adsabs/FOCAL huggingface dataset:
The comparison between Ulysses and Pamela overlapping measurements revealed that the proton flux in the rigidity interval 1.6–1.8 GV (0.92–1.09 GeV, corresponding approximately to the median energy of the GCR spectrum at solar minimum) has a radial intensity variation of 2.7 ± 0.2% AU−1, and a latitudinal gradient of −0.024 ± 0.005% degree−1 (De Simone et al. 2011). Positive (negative) latitudinal gradients are observed during positive (negative) polarity periods. In addition, Experiment 6 (E6) on board Helios-A and Helios-B provided ion data from four to several hundreds of MeV n−1 (Winkler 1976; Marquardt & Heber 2019). The Helios-A and Helios-B S/C were launched on December 10, 1974 and January 15, 1976 during a positive polarity epoch and were sent into ecliptic orbits of 190-day and 185-day periods around the Sun. The orbits perihelia were 0.3095 AU and 0.290 AU, respectively. The aphelia were approximately 1 AU. As a result, the Helios data are representative of the cosmic-ray bulk variations that are to be experienced by Solar Orbiter, which will also reach maximum distances from the Sun of about 1 AU. In the recent paper by Marquardt & Heber (2019), the Helios proton data radial gradients of the GCR flux were found to be 6.6 ± 4% above 50 MeV and 2 ± 2.5% between 250 and 700 MeV between 0.4 and 1 AU. These results are in agreement with those from Pamela/Ulysses (within the statistical and systematic errors). In conclusion, variations in the GCR proton-dominated flux along the Solar Orbiter orbit are expected to be of a few % at most; consequently, it is plausible to assume that models for cosmic-ray modulation developed on the basis of observations gathered near Earth will also apply to Solar Orbiter. On the other hand, the Metis data will allow us to verify this assumption in the unexplored region of tens of degrees above the solar equator. Analogously, even though no SEP data were gathered up to present time, it is likely that a study of the evolution of SEP events near the Sun above the solar equator will be possible for the first time also with Metis, in addition to the dedicated instruments flown on board Solar Orbiter.
Citation: Marquardt & Heber (2019)
Citation function: Similarities; Similarities
Radio astronomy is recognized as one of the most effective techniques to search for interstellar molecules. By comparing the spectra of candidate molecules in the laboratory with the spectra observed in astronomical surveys, we can determine whether these molecules exist in interstellar space. Therefore, it is necessary to provide rotational spectra of candidates for astronomical detection. Radio astronomy has helped to detect several sulfur-containing molecules in the ISM in recent years: in particular, thiols, the sulfur analogs of alcohols. Methanethiol (or methyl mercaptan, CH3SH) was detected in the Sagittarius B2 (Sgr B2) region of the center of our Galaxy (Linke et al. 1979; Gibb et al. 2000; Müller et al. 2016; Rodríguez-Almeida et al. 2021) and in the protostar IRAS 16293-2422 (Majumdar et al. 2016). Two groups reported to have detected several signs of ethanethiol (C2H5SH) in Sgr B2 (Müller et al. 2016) and Orion (Kolesniková et al. 2014). Most recently, Rodriguez-Almeida reported the first unambiguous detection of ethanethiol in the ISM, toward the G+0.603-0.027 molecular cloud (Rodríguez-Almeida et al. 2021). Moreover, several sulfur-containing species have been observed in comets (Altwegg et al. 2017). Some recent efforts, both from spectroscopy and astronomical searches, to detect S-stitutes of other classes of compounds have also been reported. For instance, thioformic acid (HC(O)SH) was very recently detected in G+0.693–0.027. Its trans-isomer has an abundance of ~1 × 10–10 (Rodríguez-Almeida et al. 2021). Conversely, thioformamide (NH2CHS), the counterpart of for-mamide (NH2CHO), was characterized in the laboratory up to 660 GHz, and its transitions were searched for toward the hot cores Sgr B2(N1S) and Sgr B2(N2), but it was not detected (Motiyenko et al. 2020). The rotational spectrum of thioac-etamide was recently analyzed in the 59.6–110.0 GHz frequency region (5.03–2.72 mm). Its emission was searched for in regions associated with star formation using the IRAM 30 m ASAI observations toward the prestellar core L1544 and the outflow shock L1157–B1. The molecule was not detected, but the study allowed placing constraints on the thioacetamide abundances (Maris et al. 2019; Remijan et al. 2022).
