adsabs/FOCAL huggingface dataset:
Characterizing the differential rotation (DR) realized at the base and in the convective envelope of solar-type stars is central to the understanding of their magnetic field generation, activity level, and rotation, as it is directly linked to the Ω effect (e.g., stretching of the poloidal magnetic field lines by large-scale shear). Hence, the role of DR in driving the star’s magnetic activity level and field properties should be clarified (Donahue et al. 1996). Doppler imaging (Donati & Collier Cameron 1997; Barnes et al. 2005), asteroseismology (Gizon & Solanki 2004; Reinhold et al. 2013; García et al. 2014), classical spot models (Lanza et al. 2014), and short-term Fourier transform (Vida et al. 2014) are methods to infer DR. The combination of all these observations on stellar rotation and magnetism helps constrain the trends linking rotation with stellar DR and magnetic activity. Various analyses of stellar DR revealed different dependencies between DR and star’s rotation (ΔΩ ∝ Ω
n
), with n varying between 0.15 and 0.7 (Barnes et al. 2005; Reiners 2006; Reinhold et al. 2013). There is no clear consensus in the community for now; some authors are even advocating that such laws should be derived per spectral stellar classes and that the confusion comes from mixing together F and K stars (Balona & Abedigamba 2016). Saar (2011), Brandenburg & Giampapa (2018) also propose that the dependency of the DR with the rotation rate may not be monotonic, with a break near Rossby equals unity. By contrast, a more systematic and stronger dependency is observed with the star’s temperature (



