adsabs/WIESP2022-NER huggingface dataset:
Paper: 2016MNRAS.458.3739B (fulltext)
). Despite this wide range of applications, the nonlinear dynamics of eccentric discs remains poorly understood. In the Solar system, several of the rings of Saturn and Uranus are observed to be elliptical, and a theory for narrow eccentric rings (with small eccentricities but arbitrary eccentricity gradients) composed of weakly collisional particles has been developed (Borderies, Goldreich Tremaine 1983 ; Chiang Goldreich 2000 ). For small eccentricities, eccentric discs can be described as slowly precessing one-armed density waves (or shocks, e.g. Okazaki 1991 ; Papaloizou, Savonije Henrichs 1992 ; Lee Goodman 1999 ; Goodchild Ogilvie 2006 ; Ogilvie 2008 ; Saini, Gulati Sridhar 2009 ). A particular solution for a global uniformly eccentric (and apsidally aligned) Keplerian disc has also been studied by Statler ( 2001 ). A general secular theory for three-dimensional eccentric discs with arbitrary eccentricities and eccentricity gradients has been developed (Ogilvie 2001 ), and we aim to explore (and test using numerical simulations) some of its implications in this work. Secular theory describes dynamical processes that occur on time-scales that are much longer than the orbital time-scale. In the more familiar context of a system of multiple planets around a star, the Keplerian orbit of each planet is subject to perturbing forces that are proportional to the planet-to-star mass ratio; secular theory accounts for the long-term behaviour of eccentricity and inclination resulting from the orbit-averaged perturbing forces. For a thin gaseous disc around a star, however, pressure provides the most important departure from Keplerian orbital motion, being of second order in the aspect ratio H / R of the disc. Other subdominant forces, such as those due to the self-gravity of the disc (Tremaine 2001 ) and viscous or turbulent stresses (Ogilvie 2001 ), can also be important. In this situation, secular theory describes the long-term evolution of eccentricity due to gas pressure (and other forces) in thin discs, but neglects contributions that are of fourth order or higher in H / R . In recent work, we developed a local model of an eccentric disc (Ogilvie Barker 2014 ), which is similar to the shearing box that is commonly used to study the dynamics of circular astrophysical discs (Goldreich Lynden-Bell 1965 ; Hawley, Gammie Balbus 1995 ). We used this model to analyse the vertical oscillatory flows that are driven by the variation in the vertical gravity around a non-circular orbit (Ogilvie Barker 2014 ), and subsequently studied the local linear stability of these discs and their vertical flows (Barker Ogilvie 2014 ). We found that eccentric discs are generically unstable (in three dimensions), being subject to a small-scale instability in which inertial waves are driven by a parametric resonance. This instability is expected to lead to wave activity or turbulence, and to damping of the disc eccentricity and eccentricity gradients (Papaloizou 2005b
Paper: 2019ApJ...879L..14R (fulltext)
; Goicoechea et al. 2017 ). Because it is easily observable at millimeter wavelengths, HCO + is an excellent candidate to investigate the gas dynamics within the cavities of nearby transition disks. Our observations suggest that the HCO + /HCN ratio is a useful chemical tool in determining the structure of transitional disks. In the case of unresolved disks, a high HCO + /HCN intensity ratio might be associated with the existence of inner dust cavities full of dense gas. We note that, together with AB Aur, HD 142527 and AA Tau were the disks with a higher HCO + J = 3–2/HCN J = 3–2 ratio in the compilation of Pacheco-Vázquez et al. ( 2015 ). Both systems show filamentary gas emission through their dust cavities (Casassus et al. 2013 ; Loomis et al. 2017 ). The other disk with a high ratio, GM Aur, has not been studied in detail. This result is also in line with recent results by Alonso-Albi et al. ( 2018 ) toward the Herbig Be star R Mon. 4.3. Gas Kinematics We show in Figure 3 (a) the first moment map of HCO + emission. The outer parts of the disk resemble those of a Keplerian disk. However, twisted isophotes are observed toward the center ( r 06). The aforementioned twisting can be reproduced by two misaligned Keplerian disks as proposed by Hashimoto et al. ( 2011 ). A radial outflow would produce a similar effect (Rosenfeld et al. 2014 ). We adopt the misaligned disks as the most plausible explanation, as it is consistent with near-IR observations by Hashimoto et al. ( 2011 ). In Figure 3 (b), we show the residual map that results from subtracting a two Keplerian disks model from the HCO + first moment map. The model consists of an outer disk extending from 350 to 45 au, with i = 26° and PA = 37°, and an inner one