions down to a mass limit of 12 MJup at 0.′′ 25 and of planets outside 0.′′5 (5 MJup at 0.′′ 5, and 3 MJup at 1′′ , according to the BT-SETTL models; Allard et al. 2012) has been ruled out based on a combination of sparse aperture masking observations at L′ band and angular differential imaging at K′ and Ks bands (Grady et al. 2013).


The core/cusp problem is a clear example of this controversy: on the one hand, cosmological dark matter only N-body simulations predict cuspy dark halo density profiles; on the other hand, the rotation curves of low surface brightness disc and gas-rich dwarf galaxies favour shallower or cored dark matter density distributions (de Blok 2010 and references therein). Also for dSphs, for which the determination of the dark matter density distribution is more difficult, there are indications that cored dark matter density profiles may be favoured with respect to cuspy profiles (Kleyna et al. 2003; Goerdt et al. 2006, Battaglia et al. 2008; Walker & Peñarrubia 2011; Salucci et al. 2012; Amorisco, Agnello & Evans 2013; Zhu et al. 2016), though this finding is still debated (Richardson & Fairbairn 2014; Strigari, Frenk & White 2017). It must be stressed, however, that cored dark haloes in dSphs do not necessarily imply a failure of ΛCDM: dark matter only cosmological simulations may not reliably predict the present-day dark matter distribution in dSphs because, by definition, they neglect the effects of baryons on the dark haloes. Even in a galaxy that is everywhere dark matter dominated today, baryons must have been locally dominant in the past to permit star formation. Therefore, the effect of baryon physics on the dark halo is expected to be important also in dSphs. For instance, Nipoti & Binney (2015) showed how, due to the fragmentation of a disc in cuspy dark halo, dynamical friction may cause the halo to flatten the original cusp into a core even before the formation of the first stars (see also El-Zant, Shlosman & Hoffman 2001; Mo & Mao 2004; Goerdt et al. 2010; Cole, Dehnen & Wilkinson 2011; Arca-Sedda & Capuzzo-Dolcetta 2017). Moreover, the results of hydrodynamical simulations suggest that, following star formation, supernova feedback can also help to flatten the central dark matter distribution, by expelling the gas (Navarro, Eke & Frenk 1996a; Read & Gilmore 2005) and thus inducing rapid fluctuations in the gravitational potential (Mashchenko, Couchman & Wadsley 2006, Pontzen & Governato 2012, Tollet et al. 2016).


Massive stars are believed to exist in the accretion disks of active galactic nuclei (AGNs). Such AGN stars and compact objects can be either the result of in situ formation inside the accretion disk or be captured from the nuclear star clusters around the AGNs (e.g., Artymowicz et al. 1993; Collin & Zahn 1999; Goodman 2003; Goodman & Tan 2004; Wang et al. 2011, 2012; Fabj et al. 2020; Cantiello et al. 2021). These AGN stars will end up with supernovae (SNe), which can eject heavy elements into the disk; this offers a possible explanation for the observational features of high-metallicity environments in AGN disks (e.g., Artymowicz et al. 1993; Hamann & Ferland 1999; Warner et al. 2003). Some compact objects, including white dwarfs (WDs), neutron stars (NSs), and black holes (BHs), can be thus formed within AGN disks. These compact objects can also be captured from the surrounding nuclear star clusters. The disk of an AGN provides a natural environment for stars and compact objects to accrete materials and to migrate within it (e.g., McKernan et al. 2012; Yang et al. 2020; Dittmann et al. 2021; Jermyn et al. 2021; Wang et al. 2021; Tagawa et al. 2021; Kimura et al. 2021). Some of these stars can be very massive and have high spin caused by accretion (Dittmann et al. 2021; Jermyn et al. 2021), so that they can easily produce high-spin stellar remnants. Abundant compact objects, especially with the presence of the massive BHs (M > 10M⊙), would likely accrete, collide, and merge within the trapping orbits, and hence would grow into ∼100 M⊙ intermediate-mass BHs (McKernan et al. 2012; Secunda et al. 2019; Yang et al. 2019b). Some AGN stars can be tidally disrupted by these BHs that can power micro-tidal disruption events (Yang et al. 2021). The death of high-spin stars and neutron star mergers are expected to power gamma-ray burst (GRB) jets, which would be always choked by the dense atmosphere of the disks (Zhu et al. 2021a, 2021b; Perna et al. 2021a). Zhu et al. (2021a) suggested that these choked jets can produce high-energy neutrinos that may contribute a substantial fraction of the diffuse neutrino background. A candidate electromagnetic (EM) counterpart that emerged from an AGN, explained as ram pressure stripping of gas within the kicked BH hill sphere colliding with the AGN disk gas (McKernan et al. 2019), was reported by the Zwicky Transient Facility (Graham et al. 2020). This was thought to be associated with a (85 + 66)M⊙ binary BH merger (GW190521) detected by the LIGO/Virgo collaboration (Abbott et al. 2020). This connection provided plausible evidence of a potentially important AGN channel for compact star mergers.


