The origin and evolution of cosmic magnetism are at present poorly understood. Answering the many open questions surrounding the physics of astrophysical magnetic fields is a difficult task since magnetic fields can be significantly affected by structure and galaxy formation and evolutionary processes. Their strength can be amplified, for example, in galaxy clusters through mergers and in galaxies through large-scale dynamos, invoking differential rotation and turbulence. Insights into the origin and properties of magnetic fields in the Universe could be provided by probing them on even larger scales. Along filaments and voids of the cosmic web, turbulent intracluster gas motions have not yet enhanced the magnetic field; its strength thus still depends on the seed field intensity, in contrast to galaxy clusters, where it probably mostly reflects the present level of turbulence (see, e.g., Donnert et al. 2009; Xu et al. 2010, 2011). Intervening magnetoionic media cause a difference in the phase velocity between the left-handed and right-handed circular polarization components of the linearly polarized synchrotron radiation emitted by a background radio source (e.g., Carilli & Taylor 2002; Govoni & Feretti 2004). This effect translates into a rotation of the intrinsic polarization angle, ψ0, (1)\begin{equation} \psi(\lambda^2)=\psi_0+\phi\lambda^2. \end{equation}ψ(λ2)=ψ0+φλ2.Following Burn (1966), the observed polarization angle, ψ, depends on the observation wavelength, λ, through the Faraday depth, φ, (2)\begin{equation} \phi=a_0\int_0^{z_{\rm s}}B_l(z)~n_{\rm e}(z)~\frac{\mathrm{d}l}{\mathrm{d}z}~\mathrm{d}z, \label{definition} \end{equation}φ=a0∫0zsBl(z)ne(z)dldzdz,where a0 depends only on fundamental constants, ne is the electron density, Bl is the component of the magnetic field along the line of sight, and zs is the redshift of the source. When the rotation is completely due to a foreground screen, the Faraday depth has the same value as the rotation measure (RM), defined by (3)\begin{equation} {\rm RM}\equiv\frac{\partial \psi}{\partial \lambda^2}\cdot \end{equation}RM≡∂ψ∂λ2·The Faraday depth is assumed to be positive when the line-of-sight average component of the magnetic field points toward the observer, otherwise it is negative for a field with an average component pointing away from the observer. The amount of Faraday depth measured by radio observations along a given line of sight is the sum of the contributions from the Milky Way, the emitting radio source, and any other source and large-scale structure in between hosting a magnetized plasma. The investigation of these contributions and of their possible dependence on redshift is essential to discriminate among the different scenarios of magnetic field formation and evolution and, therefore, crucial for the understanding of cosmic magnetism. Sensitive observations, a good knowledge of the Galactic Faraday foreground screen, and a statistical approach that is able to properly combine all of the observational information are necessary. An all-sky map of the Galactic Faraday rotation foreground and an estimate of the overall extragalactic contribution has been derived by Oppermann et al. (2012, 2015) in the framework of “Information Field Theory” (Enßlin et al. 2009) by assuming a correlated Galactic foreground and a completely uncorrelated extragalactic term. In this paper, we propose a new, fully Bayesian approach aiming at further disentangling the contribution intrinsic to emitting sources from the contribution due to the intergalactic environment between the source and the observer and at investigating the dependence of these contributions on redshift.


For the magnetic field configurations considered in this work, the polarization angle can only change exactly by Δϕ = 90○ and a gradual change of the PA is not possible. There are tantalizing hints of a 90○ change in the PA in some of the GRBs, as discussed above, but the results are not yet conclusive. The result presented by Sharma et al. (2019) where the PA changes by 90○ twice over the emission is again very exciting as such a change over a single pulse can only occur for the Btor field configuration. The only difficulty, according to the modelling done here, is that both 90○ changes occur in the decaying tail of the pulse when high latitude emission dominates the flux. In the measurement presented by Sharma et al. (2019), the PA shows a change close to the peak of the emission. Another scenario in which a 90○ PA change can be obtained includes contribution from multiple pulses and when the LOS is close to the edge of the jet, such that θobs ≈ θj, along with a change in bulk Γ between the pulses which would change ξj = (Γθj)2. Alternatively, such a change in the PA can be obtained due to magnetic reconnection, e.g. in the ICMART model (Zhang & Yan 2011), where the local magnetic field orientation, which is orthogonal to the wave vector of the emitted photon, itself changes by 90○ as the field lines are destroyed and reconnected in the emission region (Deng et al. 2016). To obtain a change in the PA other than Δϕ = 90○ or to get a gradually changing PA the condition for axisymmetry must be relaxed and the magnetic field configuration or orientation in the emission region must change. One possibility is that if the different pulses that contribute to the emission arise in a ‘mini-jet’ within the outflow (e.g. Shaviv & Dar 1995; Lyutikov & Blandford 2003; Kumar & Narayan 2009; Lazar, Nakar & Piran 2009; Narayan & Kumar 2009; Zhang & Yan 2011). In this case, the different directions of the mini-jets or bright patches w.r.t. the LOS (e.g. Granot & Königl 2003; Nakar & Oren 2004) would cause the PA to also be different between the pulses even for a field that is locally symmetric w.r.t the local radial direction (e.g. B⊥ or B∥) as well as for fields that are axisymmetric w.r.t to the centre of each mini-jet (e.g. a local Btor for each mini-jet). Finally, broadly similar result would follow from an ordered field within each mini-jet (Bord) which are incoherent between different mini-jets. Time-resolved measurement in such a case would naturally yield a time-varying PA. Alternatively, as shown by Granot & Königl (2003) for GRB afterglow polarization, a combination of an ordered field component (e.g. Bord) and a random field, like B⊥, can give rise to a time-varying PA between different pulses that, e.g. arise from internal shocks. The ordered field component here would be that advected from the central engine and the random field component can be argued to be shock-generated. Notice that the ordered field component should not be axisymmetric in order for the PA to smoothly vary.


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).


In principle, Fig. 5, central panel G, shows that (469219) 2016 HO3 may have been locked in a Kozai–Lidov resonance with ω librating about 270° for nearly 100 kyr and probably more. Because of the Kozai–Lidov resonance, both e (central panel E) and i (central panel F) oscillate with the same frequency but out of phase (for a more detailed view, see Fig. 4, panels E and F); when the value of e reaches its maximum the value of i is the lowest and vice versa ($\sqrt{1 - e^2} \cos i \sim$ constant, see Fig. 4, panel B). During the simulated time and for the nominal orbit, 469219 reaches perihelion and aphelion the farthest possible from the ecliptic. Fig. 5, G-panels, show that for other incarnations of the orbit of 469219, different from the nominal one, ω may librate about 90° as well during the simulated time interval. However, is this a true Kozai–Lidov resonance? Namouni (1999) has shown that the secular evolution of co-orbital objects is viewed more naturally in the erωr-plane, where er and ωr are the relative eccentricity and argument of perihelion computed as defined in Namouni's work (see equations 3 in Namouni 1999); these are based on the vector eccentricity and the vector inclination. Fig. 6 shows the multi-planet erωr-portrait for the nominal orbit of this object. It clearly resembles figs 13 and 19 in Namouni (1999). Asteroid 469219 librates around $\omega _{\rm r}=-90{^\circ }$ for Venus, the Earth, and Jupiter. This behaviour corresponds to domain III in Namouni (1999), horseshoe-retrograde satellite orbit transitions and librations (around $\omega _{\rm r}=-90{^\circ }$ or 90°). For a given cycle, the lower part corresponds to the horseshoe phase and the upper part to the quasi-satellite or retrograde satellite phase. This is not the Kozai–Lidov resonance; in this case, the Kozai–Lidov domain (domain II in Namouni 1999) is characterized by libration around $\omega _{\rm r}=0{^\circ }$ (or 180°) which is only briefly observed at the end of the backwards integrations (see Fig. 6). The Kozai–Lidov resonance is however in action at some stage in the orbits displayed in Figs 5 and 8. Our calculations show that the orbital evolution followed by 469219 is the result of the dominant secular perturbation of Jupiter as the periodic switching between co-orbital states ceases after about 8 kyr if Jupiter is removed from the calculations. Fig. 7 shows that, without Jupiter, 469219 switches between the Kozai–Lidov domain and that of horseshoe-quasi-satellite orbit transitions and librations (including both −90°and 90°). Jupiter plays a stabilizing role in the dynamics of objects following orbits similar to that of 469219. It is not surprising that Jupiter instead of the Earth or Venus is acting as main secular perturber of 469219. Ito & Tanikawa (1999) have shown that the inner planets share the effect of the secular perturbation from Jupiter; in fact, Venus and our planet exchange angular momentum (Ito & Tanikawa 2002). In their work, these authors argue that the inner planets maintain their stability by sharing and weakening the secular perturbation from Jupiter. Tanikawa & Ito (2007) have extended this analysis to conclude that, regarding the secular perturbation from Jupiter, the terrestrial planets form a collection of loosely connected mutually dynamically dependent massive objects. The existence of such planetary grouping has direct implications on the dynamical situation studied here; if Jupiter is removed from the calculations, the overlapping secular resonances and the recurrent dynamics disappear as well.


The measurement of galaxy clustering statistics is one of the most powerful probes in observational cosmology (Tegmark et al. 2004; Cole et al. 2005; Percival et al. 2010; Saito et al. 2011; Zehavi et al. 2011; Reid et al. 2012, 2014; Samushia et al. 2014). However, our lack of a detailed understanding of the relationship between the distribution of galaxies and that of dark matter limits the full use of the measured amplitude of the clustering signal for constraining cosmological parameters. Seljak et al. (2005) first proposed and demonstrated that it is possible to break this degeneracy between the unknown bias between galaxies and matter and the cosmological parameters by utilizing the theoretical dependence of galaxy bias on halo mass (Mo & White 1996; Sheth & Tormen 1999). By probing the halo masses of galaxies via the weak gravitational lensing around galaxies, commonly referred to as galaxy–galaxy lensing, on small scales (see also Yoo et al. 2006; Cacciato et al. 2009; Li et al. 2009; Leauthaud et al. 2012; Tinker et al. 2012; Cacciato et al. 2013, 2014; Gillis et al. 2013; More et al. 2013; Simpson et al. 2013; see also for the galaxy–galaxy lensing measurements Fischer et al. 2000; Mandelbaum et al. 2006; van Uitert et al. 2011; Velander et al. 2014). An alternative method, which uses the ratio of the clustering and lensing signals, has also been proposed in order to avoid the complex astrophysics that complicates the interpretation of these observables on scales smaller than the typical halo radii (Baldauf et al. 2010). As a proof of this concept, Mandelbaum et al. (2013, hereafter RM13) used the state-of-the-art measurement of galaxy–galaxy lensing signal and galaxy clustering up to large-scales (

) by combining the spectroscopic and multi-color imaging galaxy catalogs from the Sloan Digital Sky Survey I/II (SDSS I/II; York et al. 2000; Eisenstein et al. 2001; Strauss et al. 2002). They showed that the joint analysis provides a significant improvement in the cosmological parameters

 and

 when combined with results from the WMAP7 experiment (Komatsu et al. 2011).