extending from 45 au inward with i = 43° and PA = 65° (Hashimoto et al. 2011 ), around a 2.4 M star, and the final image is convolved with the observational beam. This simplistic model provides a reasonable fit across the disk, except in the southwestern region, where strong residuals are observed. Visual inspection of Figure 3 (a), shows that there is an anomaly (blue circle) in the velocity field that is spatially coincident with the bridge (BR, Figure 3 (b)). This anomaly is due to high-velocity wings in the line profile of HCO + at the bridge position (see Figure 2 (b)). The redshifted peak is compatible with Keplerian rotation, while the blueshifted one requires a different mechanism, most likely infalling gas. To test the possibility that the blueshifted wing is tracing infalling material, we built a pure free-falling velocity field following equationwhere r start is the starting position for free-fall accretion, and we adopted r start = 120 au (accretion starts at the inner edge of the dust ring, r ∼ 07). We assumed that infall stops at 40 au. Cuts in the first-moment map, and in our convolved models are shown in Figure 3 (c). The free-falling model has a velocity of 5.5 km s −1 at the bridge position, compared to the 5.3
Paper: 2017ApJ...835...31C (fulltext)
(). While p obs does not depend on the longitude, the diurnal cycle can still introduce a systematic bias. This is because the Sun will be systematically out of phase with the northern maximum of the antenna pattern (Figure 2 ). We find that this typically produces an increase in p obs of a few percent for mid-latitudes in the north, even though their analogs in the south have larger p obs because of the shorter solar exposure over an entire year. We note that p obs reflects the amount of localization probability that is observable in the limit of many detections. Outside of this limit, we consider an analogous quantity () defined for a finite number of detections ( N d ) with the correspondence (see the Appendix for more details). Statistical fluctuations in , caused by variations in which events occur, can be large, particularly with events. We expect the uncertainty in this estimate to scale inversely with , and Figure 3 reports as error bars along with the mean. Typical values are between 6% and 10%. We also note that the intrinsic distribution for single events ( N d = 1) may not be Gaussian but, in the limit of many detections, the distribution of the mean will be. 3.2. Minimum Zenith Distance While equatorial observatories may be able to access the largest integrated probability, and thereby have the largest probability of being able to image a source, this does not necessarily imply that they will have the best conditions for observing. An important consideration is the closest approach of each field to an observatory’s zenith (minimum zenith distance). Sources at large angles from an observatory’s zenith can be difficult to observe because of high air mass and mechanical limitations. In Figure 4, we present the mean minimum zenith distance, as a function of latitude, weighted by the probability that the source actually comes from each location: accounts for solar occlusion and incorporates when the EM facility will actually be able to observe. We find that observatories at extreme latitudes () will almost always have large D zen , with a gradual transition to lower values at lower latitudes. There is a difference in D zen between observatories at mid-latitudes, with northern sites preferred. This is because the diurnal cycle makes the Sun preferentially overlap the southern antenna pattern and forces southern facilities to observe closer to sunrise and sunset than their northern counterparts. This behavior is particularly evident at the northern winter solstice. Figure 4. D zen averaged over a year (black), near the northern summer solstice (blue), and near the northern winter soltice (red). Shaded regions correspond to the fluctuations from localization maps simulations (), and we note that 's distribution is quite broad. Figure 4 also shows the fluctuations in the analgous stastic defined for a finite number of detections (). We typically find –10 (see the Appendix for more details). Furthemore, D zen corresponds to the mean of
Paper: 2019MNRAS.485..513S (fulltext)