Many near-equal mass MBH mergers in the LISA band may occur in gaseous environments, given that the galactic mergers that lead to the eventual formation of an MBH binary often carry a fresh supply of gas into the post-merger galactic nucleus (see Mayer 2013 for a review). Likewise, ‘gas-embedded’ E/IMRIs may frequently occur in the accretion discs expected in active galactic nuclei (AGNs) in which an MBH is surrounded by a thin, dense accretion disc. Compact objects in the nucleus can eventually align their orbits with the disc, provided a sufficient number of disc-crossing intersections (e.g. Syer, Clarke & Rees 1991; Artymowicz et al. 1993; Artymowicz, Lin & Wampler 1993; Rauch 1995; Just et al. 2012; McKernan et al. 2012; Kennedy et al. 2016; Panamarev et al. 2018; Fabj et al. 2020; MacLeod & Lin 2020), or such events may arise from in-situ star formation in the disc that leaves compact remnants (Goodman & Tan 2004; Levin 2007). Embedded stars and BHs can subsequently accrete, migrate, and merge with each other (Bellovary et al. 2016; Secunda et al. 2019, 2020; Tagawa, Haiman & Kocsis 2020a), before eventually merging with the central MBH. While the event rate for E/IMRIs has previously been estimated in dry nuclei (e.g. Barausse, Cardoso & Pani 2015), the rate may be considerably higher when including formation pathways in accretion discs. The recent discovery of stellar-mass BH mergers by the ground based interferometer LIGO has stimulated work on such mergers that may be occurring in AGN discs, showing that they might contribute to LIGO events (McKernan et al. 2014; Bartos et al. 2017; Stone, Metzger & Haiman 2017; McKernan et al. 2018; Gröbner et al. 2020). Subsequent work has suggested that some of the LIGO events, based on their high chirp masses, may indeed have formed via this channel – large masses are expected both because of the preferential capture of heavier BHs by the disc (Yang et al. 2019b) and because repeated mergers are common and lead to hierarchical build-up (Yang et al. 2019a). The high effective spin provides additional support for this channel (Gayathri et al. 2020) as well as events with more unequal mass ratios (e.g. GW190412; see Tagawa et al. 2020b) which have been predicted to occur naturally via dynamical interactions in a dense, gaseous environment (McKernan et al. 2020; Secunda et al. 2020; Tagawa et al. 2020a). These results suggest that BH mergers indeed occur in gas discs, and that they could constitute the building blocks of IMBHs (McKernan et al. 2012; Tagawa et al. 2020a). Recent semi-analytical estimates of in-situ star formation suggest that the accretion of embedded compact objects may also contribute substantially to the growth of MBHs (Dittmann & Miller 2020).