ΔΩ∝Teff8.92

, Barnes et al. 2005, Reinhold et al. 2013; and 



ΔΩ∝Teff8.6

, Collier Cameron 2007). Hence, we expect large-scale shear to vary both in amplitude and profile (as a function of latitude and depth) as the global stellar parameters change. Some recent studies have confirmed this is happening in solar-type stars by inverting seismically their profile (Benomar et al. 2018), pointing to a possible antisolar DR state (e.g., slow equator/fast poles), which was possibly already guessed in F stars (Reiners 2007) and advocated to exist in numerical simulations (Matt et al. 2011; Gastine et al. 2014; Brun et al. 2015, see below).
Citation: Vida et al. 2014
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ALMA is capable of resolving internal structures of molecular clouds even in external galaxies. In particular, the Large Magellanic Cloud (LMC) is an ideal laboratory to investigate high-mass star formation thanks to its nearly face-on view (Balbinot et al. 2015) and the close distance, ∼50 kpc (Schaefer 2008; de Grijs et al. 2014). It is also a great advantage to directly compare the distributions of molecular gas observed by ALMA and positions of massive YSOs identified by Spitzer and Herschel (e.g., Gruendl & Chu 2009; Chen et al. 2010; Seale et al. 2014) without any serious contamination in the line of sight. Earlier studies using the H i gas observations by Fukui et al. (2017) found that there are supergiant shells (Kim et al. 1999, 2003) and kiloparsec-scale gas flows caused by the last tidal interaction between the LMC and the Small Magellanic Cloud (SMC). Therefore, we may be able to examine the relation between such large-scale gas kinematics and the local star formation activities. Our present target in this paper is the N159W-South clump, which was discovered by our previous ALMA Cycle 1 observations (Fukui et al. 2015, hereafter Paper I) with an angular resolution of ∼1″ (∼0.24 pc) toward a GMC in the N159W region (e.g., Johansson et al. 1998; Minamidani et al. 2008, 2011). Paper I revealed that the GMC is composed of many filamentary molecular clouds and discovered the first example of protostellar outflows in the external galaxies. Paper I also found that the protostellar source with a stellar mass of ∼37 M⊙ in the N159W-South clump is located toward an intersection of two filaments and suggested that the filament–filament collision triggered the protostar formation. Although the ALMA observations significantly improved our understanding of molecular cloud structures and star formation in this object, much higher-angular-resolution studies are needed to further resolve the filamentary structures down to a width of ≲0.1 pc (see, Arzoumanian et al. 2011, 2019) and investigate the star formation activities therein.
Citation: Gruendl & Chu 2009
Citation function: Compare/Contrast; Compare/Contrast
We derived the photospheric stellar parameters using three different techniques: the curve-of-growth approach, spectral synthesis match, and empirical calibration. The first method minimizes the trend of iron abundances (obtained from the equivalent width, EW, of each line) with respect to excitation potential and reduced EW respectively, to obtain the effective temperature and the microturbulent velocity, ξt. The gravity log g is obtained by imposing the same average abundance from neutral and ionized iron lines. We obtained the EW measurements using ARESv2
 5 (Sousa et al. 2015). We used the local thermodynamic equilibrium (LTE) code MOOG
 6 (Sneden 1973) for the line analysis, together with the ATLAS9 grid of stellar model atmosphere from Castelli & Kurucz (2003). The whole procedure is described in more detail in Sousa (2014). We performed the analysis on a co-added spectrum (SNR > 600), and after applying the gravity correction from Mortier et al. (2014) and adding systematic errors in quadrature (Sousa et al. 2011), we obtained Teff = 5346 ± 69 K, log g =4.60 ± 0.12, [Fe/H] =−0.40 ± 0.05, and ξt =0.78 ± 0.08 km s−1. The spectral synthesis match was performed using the Stellar Parameters Classification tool (SPC, Buchhave et al. 2012, 2014). It determines effective temperature, surface gravity, metallicity, and line broadening by performing a cross-correlation of the observed spectra with a library of synthetic spectra, and interpolating the correlation peaks to determine the best-matching parameters. For technical reasons, we ran the SPC on the 62 GTO spectra only7: the SNR is so high that the spectra are anyway dominated by systematic errors, and including the A40TAC_23 spectra would not change the results. We averaged the values measured for each exposure, and we obtained Teff =5389 ± 50 K, log g =4.49 ± 0.10, [M/H] = −0.36 ± 0.08, and v sin i  2 km s−1. We finally used CCFpams,8 a method based on the empirical calibration of temperature, metallicity, and gravity on several CCFs obtained with subsets of stellar lines with different sensitivity to temperature (Malavolta et al. 2017b). We obtained Teff = 5293 ± 70 K, log g =4.50 ± 0.15, and [Fe/H] = −0.40 ± 0.05, after applying the same gravity and systematic corrections as for the EW analysis. We list the final spectroscopic adopted values, i. e. the weighted averages of the three methods, in Table 3. From the co-added HARPS-N spectrum, we also derived the chemical abundances for several refractory elements (Na, Mg, Si, Ca, Ti, Cr, Ni). We used the ARES + MOOG method assuming LTE, as described earlier. The reference for solar values was taken from Asplund et al. (2009), and all values in Table 3 are given relative to the Sun. Details on the method and line lists are described in Adibekyan et al. (2012) and Mortier et al. (2013). This analysis shows that this iron-poor star is alpha-enhanced. Using the average abundances of magnesium, silicon, and titanium to represent the alpha-elements and the iron abundance from the ARES + MOOG method (for consistency), we find that [α/Fe] = 0.23.
Citation: Buchhave et al. 2012
Citation function: Uses; Uses
On the other hand, the distribution of the orbital inclination of the third companion with respect to the inner binary in the triple i3 (bottom panel) is found to peak at ∼100°, but with non-negligible tails. For comparison, isolated triples that merge due to the KL mechanism show a very pronounced peak at ∼90°, with only a few mergers happening in low-inclination systems (Antonini et al. 2017). There are two possible caveats to this. First, possible resonances between nodal precession and KL oscillations can arise. As shown in Hamers & Lai (2017), this could make even low-inclination systems merge. Secondly, there are three different KL mechanisms competing, thus the eccentricity of the inner binary of the CO triple can be pumped up by the torque either of the SMBH or the third companion in the CO triple, for which the KL time-scale is shorter (e.g. Hamers et al. 2015). We define the following ratios
(18)
\begin{eqnarray*}
\mathcal {R}_{12M}=\frac{T_{KL}^{123}}{T_{KL}^{12M}}
\end{eqnarray*}
(19)
\begin{eqnarray*}
\mathcal {R}_{123M}=\frac{T_{KL}^{123}}{T_{KL}^{123M}}
\end{eqnarray*}
(20)
\begin{eqnarray*}
\mathcal {R}_{M}=\frac{T_{KL}^{123M}}{T_{KL}^{12M}}\ ,
\end{eqnarray*}
which we plot in Fig. 4 for the BH–BH binaries that merge in our simulations in Models MW, α = 2, a3, max = 50 au and different values of β. Clearly, the shape of the three distributions does not depend on the assumed value of β, and we find that $\mathcal {R}_{12M}$, $\mathcal {R}_{123M}$, and $\mathcal {R}_{M}$ peak at ∼10−4, ∼5 × 10−3, and ∼10−1, respectively. We note that, however, KL cycles in a given CO triple may be inactive if the relative inclinations are not in the KL window. As a consequence, the initial dynamical evolution of the CO triple can ultimately be dictated by a KL cycle that takes place on a long time-scale. The latter can in turn excite the relative inclination of one of the other orbits, which could activate KL cycles that take place on a shorter time-scale. Thus, the CO triple may experience rather different and rich dynamical paths, which tend to lead to chaotic behaviour (Grishin et al. 2018).
Citation: Hamers et al. 2015
Citation function: Uses
Accretion physics has been extensively studied for decades, particularly in terms of the theoretical aspects including semi-analytic investigations as well as global numerical simulations, in an effort to further understand its physical nature and observational consequences. Many of the works on BH accretion have, in general, revealed an important generic feature of accretion, i.e., the formation of shocks as an accreting plasma is subject to outward forces via a number of decelerating mechanisms (e.g., Abramowicz & Prasanna 1990) and develops a shock front at r = rsh within the radius of the inner edge of a magnetized accretion disk7

