adsabs/WIESP2022-NER huggingface dataset:
Paper: 2016MNRAS.455.1275T (fulltext)
of each other. Finally, we compare a total system luminosity of log ( L /L ⊙ ) = 6.38 (log ( L 1 /L ⊙ ) ≈ 6.25 and log ( L 2 /L ⊙ ) ≈ 5.8) to the tracks for Galactic metallicity from Ekström et al. ( 2012 ), which go up to 120 M ⊙ . While this comparison is much less accurate than the bonnsai method, these luminosities correspond to masses of approximately M 1 ≈ 100 M ⊙ and M 2 ≈ 60 M ⊙ at the ZAMS. This is in excellent agreement with our results from the LMC tracks. 4.3 Origin and evolutionary state Due to its projected distance of 16 arcmin from the massive Westerlund 2 cluster, it has been suggested that WR21a originates from this cluster. Roman-Lopes et al. ( 2011 ) proposed that WR21a might have been dynamically ejected from the Westerlund 2 core, together with the massive binaries WR20aa and WR20c. These stars are in a similar geometrical configuration in the plane of the sky as AE Aur, μ Col, and ι Ori, for which a binary ejection scenario has been proposed (Blaauw 1961 ). Disruption of the orbit by dynamical interactions may explain the high eccentricity of the WR21a system, which is higher than any other massive binary with similar period (Sana et al. 2012 ). The systematic RV of WR21a that follows from our orbital solution is comparable to that of Westerlund 2 (Rauw, Sana Nazé 2011 ), and thus there is no indication for a significant runaway motion in the line of sight if the system indeed originates from this cluster. At the maximum distance estimate of 8 kpc, the projected distance of WR21a from Westerlund 2 is 37 pc. WR21a would have to travel at a speed of 36 km s −1 along the plane of the sky in order to reach its current position within 1 Myr. This is well within the maximum velocity at which a massive binary can be ejected (Perets Šubr 2012 ). The derived spectral types of the components of WR21a can be used to estimate their evolutionary state. Hydrogen-rich WN stars are very massive main sequence stars that are so luminous that their winds are optically thick (de Koter et al. 1997 ). They are located close to the ZAMS in the Hertzsprung–Russell diagram (e.g. Hamann, Gräfener Liermann 2006 ), and thus the primary O3/WN5ha star is expected to be very young, likely around 1–2 Myr. The O3 secondary star is likely of similar age, as stars this massive will evolve towards later spectral types within 2 Myr unless they are rotating rapidly (e.g. Brott et al. 2011 ). The full width at half-maximum of He ii λ4541 Å (3.0206 ± 0.0996 Å) indicates a rotational velocity of v rot sin i ≈ 66 km s −1 following the Ramírez-Agudelo et al. ( 2015 ) calibration ( v rot = 77 km s −1 for an inclination i = 588). Thus, we have no indication for such rapid rotation. 5 SUMMARY AND CONCLUSIONS We have presented multi-epoch observations of the massive binary system WR21a, including a full coverage of the 2011 January periastron passage. The data allow us to obtain orbital solutions for both components of WR21a. We derive very accurate minimum masses
Paper: 2020MNRAS.495.1958W (fulltext)
owned by the most massive passive galaxies (Correa et al. 2017 ; Lagos et al. 2018 ). But we note that simulated passive galaxies with are more dispersion dominated than the observed ones. It is revealing to compare our Figs 1 and 7 with the left-hand panel of fig. 1 of Wuyts et al. ( 2011 ), which visualizes the distribution of the Sersic ( 1968 ) index on the diagram. That diagram is often presented to demonstrate the connection between galaxy structure and SFR, with the passive galaxies having a index close to the de Vaucouleurs ( 1948 ) profile ( n = 4) while the star forming ones having exponential profiles ( n = 1) typical for discs. This is interpreted as galaxies generally becoming ellipticals when they quench and become passive. Our diagrams show a similar feature. However there is a crucial difference. In fact, while in the Wuyts et al. ( 2011 ) figure the region of ‘ellipticals’ span the entire mass range from just above up to the largest masses of nearly , in our diagrams there is a clear transition at a significantly larger mass of . Only above that mass being passive is associated to being slow-rotator ‘ellipticals’, while for lower masses quenching produces no more than a minor structural transformation (increasing bulges but retaining significant level of rotation). This is the key novelty we want to emphasize with this work. A transition around is not unexpected, given that only above that critical mass are slow-rotator ETGs starting to dominate, while below that mass one only finds spiral galaxies and fast rotator ETGs (e.g. Cappellari 2016 ). However, in this paper we first illustrate this fact specifically in the context of the diagram, where this fact is not yet universally appreciated. Beyond