This n = 1, CT = 216 case corresponds to a new asteroseismic-calibrated version of the original TS dynamo. The parameter CT is introduced here to account for uncertainties on the adopted timescale for the damping of the azimuthal field (while the α parameter in Fuller et al. 2019 was introduced for the saturated value of ωA, hence the relation CT = α3). We thus find that the damping timescale adopted for the azimuthal field in the original TS dynamo has to be increased by a factor of about 200 to correctly reproduce the asteroseismic data of evolved stars. Ideally, one would expect a value of CT closer to unity for a well-defined physical process. We however recall here that this timescale is known to be quite approximated as mentioned by Spruit (2002) who indicated that the original estimates of the dynamo process were made by neglecting all multiplying factors of order unity and that these factors could sometimes compound to rather large numbers. A first uncertainty is related to the exact value of the growth rate of the Tayler instability which seems to be somewhat smaller than the adopted value of ωA (e.g., Goldstein et al. 2019). In the same way, the correction to this growth rate in the case of fast rotation (i.e., Ω ≫ ωA) introduces another uncertainty that also seems to overestimate its value (Ibáñez-Mejía & Braithwaite 2015). Another source of uncertainty is related to the fact that these estimates of the growth rate are only based on the fastest growing non-axisymmetric m = 1 Tayler mode, while the small-scale dynamo process could perfectly be dominated by modes with different values of m (see e.g., Ibáñez-Mejía & Braithwaite 2015). In this context, the damping timescale adopted in the original TS dynamo seems to correspond more to a minimal than an exact value; it is thus interesting to be able to constrain its value from asteroseismic data and it is then not surprising to deduce a longer timescale in this way. Of course, it is difficult to speculate whether such a large increase of about two orders of magnitude is really physically motivated in the framework of the original TS dynamo and we can only await numerical simulations performed under more realistic stellar conditions to obtain some answers on this point.


Among these latter complex molecules, formamide (HCONH2) is of crucial importance. Chemical reactions of molecules containing H, C, N, and O such as formamide are considered a plausible pathway for synthesis of biomolecules under prebiotic conditions (Oparin 1938). Formamide is the simplest molecule containing the peptide bond, which is known to be the basis for assembling proteins and polypeptides starting from amino acids, with a crucial role in the biotic processes of life on Earth. Formamide was first detected in the gaseous phase in two high-mass star forming regions: Orion-KL, an active star forming region, and the giant molecular cloud SgrB2 (e.g., Turner 1991; Nummelin et al. 1998; Halfen et al. 2011); later it was detected in the comet Hale Bopp (Bockelee-Morvan et al. 2000), whose chemical composition is suspected to be similar to the chemical composition of the primitive Solar Nebula. Furthermore, during landing of Philae aboard Rosetta mission, in situ mass spectrometer data inferred the presence of formamide in the comet nucleus with the highest abundance after water (Goesmann et al. 2015). In recent years, formamide was also observed in two types of low-mass star forming environment: shocked regions by protostellar jets (e.g., Codella et al. 2017) and hot corinos (Kahane et al. 2013; López-Sepulcre et al. 2015; Marcelino et al. 2018; Imai et al. 2016; Oya et al. 2017; Lee et al. 2017). In high-temperature regions (> 100 K) such as hot corinos, thermal desorption is responsible for sublimation of frozen mantles into the gas phase. Moreover, outbursting young stars like V883 Ori are good new targets for looking for organic complex molecules that thermally desorb from icy mantles. The interpretation of observations can benefit from information coming from the laboratory, where it is possible to simulate the thermal desorption process and UV irradiation of formamide under simulated space conditions. Here we report two laboratory analyses. We focus both on photostability and on thermal desorption of pure formamide, and in the presence of grains, before and after UV irradiation. Section 2 presents our choice of minerals used as analog samples and the experimental setup. In Sect. 3, in situ UV irradiation of pure formamide ice and its adsorption by minerals at 63 K are investigated by infrared spectroscopy (FTIR). Section 4 presents a temperature-programmed desorption (TPD) analysis of pure formamide ice and in the presence of TiO2 dust, before and after UV irradiation.


Figure 1a shows for each cluster a visualization of the resulting background-subtracted color-magnitude diagram, produced with an approach similar to that of van der Burg et al. (2016). Specifically, we subtracted the residual background contamination as follows: 1) We start from a candidate cluster member sample obtained as discussed in Sect. 3.1, and a control field sample from the GOODS-S field (see Sect. 2.3) that is selected in the same manner. 2) For each galaxy in the candidate member sample, we calculate a “weight” that corresponds to the statistical excess of the candidate member sample over the control field density at the magnitude and colors of the given galaxy. Weights are calculated as follows (see van der Burg et al. 2016, for a more detailed description): first, all candidate member weights are initially set to 1. Then, for each galaxy in the control field sample we subtract the corresponding “background contamination” from the candidate member sample by appropriately reducing the weights of all candidate members that lie within a distance in the color (m814–m140) – color (m140–[3.6]) – magnitude (m140) space given by their photometric uncertainties (1σ), with a minimum distance of 0.3 mag, effectively resulting in a smoothing of galaxy densities in the color-color-magnitude space. If no galaxies are found within this distance, we double the search distance, and then if necessary increase the search distance to 1.3 times the distance to the closest galaxy. This criterion allows the full subtraction of the background contamination estimated from all galaxies in the control field sample, while reducing the weights of those candidate members that are more similar to the galaxies in the control field. For each considered control-field galaxy, the weights of all selected candidate members identified with the above criterion are reduced so that the contribution of the considered field galaxy (normalized by the areas of the probed cluster region and of the control field) is removed. At the end of this procedure, the contributions of all galaxies from the field sample have been subtracted from the candidate member sample.


The young starburst inferred by the detections of high ionization emission line of He II λ4686 and the blue WR bump in this and previous works (Guseva et al. 2000; Brinchmann, Kunth & Durret 2008) is confirmed by the age estimates made here for the bright and faint regions in Mrk 22 as ∼4 and ∼10 Myr, respectively. Unlike previous works, we carried out abundance analysis for both the regions separately. We found an appreciable metallicity difference of ∼0.5 dex between the bright region [12 + log (O/H) ∼ 8] and the faint region [12 + log(O/H) ∼ 7.5]. The separation between two regions is ∼0.6 kpc. Typical metallicity gradients in normal spiral galaxies have been found between −0.009 and −0.231 dex kpc−1, with an average gradient of −0.06 dex kpc−1 (Zaritsky, Kennicutt & Huchra 1994). The observed metallicity difference between the two regions in Mrk 22 is too large to be explained as a normal galactic metallicity gradient. The chemical composition as measured from the gas-phase metallicity [12 + log(O/H)] shows various degree of spatial variations in different types of dwarf galaxies. For instance, shallow gradient in metallicity is seen in SBS 0335−052 (Papaderos et al. 2006) while no significant variations were seen in Mrk 35 (Cairós et al. 2007). A study on a large sample indicates that normal BCD galaxies are chemically homogeneous (Kobulnicky & Skillman 1996; Papaderos et al. 2006; Kehrig et al. 2008; Cairós et al. 2009; Pérez-Montero & Contini 2009; Pérez-Montero et al. 2011; Hägele et al. 2011; García-Benito & Pérez-Montero 2012; Lagos & Papaderos 2013). On the other hand, the metallicity of extremely metal-poor galaxies is usually not homogeneous within the galaxy, with the low metallicity seen in regions of intense star formation (Papaderos et al. 2006; Izotov & Thuan 2009; Levesque et al. 2011; Sánchez Almeida et al. 2013, 2014, 2015). However, large metallicity gradients are not common in dwarf galaxies. The simplest explanation for large metallicity difference in a single system is a recent merger of two galaxies with different metallicity. In a few cases, significantly large metallicity differences between star-forming regions in dwarf galaxies were seen and understood in terms of recent tidal interactions or mergers (López-Sánchez, Esteban & Rodríguez 2004a,b; López-Sánchez, Esteban & García-Rojas 2006; López-Sánchez & Esteban 2009, 2010). The evolution in terms of metallicities in interacting dwarf galaxies is fairly complex as it can depend on various factors such as mixing of metals with the interstellar medium (ISM), possible outflows of metals, and inflow of metal-poor gas in tidally interacting systems.


In the past, as well as in the more recent literature, there have been many attempts to explain the different chemical evolutionary paths of different MW components, particular those of the thin and thick discs. The outcome of these studies is that the observed different chemical evolutionary paths are related to differences in the main physical processes that drive galaxy evolution, the most significant of which are the gas accretion time-scale and the star formation efficiency and, possibly, radial migration (Larson 1972; Lynden-Bell 1975; Pagel & Edmunds 1981; Matteucci & Greggio 1986; Matteucci & Brocato 1990; Ferrini et al. 1994; Prantzos & Aubert 1995; Chiappini et al. 1997, 2001; Portinari & Chiosi 1999; Bekki & Tsujimoto 2011; Micali et al. 2013; Sahijpal 2014; Snaith et al. 2014; Grisoni et al. 2017; Grand et al. 2018; Spitoni et al. 2021). A good agreement between observations and theoretical predictions for the Galaxy is obtained by models that are based on the assumption that the disc formed via the infalling of gas (Chiosi 1980; Matteucci & Francois 1989; Chiappini et al. 1997). The formation of the different components is associated with distinct sequential main episodes of gas accretion (infall phases) that, at first, rapidly accumulates in the central regions and then, more slowly, in the more external ones, according to the so-called ‘inside-out scenario’ (Chiappini et al. 2001). In particular, the three-infall model, devised by Micali et al. (2013), is capable of reproducing the abundance patterns of the MW halo, thick and thin disc at once. In this model, the halo forms in a first gas infall episode of short timescale (0.2 Gyr) and mild star formation efficiency, ν = 2 Gyr−1, lasting for about 0.4 Gyr. It is immediately followed by the thick disc formation, characterised by a somewhat longer infall timescale (1.2 Gyr), a longer duration (about 2 Gyr) and a higher star formation efficiency (ν = 10 Gyr−1). Finally, star formation continues in the thin disc with a longer infall timescale (6 Gyr in the solar vicinity) and is still continuing to this day, with a star-formation efficiency of ν = 1 Gyr−1. The [O/Fe] vs. [Fe/H] path is thus continuous across the regions populated by halo, thick, and thin disc stars. While Micali et al. (2013) described the chemical enrichment as continuous across the three different infall stages, Grisoni et al. (2017) used also an alternative scheme where the thin and thick disc components evolve separately, in a parallel approach (see also Chiappini 2009). In such a parallel approach, the disc populations are assumed to form in parallel but to proceed at different rates. The gas infall exponentially decreases with a timescale that is 0.1 Gyr and 7 Gyr, for the thick and thin disc, respectively. This alternative approach better reproduces the presence of the metal-rich α-enhanced stars in the [Mg/Fe] vs. [Fe/H] diagram obtained with the recent AMBRE data (Mikolaitis et al. 2017).