7
Armitage et al. (2001) found an ISCO-like edge in their pseudo-Newtonian MHD accretion simulations.
, perhaps equivalent to an innermost stable circular orbit (ISCO) for a pure HD Keplerian disk, before crossing an event horizon at r = rH. Previous studies include hydrodynamic shocks (e.g., Nobuta & Hanawa 1994; Lu et al. 1997; Chakrabarti 1990; Fukumura & Tsuruta 2004) and magnetohydrodynamic (MHD) shocks (e.g., Koide et al. 1998, 2000; Das & Chakrabarti 2007; Takahashi et al. 2002, 2006, hereafter T02, T06, respectively; Fukumura & Kazanas 2007b; Fukumura et al. 2007, hereafter F07; Takahashi & Takahashi 2010). In particular, extensive theoretical studies of various types of shocks have been conducted to date in an attempt to understand their dynamical behavior; e.g., shock oscillation in the context of quasi-periodic oscillations and its spectroscopic signatures (e.g., Chakrabarti & Titarchuk 1995; Molteni et al. 1996, 1999; Acharya et al. 2002; Okuda et al. 2004, 2007; Nagakura & Yamada 2008) that may be relevant for X-ray Binaries (XRBs), for example. Independent general relativistic (GR) MHD (GRMHD) simulations of the tilted accretion disk clearly show that the compression of the plunging plasma in the inner region(





) leads to the formation of standing shocks (e.g., Fragile et al. 2007; Fragile & Blaes 2008; Generozov et al. 2014) depending on the characteristics of the disk geometry and the BH spin (e.g., Morales et al. 2014). The expected highly magnetized shocked region may perhaps correspond to the magnetically arrested plasma seen in other large-scale simulations (e.g., Tchekhovskoy et al. 2011).
Citation: Das & Chakrabarti 2007
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Regardless of the cluster orientation, the spectral index observed for the halo at all available frequencies suggests that it is a USSRH. Despite the number of detected USSRH is still low, radio halos with steep indices are being discovered more and more frequently in the last years thanks to the improved observational capabilities of low-frequency instruments such as GMRT, MWA (Murchison Widefield Array) and LOFAR (Shimwell et al. 2016; Wilber et al. 2018; Bruno et al. 2021; Di Gennaro et al. 2021; Duchesne et al. 2022). An in-depth analysis of all radio halos hosted in Planck clusters and observed in LoTSS, including A1550, has recently been presented in Botteon et al. (2022). USSRH are a prediction of turbulent re-acceleration models (Cassano et al. 2006; Brunetti et al. 2008), in which particles are re-accelerated by turbulence (Brunetti et al. 2001, 2017; Petrosian 2001; Brunetti & Lazarian 2011). On the other hand, the detection of such steep indices is not expected from hadronic (or secondary) models, in which the emission of halos comes from the production of secondary electrons from hadronic collisions between thermal and CR protons (Blasi & Colafrancesco 1999; Dolag & Enßlin 2000; Pfrommer et al. 2008). Given that the integrated spectral index observed for the USSRH with LOFAR is 