fitting the light distribution with single Sersic profiles, efforts have been made to decompose galaxies into multiple components including bulges and discs. A relevant result in Morselli et al. ( 2017 ) illustrating bulge to total ratio as a function of stellar mass and SFR shows overall consistency with what we found using the spin parameter. The same difference appears in the passive population for which the spin reveals a sharp transition among massive galaxies whereas fig. 5 of Morselli et al. ( 2017 ) by contrast indicates very close bulge to total ratio over a large range of mass. In the following section, we discuss the implications of our results in the context of a ΛCDM universe in order to understand the trend of with stellar mass and star formation level. 5.1 Understanding in the context of galaxy formation and evolution within a ΛCDM universe 5.1.1 Early/late star formation and in/ex situ mass assembly To understand the current kinematics of galaxies, we need to know what factors are key to determining their kinematic state. In principle, whether a galaxy is mainly in ordered rotation or random motion (that is disc-dominated or spheroid-dominated) will depend on (1) the angular momentum of gas used as raw material for
Paper: 2019MNRAS.490.5634C (fulltext)
instability sets in (see Fig. 7 ). As predicted analytically, the main effect of increasing angular momentum ratio j for fixed e b is to monotonically decrease the relative planet-to-binary stationary tilt i s in the prograde case (where i s ≤ 90°) (see Fig. 6 ). In addition, this stationary tilt increases with increasing e b for fixed j in the prograde case. The behaviour of the stationary tilt in the retrograde case is more complicated, but agrees with the analytic predictions given in Martin Lubow ( 2019 ). In this case, the stationary inclination for non-coplanar orbits decreases with increasing j for fixed e b as in the prograde case. But i s changes from increasing with e b to decreasing at . In addition, there are no non-coplanar stationary orbits below a certain j value, denoted by j cr , that depends on e b (see Fig. 10 and equation 4 ). This property does not hold in the prograde case. Another difference between the prograde and retrograde cases is the topology of librating orbits. In the prograde case, the librating orbits are always nested in a i cos φ– i sin φ phase plane about point with i = i s and φ = ±90° (e.g. red and cyan lines in Fig. 1 ). In the retrograde case, for j > j cr described above, librating orbits are not fully nested within each other and do not orbit about the stationary point in the i cos φ– i sin φ phase plane (e.g. magenta lines in Fig. 5 ). In this phase plane, prograde librating orbits have an oval shape, while retrograde librating orbits have a crescent shape. The variation of e b in time is significantly larger for a higher mass planet. In the simulation with initial conditions e b = 0.2, f b = 0.1, and i = 170°, the binary eccentricity can be excited to values very close to 1 (see Fig. 1 ). This behaviour is similar to what occurs with Kozai–Lidov oscillations in which the outer object is a planet (e.g. Naoz 2016 ). The recent release of data from Gaia allowed us to better characterize the kinematics of the eccentric equal mass close binary HD 106906 in the Lower Centaurus Crux group (Bailey et al. 2014 ). This system hosts both a wide asymmetric debris disc and a planetary-mass companion. The formation mechanism of the planet and the stability of its orbit are still under debate (Rodet et al. 2017 ; De Rosa Kalas 2019 ). The binary components have masses and . The orbital period is and the binary eccentricity is e = 0.67 (De Rosa Kalas 2019 ). The planet, HD 106906b, was directly imaged with a projected separation of 738 au and was found to be oriented at 21° from the position angle of the disc mid-plane, suggesting that the planet’s orbit is not coplanar with the system (Kalas et al. 2015 ). The planet mass was inferred to be (Bailey et al. 2014 ). While the orbital properties of the planet are uncertain, if we assume that the semimajor axis is and the eccentricity is zero, the ratio of the angular momentum of the planet to the angular momentum of the binary is j = 1.13. According to our
Paper: 2017MNRAS.470.2351W (fulltext)