Extensive studies have attempted to probe the near-infrared EBL through different methods. Galaxy counts measures emission from resolved galaxies and the observations are extrapolated to estimate contributions from faint galaxies below the detection limit (Keenan et al. 2010; Domínguez et al. 2011; Helgason et al. 2012; Driver et al. 2016; Saldana-Lopez et al. 2021; Koushan et al. 2021). This sets a lower bound to the integrated galaxy light (IGL) component of EBL, as EBL from diffuse emission or sources not associated with galaxies is not included. Direct measurements using absolute photometry capture all emission in the EBL (Bernstein 2007; Levenson et al. 2007; Tsumura et al. 2013; Matsumoto et al. 2015; Sano et al. 2015; Matsuura et al. 2017; Zemcov et al. 2017; Lauer et al. 2021; Sano et al. 2020), however, absolute photometry is challenging since systematic errors and foreground contamination have to be tightly controlled. Fluctuation analysis is an alternative approach that is less susceptible to foreground contamination (e.g., zodiacal light, Galactic cirrus), since foregrounds and the EBL signal have distinct spatial and spectral correlation features (Kashlinsky et al. 2005; Thompson et al. 2007; Matsumoto et al. 2011; Cooray et al. 2012; Kashlinsky et al. 2012; Zemcov et al. 2014; Mitchell-Wynne et al. 2015; Seo et al. 2015; Kim et al. 2019; Matsumoto & Tsumura 2019); nevertheless inferring the absolute intensity of the EBL from fluctuation measurements depends on model assumptions. Another limitation of absolute photometry and fluctuation measurements is the inferred EBL redshift resolution. As the measured intensity is a projection of all emission along the line of sight, one way to infer the redshift dependency of the EBL is to measure the opacity of gamma-ray photons from individual blazars. Near-infrared photons along the line of sight will interact with gamma-ray photons by pair production, and thus the redshift composition of EBL can be constrained by the absorption features in blazar spectra (e.g., Aharonian et al. 2006, 2007; MAGIC Collaboration et al. 2008; Abdo et al. 2010; Ackermann et al. 2012; H. E. S. S. Collaboration et al. 2017; Ackermann et al. 2018; Abeysekara et al. 2019; Acciari et al. 2019; Abdalla et al. 2020). This method enables a redshift tomography of the EBL by observing blazars from different distances. However, these estimates have low spectral resolution and depend on the assumption of intrinsic blazar spectra.


We have used 3.0–75.0 keV NuSTAR data to probe any cyclotron line feature. To describe the continuum of 4U 1700–37, we have applied the NPEX model [cons*TBpcf*(powerlaw*npex+gaus+gaus)], following the previous work of Jaisawal & Naik (2015a). The NPEX model has been created by adding two cutoffpl models with their cutoff energies tied to each other and keeping the photon index of one to be frozen at –2.0. For the best fit, the χ2/d.o.f is found to be 577.64/475. The fit shows some residuals in the overall spectrum. We added a Gaussian absorption model around 39 keV (following the previous work of Jaisawal & Naik 2015a), but the best fit gives the line energy as $15.44^{+0.56}_{-0.53}$ keV with χ2/d.o.f = 487.32/472. The width and the depth of the line are found to be $5.47^{+0.90}_{-0.78}$ keV and $1.29^{+0.51}_{-0.39}$, respectively. The chance probability of the line has been computed using the ftest task in xspec. The F-test with this absorption line gives an F value  = 29.2 and a chance probability of 2.61 × 10−17(Table 3). If we add another Gaussian absorption line at 38.9 keV (Energy value frozen) the best-fitting χ2/d.o.f is found to be 486.8/470. This indicates that the second absorption line is not required for the fit. If we use only one Gaussian absorption line and freeze the line energy at 38.9 keV then the width and the depth of the line are found to be $4.54_{-0.87}^{+0.90}$ keV and $2.87_{-1.05}^{+1.24}$, respectively with a χ2/d.o.f  = 549.2/473. The ftest gives a chance probability of the 38.9 keV line to be 6.4 × 10−6. So, with NPEX model we find two valid model combinations of the data. One, the presence of a Gaussian absorption line at ∼15 keV, two, the presence of a Gaussian absorption line at 38.9 keV. But, the presence of both lines together is not supported by the data. The 10.0–70.0 keV flux of the source is found to be (2.26 ± 0.01) × 10−9 erg cm-2s-1, much lower than the value (5.6 ± 0.3) × 10−9 erg cm-2s-1, previously reported from SUZAKU data (Jaisawal & Naik 2015a).


Sudden outbursts of NH3 simultaneously with H2S detected with the ROSINA-DFMS instrument on the Rosetta S/C point to the presence of abundant ammonium hydrosulphide in or on carbonaceous grains from comet 67P/Churyumov-Gerasimenko. There seems to be a clear distinction between the nucleus ice, where H2S and NH3 exist independently and grains, where they desorb together. S2 is much more abundant on grains compared to water than in the ice of the comet, while S3 is found only in grain impacts. This higher abundance points to radiolysis in these grains, which means they must have been exposed to energetic particles over an extended time. While for operational reasons, S4 could not be measured close to the dust impacts, S4 was clearly identified in periods where the coma was very dusty (Calmonte et al. 2016). Longer sulphur chains very likely are refractory, not sublimating at temperatures reached in the instrument or on grains in the coma. While Sn can also be formed from pure H2S ice by photo processing (Cazaux et al. 2022), the fact that S3 is clearly related to dust and is not found in the normal nucleus ice, where H2S is quite abundant, indicates that S3 is a product of radiolysis of the ammonium salt. In addition, photo processing of H2S results not only in Sn, but also in H2S2 (Cazaux et al. 2022), a species not detected in the DFMS m/z 66 and m/z 65 (HS2) spectra. This exposure rules out a contemporary formation of the salt on the surface or in the interior of the comet or a formation of the salt in the mid-plane of the protoplanetary disc, while the comet accreted. A pre-stellar formation is therefore likely. The salt is semivolatile, less volatile than water and could probably have survived quite high temperatures. It seems that on these grains, acids and ammonia are all locked in salts, be it sulphur, halogens, or carbon bearing acids like HOCN. If indeed, a relatively large part of sulphur and nitrogen is therefore in a semivolatile state in these grains, then the depletion of nitrogen in comets and of sulphur in star-forming regions could probably be explained, primarily because salts escape detection unless they experience temperatures above water sublimation. With the JWST S/C in orbit, there is hopefully the possibility to detect salts, or at least several of the acids in ices, which are supposed to be part of ammonium salt, like HOCN, H2CO, and formamide while looking for ammonium salts in star-forming regions and possibly comets.


Solar energetic particle (SEP) events observed in interplanetary space present a large variability in terms of intensity, composition, and spatial and temporal extent (e.g., Kahler et al. 1999; von Rosenvinge & Cane 2006; Gopalswamy 2012). In particular, the observed SEP intensity time profiles result from both (i) the injection history of SEPs as they are released from their acceleration sites, and (ii) the transport processes undergone by the particles as they travel through the interplanetary medium from their sources to the particle detectors on board spacecraft. The transport effects pose the main difficulty in reconstructing the processes of particle release occurring at the Sun from in situ spacecraft observations. In order to correctly extract interplanetary transport effects, an effective treatment of the SEP transport processes in the heliosphere is required. Several approaches have been used over the years to characterize the SEP transport conditions (e.g., Reid 1964; Earl 1974, 1976; Roelof 1975, 1979, 2008; Hamilton 1977; Beeck et al. 1987; Kallenrode et al. 1992; Ruffolo 1995; Kocharov et al. 1998; Ruffolo et al. 1998; Laitinen et al. 2000, 2013; Dröge 2003; Qin et al. 2005; Wang et al. 2006; Agueda et al. 2008, and references therein). Such approaches allow us to reproduce spacecraft SEP observations and thereby infer SEP injection histories. The particle angular distributions relative to the local direction of the magnetic field (i.e., pitch-angle distributions (PADs)) have proven to be relevant in these analyses. A given intensity time profile can be fitted using a large variety of combinations of the injection profile at the Sun and interplanetary transport conditions, although this non-uniqueness can be constrained by a simultaneous analysis of the omni-directional intensity and the computed anisotropy time profiles (e.g., Schulze et al. 1977). More recently this problem has been further constrained by including the most direct form of data in the analysis, that is, the measured directional distributions together with the angular response of the detector (Agueda et al. 2008, 2009a, 2014).


The EWs were measured with the methods described in Vásquez et al. (2015). As in Paper I, we used the sum of the EWs of the two strongest CaT lines (λ8542, λ8662) as a metallicity estimator, following the Ca II triplet method of Armandroff & Da Costa (1991). Different functions have been tested in the literature to measure the EWs of the CaT lines, depending on the metallicity regime. For metal-poor stars ([Fe/H] ≲ −0.7 dex) a Gaussian function was used with excellent results (Armandroff & Da Costa 1991), while a more general function (such as a Moffat function or the sum of a Gaussian and Lorentzian, G + L) is needed to fit the strong wings of the CaT lines observed in metal-rich stars (Rutledge et al. 1997; Cole et al. 2004). Following our previous work (Gullieuszik et al. 2009; Saviane et al. 2012) we have adopted here a G+L profile fit. To measure the EWs, each spectrum was normalised with a low-order polynomial using the IRAF continuum task, and set to the rest frame by correcting for the observed radial velocity. The two strongest CaT lines were fitted by a G+L profile using a non-linear least squares fitting routine part of the R programming language. Five clusters from the sample of Saviane et al. (2012) covering a wide metallicity range were re-reduced and analysed with our code to ensure that our EWs measurements are on the same scale as the template clusters used to define the metallicity calibration. Figure 5 shows the comparison between our EWs measurements and the line strengths measured by Saviane et al. (2012) (in both cases the sum of the two strongest lines) for the five calibration clusters. The observed scatter is consistent with the internal errors of the EW measurements, computed as in Vásquez et al. (2015). The measurements show a small deviation from the unity relation, which is more evident at low metallicity. A linear fit to this trend gives the relation: ΣEW(S12) = 0.97 ΣEW(this work) + 0.21, with an rms about the fit of 0.13 Å. This fit is shown in Fig. 5 as a dashed black line. For internal consistency, all EWs in this work have been adjusted to the measurement scale of Saviane et al. (2012) by using this relation. In Table 3 we provide the coordinates, radial velocities, and the sum of the equivalent widths for the cluster member stars, both measured (“m”) and corrected (“c”) to the system of Saviane et al. 2012.