≈ x .). For the sample galaxies. the resulting rotation curves predicted by Newton (dashed curves) and by MOND (solid curves) are compared with the observations in Fig. 2 (lower panels), along with the surface density distributions of the baryonic components. It is striking that in several cases (DDO 87, WLM, IC 2574, NGC 3741) the observed structure corresponds quite precisely to that predicted by the baryonic mass distribution in the context of MOND. Note that for WLM, there are a large number of points on the derived rotation curve given by Oh et al. These are certainly not independent, and given their high density obscure the match of the predicted rotation curve to the observations; therefore I have taken only every fourth point in the curve presented here. Figure 2. Each galaxy is represented in two panels. The upper panel is the surface densities of gas (dashed) and stars (dotted) as a function of radius. The lower panel shows the observed rotation curve (points), the Newtonian rotation curve of baryonic components (long dashed curve), and MOND rotation curve. calculated from the Newtonian curve via equation (1) (long dashed curve). The claim here is that these rotation curves are essentially predictions with no free parameters because of the dominance of the gaseous component. But of course there is some contribution from the luminous disc so one might question the extent to which M/L of the disc does vanish as an adjustable parameter. The stellar masses of the sample galaxies (column 6 in Table 1 ) are taken from fitting the colours of the galaxies to population synthesis models in the cases of the seven LT galaxies (Oh et al. 2015 ). For the other five cases they are taken from kinematic considerations (e.g. not exceeding the observed rotation velocity). In half the cases, the implied stellar masses exceed 15 per cent of the total baryonic mass (those objects in which the ratio of gas mass to stellar mass is less than six, column 8). This can certainly affect the shape of the galaxy rotation curves, especially in the inner regions where the stellar disc often contributes more significantly to the baryonic surface density distribution. In Fig. 3 we see the calculated rotation curves for one case where the fraction of stellar mass is fairly typical, DDO 87. The lower dashed curve is the Newtonian rotation curve of baryons excluding the estimated contribution of the visible disc and the upper dashed curve is the same but including the stellar disc with a contribution of 17.5 per cent of the total baryonic mass as given in Table 1 . The upper and lower solid curves are the same but for the MOND rotation curves. While it is obvious that the contribution of the stellar disc provides better agreement with the observations, it is also clear that, with no stellar contribution at all, the rotation curve is qualitatively similar: The overall form of the calculated rotation curves is quite independent of the mass-to-light ratio of the stellar
Paper: 2021ApJS..252...29K (fulltext)
of BAT 677; Right: CO(2–1) spectra (detection) of BAT 677. Figure 2.138. BAT 679 Left: Pan-STARRS gri color cutout of BAT 679; Right: CO(2–1) spectra (detection) of BAT 679. Figure 2.139. BAT 682 Left: Pan-STARRS gri color cutout of BAT 682; Right: CO(2–1) spectra (nondetection) of BAT 682. Figure 2.140. BAT 687 Left: Pan-STARRS gri color cutout of BAT 687; Right: CO(2–1) spectra (nondetection) of BAT 687. Figure 2.141. BAT 694 Left: Pan-STARRS gri color cutout of BAT 694; Right: CO(2–1) spectra (nondetection) of BAT 694. Figure 2.142. BAT 696 Left: Pan-STARRS gri color cutout of BAT 696; Right: CO(2–1) spectra (nondetection) of BAT 696. Figure 2.143. BAT 707 Left: DSS cutout of BAT 707; Right: CO(2–1) spectra (nondetection) of BAT 707. Figure 2.144. BAT 710 Left: DSS cutout of BAT 710; Right: CO(2–1) spectra (nondetection) of BAT 710. Figure 2.145. BAT 717 Left: Pan-STARRS gri color cutout of BAT 717; Right: CO(2–1) spectra (detection) of BAT 717. Figure 2.146. BAT 719 Left: Pan-STARRS gri color cutout of BAT 719; Right: CO(2–1) spectra (detection) of BAT 719. Figure 2.147. BAT 723 Left: Pan-STARRS gri color cutout of BAT 723; Right: CO(2–1) spectra (detection) of BAT 723. Figure 2.148. BAT 733 Left: Pan-STARRS gri color cutout of BAT 733; Right: CO(2–1) spectra (detection) of BAT 733. Figure 2.149. BAT 735 Left: Pan-STARRS gri color cutout of BAT 735; Right: CO(2–1) spectra (detection) of BAT 735. Figure 2.150. BAT 751 Left: DSS cutout of BAT 751; Right: CO(2–1) spectra (detection) of BAT 751. Figure 2.151. BAT 754 Left: Pan-STARRS gri color cutout of BAT 754; Right: CO(2–1) spectra (detection) of BAT 754. Figure 2.152. BAT 760 Left: Pan-STARRS gri color cutout of BAT 760; Right: CO(2–1) spectra (detection) of BAT 760. Figure 2.153. BAT 772 Left: Pan-STARRS gri color cutout of BAT 772; Right: CO(2–1) spectra (detection) of BAT 772. Figure 2.154. BAT 783 Left: Pan-STARRS gri color cutout of BAT 783; Right: CO(2–1) spectra (detection) of BAT 783. Figure 2.155. BAT 795 Left: DSS cutout of BAT 795; Right: CO(2–1) spectra (nondetection) of BAT 795. Figure 2.156. BAT 801 Left: DSS cutout of BAT 801; Right: CO(2–1) spectra (nondetection) of BAT 801. Figure 2.157. BAT 836 Left: Pan-STARRS gri color cutout of BAT 836; Right: CO(2–1) spectra (detection) of BAT 836. Figure 2.158. BAT 841 Left: Pan-STARRS gri color cutout of BAT 841; Right: CO(2–1) spectra (detection) of BAT 841. Figure 2.159. BAT 898 Left: DSS cutout of BAT 898; Right: CO(2–1) spectra (detection) of BAT 898. Figure 2.160. BAT 970 Left: DSS cutout of BAT 970; Right: CO(2–1) spectra (detection) of BAT 970. Figure 2.161. BAT 981 Left: Pan-STARRS gri color cutout of BAT 981; Right: CO(2–1) spectra (nondetection) of BAT 981. Figure 2.162. BAT 986 Left: DSS cutout of BAT 986; Right: CO(2–1) spectra (detection) of BAT 986. Figure 2.163. BAT 988 Left: DSS cutout of BAT 988; Right: CO(2–1) spectra (nondetection) of BAT 988. Figure 2.164. BAT 995 Left: DSS cutout of BAT 995; Right: CO(2–1)