at low redshifts. Despite this some uncertainty remains as to whether the smaller scatter of Aquarius haloes is mainly due to differences between the particle tagging approach and hydrodynamical simulations. The way to verify this would be to construct mock stellar halo catalogues for apostle haloes and make direct comparisons. Such mock catalogues are not yet available for apostle haloes. Nevertheless, we note that as there are only five Aquarius haloes used for our analysis, it is quite possible that these haloes happen to be good cases simply due to statistical fluctuations. To quantify the statistical significance of the difference, we perform a one-dimensional KolmogorovSmirnov (KS) test to estimate the probability that the fitted parameters of the two samples are drawn from the same distribution. This is done separately for the two parameters. The resulting p -values are 0.3656 for M 200 and 0.6196 for c 200 , This means that we have 36.56percent (61.96percent) probability of observing an equal or even larger difference in the two mass (concentration) samples, which implies that the two samples are not statistically distinguishable for either parameter. Repeating the one-dimensional KS test for the parameter combination corresponding to anticorrelation direction we find a p -value of 0.6506, again compatible with the smaller scatter of Aquarius haloes appearing by chance due to the small sample size. With the larger sample of apostle haloes, we found a significantly larger scatter in the best-fitting parameters compared to those based on Aquarius haloes. The nearly a factor of 2 scatter in M 200 and a factor of 3 scatter in c 200 is worrying for dynamical modelling of MW halo mass. As discussed above, this amount of systematic uncertainty is irreducible and applies to any steady-state models. The typical size of the statistical errors is smaller than the symbol size in Fig. 2 , and is about a factor of 0.03 of the scatter of the systematic uncertainty (blue ellipse). With an average sample size of 4.5 10 4 star particles in each apostle halo, we find the effective number of independent star particles (see Section 4 ) to be N eff 0.03 2 4.5 10 4 40. Recall that in Section 4 , we estimated the effective number of dark matter particles in MW-like haloes to be about 1000. This means, star particles in our hydrodynamical simulations are far more correlated than dark matter particles. This is not surprising, because we know stars have much higher binding energy than dark matter and are more centrally concentrated. They are less relaxed and less phase mixed than dark matter. In addition, we expect about 3040percent of dark matter particles are smoothly accreted instead of being accreted as part of a bound substructure (see details in Wang etal. 2011 , where a detailed investigation on possible dependencies on the resolution has been made), whereas we have checked that more than 80percent of star particles beyond 20kpc of the halo centre
Paper: 2018ApJ...855...58M (fulltext)
opposite polarity (see the orange and black arrows in Figures 5 (f) and (g), respectively). Noticeably, at the end of the penumbra formation process (Figure 5 (j)), the penumbra covers only half of the umbra, the one facing the opposite polarity. 3.2. Velocity Pattern In Table 2 we report the presence of the inverse Evershed flow. In particular, in 11 spots we observe a flow of opposite sign with respect to that observed when the penumbra has formed, i.e., an inverse Evershed flow. In Figure 6 , we show images of the continuum and LOS velocity maps for the following polarities of the AR 11610 and 11630, respectively. In these cases the inverse Evershed flow was clearly detected before the penumbra formation, although this process has already started. Figure 6. From top to bottom: zoom of the continuum and LOS velocity maps of the following sunspot of AR 11610 ((a)–(h)) and of the following sunspot of AR 11630 ((i)–(p)). The boxes in all of the panels indicate the regions where we calculated the values of the velocity reported in Table 3 . Table 3 reports the mean values of the velocity before and after the penumbra formation, calculated inside the boxes shown in Figure 6 . Table 3 LOS Velocity around Sunspots In fact, in AR 11610, despite that the penumbra surrounds almost all of the umbra, there is a sector without penumbra on the eastern side of the following spot where we observe the onset of the Evershed flow in about 6 hr. The mean velocity before the onset of the Evershed flow is around −160 m s −1 , which becomes 210 m s −1 when the penumbra is completely formed. Concerning AR 11630 (Figure 6 (i)–(p)), we observe at 11:00 UT (Figure 6 (m)), when no penumbra filament is present (Figure 6 (i)), that most of the area inside the black square is redshifted, with a mean velocity of about 220 m s −1 . After 1 hr, filaments appear and the area becomes blueshifted (see Figures 6 (j) and (n)). 4. Discussion and Conclusions In this paper we studied the penumbra formation in 12 ARs. We followed the evolution of the preceding and following spots using continuum and LOS velocity maps and, depending on where the first penumbral sector started to form, we classified the following and preceding polarities of each AR. Despite the fact that not all of the spots in our sample are fully surrounded by a penumbra, we found that the last penumbral sector does not always appear on the side toward the opposite polarity (see the preceding polarity of AR 11150 in Figure 5 ), contrarily to what was reported by Zwaan ( 1992 ). We found that in eight spots the first stable penumbral sector formed on the side toward the opposite polarity, and in nine spots it formed away from the opposite polarity (see Table 2 ). We can also note that the time needed to form the penumbra seems to be related to the side where the penumbra appears. In particular, it seems that the penumbra formation in B-type spots is quicker (about 21 hr) than in the A-type spots (about 39 hr). In