The total energy released at an SN type II explosion,

, exceeds, by two orders of magnitude, the energy transferred to the ejecta,

. The bulk of energy escapes with the neutrino emission. Typically, the pulsar rotation energy is small compared to the ejecta energy. However, it cannot be excluded that at some circumstances the pulsar can receive a larger fraction of the explosion energy. When it becomes comparable to the kinetic energy of the ejecta, the sizes of both the SNR and the PWN can significantly deviate from Sedov’s solution. To illustrate the implication of this scenario, we considered a specific case of HESS J1825−137, a very extended and bright in VHE gamma-ray PWN (Aharonian et al. 2006; Pavlov et al. 2008; Mitchell et al. 2017a, 2017b; H.E.S.S. Collaboration et al. 2018a). The X-ray and gamma-ray observations of HESS J1825−137 show that the shape of the nebula deviates from the spherically symmetric geometry. Thus, the 1D model described in Section 2 has limited capability for accurate quantitative predictions. However, in the framework of the suggested scenario, the hydrodynamic processes evolve differently from the conventional situations, and the 1D model should provide a correct estimate for the energy required for the PWN/SNR inflation. In the framework of the scenario, the pressure in the PWN is the main driving force of the SNR expansion. Independently on symmetry of the system and dimension of the used model, the PWN is nearly isobaric, thus the radius of the pulsar wind TS provides an observational constraint for the pressure in the nebula. Therefore, we adopt the following requirement: the present-day pressure in the nebula should be consistent with the pulsar wind TS located at

 from the pulsar (Van Etten & Romani 2011). The 1D model allows us to obtain the radii of the SNR, PWN, and pulsar wind TS as functions of three key model parameters: density of the ISM, pulsar braking index, and the initial angular velocity of the pulsar. In the framework of this model, it is possible to reproduce the three key properties of the system:

,

, and

, provided that (i) the pulsar obtains, at its birth, a significant fraction of the explosion energy (

), and (ii) the braking index is small,

. The conventional Sedov-like solution implies a low density of the ISM,

. In contrast, the model proposed in this paper requires a rather dense environment,

. This agrees with the presence of dense molecular clouds reported in the vicinity of the source (Voisin et al. 2016). What concerns the requirement for the pulsar braking index,

, is that it is small compared to the value measured for the Crab pulsar (Lyne et al. 1993), but it matches both the old (e.g., Vela; n = 1.4 ± 0.2; Lyne et al. 1996) and young (e.g., J1833–1034; n = 1.8569 ± 0.001; Roy et al. 2012) pulsars.


Three additional products were detected using the QMS during the TPD of the processed ice analogs in Experiments 1−3: C2O,3

3
No other carbon chain oxide molecules were monitored with the QMS.
 H2C2O, and H15NCO. The TPD curves of these product main mass fragments (m/z = 40, C2O; m/z = 14, H2C2O; and m/z = 44, H15NCO4

4
We assign the thermal desorption detected for the m/z = 44 mass fragment at T > 100 K to H15NCO because it is the most stable isomer among HOC15N, H15NCO, HC15NO, and HO15NC. In previous experimental simulations where HNCO ice molecules were produced, the metastable isomers were only tentatively detected, if at all (see, e.g., Jiménez-Escobar et al. 2014). In addition, gas-phase observations of different astrophysical environments reveal an abundance of the metastable isomers with respect to HNCO of less than 1% (Quan et al. 2010 and references therein).
 in Experiment 3 are also shown in Figure 3. The C2O IR feature at 1989 cm−1 (Palumbo et al. 2008) was only tentatively detected at the edge of the hatched region in the top panel of Figure 1. The H2C2O and H15NCO IR features at 2129 cm−1 and 2260 cm−1, respectively (van Broekhuizen et al. 2004; Hudson & Ferrante 2020), overlapped with different CO and carbon chain oxide IR features in the hatched region and could not be unambiguously detected. In order to confirm the assignments of the m/z = 40, m/z = 14, and m/z = 44 desorptions in Figure 3, to C2O, H2C2O, and H15NCO (the thermal desorption detected at T > 100 K), respectively, we energetically processed four additional ice analogs composed of different combinations of isotopically labeled H2, CO, and N2 molecules with 2 keV electrons (Experiments 4−7; see Table 1),  and checked that the same thermal desorption was observed for the expected mass fragments, considering the shift in the mass of the main fragments according to their isotopic composition in each experiment. The results are shown in Figure 4, confirming the formation of these species upon electron irradiation of H2:CO:N2 ice analogs.


We first determined the orbital parameters for RS Ser, V449 Per, and V1095 Her. Further, we updated the parameters for V593 Cen and MR Del. Using the formula f  = (Ωin – Ω1)/(Ωin – Ωout), we calculated the contact factors f for RS Ser, V593 Cen, and V1095 Her as 6.5 per cent, 40 per cent, and 53 per cent, respectively. RS Ser is a contact binary with a small temperature difference of 131 K and a low contact factor. For V593 Cen, we updated the orbital parameters using more complete light curves. The orbital inclination of 83°.18 is similar to the result (82°.6) obtained by Zhao et al. (2019). The temperature of the secondary component (15 284 K) is higher than the previous result of 15 099 K. However, the mass ratio of 0.6 is lower than the previous result of 1.05 (Zhao et al. 2019). More spectroscopic observations are required to confirm the mass ratio. We confirmed that V593 Cen is an early-type contact binary with a deep contact factor as well as a black hole candidate. For MR Del, we revised the absolute parameters using its full light curve and the published radial velocities, which are similar to those published previously (Zhao et al. 2019; Pribulla et al. 2009; Djurašević et al. 2011). V1095 Her is also a contact binary with a deep contact factor of 40 per cent and a temperature difference of about 172 K. Looking over our four complete light curves, we found no evident starspot activity, and estimated variations exist over a long-term time-scale of years. V449 Per is an interesting target for detecting extra-solar and brown dwarfs using the minima timing variability of a low-mass eclipsing binary (Pribulla et al. 2012). Additional minima with higher precision are required to study its periodic variation further. Our physical parameters for RS Ser, V593 Cen, and V1095 Her are based on a light curve with a q-search-determined mass ratio. The nature of these parameters is speculative and preliminary. Radial velocities may eventually come to rescue them and provide a more definitive determination.


Two major limitations, often neglected, affect this type of analysis: the adoption of oversimplified models to describe the wide variety of observed galaxy SEDs and the presence of ‘systematic’ model uncertainties. This second limitation has been addressed in several studies already (e.g. Charlot, Worthey & Bressan 1996; Cerviño, Luridiana & Castander 2000; Conroy, Gunn & White 2009; Percival & Salaris 2009; Conroy & Gunn 2010; Conroy, White & Gunn 2010a). The difficulty of precisely quantifying systematic model uncertainties has led to mainly qualitative conclusions, leaving the problem unsolved. The first limitation is easier to tackle, for example, by using more physically realistic models of galaxy SEDs and combining these with advanced statistical techniques to extract physical constraints from data. This appears as the most promising route to fully exploit the information gathered by modern photometric and spectroscopic galaxy surveys. Yet, the several tools proposed so far to interpret galaxy SEDs in terms of physical parameters do not allow one to fully exploit the high quality of modern data. For example, most existing approaches rely on the adoption of a rigid physical model (e.g. analytic, two-parameter star formation histories combined with a standard dust attenuation curve and the assumption that all stars in a galaxy have the same metallicity) to describe galaxy SEDs (e.g. Bolzonella et al. 2010; Wuyts et al. 2011; Hernán-Caballero et al. 2013; Ilbert et al. 2013; Bauer et al. 2013; Muzzin et al. 2013; Lundgren et al. 2014; Kochiashvili et al. 2015; Mortlock et al. 2015; Kawinwanichakij et al. 2016). Even with the inclusion of superimposed bursts of star formation (e.g. Kauffmann et al. 2003; Gallazzi et al. 2005; Pozzetti et al. 2007; Gallazzi & Bell 2009; da Cunha et al. 2010), this does not allow a physically consistent description of the contributions by stars, gas and dust to the integrated emission from a galaxy, nor the inclusion of a potential AGN component (a notable exception is the approach of Pacifici et al. 2012, who incorporate star formation and chemical enrichment histories from numerical simulations of galaxy formation and emission from photoionized gas). Also, current spectral analysis tools are generally optimized to interpret either photometric or spectroscopic observations of galaxies, but not arbitrary combinations thereof. Finally, most existing tools suffer from additional limitations: many focus on the selection of ‘best-fitting’ parameters rather than on the uncertainties associated with these parameters (e.g. chi-square minimization techniques; Arnouts et al. 1999; Bolzonella, Miralles & Pelló 2000; Kriek et al. 2009); when this is not the case, the number of free parameters that can be explored is generally limited (e.g. with grid-based Bayesian techniques; da Cunha, Charlot & Elbaz 2008; Noll et al. 2009; Pacifici et al. 2012); and when more sophisticated (e.g. Markov Chain Monte Carlo, hereafter MCMC) techniques allow the exploration of more parameters, instrumental effects are generally not incorporated in the analysis (e.g. Acquaviva, Gawiser & Guaita 2011; Serra et al. 2011; Han & Han 2014).