The evolution of our Universe from the Cosmic Dawn (CD) and Epoch of Reionization (EoR) is not very well understood. The H i 21-cm line promises to be an excellent probe into these epochs (Furlanetto, Oh & Pierpaoli 2006a; Morales & Wyithe 2010; Pritchard & Loeb 2012). The global 21-cm experiments aim to measure the sky-averaged signature of this redshifted line, by using ground-based radio telescopes. Examples of such experiments are the Shaped Antenna measurement of the background RAdio Spectrum (SARAS; Patra et al. 2013; Singh et al. 2017), the Large-Aperture Experiment to Detect the Dark Ages (LEDA; Greenhill & Bernardi 2012), SCI-HI (Voytek et al. 2014), the Broadband Instrument for Global HydrOgen ReioNisation Signal (BIGHORNS; Sokolowski et al. 2015), and the Cosmic Twilight Polarimeter (CTP; Nhan et al. 2019). The Experiment to Detect the Global EoR Signature (EDGES; Bowman et al. 2018) has reported a possible detection of the sky-averaged H i 21-cm global signal from the CD. However, this signal has an absorption trough of about 0.5 K, which is twice the amplitude predicted by the standard model of cosmology. If confirmed, this measured signal would give us a completely new insight into the physics of the evolution of the Universe. Following this detection, several models explaining this exceedingly deep absorption trough has been explored. Barkana (2018), Fraser et al. (2018), Pospelov et al. (2018), and Slatyer & Wu (2018) had explained this with models with excess cooling from non-standard physics, including dark matter particles scattering off baryons. Fialkov, Barkana & Cohen (2018), Fraser et al. (2018), Pospelov et al. (2018), Ewall-Wice et al. (2018), and Feng & Holder (2018) have explored various possible 21-cm signals, varying the properties of the dark matter particles, in addition to varying the astrophysical parameters. Ewall-Wice et al. (2018), Feng & Holder (2018), and Fialkov & Barkana (2019) have explored models that produce an excess radio background, in addition to the cosmic radio background to explain the large amplitude of the absorption feature in the EDGES detection. This radio excess could be, for example, due to supernovae (Jana, Nath & Biermann 2019; Mirocha & Furlanetto 2019) or primordial black holes (Ewall-Wice et al. 2018).


Calculating the magnetic helicity in the corona by finite volume methods is more complicated than estimating the magnetic helicity flux through the photosphere by optical flow methods, and the significant point of the finite volume methods is how to obtain coronal magnetic fields. Cargill (2009) pointed out the difficulties in the traditional approach of using the Zeeman effect to measure coronal magnetic fields. Some researchers have attempted to explain the observations of coronal oscillations by using magnetohydrodynamic (MHD) wave models, and the magnetic field strength of coronal magnetic fields can be inferred in this process (Nakariakov et al. 1999; Tomczyk et al. 2007). Another approach involves using sophisticated numerical computations to reconstruct realistic 3D nonlinear force-free coronal magnetic field models, which need observed photospheric vector magnetograms as boundary conditions (Wiegelmann & Sakurai 2012, 2021). These coronal models include the MHD models, the magnetohydrostatics (MHS) models, the nonlinear force-free field (NLFFF) models, and the potential-field source-surface models. The force-free approach is a static model that neglects time-dependent phenomena and plasma flows, and the gradient of the plasma pressure and the gravity force in the MHS equation are also neglected as these terms are at least four orders of magnitude smaller than the magnetic pressure in the corona, so that the Lorentz force is vanishing and the electric currents are parallel/antiparallel to the magnetic field lines (Wiegelmann et al. 2017). However, whichever numerical computation method is chosen to approximate the 3D coronal magnetic field, they all have limitations. DeRosa et al. (2015) compared the influence of spatial resolution on the NLFFF model, and they found that the output of the NLFFF model depends on the spatial resolution of the input photospheric magnetograms (bottom boundary), with the values of free energy generally tending to be higher with increasing resolution, while the values of the relative magnetic helicity vary significantly with different resolutions. They also found that the results from the more highly resolved data were more self-consistent.


The exciting star of the H ii region has not been clearly identified so far. According to Ortiz et al. (2007), Obj1a (B0 v) and Obj2 (O9 v) are the best candidates for ionization sources of the RCW 41 region. At 5.8 μm, the region shows a cavity at its center, surrounded by PAH emission in the PhotoDissociation Region (PDR). The Hα emission is strongest in the center of the nebula (see Fig. 1), implying that the ionizing source might be embedded within the nebula. This phenomenon has been observed in many bubbles associated with H ii regions (e.g., Deharveng et al. 2010). Thus, we believe that the exciting star must be inside the 5.8 μm cavity that surrounds the Hα emission, which excludes the Obj1a source as a potential candidate. Also Obj1a is at the extreme edge of the Hα emission, which makes it unlikely to be the ionizing candidate. To identify the probable ionizing candidates of the individual H ii regions, we then used a JHKs catalog of the region inside the cavity and searched for ionizing sources in a circular area of radius ~1.15 pc (i.e., the radius of the 5.8 μm cavity) from the center of the bubble. Using the extinction laws of Rieke & Lebofsky (1985), the observed (J − H) color and MJ-spectral type calibration table of Bessel & Brett (1988), and a distance of 1.3 kpc, we selected luminous sources that have spectral types earlier than B3 MS star. We followed the same prescription as described in Samal et al. (2010) of rejecting the most likely giants and foreground sources based on (J × [J − H]) and ([J − H] × [H − Ks]) diagrams. After these eliminations, we are left with only one massive O-type star located close to the northwestern border of 5.8 μm cavity. This source is associated with a group of stars in its close vicinity, possibly part of an exciting cluster. The source corresponds to the “Obj2” identified by Santos et al. (2012), whose spectroscopic spectral type agrees with the photometric spectral derived form our observations. From the above discussion, we conclude that the Obj2 source is the most likely ionizing star of the RCW 41 H ii region.