Paper: 2020MNRAS.491.2779V (fulltext)
in mass by up to one or two order of magnitudes from z 8.5 to z 0. Its final mass ranges between 10 6 and 10 7 M . On the other hand, when the AGN feedback energy is entirely supplied to the cold phase, the multiphase ISM is not promoted to outflow and remains close to the BH: as a consequence, the BH experiences a rapid phase of mass growth (in the redshift range 3 z 5) during which it deprives of gas the centre of the host galaxy, and then its growth is suppressed. The BH mass at z 0 can be as high as 10 9 M in this case. Therefore, a prediction of our model is that at least a share of the AGN feedback energy has to couple with the diffuse hot gas. We examined the effect of coupling the AGN feedback energy injected in a multiphase ISM to its phases according to their physical properties. We considered a model where feedback energy coupling is driven by the covering factors of the hot and cold phases, assuming that the larger is the volume occupied by the cold gas clumps, the larger is the amount of energy that the cold gas absorbs. Gas accretion is the process that contributes the most to the BH growth, rather than mergers with other BHs (Section 5.2 ). Throughout BH evolution, the total accretion rate is dominated by cold gas accretion, with respect to hot. Remarkably, this is in line with Gaspari etal. ( 2019 ), even if they derived such a conclusion by means of a phenomenological analysis focused on more massive systems. Our conclusion that gas accretion is a more viable channel for BH growth than BH mergers is true unless cold gas which is supported by rotational velocity is prevented from accreting (see below). The quiet merging history that characterizes our simulated disc galaxies also contributes to the minor role of BH mergers to the BH mass growth. The contribution to the BH growth by BHBH mergers is expected to become more significant for increasing BH mass (Fanidakis etal. 2011 ; Dubois, Volonteri Silk 2014a ; Weinberger etal. 2018 ). We find that when the BH only accretes cold gas, it experiences a growth by gas accretion that is faster than (or at most comparable to) the case in which both cold and hot gas are accreted. As for the galaxy M bulge M BH scaling relation, predictions from simulations are in keeping with observations, considering a BH seed mass as large as 10 5 M . When the accretion of cold gas that is supported by rotational velocity is reduced, the BH mass growth is delayed and the BH mass at z 0 is reduced by up to an order of magnitude with respect to the case in which both hot and cold gas accretion proceed unimpeded. Within the scenario emerging from this model, the SMBH in MW-sized galaxies is prevented from growing by gas accretion below z 2, aside from possible BH mergers. Also, the lower is the viscosity assumed for the cold gas which is accreting (i.e. the larger C visc ), the more the BH mass growth is reduced. Simulations that include AGN feedback produce spiral galaxies with a more extended stellar
Paper: 2017ApJ...835...92C (fulltext)
always is assumed, that β is independent of r . Following the well-known spherical Jeans equation (Binney 1980 ), the radial velocity dispersion of the luminous matter in the early-type lens galaxies can be expressed aswhere β is a constant velocity anisotropy parameter. Combining the mass density profiles in Equation ( 4 ), we obtain the relation between the mass enclosed within a spherical radius r and M E aswhere by we denoted the ratio of respective Euler’s Gamma functions. Simplifying the formulae with the notation ξ = δ + α − 2 taken after Koopmans ( 2006 ), we obtain a convenient form for the radial velocity dispersion by scaling the dynamical mass to the Einstein radius: In all strong lensing measurements used, the observed velocity dispersion is reported, which is a projected luminosity-weighted average of the radially dependent velocity dispersion profile of the lensing galaxy. Its theoretical value can be calculated from Equation ( 7 ) with the assumption that the relationship between stellar number density and stellar luminosity density is spatially constant. This assumption is unlikely to be violated appreciably within the effective radius