α

54

MHz


144

MHz


∼
−
1.6


$ \alpha_{54\,\rm MHz}^{144\,\rm MHz} \sim -1.6 $


, we expect an index for the spectral energy distribution8δ = 2α − 1 = −4.2. If there is no break in the spectrum, the energy budget for these particles would be untenable (Brunetti et al. 2008). Therefore, a break at low energies (∼GeV) should exist, suggesting a possible interplay between radiative losses and turbulent re-acceleration during the lifetime of emitting electrons (Brunetti & Jones 2014). Moreover, re-acceleration models predict that a large fraction of halos associated with clusters of masses between 4 and 7 × 1014 M⊙ should exhibit steep spectra (Cassano et al. 2010, 2012; Brunetti & Jones 2014; Cuciti et al. 2021). The mass of A1550 of ∼6 × 1014 M⊙ estimated from Planck Collaboration XXVII (2016) falls in this range9.
Citation: Brunetti et al. 2008
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Citation: Brunetti et al. 2008
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We carry out analysis of the orbital properties of our clumps only using the sample as detected by the DDS, as this method is sensitive to most clump masses and semimajor axes. The total semimajor axis evolution of all clumps is shown in the left-hand panel of Fig. 3, which we have already discussed, and refer the reader back to. Circles mark surviving clumps (including clumps that subsume another clump), squares mark destroyed clumps and triangles mark merged clumps. Larger markers correspond to more massive clumps. For destroyed clumps, we take the last measured mass. Roughly half of our most massive clumps migrate radially inwards, which is consistent with migration in locally isothermal discs, as objects exchange angular momentum with the surrounding gas and move inwards. However, about half of our most massive clumps migrate radially outwards. This is known to be possible in radiative discs (Kley & Nelson 2012), but requires either large torques or steep surface density gradients (D'Angelo & Lubow 2010). Large torques can have many sources, but in massive, self-gravitating discs they are likely to be in the form of global spiral arms. We carried out a Fourier analysis on the density structure of our discs, to determine the Fourier amplitude of each m mode (where m is the number of spiral arms). The amplitude, Am, of each mode, m, is calculated by
(4)
\begin{equation}
A_{\mathrm{m}} = \Bigg | \sum _{i=1}^{N_{\mathrm{region}}} \frac{{\rm e}^{-im\phi _i}}{N_{\mathrm{region}}} \Bigg |,
\end{equation}
where Nregion is the number of particles in the region we are considering (for our case, R = 20 to R = 100 au), and ϕi is the azimuthal angle of the ith particle. Some example amplitudes are shown in Fig. 9, which shows the first 10 Fourier components of the density structure of two discs in their initial state (i.e. when they have just begun to fragment), marked in red, and the same two discs in their final state, marked in black. The discs are from simulation 1 and simulation 5, and their final state can be seen in their column density plots, shown in Fig. 1. These discs were selected because they ran for the same length of time, and they have contrasting final m-modes states, simulation 1 ultimately peaks in the m = 2 mode and simulation 5 ultimately peaks in the m = 6 mode.
Citation: D'Angelo & Lubow 2010
Citation function: Compare/Contrast; Compare/Contrast
The age of a neutron star is difficult to measure, as for many other astronomical sources. The most robust way to do it is by identifying the birth supernova of the neutron star. However, this can be done precisely only for a very small number of objects, as 5–10 supernovae have historically been observed in our galaxy (Stephenson & Green 2005), and neutron stars are faint sources–practically undetectable at distances beyond the Magellanic Clouds. The explosions, however, leave imprints in the interstellar medium that can remain visible at radio wavelengths for 10 − 100 kyr (Sarbadhicary et al. 2017), thereby allowing the association of pulsars with supernova remnants (SNRs). However, pulsars are rarely found at the centre of SNRs (Frail et al. 1994), as most are expelled like bullets during the explosions possibly due to asymmetries in the process (e.g. Socrates et al. 2005). The transverse velocities of pulsars (based on proper motion and distance estimates) are particularly large, with a mean close to 310 km s−1 (Hobbs et al. 2005), which is at least ten times larger than the average velocities for stars in the solar neighbourhood (e.g. Gaia Collaboration 2018). Moreover, some measured velocities range as high as 1000 km s−1 (Chatterjee et al. 2005; Deller et al. 2019). Thus, associations between SNRs and pulsars are not always straightforward to make (e.g. see the chapter on young pulsars in Lyne & Graham-Smith 2012). The farther the pulsar is from the explosion site, the higher the possibility that the pulsar and SNR are unrelated. In order to confirm an association, it could be necessary to account for up to 100 kyr of evolution of the SNR (that we assume as the maximum possible age of a SNR), and movement across the Galaxy of the pulsar (e.g. Suzuki et al. 2021). In some situations, proper motion measurements for the pulsars can shed light on the matter. For an association to be secure, the pulsar must be moving away from where the explosion took place (usually adopted as the centre of the SNR), and the time necessary to move the pulsar to its current position must match the age of the system. If such time coincided with an independent age measurement of the SNR or the pulsar, or both, then the association would be concretely confirmed. However, this is rarely possible as SNR and pulsar ages are hard to obtain.