Situated in the closest vicinity of their host stars (0.05 AU) and having no counterparts in our Solar system, ultra-hot Jupiters (Arcangeli et al. 2018; Bell & Cowan 2018; Parmentier et al. 2018) are ideal testbeds for studying the impact of 3D effects on high-resolution spectra. There are two important reasons for this. First, ultra-hot Jupiters are accessible objects to observe. Their short orbital periods (1–2 d) and hot, extended atmospheres make them perfect targets for transmission spectroscopy (Hoeijmakers et al. 2019; Von Essen et al. 2019; Ehrenreich et al. 2020; Borsa et al. 2021), emission spectroscopy (Evans et al. 2017; Arcangeli et al. 2018; Mikal-Evans et al. 2020) and phase-curve studies (Zhang et al. 2018; Bourrier et al. 2020b; Mansfield et al. 2020). Secondly, ultra-hot Jupiters display extreme variations across their atmospheres, because they are expected to become tidally locked soon after their formation (Rasio et al. 1996; Showman & Guillot 2002). As a result, their atmospheres virtually consist two different worlds: a permanently irradiated dayside and a permanently dark nightside. The scorching, cloud-free dayside (T ≳ 2500 K) nearly resembles a stellar photosphere, where most molecules are dissociated1 and metals become ionized (Parmentier et al. 2018; Hoeijmakers et al. 2019). On the other hand, the nightside is substantially cooler (T ≲ 1000 K) and may even serve as a stage for cloud formation (Helling et al. 2019; Ehrenreich et al. 2020). Ultra-hot Jupiters also exhibit large differences in their thermal structures: the dayside is expected to show strong thermal inversions (Haynes et al. 2015; Evans et al. 2017; Kreidberg et al. 2018; Pino et al. 2020; Yan et al. 2020), whereas nightside temperatures are expected to monotonically decrease with altitude. Furthermore, ultra-hot Jupiters feature strong winds in the order of 1–10 km s−1 (Tan & Komacek 2019), which arise as a result of the continuous day-night forcing. Many observational studies have measured Doppler shifts due to winds on ultra-hot Jupiters (Casasayas-Barris et al. 2019; Bourrier et al. 2020a; Cabot et al. 2020; Ehrenreich et al. 2020; Gibson et al. 2020; Hoeijmakers et al. 2020; Nugroho et al. 2020; Stangret et al. 2020; Borsa et al. 2021; Kesseli & Snellen 2021; Rainer et al. 2021; Tabernero et al. 2021), yet inferring the underlying 3D circulation pattern is a formidable challenge.


Here, we report on molecular gas observations of NGC 0708, the BCG in the low-mass galaxy cluster Abell 262, itself part of the Perseus–Pisces galaxy supercluster. NGC 0708 lies 58.3 ± 5.4 Mpc away (estimated using infrared surface brightness fluctuations; Jensen et al. 2003). It is a giant elliptical galaxy with a weak dust lane (Ebneter & Balick 1985; Wegner et al. 1996) and an effective radius of 33 arcsec ($\approx \, 9.3$ kpc; Wegner et al. 2012). See Fig. 1 for an HST image of NGC 0708. Abell 262 was identified as having an X-ray emitting ICM by Jones & Forman (1984), and Stewart et al. (1984) measured the cooling time to be 1.3 × 109 yr, smaller than the age of the Universe so that the cluster is expected to form a cooling flow. The 20-cm observations of Parma et al. (1986) revealed a double-lobed, ‘S’-shaped jet and led to the classification of NGC 0708 as a weak Fanaroff–Riley Class I radio source (Blanton et al. 2004). The top panel of Fig. 1 also has 330 MHz continuum observations from Clarke et al. (2009) overlaid (blue contours) to show the shape and orientation of the large-scale jet. Analysis of Chandra observations revealed a hole or bubble within the ICM, cospatial with the eastern lobe of the jet (Blanton et al. 2004). Clarke et al. (2009) found additional 3–6 kpc radius cavities at differing position angles within the X-ray gas, and at a range of radial distances from the BCG (8–29 kpc), indicating multiple episodes of AGN activity from a precessing SMBH jet. They concluded that the total AGN emission should be capable of counteracting the cooling flow over several outbursts. Using their multifrequency observations of NGC 0708, Clarke et al. (2009) also calculated the radio spectral index (α) from 235 to 610 MHz, finding the spectrum to be flat in the core (α = −0.5), typical of new particles in a jet. They also estimated a lower limit on average outburst repetition time-scales in Abell 262 to be τrep ≥ 28 Myr.


For the launching of a two-sided jet, the BZ power depends on the BH spin (assumed to be aligned with the disc) and on the magnetic flux threading the BH horizon at rh (e.g. Tchekhovskoy, Narayan & McKinney 2011):1(1)$$\begin{eqnarray*}
L \approx \frac{10^{-3}}{c} \Phi _h^2\Omega _h^2f(\Omega _h)\approx 10^{51} M_{\, {\rm BH},5}^2 B_{h,15}^2a_{-0.1}^2 \, {\rm erg}~\, {\rm s}^{-1},
\end{eqnarray*}$$where Qx denotes the value of the quantity Q in units of 10x times its c.g.s. units, except for Mx, which is given in units of $\, {\rm M_{\odot }}$. $\Phi _h = 4\pi r_h^2|B_h|$ is the integrated magnetic flux on one hemisphere of the BH horizon, |Bh| is the value of the radial contravariant magnetic field on the horizon, $\, {M_{\rm BH}}$ and a are the BH mass and spin, Ωh = ac/(2rh) is the angular velocity at the BH horizon, and f(Ωh) ≈ 1 + 1.38x2 − 9.2x4, where $x \equiv 0.5a\left(1+\sqrt{1-a^2}\right)^{-1}$. A second necessary condition for a successful launching of a BZ jet is that the BZ jet power will be sufficient to overcome the accretion power of the infalling material along the jet path (Burrows et al. 2007; Komissarov & Barkov 2009). Prior to the jet launching, matter is free-falling on the BH quasi-spherically with a power on one hemisphere of
(2)$$\begin{eqnarray*}
\dot{M}c^2 = 4\pi r_g^2 \rho _h \beta ^r_h c^3\approx 2\times 10^{51} M_{\, {\rm BH},5}^2\beta ^r_h\rho _{h,7} \, {\rm erg}~\, {\rm s}^{-1},
\end{eqnarray*}$$where ρh is the mass density on the horizon at the time of the jet launching, and $\beta ^r_h$ is the dimensionless radial velocity of the infalling material at that time, which is expected to be close to unity. Comparing the jet luminosity from equation (1) with the accretion power from equation (2), we get a necessary condition for the strength of magnetic flux on the horizon that allows a successful jet launching
(3)$$\begin{eqnarray*}
\Phi _h \gtrsim \, {\Phi _{h,\rm min}}\approx 7\times 10^{27}\frac{\sqrt{\beta ^r_h\rho _{h,7}}}{a_{-0.1}}~{\rm G~{\rm cm^2}},
\end{eqnarray*}$$corresponds to minimal magnetic field on the horizon $\, {B_{h,\rm min}}\approx 1.4\times 10^{15}$ G for the same normalization of parameters. Note that since a and $\beta ^r_h$ are both of order unity, the minimal magnetic field is primarily dictated by the central density of the star, which in turn depends on the stellar mass, radius, and density profile.


In the left-hand panel of Fig. 2, we compare the morphological types assigned by the STAGES collaboration for the galaxies in the whole OMEGA sample and the jellyfish candidates sample. The sample of jellyfish galaxies (JC345) is composed mainly of late-type spirals and irregulars. In the middle panel of Fig. 2, we show the distribution of SED types for both samples. Based on the SED types of the galaxies, of the 70 jellyfish galaxy candidates analysed, 66 were found to be part of the blue cloud and 4 as being dusty reds (IDs: 11633, 17155, 19108, 30604). However, contrary to what could be expected, dusty red galaxies are only a small portion of our sample of jellyfish candidates. One reason why we may not detect many dusty reds as jellyfish galaxies might be due to the fact that these galaxies, despite having relatively high SFRs (only four times lower than that in blue spirals at fixed mass, Wolf et al. 2009), have significant levels of obscuration by dust that might hamper the identification of the jellyfish signatures. Another reason for that is that we selected jellyfish galaxy candidates within a parent sample of H α-emitting galaxies that already had a low fraction of dusty red galaxies (≈15 ${{\ \rm per\ cent}}$). As these galaxies have low star formation, it is harder to perceive the morphological features of RPS. Dusty red galaxies have been previously studied in this same system (Wolf et al. 2009), and RPS was suggested to be the main mechanism acting in these galaxies (Bösch et al. 2013). While in Bösch et al. (2013) one of the main pieces of evidence suggesting the action of enhanced RPS were the existence of disturbed kinematics without disturbed morphologies, in our study we strongly base our selection on such morphological distortions. Both our jellyfish galaxy candidates and the dusty red galaxies show different characteristics that can be correlated to the effect of RPS. Nevertheless, they might be tracing different stages of the same phenomenon, where dusty red galaxies have more regular morphologies, but disturbed kinematics. Our sample of morphologically disturbed jellyfish galaxy candidates may be showing the stage where the features of RPS are the most visible and the SFRs are enhanced.


Molecular outflows are a common and essential component in the formation process of low- and high-mass stars. In the past 40 yr, astronomers have mapped outflows in the whole mass range of young stellar objects (YSOs; e.g., Frank et al. 2014; Bally 2016; Anglada et al. 2018; Ray & Ferreira 2021). Magnetohydrodynamical (MHD) simulations have shown that the magnetic field plays a crucial role in the launching of molecular outflows (e.g., Pudritz & Ray 2019), more significantly so in the case of massive YSOs (e.g., Matsushita et al. 2018). Here, for instance, the presence of a magnetic field leads to the formation of early outflows. These reduce the radiation pressure, which allows the protostar mass to grow further (Banerjee & Pudritz 2007; Rosen & Krumholz 2020). In addition, the intensity of the magnetic field may influence the collimation of the outflows in massive YSOs. The outflows are well collimated for weak fields and poorly collimated for strong fields (Hennebelle et al. 2011; Seifried et al. 2012). In case of strong magnetic fields, the structure of the outflows is determined by the large-scale geometry of the magnetic field lines (Matsushita et al. 2017). Recently, Machida & Hosokawa (2020) have found a strong dependence of the evolution of outflows in massive YSOs on the initial magnetic field strength of the prestellar cloud for different accretion rates. In their 3D MHD simulations, they grouped the results into three categories: successful outflows, failed outflows, and delayed outflows. In the successful outflows, the outflows appear only when the prestellar cloud is strongly magnetized (μ1 = 2,3), and after an evolution time of ~104 yr, they reach a distance from the central protostar of about 104 au. When the magnetic field is weak (μ ≥ 5), we have failed and delayed outflows; even though small outflows of about 100–1000 au are observed in both cases, only in delayed outflows they can overcome the ram pressure and can ultimately grow. In a massive YSO, a large molecular outflow is therefore formed only if the initial magnetic field strength is B0 ≳B0,cr = 10−4(Mcl∕100M⊙) G, where Mcl is the cloud mass (Machida & Hosokawa 2020).