of the early-type lens galaxies under consideration. Moreover, the actual observed velocity dispersion is measured over the effective spectrometer aperture θ ap and effectively averaged by line-of-sight luminosity. Taking into account the effects of aperture with atmospheric blurring and luminosity-weighted averaging, the averaged observed velocity dispersion takes the formwhere and χ = θ ap / σ atm (Schwab et al. 2010 ); σ atm is the seeing recorded by the spectroscopic guide cameras during observing sessions (Cao et al. 2016 ). The above equation tells us that we can constrain the PPN parameter γ on a sample of lenses with known redshifts of the lens and the source with a measured velocity dispersion and the Einstein radius, provided we have reliable knowledge about the cosmological model and the parameters describing the mass distribution of lensing galaxies ( α , β , δ ). For the purpose of our analysis, the angular diameter distances D A ( z ) between redshifts z 1 and z 2 were calculated using the best-fit matter density parameter Ω m given by the Planck Collaboration assuming a flat FRW metric (Ade et al. 2014 ). Moreover, we allow the luminosity density profile to differ from the total mass density profile, i.e., , and the stellar velocity anisotropy exits, i.e., . Based on a well-studied sample of nearby elliptical galaxies from Gerhard et al. ( 2001 ), the anisotropy β is characterized by a Gaussian distribution, β = 0.18 ± 0.13, that is also extensively used in previous works (Bolton et al. 2006 ; Schwab et al. 2010 ). More recently, Xu et al. ( 2016 ) measured the stellar velocity anisotropy parameter β and its correlations with redshifts and stellar velocity dispersion, based on the Illustris simulated early-type galaxies with spherically symmetric density distributions. It is
Paper: 2020MNRAS.496L.133S (fulltext)
conclusions of this paper are correct and valuable. The data presented here suggest another mechanism for the ECD instability. The LHD electric fields of 20 mV m −1 in B ∼ 15 nT produce ExB drift of 1300 km s −1 , comparable to the electron thermal speed. Since this field exists in narrow channels with a width of a few electron gyroradii, only electrons can participate, making ion–electron drift V d ∼ te . Incidentally, this instability attracted attention of researchers working with Hall ion thrusters, because it affects their performance (Ducrocq et al. 2006 ; Boeuf Garrigues 2018 ). In these devices, the instability is also caused by the ExB drift of electrons only, because ions have gyroradius larger than the drift channels. The theory of ECD instability that links electron–cyclotron harmonics with ion-acoustic waves and wavelengths at scales below the electron gyroradius provides convincing explanation for waves in Fig. 2(a) , which exhibit both large E ∥ and E ⊥ , and contain f ce harmonics and Doppler shifted structures smaller than electron gyroradius. 3 WHAT HEATS IONS AND ELECTRONS? We focus now on the fundamental question: What kinds of processes can increase the ion energy by 400 eV (from 50 to 450 eV), and the electron energy by 50 eV (from 20 to 70 eV), within a few seconds, or during one proton gyroperiod, as seen in Fig. 1 . Additional constraint is that heating of electrons is isotropic, while that of ions is mostly perpendicular. The mechanism of stochastic ion heating on LH waves related to condition (1 ) has been explained by Karney ( 1979 ), and on other wave structures by other authors: Cole ( 1976 ), McChesney et al. ( 1987 ), Balikhin et al. ( 1993 ), Mishin Banaszkiewicz ( 1998 ), Stasiewicz et al. ( 2000 , 2013 ), Stasiewicz ( 2007 ), Vranjes Poedts ( 2010 ), and Yoon Bellan ( 2019 ). The essence is that particles stressed by strong gradients lose adiabaticity and can be scattered along the electric field for direct acceleration by both DC and wave fields. The computed χ (Fig. 4b ) shows values greatly exceeding 1, needed to stochastically perturb proton orbits; however, significant ion heating is observed when χ > 10. Formally, the error of χ is equivalent to the error of the electric field measurements, i.e. ∼1 mV m −1 , or 10 per cent of large-amplitude fields, because of gain uncertainty in amplifiers (Lindqvist et al. 2016 ). However, in the case of ECD waves with wavelengths of the electron gyroradius, the gradient computations underestimate real values because the spacecraft separations are larger than wavelengths. In Fig. 4(c) , we show the difference in E y components measured by satellites 1 and 2. Similar differences are seen on any pair of the satellites. A difference Δ E y ≈100 mV m −1 on scales of the electron gyroradius r e ≈ 1 km in the field B = 15 nT would produce χ ≈ 4600, which could effectively demagnetize electrons and subject them to stochastic heating. Applying 10 per cent error to this value