Paper: 2020MNRAS.499.2608F (fulltext)
capture times for the SG model are always shorter, due to higher gas densities; thus, an SG disc captures all stars with a 10 4 R g at i 0 = 45 ○ , while a TQM disc captures only red giants at most radii, and captures other stars only at very small disc radii. Fig. 3 shows T cap as function of i 0 for different stellar types assuming a 0 = 10 4 R g . The curves in Fig. 3 correspond to the analytic expression in equation ( 4 ), which is very weakly dependent on i , hence the flatness of the curves. However, Fig. 3 also shows that numerical integration is required for highly inclined orbiters, and for disc models with highly variable radial height profiles (e.g. TQM ). Counter-intuitively, highly inclined stellar orbiters are captured faster by the SG disc since relative velocity is largest for high i 0 and therefore F GEO is largest. The TQM disc model is less efficient than the SG disc model at star capture at a 0 = 10 4 R g for all stellar types, with only red giants ending up within the disc for plausible AGN lifteimes. For simplicity, we assume no change in stellar mass due to disc crossings. For red giants in particular, this is likely incorrect since Kieffer Bogdanović ( 2016 ) find that RG can lose up to 10 per cent of their mass during a disc crossing (though for column densities at least two orders of magnitude greater than any considered here). Further complicating the expected capture time of giants, Armitage, Zurek Davies ( 1996 ) find that mass-loss due to repeated impacts with the disc leads to an expansion of the star and a subsequent increase in cross-section. Stars with a larger surface area are captured by the disc faster since they experience a stronger drag from equation ( 1 ), and therefore including the mass-loss in our calculations could reduce capture time for giants in both SG and TQM . In addition, Armitage finds that a main-sequence star can survive repeated disc passages while RG are destroyed much more quickly; this could explain the observed absence of RG in the NSC of the Milky Way. Some variations in T cap as a function of i for the TQM disc appear to be due to changes in a across the sharp (unphysical) density and scale height changes at a ∼ 5 × 10 3 R g . Figure 3. Capture time T cap due to geometric drag as a function of initial orbital inclination ( i 0 ) with notation as for Fig. 2 . We assumed Keplerian prograde orbits with a 0 = 10 4 R g . Curves correspond to the analytic estimate for T cap from equation ( 4 ) and star symbols indicate T cap from numerical integration of equation ( 10 ). Conservation of energy causes higher orbital inclinations to produce large changes in a , as the number of orbits needed to reach i crit increases. This results in a lower T cap for higher inclinations at the same initial semimajor axis. Changing a also causes the anomalies seen in the TQM panel, due to orbiters crossing the (unphysical) density discontinuity at approximately 5 × 10 3 R g . From the top panels of Figs 2
Paper: 2016A&A...585A.108V (fulltext)
of the field defined by the generating cylinder, which was used for the construction of the flux rope shown in panel a) , i.e., the field ( 9 )–( 11 ). In contrast to panel a) , they are shown in the whole field of view because the magnetic field from all space contributes to the solution displayed in panel a) . The cross section of the generating cylinder is plotted by the dashed circle, and the tilde coordinates are the local coordinates defined in Fig. 1 . The magnetic-field magnitude scale is the same, but the values of are different and correspond to the maxima in the displayed fields in panels a) and b) . The thick lines indicate magnetic surfaces on which the axial magnetic field is zero. This method is able to generate toroidal flux ropes with another cross sections. Figure 6 displays shapes very close to ellipses, a prolate shape in Fig. 6 a and an oblate one in Fig. 6 b. Only ten coefficients were used to define these fields (it was , and half of the coefficients were close to zero, as in the previous case). The axial field does not vanish at the boundary shown, but it is small, as is shown in Fig. 3 . There are limitations of our