Other important result we reported in Section 3.3 is the reversing behaviour of red and blue galaxies with respect to velocity and groupcentric distances segregation, with redshift. Regarding velocity segregation, the preceding paragraph provides a qualitative scenario. Now, to explain the spatial segregation, we should notice that our analyses in Sections 3.2 and 3.3 take into account galaxies within 2R/R200. One can reasonably assume that such objects at lower redshifts correspond to a mixture of descendants of galaxies at higher redshifts in the same radii and of infalling objects from outer radii. Thus, both survival and replenishment of galaxies should be expected over the time, and two important factors come into play: (i) the accretion rate of galaxies; and (ii) the orbital dependence of galaxy properties (e.g. Biviano & Katgert 2004; Iannuzzi & Dolag 2012). Indeed, regarding velocity segregation, it has also been interpreted as red and blue galaxies having different kinds of orbits, with the orbits of blue galaxies being more anisotropic than the red ones (e.g. Biviano & Katgert 2004). Recently, Biviano et al. (2016) verified that the anisotropy profile of z ∼ 1 clusters is nearly isotropic near the cluster centre, and increasingly elongated with radius. This result is consistent with a halo evolution through an initial phase of fast collapse and a subsequent slow phase of inside-out growth by accrection of field material (e.g. Lapi & Cavaliere 2009). Since the accretion rate of galaxies from the field is higher at higher redshifts (e.g. McGee et al. 2009), our sample at z ∼ 0.8 is expected to be more affected by recent infalls, which had less time to go deeper into the group potential. This could explain the development of a more marked difference between the mean groupcentric distance of red and blue galaxies (see Fig. 12). After ∼3 Gyr, part of these infalling galaxies may reach the R  2R200 region, at z ∼ 0.4, mixing with virialized and backsplash objects, and thus presenting a less pronounced radial segregation between red and blue galaxies.


In order to determine the fundamental parameters of DM Ori, we take a similar approach to our V409 Tau study (Rodriguez et al. 2015), namely, to infer stellar parameters using stellar evolution isochrone models. However, unlike the V409 Tau analysis, we are very limited in the available data for DM Ori. We are only able to use the temperature of

 = 6740 ± 250 K determined from the fits to the SED, as well as the star’s B- and V-band magnitudes (See Table 1). The longer wavelength photometric data for DM Ori are not useful due to contamination at these wavelengths from the disk. Assuming DM Ori is associated with the OB1c or the Orion Nebula Cluster portion of the Orion association (Bally 2008) allows us to place priors on some of the parameters. We assume uniform priors for distance (250–550 pc), metallicity (

 dex), and age (0–6 Myr). We also assume an extinction of

 based on our best-fit SED. We use both the Dartmouth Stellar Evolution Models (Dotter et al. 2008) and the MIST stellar evolution models (Choi et al. 2016) combined with a Markov-Chain Monte Carlo (MCMC) to derive posterior distributions for the mass, age, radius, and distance of DM Ori (see Figure 4). From this analysis, we determine the most probable parameter values based on the posterior medians with errors from their 68% confidence interval uncertainties. For the Dartmouth models, we find a mass of

 M⊙, an age of

 Myr, a radius of

 R⊙, and a distance of

 pc. Similarly, for the MIST models, we find a mass of

 M⊙, an age of

 Myr, a radius of

 R⊙, and a distance of

 pc. Both sets of stellar evolution models produce consistent parameters for DM Ori, and the inferred age and distance are consistent with it being associated with the Orion star-forming region. To rule out the possibility that DM Ori is actually a foreground star in our line of sight to the Orion association, we reran our analysis with distance prior of 0–550 pc. Our results are very similar to the distribution shown in Figure 4, providing strong evidence that DM Ori is not a foreground star with a distance  250 pc.


For normal single AGNs, the bolometric luminosity,

, can usually be estimated from either optical or X-ray luminosities. However, for our targets, the hard X-ray luminosities are much lower than for single AGNs with the same [O iii] luminosities (Paper I). Three possible reasons are: (1) the observed X-rays are low due to high gas absorption (e.g., Bassani et al. 1999); (2) the X-rays are intrinsically weak due to a high accretion state that radiates little coronal emission (e.g., Desroches et al. 2009; Dong et al. 2012); (3) there are significant [O iii] luminosity excesses due to shocks in our galaxy mergers (e.g., Dopita & Sutherland 1995). The emission-line diagnostic ratios featuring [O iii]/Hβ and [N ii]/Hα show that our targets are well in the regime of Seyferts, with only one displaying relatively large uncertainty (Liu et al. 2010a). It is unlikely that the emission lines of our AGNs are mainly powered by shocks, as they do not lie in the region of LINERs on the diagnostic diagrams (Ho et al. 1993). It is more likely that our targets are highly obscured rather than in a high accretion state, since the estimated Eddington ratios (Table 4; see discussion below) are not close to unity. Additionally, our targets are all detected by the Wide-field Infrared Survey Explorer (Wright et al. 2010) with λLλ(12 μm) ∼ 1044 erg s−1. The X-ray–MIR ratios of our target binary AGNs (≲0.01) are much smaller than those of normal AGNs (∼0.3; Horst et al. 2008), indicating that the X-ray emission of the AGNs is absorbed and reprocessed into IR emission. As shown by Heckman et al. (2005) at low redshift, selection by narrow optical emission lines will recover most AGNs selected by hard X-rays (with the exception of BL Lac objects). On the other hand, selection by hard X-rays misses a significant fraction of the local AGN population with strong emission lines. In view of the uncertainties associated with X-ray absorption in gas-rich mergers, we estimate the bolometric luminosities of the binary AGNs from their extinction-corrected [O iii] luminosity (Paper I),
3

with intrinsic scatter 0.4 dex (see Trump et al. 2015 and references therein). The results are listed in Table 4. We adopt extinction-corrected rather than observed [O iii] luminosity (e.g., Stern & Laor 2012) to estimate the bolometric luminosity, since the former provides a smaller scatter.


The Stokes V profile of maser A+B from our 2009 observations (lower panel of Figures 2 and 3) reveals an S-shaped structure that is usually taken to be a detection of the Zeeman effect (also see the discussion in Section 4 below); so does the Stokes V profile from our 2017 observations (lower panel of Figures 4 and 5). No other compact maser spots in this field show any such feature. Whenever an S-shaped feature is observed in Stokes V, the magnetic field strength is usually determined by fitting a numerical frequency derivative of the Stokes I spectrum to the Stokes V spectrum; details are in, e.g., Momjian & Sarma (2017). The Stokes V profile is usually fit simultaneously to the derivative of the I profile and a scaled replica of the I profile itself via the equation (Troland & Heiles 1982; Sault et al. 1990)
1

The scaled replica of the I spectrum is included in the fit to account for small calibration errors in RCP versus LCP; for all results reported in this paper, a ≲ 10−3. The magnetic field values are contained in the fit parameter b, which is equal to z

, where z is the Zeeman splitting factor, and

 is the line-of-sight (LOS) magnetic field strength (assuming, of course, that the signature in Stokes V is due to the magnetic field in the region; see Section 4.2). We used the AIPS task ZEMAN (Greisen 2015) to carry out the fit in Equation (1). This task allows multiple Gaussian components in I to be fitted simultaneously to V, with each Gaussian component fitted for a different b, and hence a different LOS magnetic field strength. For the three Gaussian components of maser A+B from our 2009 observations (listed in Table 2, and shown in the upper panel of Figure 2), the derivative profiles scaled by the respective values fitted for b = z

 are each shown in the lower panel of Figure 2; the composite profile obtained by adding together these three scaled derivative profiles is shown in the lower panel of Figure 3. Of these three components for maser A+B from our 2009 observations, only component 2 showed a significant fit, with the fitted value given by z

 = 152 ± 12 Hz. Following customary practice in the field of Zeeman observations, we consider fits to be significant only if the ratio of fitted value to the fitted error is at the 3σ level or greater. Meanwhile, for the three Gaussian components of maser B from our 2017 observations (listed in Table 2, and shown in the upper panel of Figure 4), the derivative profiles scaled by the respective fitted values for

 are each shown in the lower panel of Figure 4, and the composite profile is shown in the lower panel of Figure 5. Only component 2 of maser B from our 2017 observations showed a significant fit, with the fitted value given by z

 = 149 ± 19 Hz. Since component 2 of maser A+B from our 2009 observations and component 2 of maser B from our 2017 observations are very likely the same maser spot (see Section 4.1), this is a remarkable coincidence in

 over observations taken eight years apart.


A number of semi-analytic models (SAMs) have attempted to reproduce submm number counts (e.g. Granato et al. 2000; Fontanot et al. 2007; Somerville et al. 2012). One such model is the galform (SAM), which has been tuned to successfully reproduce the number counts of 850 μm and $\mathrm{1.1 \, mm}$ selected galaxies.1 However, in order to achieve this good agreement galform invokes a top-heavy initial mass function (IMF). Early versions of the model used a flat IMF above $1 \, \mathrm{M_{\odot }}$, in sub-L* mergers (Baugh et al. 2005; Swinbank et al. 2008). This is required to produce sufficiently bright submm emission during frequent low-mass merger events. Later versions of the model used a more moderately top-heavy IMF in starbursts, triggered by disc instabilities rather than mergers, and found similarly good agreement with the number counts (Cowley et al. 2015, 2019; Lacey et al. 2016; Park et al. 2016). However, such IMF variability is still controversial, particularly extreme forms and any dependence on merger state (Bastian, Covey & Meyer 2010; Hopkins 2013; Krumholz 2014), and is inconsistent with the constraints on the IMF in massive star-forming galaxies that are significantly less extreme (e.g. Tacconi et al. 2008), though there is tentative evidence of a bottom-light/top-heavy IMF in both local star-forming region analogues (Motte et al. 2018; Schneider et al. 2018) and some gravitationally lensed high-redshift starbursts (Zhang et al. 2018). Safarzadeh, Lu & Hayward (2017) showed that a variable IMF is degenerate with a number of other modelling processes in SAMs, such as the form of stellar feedback. They highlight that taking in to account dust mass allows for a good fit to the number counts without resorting to a variable IMF. Most recently, the shark SAM (Lagos et al. 2018) is able to broadly reproduce the 850 μm counts (whilst slightly overestimating the bright-end counts compared to S2CLS; Geach et al. 2017) using a fixed Chabrier (2003) IMF (Lagos et al. 2019). They attribute the good agreement to their use of physically motivated attenuation curves obtained from a self-consistent galaxy evolution model (eagle; Trayford et al. 2020).