Citation: Hobbs et al. 2005
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Citation: Sarbadhicary et al. 2017
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While the status of the S8 discrepancy is perhaps somewhat less clear than that of the H0 tension, it is beyond question that there overall is some disagreement between high- and low-redshift probes of the amplitude of matter fluctuations (see, for instance, Di Valentino et al. 2020c, for a concise review of the problem). It is thus worthwhile to investigate whether new physics might solve or at least alleviate the S8 discrepancy, a possibility that has been investigated in several works. Models that have been contemplated in this sense include for example active and sterile neutrinos (Battye & Moss 2014; MacCrann et al. 2015; Feng, Zhang & Zhang 2017; Vagnozzi et al. 2017; Mccarthy et al. 2018), ultra-light axions (Hlozek et al. 2015), decaying dark matter (DM; Enqvist et al. 2015; Chudaykin, Gorbunov & Tkachev 2018; Di Valentino et al. 2018; Abellán et al. 2020; Chen et al. 2021; Pandey, Karwal & Das 2020; Xiao et al. 2020; Abellán, Murgia & Poulin2021), extended or exotic DM and/or dark energy (DE) models and interactions (Kunz, Nesseris & Sawicki 2015; Kumar & Nunes 2016; Pourtsidou & Tram 2016; Gariazzo et al. 2017; Benetti, Graef & Alcaniz 2018; Buen-Abad et al. 2018; Kumar, Nunes & Yadav 2018, 2020a, b; Poulin et al. 2018; Archidiacono et al. 2019; Di Valentino et al. 2019b, 2020b; Lambiase et al. 2019; Vagnozzi et al. 2019; Chamings et al. 2020; Dutta et al. 2020; Heimersheim et al. 2020; Jiménez et al. 2020; Choi, Yanagida & Yokozaki 2021) including unified dark sector models (Camera, Martinelli & Bertacca 2019), modified gravity models (Dossett et al. 2015; De Felice & Mukohyama 2017; Nesseris, Pantazis & Perivolaropoulos 2017; Kazantzidis & Perivolaropoulos 2018, 2019; Barros et al. 2020; De Felice, Nakamura & Tsujikawa 2020; Skara & Perivolaropoulos 2020; Zumalacarregui 2020; Marra & Perivolaropoulos 2021), and more generally extended parameter spaces (Di Valentino & Bridle 2018; Di Valentino, Melchiorri & Silk 2020), among the others. It is also worth noting that most of the models invoked to address the S8 discrepancy do so at the expense of worsening the H0 tension, and vice versa (see e.g. Vagnozzi et al. 2018; Poulin et al. 2018; Kumar et al. 2019a; Hill et al. 2020; Alestas & Perivolaropoulos 2021), highlighting the importance of a conjoined analysis of the two tensions (Di Valentino et al. 2020b; Di Valentino, Linder & Melchiorri 2020a).
Citation: Buen-Abad et al. 2018
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With the increase in precision of CRSF measurements, the dependence of CRSFs on luminosity and spin phase has become obvious and is one of the important areas of current X-ray pulsar research, as it potentially allows probing of emission region geometry and properties (Staubert et al. 2019). Of particular interest is the luminosity dependence of the line properties, as it might be used to probe the mechanism of plasma deceleration and the transition between so-called sub- and supercritical accretion regimes associated with the onset of an accretion column first suggested by Basko & Sunyaev (1976). As a result, two main accretion regimes, super- and subcritical accretion, are expected depending on whether the source luminosity is higher or lower than a “critical luminosity” Lcrit, which strongly depends on the magnetic field of the NS (Basko & Sunyaev 1976; Becker et al. 2012; Mushtukov et al. 2015a). In the supercritical regime, for L > Lcrit, an accretion column forms, and the falling plasma is decelerated by a radiation shock that forms at a certain distance from the NS surface. In this case, the emission height increases with increasing luminosity. In the subcritical regime, for L Lcrit, the infalling matter is presumably decelerated by Coulomb interaction, forming a region whose height decreases with increasing luminosity. At even lower luminosity, the description of the deceleration process of falling material is not very conclusive. A reasonable scenario is that there exists a transition for the regime from Coulomb-stopping to gas-shock dominance beyond which only a small accretion mound forms on the NS surface. Based on this picture, and considering that the local magnetic field strength decreases with height, the correlation between the CRSF line energy and luminosity can be used to trace the accretion regimes. For instance, a transition between the sub- and supercritical regimes was recently reported by Doroshenko et al. (2017) and Vybornov et al. (2018) for V0332+53 during a giant outburst.
Citation: Mushtukov et al. 2015a
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