Citation: Rodríguez-Almeida et al. 2021
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Citation: Rodríguez-Almeida et al. 2021
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Citation: Rodríguez-Almeida et al. 2021
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Magnetic fields observed in various astrophysical systems, such as the Earth, the Sun, disk galaxies, accretion disks, etc., possess large-scale magnetic fields in addition to a fluctuating component. The magnetic field survives for timescales much larger than the diffusion timescales in those systems, and therefore are thought to be self-sustained by turbulent dynamo action. The standard model of such a turbulent dynamo producing a large-scale magnetic field involves the amplification of seed magnetic fields due to the usual α effect, where α is a measure of the net kinetic helicity in the flow (see, e.g., Moffatt 1978; Parker 1979; Krause & Rädler 1980; Brandenburg & Subramanian 2005; Brandenburg et al. 2012). Since it is not necessary for the turbulent flow always to be helical, it is interesting to study the dynamo action in non-helically forced shear flows. Dynamo action due to shear and turbulence in the absence of the α effect received some attention in the astrophysical contexts of accretion disks (Vishniac & Brandenburg 1997) and galactic disks (Blackman 1998; Sur & Subramanian 2009). The presence of large-scale shear in turbulent flows is expected to have significant effects on transport properties (Rädler & Stepanov 2006; Rüdiger & Kitchatinov 2006; Leprovost & Kim 2009; Sridhar & Singh 2010; Singh & Sridhar 2011). It has also been demonstrated that the mean shear in conjunction with rotating turbulent convection gives rise to the growth of large-scale magnetic fields (Käpylä et al. 2008; Hughes & Proctor 2009). The problem we are interested in may be stated as follows: in the absence of the α effect, will it be possible to generate a large-scale magnetic field solely through the action of non-helical turbulence in the background shear flow on the seed magnetic field? This question was recently numerically studied by Brandenburg et al. (2008), Yousef et al. (2008a, 2008b). These works clearly demonstrated the growth of large-scale magnetic fields due to non-helical stirring at small scales in the background linear shear flow.
Citation: Moffatt 1978
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Moreover, if mixing is effective over kiloparsec scales, then we would expect the neutral gas observed toward the QSO and the ionized gas seen toward the central H ii region to have the same metallicity. In which case, in order to find 





  





, a significant fraction of the neutral gas must be many kiloparsecs away from the star-forming regions in order to not be contaminated. Such an explanation was adopted by Cannon et al. (2005), who postulated the existence of a low-metallicity halo beyond the inner ISM to explain the discrepancy between 





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 toward star-forming regions in NGC 625. Our results are consistent with this idea and provide additional evidence for IGM gas feeding into galaxies through streams from the cosmic web (e.g., Sánchez Almeida et al. 2014a, and references therein). Dwarf galaxy pairs in particular are thought to have enhanced star formation because they are fed by significant reservoirs of neutral gas in which they reside, or because of their mutual interactions (Lelli et al. 2014; Stierwalt et al. 2015; Pearson et al. 2016). As noted in Section 2.4, UGC 5282 does lie near a galaxy of similar mass (UGC 5287 in Figure 3) and interactions between the two galaxies may be the source of gas flowing into UGC 5282. For example, Pearson et al. (2018) have suggested that multiple encounters between dwarf galaxies can “park” gas at significant distances from the protagonists, which can then return over several Gyr. It remains unknown whether the metallicity of such returning debris would be low enough to cause the decrease in metallicity in either UGC 5282 or UGC 5287, but it may reflect whatever buildup of metals occurred in the dwarfs at much earlier times. Alternative tidal models that cause strong metallicity gradients and the removal of low-metallicity gas at the edges of dwarf galaxies (Williamson et al. 2016) seem less well supported by our results. Indeed, the situation for UGC 5282 may be even more complicated, depending on whether it has entered the halo of NGC 3003 (Figure 3) and has begun to feel any effects from ram pressure stripping by gas in the host’s halo. The effects on the metallicity of the dwarf galaxy may, however, be less significant than any effects from tidal stripping (Williamson & Martel 2018).