The field of extrasolar planetary transits is one of the most productive and innovative subject in astrophysics in the last decade. Transit observations can be used to measure the size of planets, their orbital parameters (Seager and Mallén-Ornelas 2003), and stellar properties (Mandel & Agol 2002; Howarth 2011), to study the atmospheres of planets (Brown 2001; Charbonneau et al. 2002; Tinetti et al. 2007), and to detect small planets (Miralda-Escudé 2002; Agol et al. 2005) and exomoons (Kipping 2009a, 2009b). In particular, the study of planetary atmospheres requires a high level of photometric precision, i.e., one part in ∼104 in stellar flux (Brown 2001), which is comparable to the effects of current instrumental systematics and stellar activity (Berta et al. 2011; Ballerini et al. 2012), hence the necessity of testable methods for data detrending. In some cases, different assumptions, e.g., using different instrumental information or functional forms to describe them, leed to controversial results even from the same data sets; examples in the literature are Tinetti et al. (2007), Ehrenreich et al. (2007), Beaulieu et al. (2008) and Désert et al. (2009, 2011) for the hot-Jupiter HD 189733b, and Stevenson et al. (2010), Beaulieu et al. (2011) and Knutson et al. (2011, 2014) for the warm-Neptune GJ436b. Some of these controversies are based on Spitzer/IRAC data sets at 3.6 and 4.5 μm. The main systematic effect for these two channels is an almost regular undulation with period ∼3000 s, so called pixel-phase effect, as it is correlated with the relative position of the source centroid with respect to a pixel center (Fazio et al. 2004; Morales-Caldéron et al. 2006). Conventional parametric techniques correct for this effect by dividing the measured flux by a polynomial function of the coordinates of the photometric centroid; some variants may include time-dependence (e.g., Stevenson et al. 2010; Beaulieu et al. 2011). Newer techniques attempt to map the intra-pixel variability at a fine-scale level, e.g., adopting spatial weighting functions (Ballard et al. 2010; Cowan et al. 2012; Lewis et al. 2013) or interpolating grids (Stevenson et al. 2012a, 2012b). The results obtained with these methods appear to be strongly dependent on a few assumptions, e.g., the degree of the polynomial adopted, the photometric technique, the centroid determination, calibrating instrument systematics over the out-of-transit only or the whole observation (e.g., Beaulieu et al. 2011; Diamond-Lowe et al. 2014; Zellem et al. 2014). Also, the very same method, applied to different observations of the same system, often leads to significantly different results. Non-parametric methods have been proposed to guarantee a higher degree of objectivity (Carter & Winn 2009; Thatte et al. 2010; Gibson et al. 2012; Waldmann 2012, 2014; Waldmann et al. 2013). Morello et al. (2014, 2015) reanalyzed the 3.6 and 4.5 μm Spitzer/IRAC primary transits of HD 189733b and GJ436b obtained during the cryogenic regime, so called “cold Spitzer” era, adopting a blind source separation technique, based on an Independent Component Analysis (ICA) of individual pixel timeseries, in this paper called “pixel-ICA”. The results obtained with this method are repeatable over different epochs, and a photometric precision of one part in ∼104 in stellar flux is achieved, with no signs of significant stellar variability as suggested in the previous literature (Désert et al. 2011; Knutson et al. 2011). The use of ICA to decorrelate the transit signals from astrophysical and instrumental noise, in spectrophotometric observations, has been proposed by Waldmann (2012, 2014) and Waldmann et al. (2013). The reason to prefer such blind detrending methods is twofold: they require very little, if any, prior knowledge of the instrument systematics and astrophysical signals, therefore they also ensure a higher degree of objectivity compared to methods based on approximate instrument systematics models. As an added value, they give stable results over several data sets, also in those cases where more conventional methods have been unsuccessful. Recently, Deming et al. (2015) proposed a different pixel-level decorrelation method (PLD) that uses pixel timeseries to correct for the pixel-phase effect, while simultaneously modeling the astrophysical signals and possible detector sensitivity variability in a parametric way. PLD has been applied to some Spitzer/IRAC eclipses and synthetic Spitzer data, showing better performances compared to previously published detrending methods.