The fireball model remains the most popular scenario for the gamma-ray burst (GRB) phenomenon (Cavallo & Rees 1978; Goodman 1986; Paczynski 1986; Shemi & Piran 1990; Rees & Mészáros 1992, 1994; Mészáros & Rees 1993). In this model, the GRB central engine is a stellar-mass black hole or a rapidly spinning and highly magnetized neutron star formed by either the collapse of a supermassive star (collapsar; Woosley 1993; MacFadyen & Woosley 1999; Woosley & Heger 2006) or the merger of two compact objects (Paczynski 1986; Fryer et al. 1999; Rosswog 2003). In both cases, the original explosion creates a bipolar collimated jet composed mainly of photons, electrons, positrons, and a small fraction of baryons. The relativistic explosion ejecta within the jet are not homogeneous—they form multiple high density layers, which propagate at various velocities. When the fastest layers catch up with the slowest, the charged particles contained in the layers are accelerated through mildly relativistic collisionless shocks (internal shocks; Rees & Mészáros 1994; Kobayashi et al. 1997; Daigne & Mochkovitch 1998). The particles subsequently cool via emission processes such as synchrotron, Synchrotron Self Compton (SSC), and Inverse Compton (IC). The internal shock phase is usually associated with the so-called GRB prompt emission,17

17
See Pe’er (2015) for a recent review of GRB prompt emission.
 mainly observed in the keV−MeV energy range (see, e.g., the spectral catalogs by Gruber et al. 2014; von Kienlin et al. 2014) and usually lasting from a few ms up to several tens to hundreds of seconds. As the ejecta interact with the interstellar medium they slow down via relativistic collisionless shocks (external shocks; Rees & Mészáros 1992; Mészáros & Rees 1993), accelerating charged particles, which then emit non-thermal synchrotron photons. This external shock phase is usually associated with the so-called GRB afterglow emission observed at radio wavelengths up to X-rays and in some cases even up to the GeV regime hours after the prompt phase, and days and even years for the lowest frequencies. The detailed origin of the gamma-ray emission, however, is not fully understood and many theoretical difficulties remain, such as the composition of the jet, the energy dissipation mechanisms, as well as the radiation mechanisms (e.g., Zhang 2011).


The GALEX NUV observations span a wide wavelength range, from 1771 to 2831 Å. While these data provide no spectral information within that bandpass, we rely on solar and stellar flare studies to inform the likely contributors to the flare flux. The NUV spectral region has not had as many observational constraints as the far-UV region in flare studies. Few NUV stellar flare spectra exist at all, and the few that do were obtained either for solar flares or on nearby M dwarfs. Flares observed in the UV are often associated with the more impulsive phases of solar flares, starting with early observations showing a close temporal association between UV and hard X-ray emission (Cheng et al. 1981). Welsh et al. (2006) reported on high time-resolution NUV+FUV flares seen with GALEX on nearby M dwarfs, and Hawley et al. (2007) presented high spectral-resolution NUV flare measurements of an M-dwarf flare. From these two studies, the contribution of emission lines relative to continuum emission could be determined; the main emission lines in the flare NUV spectrum were Mg ii, Fe ii, Al iii, and C iii. However, the main emission component overall was a continuum component. Recent results from solar flares observed from space (Heinzel & Kleint 2014; Kleint et al. 2016) demonstrate an NUV spectrum originating largely from Hydrogen Balmer continuum emission. The formation of the NUV emission appears to originate from an impulsive thermal and nonthermal ionization caused by the precipitation of electron beams through the chromosphere. This explains the temporal correlation with solar flare hard X-ray emission observed previously. More recently, Kowalski et al. (2019) presented accurately calibrated NUV flare spectra at high time cadence on an M dwarf, again finding a large flux enhancement due to continuum radiation. They commented that the oft-used 9000 K blackbody used to describe blue-optical stellar flare emission (Hawley et al. 2003) under-predicts the NUV continuum flare flux by a factor of two. Based on general similarities in radiative properties between solar and stellar flares studied thus far (Osten 2016), it is likely that a combination of line and continuum emission enhancements are present in the NUV flare flux from the flares being considered, but we cannot speculate about the relative contribution of one versus the other. These sources originate from different layers of the stellar atmosphere: singly and doubly ionized emission lines likely originate in the chromosphere, and the Balmer continuum emission also originates from the chromosphere. Some lines, such as Mg ii, exhibit absorption components and self-reversals, indicating optical depth effects in the atmosphere, while other lines such as Fe ii appear to be optically thin. Any hot blackbody emission might originate further in the photosphere.


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


It is well known that giant molecular clouds (GMCs) are the major gas reservoirs for star formation (SF) and the sites where essentially all stars are born. Understanding the properties of GMCs is thus key to unravelling the interplay between gas and stars within galaxies. Early GMC studies were restricted to our own Milky Way (MW) and the late-type galaxies (LTGs) in our Galactic neighbourhood (e.g. Engargiola et al. 2003; Rosolowsky 2005, 2007; Rosolowsky et al. 2007; Gratier et al. 2012; Colombo et al. 2014; Wu, Sakamoto & Pan 2017; Faesi, Lada & Forbrich 2018), where GMCs have relatively uniform properties and generally follow the so-called Larson relations (between size, velocity dispersion, and luminosity; e.g. Blitz et al. 2007; Bolatto et al. 2008). However, more recent studies of other local galaxies have raised doubts on the universality of cloud properties. The cloud properties in some LTGs (such as M51 and NGC 253) vary with galactic environment and do not universally obey the usual scaling relations (e.g. Hughes et al. 2013; Leroy et al. 2015; Schruba, Kruijssen & Leroy 2019). The first study of individual GMCs in an early-type galaxy (ETG; NGC 4526) has also clearly shown that the clouds in that galaxy do not follow the usual size–linewidth correlation and tend to be more luminous, denser and to have larger velocity dispersions than the GMCs in the MW and other Local Group galaxies (Utomo et al. 2015). The differences in NGC 4526 may be due to a higher interstellar radiation field (and/or cloud extinctions), a different external pressure relative to each cloud’s self-gravity, and/or different galactic dynamics. GMCs in ETGs seem to have shorter orbital periods and be subjected to stronger shear/tidal forces, analogous to the highly dynamic environment in the MW central molecular zone (CMZ; e.g. Dale, Kruijssen & Longmore 2019; Henshaw et al. 2019; Kruijssen et al. 2019). Although we are entering an era of large surveys of GMC populations (e.g. Sun et al. 2018), current samples of ETGs are still very limited. More studies of GMCs in varied LTGs and ETGs are thus required to provide a comprehensive census of GMC properties across different galaxy environments.


The CO photodesorption yield reaches its highest value when this ice is deposited at low temperatures (down to 7 K, the lowest temperature studied experimentally) and decreases gradually at higher deposition temperatures (Öberg et al. 2007; Öberg et al. 2009; Muñoz Caro et al. 2010, 2016; Sie et al. 2022). The explanation for this phenomenon motivated further research. It was found that the columnar structure of CO ice samples, grown at incidence angles larger than 45°, increases the effective ice surface exposed to UV photons and therefore the photodesorption efficiency (González Díaz et al. 2019), but ice surface effects cannot account for the large variations observed in the photodesorption of CO ice samples deposited at different temperatures (Muñoz Caro et al. 2016). Absorption band shifts of CO ice in the UV and IR ranges only occurred at deposition temperatures above 20 K (Lasne et al. 2015; Muñoz Caro et al. 2016), suggesting that CO ice grown at lower temperatures is amorphous below 20 K in our experiments, and therefore, the decreasing photodesorption yield is not related to a transition from amorphous to crystalline ice, instead it might be associated to a different degree of molecular disorder in CO ice samples, depending on their deposition temperature. Photon energy transfer via Wannier-Mott excitons between the first photoexcited molecule in the ice and a molecule on the ice surface capable to desorb was proposed (Chen et al. 2017; McCoustra & Thrower 2018). Molecular disorder seems to enhance this energy transfer between neighbour molecules. The colour temperature variations measured at different deposition temperatures could also be the result of molecular disorder (Carrascosa et al. 2021). Urso et al. (2016), Cazaux et al. (2017), and Carrascosa et al. (2021) did not find significant changes in the desorption behaviour or the colour temperature of pure CO ice during controlled warm-up, which points to a low value of the diffusion in the ice. Finally, Sie et al. (2022) investigated the CO photodesorption yield dependence on ice thickness.


Since the discovery of the radio burst, there have been extensive follow-up observations of SGR J1935+2154 across the electromagnetic spectrum. The lack of another radio pulse coincident with an X-ray flare puts interesting constraints on the emission mechanism and begs the question of whether we should be able to see such radio bursts in other active Galactic magnetars. In this context, connecting FRBs with extragalactic magnetars is tantalizing. Current theories that propose FRB emission from a magnetar can be broadly divided into two categories: (1) far-away models, where the FRB is generated by a maser away from the neutron star, and (2) close-in models where the FRB is produced in the magnetospehere of the star. The maser emission model runs into difficulties when explaining all the observed radio and X-ray properties of the contemporaneous radio/X-ray burst seen from SGR J1935+2154 (see Lu, Kumar & Zhang 2020, for more details). Younes et al. (2020a) have shown that the X-ray burst contemporaneous with the radio burst was spectrally unique compared to all other burst in the activity period and it also supports it having a polar cap origin. Hence, if we assume that FRBs produced by magnetars are created in the magnetosphere close to the polar cap, we can expect them to be significantly beamed (Lu, Kumar & Zhang 2020). This of course also means that the source must still be exhibiting bursts infrequently in the radio and that more of them might be associated with an X-ray burst than we observe. Observational evidence so far does suggest a connection between the X-ray and the radio emission mechanisms prevalent in neutron stars and any changes in one of them affects the other (Archibald et al. 2017). It is believed that while the X-ray bursts and radio pulsations in these sources come from different regions in the magnetosphere, the pair plasma causing the X-ray flares can affect the acceleration of radio-emitting particles. This was shown in PSR J1119−6127, a high B-field radio pulsar where a series of X-ray bursts from the source quenched the radio pulsations with the radio emission returning a few minutes after the last X-ray burst (Archibald et al. 2017).


Sagittarius A* (Sgr A*) is a supermassive black hole system that allows one to observationally test the aforementioned GRMHD models of accretion flows (Goddi et al. 2017). Millimeter-Very Long Baseline Interferometry (mm-VLBI) is capable of resolving the shadow of the event horizon (Falcke et al. 2000), making this an ideal laboratory not only to tests Einstein’s General Theory of Relativity (GR) but also to investigate electron acceleration in the vicinity of a black hole. Most of the radiative models for Sgr A*, which are based on post-processing GRMHD simulations, assume that electrons have a thermal, relativistic (Maxwell–Jüttner) distribution function, and that the proton-to-electron temperature ratio is constant across the simulation domain (Goldston et al. 2005; Noble et al. 2007; Mościbrodzka et al. 2009; Dexter et al. 2010, 2012a; Shcherbakov et al. 2012). When the proton-to-electron temperature is constant, the disk dominates the images and spectra since most of the matter resides there. We have recently extended these radiative models by making the temperature ratios a function of the plasma β parameter, where

$\beta = \frac{P_{\textrm{gas}}}{P_{\textrm{B}}}$

β=

P

gas

P
B

 is the ratio of gas to magnetic pressures. In these extended models, the electrons are hotter in the more magnetized plasma, which is usually outflowing from the system. The reason for this is that the previously mentioned models do not recover the flat radio spectra. The β parameterization enforces that the disk emission is suppressed by significantly decreasing the temperature of the electrons in those regions. As a consequence of this, the jet will be the dominant source of emission. These modifications to the electron temperature model allowed us to recover some basic observational characteristics of Sgr A* (a roughly flat radio spectral slope and a size vs. wavelength relationship that is in agreement with observations) (Mościbrodzka & Falcke 2013; Mościbrodzka et al. 2014; Chan et al. 2015b,a; Gold et al. 2017). Our model for the electron temperatures as a function of the β plasma parameter is now roughly confirmed with extended-GRMHD simulations that self-consistently take into account the evolution of the electron temperatures (Ressler et al. 2015, 2017). Moreover, GRMHD simulations with the new electron temperatures can naturally explain the symbiosis of disks and jets observed in many accreting black hole systems (Falcke & Biermann 1995; Mościbrodzka et al. 2016a).