Citation: Sánchez Almeida et al. 2014a
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Similarly to the [α/Fe] ratio, the ratio of the slow (s-) neutron capture process elements to iron can be regarded as a cosmic clock. Ba, Sr, La, and Y are mainly s-process elements produced on long timescales by low mass AGB stars (Matteucci 2012). Since a low mass star must evolve to the AGB phase before the s-process can occur, the s-process elements are characterized by a delay in the production, much like the delay of iron production by SNe Ia relative to the α elements production by core collapse SNe. Among the four s-process elements mentioned above, GES provides the abundances of Y II (the first s-process peak element) and Ba II (the second s-process peak element) for all our sample stars. Their abundances behave differently in the Galactic thick and thin discs (Bensby et al. 2005, 2014; Israelian et al. 2014; Bisterzo et al. 2017; Delgado Mena et al. 2017). Unlike the Galactic thick disc stars, which show an almost constant [Ba/Fe] abundance close to the solar value, the Galactic thin disc stars have their [Ba/Fe] abundances increasing with [Fe/H] and reaching their maximum values around solar metallicity, after which a clear decline is seen (see also Cristallo et al. 2015a,b, for the most recent s-process calculation in AGB yields). The same trend is observed in our sample. In Fig. 13 we display the Li-[Ba/Fe], [Ba/Fe] as a function of [Fe/H], and the evolution of absolute Ba abundance A(Ba), as derived from Ba II lines. Similar figures are also plotted for yttrium (Y II). [Ba/Fe] and [Y/Fe] values here are derived from MCMC simulations, taking into account the measurement uncertainties of A(Ba II)/A(Y II) and [Fe/H]. By applying the same MCMC setups used for [α/Fe] (see Sect. 3.1), we calculate the mean values of [Ba/Fe] and [Y/Fe] for each star. These values, together with their corresponding 1σ uncertainties, are listed in Table 1. In the literature there are several theoretical works on the evolution of [Ba/Fe] and [Y/Fe] in the Galactic thin disc (e.g. Pagel & Tautvaisiene 1997; Travaglio et al. 1999, 2004; Cescutti et al. 2006; Maiorca et al. 2012; Bisterzo et al. 2017). For comparison, we show in Fig. 13 the predictions of the most recent one (Bisterzo et al. 2017) where the updated nuclear reaction network was used.
Citation: Bisterzo et al. 2017
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Citation: Bisterzo et al. 2017
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Citation: Bisterzo et al. 2017
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In this paper we extend previous work based on cosmological simulations by analysing the general magnetic field properties and the diffuse radio halo emission in galaxy clusters in the IllustrisTNG project, a set of cosmological magnetohydrodynamics simulations run with the moving-mesh code arepo (Springel 2010) that include a comprehensive module for galaxy formation physics. The main and novel aspect of our work is the analysis of the diffuse radio emission resulting from radio haloes in galaxy clusters (Feretti & Giovannini 1996; Murgia et al. 2009; Vacca et al. 2011; Feretti et al. 2012). We investigate radio emission from clusters by a detailed comparison with observations, trying to match the current observational constraints and to make predictions for the upcoming radio surveys that will be performed with the new generation of radio instruments such as SKA and LOFAR. The analysis of simulated radio haloes gives us a complementary view on the spatial extent and energy content of magnetic fields in galaxy clusters, since the radio emission is proportional to their strength. As such, the study of radio halo scaling relations (Giovannini et al. 2009; Cassano et al. 2013; Zandanel, Pfrommer & Prada 2014) with the total X-ray power and halo mass may yield important information about the amplification mechanisms of magnetic fields in clusters and the level of turbulence in the ICM. The modelling of radio emission makes it also possible to study the transport of charged particles and their re-acceleration to relativistic speeds, and it constrains the probability of detecting extended radio-emitting structures in a statistical sample of realistic simulated clusters. The comparison of the simulated radio emission with actual observations might also be employed as a useful check for the implementation of the galaxy formation physics modules used to perform the simulations, although our modelling of relativistic particles is rather preliminary and might have a non-negligible impact on the results.