Complex organic molecules (or COMs) are the building blocks of life. COMs are believed to first form on the icy mantle of dust grains (e.g., Garrod et al. 2008; Jiménez-Serra et al. 2016). Subsequently, COMs are released to the gas phase during the warm and hot phase, where icy grain mantles can be heated to high temperatures

T

d

∼
100
–
300

K

 (e.g., Blake et al. 1987; Brown et al. 1988; Bisschop et al. 2007). COMs are increasingly observed in the environs of young stellar objects, including hot cores/corinos around high-mass/low-mass protostars and protoplanetary disks (see Herbst & van Dishoeck 2009 and van Dishoeck 2014 for recent reviews). In particular, many surveys that search for COMs toward the nearest massive star-forming regions, the Orion Becklin–Neugebauer/Kleinmann–Low object (BN/KL), have been conducted with single-dish telescopes from the ground, e.g., IRAM-30 m (Tercero et al. 2010, 2011; Cernicharo et al. 2016), in space, e.g., Herschel (Bergin et al. 2010; Crockett et al. 2014), and with interferometers, e.g., IRAM Plateau de Bure (Favre et al. 2011; Peng et al. 2012; Brouillet et al. 2013), and ALMA (Tercero et al. 2015, 2018; Favre et al. 2017; Pagani et al. 2017, 2019; Peng et al. 2017, 2019). The single-dish telescopes are unable to spatially/spectrally separate the contribution of the different sources in Orion BN/KL because of their low resolution (i.e., lines are overlapped). All constraints from those data, therefore, are manifested as uncertainties. Conversely, the extremely high spatial resolution of interferometers naturally can separate the components, which reveals the complexity of the chemical and physical structure in Orion BN/KL. Observations show the existence of large COMs with very strong binding energies, such as acetic acid (CH3COOH), ethyl formate (C2H5OCHO), propyl cyanide (C3H7CN), methyl acetate (CH3COOCH3), methoxymethanol (CH3OCH2OH), ethylene glycol (OHCH2CH2OH), etc. The sublimation temperature of these large COMs is higher than that of water, i.e.,

T

sub

≳
152

 K (see Section 2.1). However, the dust temperature estimated in Orion BN/KL is far from Tsub. This casts doubt on the popular sublimation mechanism and suggests nonthermal mechanisms that can desorb COMs within these environments.


In spite of the above considerations, we can appreciate a statistical trend of increasing spectral index (i.e. softer average spectra) while moving through the HSP, ISP, and LSP classes. This result, summarized in Table 1, is consistent with our natural expectations and it supports the reliability of spectral decomposition techniques to extract and analyse the non-thermal emission of these objects. As a consequence, we can investigate the relation existing between the non-thermal component of the optical spectra and the corresponding γ-ray spectra. It is well known that the γ-ray photon index correlates with the position of the synchrotron peak in frequency (e.g. Ajello et al. 2020). So far, however, the presence of thermal contributions in the optical domain has made it very difficult to perform direct comparisons of spectral indices between the optical and the γ-ray energy domains. From our sample, instead, we can infer a substantial degree of linear correlation between the optical spectral index αopt and its γ-ray counterpart αγ. The situation, summarized in Fig. 4, is well represented by a linear relation described by
(2)$$\begin{eqnarray}
\alpha _{\rm opt} = (0.862 \pm 0.110) \cdot \alpha _{\rm \gamma} - (0.818 \pm 0.445),
\end{eqnarray}$$with weighted correlation coefficient R = 0.743 and null-hypothesis probability p0 = 2.71 × 10−10 (i.e. statistical significance at $6.3\, \sigma$ level), for the whole sample, and by
(3)$$\begin{eqnarray}
\alpha _{\rm opt} = (1.469 \pm 0.224) \cdot \alpha _{\rm \gamma} -(1.931 \pm 0.919),
\end{eqnarray}$$with weighted correlation coefficient R = 0.751 and null-hypothesis probability p0 = 1.54 × 10−8 (i.e. $5.7\, \sigma$), for the subset of 98 objects that were fitted with Δαopt ≤ 0.6 (corresponding to 3 times the systematic uncertainty estimated for the method). The observed correlations are particularly suggestive if compared to the situation that is obtained by simply fitting a power-law model to the optical data without accounting for the host component (more details in Appendix C). Another interesting result, also presented in Fig. 4, is that the above correlation results in a situation where the power-law fits of the γ-ray spectra appear to be softer than the associated optical non-thermal emission by a value that lies mostly close to 1.0. This circumstance points towards a tight relationship between the population of particles that explain the non-thermal component of the optical spectra and the ones that are responsible for the γ-ray emission. The existence of a similar relationship between the observed spectral indices is a characteristic prediction of SSC-based models. However, the systematic difference between the optical and γ-ray energy regions requires further investigation to be properly interpreted.