Among the existing IACT systems, HESS has the largest FoV and hence provides the highest sensitivity for the diffuse γ-ray flux. Its electron spectrum analysis technique could be directly used to obtain a measurement of the diffuse Galactic γ-ray flux above energies of several TeV in the Galactic Ridge (|l|  30°, |b|  2°) region; see Figs. 3 and 4. A multi-year exposure of HESS could be sufficient for detection of the diffuse emission even from regions of higher Galactic latitude. This is illustrated in Fig. 5, where thick blue and red data points show mild high-energy excesses of the electron spectra derived by Kraus (2018), Kerszberg et al. (2017), Kerszberg (2017) over broken power-law models derived from the fits to lower energy data. Comparing these excesses with the level of the IceCube astrophysical neutrino flux and with the Fermi/LAT diffuse sky flux from the region |b| > 7° (corresponding to the data selection criterium of HESS analysis Kerszberg et al. 2017; Kerszberg 2017) we find that the overall excess flux levels are comparable to expected diffuse γ-ray flux from the sky region covered by the HESS analysis (the quoted systematic error on the electron flux is Δlog(EFE) ≃ 0.4). The overall excesses within 805 and 1186 h of HESS exposures (Kraus 2018; Kerszberg 2017) are at the levels of >4σ for the analysis of Kraus (2018) and 1.7σ for the analysis of Kerszberg (2017). A factor-of-ten longer exposure (which is potentially already available with HESS) could reveal a higher significance excess at the level of up to 5σ. Such an excess is predicted in a range of theoretical models including interactions of cosmic rays injected by a nearby source (Andersen et al. 2018; Neronov et al. 2018; Bouyahiaoui et al. 2019) or decays of dark matter particles (Berezinsky et al. 1997; Feldstein et al. 2013; Esmaili & Serpico 2013; Neronov et al. 2018) or a large-scale cosmic ray halo around the Galaxy (Taylor et al. 2014; Blasi & Amato 2019).


Irregular refraction (scattering) of radio waves due to density turbulence in the solar corona broadens the angular size of the background “radio Sun” and the compact radio sources there at any given observing frequency. But the extent of broadening and the interferometer baselines required to image the solar atmosphere in detail at radio frequencies remain a puzzle, particularly at frequencies 100 MHz (Erickson 1964; Aubier et al. 1971; Riddle 1974; McMullin & Helfer 1977; Robinson 1983; Melrose & Dulk 1988; Subramanian & Sastry 1988; Thejappa & Kundu 1992, 1994; Sastry 1994; Schmahl et al. 1994; Ramesh & Sastry 2000; Ramesh 2000; Ramesh et al. 2001; Kathiravan et al. 2002; Bastian 2004; Subramanian 2004; Thejappa & MacDowall 2008). Past/present solar-dedicated radio imaging instruments in the above frequency range had/have limited angular resolution (>3′; Wild 1967; Labrum 1972; Kundu et al. 1983; Ramesh et al. 1998). Interestingly, observations carried out during different solar eclipses (similar to the lunar occulation technique) and the bandwidth, duration of some of the solar radio transients indicate that radiowave emitting sources with angular sizes ≲1′ are present/observable in the solar atmosphere from where radio emission at the above frequencies originate (Letfus et al. 1967; Melrose 1980; Benz & Wentzel 1981; McConnell 1983; Ramesh et al. 1999; Ramesh & Ebenezer 2001; Kathiravan et al. 2011; Ramesh et al. 2012). These are consistent with the theoretical predictions that solar radio sources of angular sizes ≲10″ and ≲30″ are observable at the typical frequencies of 327 MHz and 80 MHz, respectively (Riddle 1974; Subramanian & Cairns 2011). Encouraged by the above results and the availability of logistics support, we conducted interferometeric observations of the solar corona at frequencies 100 MHz on a ≈200 km long interferometer baseline for the first time, the description of which is the subject matter of this article.


For the NIR data set, we used standard IRAF11

11
IRAF is distributed by the National Optical Astronomy Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under cooperative agreement with the National Science Foundation.
 (Tody 1986, 1993) tools to correct the raw images for flat-field and to perform the sky subtraction. A master sky was obtained by combining five sky images of a relatively empty field. For the optical data set, instead, we used images processed, flat-fielded, bias subtracted, and corrected for Charge Transfer Efficiency losses by standard HST pipelines (_flc images). The WFC3 images have also been corrected by the Pixel Area Map using the files available on the HST website. For both NIR and optical data, the photometric reduction was carried out via point-spread function (PSF) fitting techniques in each chip of each image independently, by using DAOPHOTIV (Stetson 1987). The PSF has been modeled by selecting about 200 bright and isolated stars uniformly distributed in each chip, and by using the DAOPHOTIV/PSF routine. We allowed the PSF to vary within each chip following a cubic polynomial spatial variation. The best-fit PSF analytic models obtained for the HST F555W and F814W images, are a Moffat function with β = 1.5 (Moffat 1969) and a Penny function (Penny 1976), respectively. The typical PSF model for the GEMINI images is a Penny function, but in some cases it was necessary to adopt a Lorentz function (Melcher & Gerth 1977) as well. The PSF models thus obtained were then applied to all the star-like sources detected at a 3σ level above the local background by using ALLSTAR. We have derived in this way the stellar instrumental magnitudes. Then, starting from the star lists thus obtained and to fill the gaps among the GSAOI chips, we created a GEMINI master star list containing all the stars measured in at least three Ks images. For HST instead, the master list was made up of all the stars measured in at least four F814W observations. As done in previous works (e.g., Dalessandro et al. 2014 and references therein), the master lists thus created for the two data sets have been used as input for ALLFRAME (Stetson 1994). The files obtained as output have been independently combined to get a GEMINI catalog containing all the stars measured in at least three J and three Ks images and an HST catalog containing stars measured in at least four F555W and four F814W exposures. For every stellar source in each catalog, different magnitude estimates have been homogenized and their mean values and standard deviations have been adopted as the star magnitudes and photometric errors in the final catalog (Ferraro et al. 1991, 1992).


We simulated a laboratory impact experiment into a basaltic rock performed by Nakamura & Fujiwara (1991) to test the implementation of the damage model. In their experiment, a small 0.2 g nylon bullet impacts with an impact speed of 3200 m s-1 into a basaltic rocky sphere with a diameter of 6 cm. We chose to simulate an off-axis impact with an impact angle of 30 ◦ (see Fig. 9 for the definition of the impact angle), which corresponds to an impact parameter of 25% of the diameter. We modeled the basalt target with 523 741 particles and applied the Tillotson equation of state. Owing to the lack of parameters for nylon, we used lucite for the projectile material (values were taken from Benz & Asphaug 1994). The basalt target was modeled with the additional damage model and activation threshold strains were distributed following the Weibull distribution statistically as a preprocessing step (see Sect. 3.2 for a detailed description of the algorithm). Following Benz & Asphaug (1994), we performed several simulations with varying Weibull parameter pairs k and m. Figure 7 shows the damage pattern in the target after 50 μs for the simulation that matched the experimental outcome best. The damage in the region around the impact point is the largest and all particles close to the impact point were immediately damaged upon impact. The damage pattern is radially symmetric around the impact point. Another source of damage is found near the surface of the target. There, damage grows due to spallation stresses that occur when compressive waves get reflected at the free surface. As a result of this nature, the inner core of the target remains intact while the surface is coated with cracks. After 50 μs simulation time, the damage pattern in the target remains unchanged. We identified single fragments using a friend-of-friend algorithm in the following way: first, we removed all fully damaged particles. Then, we clustered all remaining particles that are closer than 1.01 of the original smoothing length to their neighboring particles. Fragments consisting of less than three particles were neglected. Figure 8 shows the fragment mass spectrum obtained with this friend-of-friend clustering algorithm.

Benz & Asphaug 1994
Benz & Asphaug (1994)


Interestingly, from ∼11:33:40 UT, the PAD of the suprathermal electrons changes to cigar type, in association with a dramatic drop of electron flux (Figure 2(a)). This change of electron PAD and flux is related to a magnetic dip structure that is manifested by a conspicuous decrease of the magnetic field strength (Figure 2(b)). In contrast to the magnetic field enhancement observed at ∼11:33:08 UT, the magnetic dip structure should arise from the local expansion of flux tubes, which are driven by the two opposite flows (see the shaded region in Figure 2(c)). The observed electron cigar distribution and the associated magnetic dip are a strong indication of the betatron cooling effect. This betatron-mediated cigar distribution has been suggested in previous studies (Fu et al. 2011b, 2012c, 2013b; Liu et al. 2017c) but never clearly observed. These observations, for the first time, show a direct link between the cigar distribution and betatron cooling. Note that in the trailing edge of the magnetic dip region, a magnetic hump structure, indicated by the sharp enhancement of magnetic field, is observed at ∼11:33:55 UT (Figure 2(b)). This magnetic hump, reminiscent of the Earthward-propagating dipolarization-front structure typically generated by magnetic reconnection in the midtail (Fu et al. 2012d, 2012e, 2013a, 2015, 2016, 2017; Liu et al. 2013, 2018a, 2018b, 2018c; Cao et al. 2017; Peng et al. 2017; Yao et al. 2017; Chen et al. 2018), was possibly formed due to the local contraction of flux tubes driven by the ion flow with an increasing velocity in the Earthward direction (Figure 2(c)). Associated with this magnetic hump, a very weak pancake distribution of suprathermal electrons is observed (Figure 2(a)), and strong waves near the electron gyrofrequency are also observed (Figures 2(e) and (f)). These waves are whistler-mode; they indicate that the betatron acceleration inside the magnetic hump was accompanied by non-adiabatic effects (Fu et al. 2009, 2010a, 2010b, 2012a, 2012b) and is still ongoing (Fu et al. 2011a; Khotyaintsev et al. 2011; Wang et al. 2017; Yang et al. 2017).