Citation: Murgia et al. 2009
Citation function: Extends
These observations have identified a large reservoir of baryons surrounding galaxies. This circumgalactic gas extends to roughly the virial radius (Shull 2014) and contains a substantial fraction of the baryons (Werk et al. 2014; Bregman et al. 2018) and metals (Peeples et al. 2014) associated with the dark matter halo. The larger column densities of the O+5 ion in the CGM of star-forming galaxies compared to passive galaxies (Tumlinson et al. 2011) has generated great interest in the CGM, because the processes producing this dichotomy may explain why star formation is quenched in massive halos (Blanton et al. 2003; Kauffmann et al. 2003; Schawinski et al. 2014). In cosmological hydrodynamical simulations, the O vi absorbing gas lies behind the halo accretion shock and is maximal in L* galaxies because their virial temperature is close to the temperature T ≈ 105.5 K where the O+5 ionization fraction peaks (Oppenheimer et al. 2016). Feedback from supermassive black holes may suppress the O+5 fraction in the halos of red galaxies relative to the halos of blue galaxies of similar stellar mass (Nelson et al. 2018). The nucleus would not typically still be active by the time its outflow impacted the gas properties at half the virial radius, so differentiating between nuclear activity and halo mass is challenging observationally (Berg et al. 2018). Simulations that zoom in on individual galaxies include more physics than cosmological simulations (Hummels et al. 2013; Su et al. 2018). They qualitatively agree that enhanced star formation feedback increases the strength of high-ionization absorption lines, as Heckman et al. (2017) observed. Quantitatively, however, the star formation feedback does not produce enough O vi absorption, nor does it permanently quench star formation. A solution may require a completely different schema for the CGM. Stern et al. (2018) argue, for example, that the O vi absorption occurs beyond the accretion shock, where O vi would be photoionized by the UV background, a low-pressure scenario.
Citation: Oppenheimer et al. 2016
Citation function: Uses
Ikarashi et al. (2015) discussed that if both the radio and FIR continuum are tracers of star-forming regions, then the z ≳ 3 SMGs are more compact than the lower-redshift SMGs typically observed in radio continuum emission (e.g. Biggs & Ivison 2008). As shown in Fig. 7, our present VLA 3 GHz data do not suggest such a trend, and, as mentioned earlier, there is actually a hint of larger radio sizes at z ~ 2.5–5 compared to lower redshifts. However, the highest-redshift SMG in our sample, AzTEC3 at z ≃ 5.3, shows the most compact size among our sources, consistent with the rest-frame FIR sizes from Ikarashi et al. (2015). We note that Capak et al. (2011) found that AzTEC3 belongs to a spectroscopically confirmed protocluster containing eight galaxies within a 1 arcmin2 area, and therefore the environment might also play a role in the galaxy size evolution (see also Smolčić et al. 2015b). However, it is currently unclear whether the environmental effects in a galaxy overdensity will lead to a more compact or more extended radio-emitting size than field galaxies. On one side, a protocluster environment is expected to show an elevated merger rate (e.g. Hine et al. 2015), and, as discussed above, mergers are expected to pull the galactic magnetic fields to larger spatial scales, and hence lead to a more extended radio synchrotron emission. On the other side, the ram and/or thermal pressures of the intracluster medium could compress the ISM of the galaxy, increase the magnetic field strength, and hence cause an excess in radio emission (consistent with a low IR-radio q parameter of ≲2 for AzTEC3; Miettinen et al., in prep.). The aforementioned pressure forces can drive shock waves into the ISM, and hence accelerate the CR particles (Murphy 2009). Consequently, the cooling time and diffusion length-scale of CR electrons can decrease (see Appendix E), resulting in a compact radio-emitting area. More detailed environmental analysis of SMGs is needed to understand this further.
Citation: Smolčić et al. 2015b