Figure 1 shows that in the regions where activity was detected visually, i.e., Hapi, Seth, and Ma’at pits have lower (8–13%/100 nm) spectral slopes than the rest of the comet surface (13–22%/100 nm). In addition to those places, Seth alcoves, the wall of the large Anuket alcove, around the circular features, both clustered and isolated bright features (see Thomas et al. 2015b; Auger et al. 2015; Pommerol et al. 2015b, for definitions) show similar lower spectral slopes than the rest of the surface, even though there was no visual detection of activity features rising from them at the time of the observations used in this study4. This may be because the observing geometry was not suited for their detections during the observations. In the regions we investigated, the Hapi region displays the lowest spectral slopes 8–11%/100 nm (see also Fornasier et al. 2015) together with the isolated bright features (IBFs) and the clustered bright features in the Imhotep region. The locations of the bright features on the Imhotep image (image #4) are shown in Fig. B.4. According to the spectral slope values, the IBFs of Imhotep seem to be more similar to the Hapi region than the active pits of Seth and Ma’at regions. Active pits, alcoves, and the large alcove of Anuket have slope values of typically 10–13%/100 nm. The Ma’at region, which is located on the smaller lobe (head) of the comet, displays higher spectral slope values than the Seth region, which is located on the larger (body) lobe of the comet. In the investigated regions, the highest slope values are detected in the Imhotep region (see Fig. 1d). Here it should be mentioned that the comparison of spectral slopes is performed under the assumption of no spectral reddening between the phase angles of the images we investigated, although the spectral slopes show reddening by phase as presented in Fornasier et al. (2015). Unfortunately, the previous work does not cover all the phase angles of the images we investigated, but the spectral slope variation between 35–54° (Fig. 3 of  Fornasier et al. 2015) is small so that we can make this comparison. However, if we follow the linear trend of the phase reddening, for the image taken in 70.45° phase angle (image #4), the spectral slopes would vary from 15%/100 nm to 18%/100 nm in the observations we used.


In past decades, single-dish submillimeter surveys have identified populations of massive, dusty star-forming galaxies at z > 1 (e.g., Casey et al. 2014). While these galaxies are rare even at Cosmic Noon (1  z  3) when the star formation activity in the universe peaks, their contribution to the cosmic star formation rate density (CSFRD) equals that of all optical and near-infrared selected galaxies combined (Madau & Dickinson 2014). However, at z > 3 the situation is much less certain. A tail of submillimeter-selected galaxies have been confirmed beyond z > 4, but they trace only the very tip of the star formation rate (SFR) distribution at early times (e.g., Cooray et al. 2014; Strandet et al. 2017; Marrone et al. 2018). The total contribution of dust-obscured star formation, and therefore the census of star formation in the early universe, is unknown. Despite the strongly negative k-correction allowing sources to be found to z = 10, the overwhelming majority of (sub)millimeter-selected galaxies continue to be confirmed at z  3 with Atacama Large Millimeter/submillimeter Array (ALMA) spectroscopy (Brisbin et al. 2017; Danielson et al. 2017). While some dusty galaxies have been discovered beyond z > 5 through gravitational lensing (Spilker et al. 2016; Zavala et al. 2018b), the lensing correction and selection effects make it challenging to establish their contribution to the CSFRD. Progress is hampered by the limited sensitivity and low spatial resolution of single-dish submillimeter observations and the difficulty of associating detections with counterparts in the optical–near-infrared (NIR). Ultradeep SCUBA surveys over moderate ∼100 arcmin2 are now pushing into the range of “normal” SFRs (several 100 M⊙ yr−1, main-sequence galaxies; e.g., Koprowski et al. 2016; Cowie et al. 2017, 2018) and extending to z > 4, but the analysis is often limited by the ability to identify counterparts at other wavelengths and derive accurate redshifts.