procedure. One has been mentioned: it was not commonly possible to obtain the desired shape of the flux rope for low aspect ratios. But even if the desired shape is obtained, the flux rope may be multipolar, that is, with the axial field reversed inside. For instance, the generating toroid of the flux rope shown in Fig. 6 a has an oblateness 2:3, but the flux rope has a dual polarity. Therefore we limited it to the inner unipolar part, displayed in Fig. 6 a, which has a smaller oblateness and a different aspect ratio (if defined as ) from 5. If the generating toroid has an oblateness or prolateness larger than about two, unipolar flux-rope cross sections deviate from desired elliptic shapes (they more resemble a rectangular shape). Fig. 6 Magnetic field magnitude distribution inside toroidal flux ropes with practically elliptic cross sections. The closed lines are cross sections of magnetic surfaces. The values of free parameters are a) , , , , , , , , , , , and ; b) , , , , , , , , , , , and . The other coefficients are (numerical) zero. 3.1. Calculating the helicity It is relatively easy to (numerically) calculate the helicities of these flux ropes. Introducing toroidally curved cylindrical coordinates , , and in our global system, the helicity for toroidal flux ropes with an axially symmetric linear force-free field ( Vandas Romashets 2015 ) is where determines the boundary; and are polar coordinates in a cross-section plane (like in Figs. 5 and 6 , where we should have for the case of Fig. 5 a and for Fig. 6 , where and are semi-axes of the boundary ellipses; for a more general boundary, would be defined numerically from the results). To compare different flux ropes, Vandas Romashets (2015) used the unitless quantity derived from the helicity by where is the volume of the toroidal flux rope and
Paper: 2020ApJ...890L...9P (fulltext)
reversals are also sometimes seen in other regions of the disk, potentially complicating the extraction of the planet position. The rotation maps presented in Figure 3 were generated with a perfect knowledge of the velocity field and taking into account the radiative transfer effects at the emitting surface. For actual data, the velocity field and altitude of the emitting layers have to be estimated. Uncertainties in the Keplerian velocity model that is subtracted may limit the detectability of Doppler flips to high signal-to-noise cases. In particular, the predicted Doppler flip for the orientation of HD 163296 (labeled panel in Figure 3 ) shows an amplitude twice smaller (≈150 m s −1 ) than the residuals in the differential rotation map presented in Casassus Pérez ( 2019 ) (≈300 m s −1 ). This explains why they did not detect the counterparts of the kink as a Doppler flip in the first moment map. The absence of visible Doppler flip corresponding to the kink in HD 97048 is also not surprising given the residuals in the differential rotation maps presented by Casassus Pérez ( 2019 ). Because of the tentative nature of the detections and the need for higher-resolution observations, we are not yet confident enough to estimate planet masses from the candidate kinks seen in the DSHARP data. Detailed hydrodynamical and radiative transfer modeling of the kink candidates is currently the only way to determine planet masses from velocity deviations in a quantitative manner but would result in poorly constrained estimates given the low signal-to-noise ratio and poor velocity resolution of the data. We estimated the velocity deviations from the number of channels in which the kinks are detected. The limited spectral resolution prevents us from measuring velocity deviations smaller than 640 m s −1 . By comparing with the expected location of the isovelocity curves if the disks were in Keplerian rotation, we estimate the observed perturbations to be of the order of 10%–15% of the local Keplerian velocity (Table 1 ). From our previous modeling of velocity kinks, we expect masses of the order of 1–3 M Jup . In HD 143006, the velocity deviation appears significantly larger, pointing toward a more massive planet. With the exception of HD 143006, such masses are larger by a factor of 4–10 than the masses derived from the continuum gaps by Zhang et al. ( 2018 ) or Lodato et al. ( 2019 ). We found a similar discrepancy for HD 97048 (Pinte et al. 2019 ), where to get a coherent match to both the continuum and line data, our models required the dust grains dominating the emission to have a Stokes number of a few 10 −2 , suggesting very porous and/or fluffy aggregates. The high detection rate of velocity kinks at several tens of astronomical units in the DSHARP data set may appear in contradiction with the occurrence rate of known giant extrasolar planets at large distance from their host stars: in the range of a few up to 5% for massive planets ( M > 2 M Jup )