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Among the main proposed formation channels for merging binary COs, we find: pairing of primordial BHs (e.g. Carr & Hawking 1974; Bird et al. 2016; Carr et al. 2016; Scelfo et al. 2018; De Luca et al. 2021); isolated binary evolution via common envelope (e.g. Tutukov & Yungelson 1973; Bethe & Brown 1998; Portegies Zwart & Yungelson 1998; Belczynski, Kalogera & Bulik 2002; Belczynski et al. 2008; Dominik et al. 2013; Belczynski et al. 2016; Eldridge & Stanway 2016; Mapelli et al. 2017; Stevenson, Berry & Mandel 2017; Ablimit & Maeda 2018; Klencki et al. 2018; Kruckow et al. 2018; Mapelli & Giacobbo 2018; Eldridge, Stanway & Tang 2019; Mapelli et al. 2019; Neijssel et al. 2019; Spera et al. 2019), via stable mass transfer (e.g. Kinugawa et al. 2014; Inayoshi et al. 2017; van den Heuvel, Portegies Zwart & de Mink 2017; Kinugawa, Nakamura & Nakano 2020; Tanikawa et al. 2021a,b), or via chemically homogeneous mixing (e.g. de Mink & Mandel 2016; Mandel & de Mink 2016; Marchant et al. 2016; du Buisson et al. 2020); dynamical perturbations in the field (Michaely & Perets 2019, 2020); dynamical formation in young star clusters (YSCs, e.g. Banerjee, Baumgardt & Kroupa 2010; Ziosi et al. 2014; Mapelli 2016; Askar et al. 2017; Banerjee 2017; Banerjee 2018; Rastello et al. 2018; Di Carlo et al. 2019, 2020a,b; Kumamoto, Fujii & Tanikawa 2019, 2020; Rastello et al. 2020; Banerjee 2021; Rastello et al. 2021; Trani et al. 2021); globular clusters (GCs, e.g. Portegies Zwart & McMillan 2000; Downing et al. 2010; Tanikawa 2013; Samsing, MacLeod & Ramirez-Ruiz 2014; Rodriguez et al. 2015; Rodriguez, Chatterjee & Rasio 2016; Rodriguez & Antonini 2018; Samsing, Askar & Giersz 2018; Zevin et al. 2019; Antonini & Gieles 2020); nuclear star clusters (NSCs, e.g. Miller & Lauburg 2009; O’Leary, Kocsis & Loeb 2009; Antonini & Perets 2012; Prodan, Antonini & Perets 2015; Antonini & Rasio 2016; Petrovich & Antonini 2017; Arca-Sedda & Gualandris 2018; Gondán et al. 2018; Arca-Sedda & Capuzzo-Dolcetta 2019; Rasskazov & Kocsis 2019; Arca Sedda 2020; Arca Sedda et al. 2020); and AGN discs (e.g. McKernan et al. 2012; Bartos et al. 2017; Stone, Küpper & Ostriker 2017; McKernan et al. 2018; Yang et al. 2019; Tagawa, Haiman & Kocsis 2020).
Citation: Tanikawa et al. 2021a
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As the H ii regions S235 A and S235 C are deeply embedded in the molecular cloud, we cannot use published predictions from standard plane-parallel PDR models without foreground absorption (e.g. Kaufman et al. 1999). In order to understand how the observational view by SOFIA is matched by a ’classical’ model of expanding H ii regions, described analytically and numerically by Spitzer (1978), Elmegreen & Lada (1977), Hosokawa & Inutsuka (2006), Raga et al. (2012), Kirsanova et al. (2009), and Bisbas et al. (2015), we make simulations with the MARION model (Kirsanova et al. 2009; Akimkin et al. 2015). The gas-phase chemical network from Röllig et al. (2007) (mainly based on the UMIST99 ratefile; Le Teuff, Millar & Markwick 2000) allows us to reproduce the C+, CO, and HCO+ abundances in PDRs (see Kirsanova & Wiebe 2019), so we use this network together with the ionization of the atomic species and corresponding recombinations in the H ii regions. The cross-sections for most of photoreactions are taken from the Leiden data base of ‘Photodissociation and photoionization of astrophysically relevant molecules’ (Heays, Bosman & van Dishoeck 2017). We implement the formation of H2 on grain surfaces and accretion and desorption processes of other neutral species, but other chemical reactions on dust surfaces are not considered in the calculations to save computation time. The rates of accretion and desorption processes are based on the work by Hasegawa & Herbst (1993), with updated desorption energies from Garrod, Wakelam & Herbst (2007). We use the ‘high-metallicity’ initial elemental abundances based on the ‘EA2’ set from Wakelam & Herbst (2008). The initial conditions are cold, molecular, and solid. This means that we start with all carbon and oxygen in CO and H2O on dust surfaces. Fifty two chemical species are included: H, H+, H2, H$_2^+$, H$_3^+$, O, O+, O++, OH+, OH, O2, O2:d, O$_2^+$, H2O, H2O+, H3O+, C, C+, C++, CH, CH+, CH2, CH$_2^+$, CH3, CH$_3^+$, CH4, CH$_4^+$, CH$_5^+$, CO, CO:d, CO+, HCO+, He, He+, S, S+, S++, Si, Si+, H:d, H2:d, O:d, OH:d, H2O:d, C:d, CH:d, CH2:d, CH3:d, CH4:d, S:d, Si:d, and e−, where the postfix ‘:d’ indicates species on dust grain ices. Chemical species containing Si and S are included only to obtain correct gas temperature in ionized region. We recognize that the chemical network is far from complete, but our choise was motivated by limited computation time. The heating and cooling processes included in the model are listed in Akimkin et al. (2015) and Kirsanova & Wiebe (2019).
Citation: Le Teuff, Millar & Markwick 2000
Citation function: Uses; Uses; Uses