As a class, the fastest stars in our Galaxy are expected to be hypervelocity stars (HVSs). These were first theoretically predicted by Hills (1988) as the result of a three-body interaction between a binary star and the massive black hole in the Galactic Centre (GC), Sagittarius A*. Following this close encounter, a star can be ejected with a velocity ∼1000 km s−1, sufficiently high to escape from the gravitational field of the MW (Kenyon et al. 2008; Brown 2015). The first HVS candidate was discovered by Brown et al. (2005); a B-type star with a velocity more than twice the Galactic escape speed at its position. Currently about ∼20 unbound HVSs with velocities ∼300–700 km s−1 have been discovered by targeting young stars in the outer halo of the MW (Brown, Geller & Kenyon 2014). In addition, tens of mostly bound candidates have been found at smaller distances but uncertainties prevent the precise identification of the GC as their ejection location (e.g. Hawkins et al. 2015; Vickers, Smith & Grebel 2015; Zhang, Smith & Carlin 2016; Marchetti et al. 2017; Ziegerer et al. 2017). HVSs are predicted to be ejected from the GC with an uncertain rate around 10−4 yr−1 (Yu & Tremaine 2003; Zhang, Lu & Yu 2013), two orders of magnitude larger than the rate of ejection of RSs with comparable velocities from the stellar disc (Brown 2015). Because of their extremely high velocities, HVS trajectories span a large range of distances, from the GC to the outer halo. Thus, HVSs have been proposed as tools to study the matter distribution in our Galaxy (e.g. Gnedin et al. 2005; Sesana, Haardt & Madau 2007; Kenyon et al. 2014; Fragione & Loeb 2017; Rossi et al. 2017; Contigiani, Rossi & Marchetti 2018) and the GC environment (e.g. Zhang et al. 2013; Madigan et al. 2014), but a larger and less observationally biased sample is needed in order to break degeneracies between the GC binary content and the Galactic potential parameters (Rossi et al. 2017). Using the fact that their angular momentum should be very close to zero, HVSs have also been proposed as tools to constrain the solar position and velocity (Hattori, Valluri & Castro 2018a). Other possible alternative mechanisms leading to the acceleration of HVSs are the encounter between a single star and a massive black hole binary in the GC (e.g. Yu & Tremaine 2003; Sesana, Haardt & Madau 2006, 2008), the interaction between a globular cluster with a single or a binary massive black hole in the GC (Capuzzo-Dolcetta & Fragione 2015; Fragione & Capuzzo-Dolcetta 2016), and the tidal interaction of a dwarf galaxy near the centre of the Galaxy (Abadi et al. 2009). Another possible ejection origin for HVSs and high-velocity stars in our Galaxy is the Large Magellanic Cloud (LMC; Boubert & Evans 2016; Boubert et al. 2017; Erkal et al. 2018), orbiting the MW with a velocity ∼380 km s−1 (van der Marel & Kallivayalil 2014).


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.


Consequently, the neutral gas measured in situ in the coma of comet 67P by the ROSINA experiment (and also MIRO, VIRITS, and Alice) on board Rosetta likely originated several tens of meters beneath the primordial surface of the comet. ROSINA observations provided evidence that this comet is formed from pristine material that has not been significantly altered after its formation in the first Myr of the solar nebula stage. The high abundance of super-volatiles like CO and CO2 (Le Roy et al. 2015), the detection of argon (Balsiger et al. 2015), of molecular nitrogen (Rubin et al. 2015), of molecular oxygen (Bieler et al. 2015), of a high D/H in HDO/H2O and D2O/HDO and HDS/H2S (Altwegg et al. 2015, 2017), and of hydrogen halides (De Keyser et al. 2017; Dhooghe et al. 2017), coupled with the low density, high porosity, and homogeneity of the nucleus (Pätzold et al. 2016) and the absence of signatures of aqueous alteration (see Capaccioni et al. 2015; Davidsson et al. 2016; Quirico et al. 2016; Bardyn et al. 2017) all indicate that comet 67P formed at low temperature and did not experience any substantial global-scale heating after its formation. This suggests that 67P is representative of the solar nebula material from which the solar system had formed. This has strong implications not only for how the measurements made in cometary environments can be used to constrain the protosolar environment but also for the contribution of comets to Earth’s composition. For instance, the measurement of the D/H isotopic ratio in 67P (Altwegg et al. 2015) suggests that comets cannot be considered as the main source of water on Earth. The discovery of significant amounts of O2 in comets (Bieler et al. 2015) was not predicted by astrochemical models and challenges our understanding of the chemistry of molecular clouds and of the protosolar nebula. However, the Jupiter-family comets (JFCs; which include 67P) are a diverse groups. Indeed, even if Giotto measurements indicate that comet 1P/Halley contains similar amounts of O2 (Rubin et al. 2015), different D/H ratios (lower than observed for 67P and compatible with the D/H ratio in the Earth’s oceans) have been measured for other JFC comets like Hartley 2 (Balsiger et al. 2015) and 46P/Wirtanen (Lis et al. 2019). The causes for this diversity may be already present at the formation of these comets or may result from a different evolution after their formation.


The main challenge in detecting the cosmological H i signal, common to all of these experiments, is the strong contamination of systematic effects (ionospheric distortion, telescope response, calibration, etc.) and bright foregrounds (Galactic and extragalactic) (Datta, Bhatnagar & Carilli 2009). Foreground sources include diffuse Galactic synchrotron emission (DGSE) from our Galaxy (Shaver et al. 1999), free–free emission from Galactic and extragalactic sources (Cooray & Furlanetto 2004), faint radio-loud quasars (Di Matteo et al. 2002), synchrotron emission from low-redshift Galaxy clusters (Di Matteo, Ciardi & Miniati 2004), extragalactic point sources, etc. Typically, foregrounds are four to five orders of magnitude stronger than the redshifted H i signal (Zaldarriaga, Furlanetto & Hernquist 2004; Bharadwaj & Ali 2005; Jelić et al. 2008; Bernardi et al. 2009; Jelić et al. 2010; Zaroubi et al. 2012; Chapman et al. 2015). There are several different ways to deal with foregrounds, but all the methods rely on the fact that foreground sources have a smooth spectral shape. However, the redshifted H i 21 cm signal has spectral structure (Pritchard & Loeb 2012). In fact, this difference in spectral properties between the strong foreground and faint 21 cm signal can be used favourably for the detection of the cosmological signal (Datta, Bowman & Carilli 2010). Hence, accurate knowledge of the spectral ‘smoothness’ of the foreground becomes critical. Our current study makes an attempt to constrain the spectral behaviour of the foregrounds near the redshifted 21 cm signal frequencies. The three main techniques proposed to overcome foreground contamination are foreground avoidance, foreground removal and foreground suppression. Instead of an isotropic 1D power spectrum, P(k), of H i brightness temperature fluctuation, a cylindrical (2D) power spectrum, P(k⊥, k∥) is a useful diagnostic in terms of foreground avoidance. Spectral smoothness of foregrounds confines the majority of foreground power to low k∥ modes, resulting in ‘foreground wedge’. In the foreground avoidance technique, the EoR signal is searched for outside this wedge, in the so-called ‘EoR window’ (Datta et al. 2010; Parsons et al. 2012; Vedantham, Udaya Shankar & Subrahmanyan 2012; Pober et al. 2013a; Thyagarajan et al. 2013; Dillon et al. 2015). However, errors in calibration of chromatic instruments and insufficient knowledge of the wedge boundary can leak foreground power into the wedge and consequently detection of the 21 cm signal becomes challenging even inside the EoR window. Foregrounds can be modelled very precisely and subtracted from the data set. Also, without any modelling a component analysis method can be used to mitigate foregrounds (for details see Chapman et al. 2012, 2013). The foregrounds can be suppressed by weighting foreground-dominated modes appropriately (Liu & Tegmark 2011).