adsabs/WIESP2022-NER huggingface dataset:
Paper: 2018ApJ...860L..13P (fulltext)
light images with HST /STIS at 260 au, and estimated the mass of a potential planet to be 0.4 M jup (based on some simple analytical derivation). Isella et al. ( 2016 ) also detected a small dip in the integrated CO brightness profile at ≈22 (see their Figure 1, or Figure 5 in Liu et al. 2018 ). In our model, the gap appears in scattered light for a planet mass larger than 2 M jup , but remains undetected in the synthetic CO maps. The final profile of a planetary gap establishes itself on a viscous timescale (thousands of orbits with a viscosity of 10 −3 ), however, and the gap width and depth in our models are only lower limits. The effect of the planet appears fainter in the 13 CO channels maps than in the 12 CO maps, even if the planet is located in the midplane. This is due to optical depth and vertical temperature gradient effects: the 12 CO is coming from a vertically narrow and warm layer above the midplane, while the 13 CO is originating from a deeper, thicker layer, where the disk is almost vertically isothermal, resulting in a uniform emissivity that washes out some of the kinematics signal. Are we seeing the signature of an embedded planet? Can we exclude wishful thinking? The strongest evidence is that the perturbation to the disk kinematics is highly localized in both space and velocity. This excludes any mechanism that merely produces axisymmetric rings in disks. This excludes, for example, ice lines (Zhang et al. 2015 ), self-induced dust traps (Gonzalez et al. 2015 ), instabilities (Takahashi Inutsuka 2014 ; Lorén-Aguilar Bate 2015 ), and zonal flows (Flock et al. 2015 ). A spiral wave could in principle result from the disk self-gravity, but multiple, large-scale spirals would be expected in that case (e.g., Dipierro et al. 2015 ), which the localized deviation seen in HD 163296 would seem to exclude. The localized nature of the kinematic perturbation, that it occurs close to the gap found by Grady et al. ( 2000 ), and the similarity to the signatures predicted by our hydrodynamic models is strong evidence for a young protoplanet in a gas-rich disk. However, confirmation with direct imaging is the only way to be sure. The relatively large planet mass and its known location in the disk means direct imaging follow-up might be able to detect it, depending on how embedded it is in the disk. So far, no point source has been detected at the location of the potential planet with near-IR adaptive optics systems. A 2 M Jup planet is consistent with the upper limits (for an unobscured planet) obtained by adaptive optics systems, such as SPHERE (Muro-Arena et al. 2018 ) and Keck L’ (Guidi et al. submitted). Using the formalism developed in Pinte et al. ( 2018 ), we find that the velocity kink is located at a distance of ≈260 au, and an elevation above the midplane of ≈70 au. Assuming that the potential planet is located in the midplane, it would be at a projected distance of 2.3 ± 02 and PA = −3° ± 5° from the star, where we
Paper: 2018MNRAS.481.3394O (fulltext)
that sometimes show a periodic structure (one of the most famous example is the Guitar nebula, see e.g. Chatterjee Cordes 2002 , 2004 ; van Kerkwijk Ingle 2008 ). While at present the structures in the vicinity of the bow-shock head are reasonably well understood, the same cannot be said of the structures in the tail (Brownsberger Romani 2014 ; Klingler et al. 2016 ; Pavan et al. 2016 ). The possibility that the dynamics of PWNe can be strongly affected by the mass loading was discussed by Bucciantini and Bandiera ( 2001 ) and Bucciantini ( 2002c ). There the authors have shown that a non-negligible fraction of neutral atoms is expected to penetrate in the bow shock through shocked ISM, and then interact with the pulsar wind, modifying the predicted dynamics. These first models provide a good description of both the hydrogen penetration length-scale and the Hα luminosity. In Morlino, Lyutikov, and Vorster ( 2015 ) a quasi-1D steady-state model has been proposed to investigate the effect of mass loading on the tail morphology of BSPWNe. If a significant fraction of neutral atoms from the ISM penetrate into the bow shock, they can undergo ionization essentially by interacting with the UV photons emitted by the relativistic plasma of the nebula. The resulting protons and electrons interact, in turn, with the wind thorough its magnetic field, leading to a net mass loading of the shocked wind in the tail. The newly formed protons and electrons are at rest in the rest frame of the ISM. Moreover they originate from the cold neutrals of the ISM, which carry negligible thermal energy. Hence they do not add momentum or internal energy to the flow (they however add their rest mass energy). Given that momentum and energy are conserved, the rise in rest mass energy density causes the wind to slow down and the pressure to rise, resulting ultimately in a lateral expansion. This effect indeed produces a shape which resembles the head-and-shoulder morphology. Nevertheless the analytic model by Morlino et al. ( 2015 ) has few shortcomings: being 1D it does not account for the fluid dynamics in the lateral direction, the ISM ram pressure is neglected despite the supersonic motion, and, being stationary, it cannot capture possible instabilities. In this paper we extend this model by means of 2D relativistic HD axisymmetric simulations, with the aim of validating the head–shoulder morphology of BSPWNe predicted by the aforementioned work, and extending it beyond its limitations. Although magnetic field might influence the dynamics of the flow, its response to mass loading, and the expected opening of the tail, in order to avoid a further level of complexity we limit this work to pure HD. This paper is organized as follows: in Section 2 the numerical tool and setup are described; in Section 3 we present and discuss our findings. Conclusions are then drawn in Section 4 . 2 NUMERICAL SETUP The typical length-scale of BSPWNe is the so called stand off distance d
Paper: 2016ApJ...817L..18K (fulltext)
transfer, to atmospheric chemistry and dynamics, and they influence—if not control—aspects such as the surface temperature and, thus, the potential habitability of a terrestrial planet (Marley et al. 2013 ). Understanding the impact of clouds is thus instrumental for the study of planetary climates. Clouds composed of carbon dioxide (CO 2 ) ice particles are important for cold, CO 2 -rich atmospheres. This includes, for example, the present and early Mars (Forget Pierrehumbert 1997 ), the early Earth (Caldeira Kasting 1992 ), or terrestrial exoplanets at the outer boundary of the habitable zone (HZ; Kasting et al. 1993 ; Forget Pierrehumbert 1997 ). Provided that condensation nuclei are available, such clouds would form easily in a supersaturated atmosphere. Such as in the case of water clouds (e.g., Kitzmann et al. 2010 ), the presence of CO 2 clouds will first result in an increase of the planetary albedo by scattering incident stellar radiation back to space, which leads to a cooling effect (albedo effect). In contrast to liquid or solid water, CO 2 ice is mostly transparent with respect to absorption in the infrared (Hansen 1997 , 2005 ). Thus, as argued by Forget Pierrehumbert ( 1997 ) or Kasting et al. ( 1993 ), a classical greenhouse effect by absorption and re-emission of thermal radiation is unlikely to occur for a cloud composed of dry ice. On the other hand, CO 2 ice particles can efficiently scatter thermal radiation back to the planetary surface, thereby exhibiting a scattering greenhouse effect. In their seminal study, Forget Pierrehumbert ( 1997 ) showed that this scattering greenhouse effect of CO 2 ice clouds alone would have been efficient enough to allow for liquid water on the surface of the early Mars. This strong heating effect was also found in later studies by, e.g., Pierrehumbert Erlick ( 1998 ), Mischna et al. ( 2000 ), or Colaprete Toon ( 2003 ). However, by using three-dimensional general circulation models, it has been suggested, that a limiting factor for the impact of CO 2 clouds on early Mars might be the cloud coverage, which could be well below 100% (Forget et al. 2013 ). In particular, the outer boundary of the classical HZ might also be influenced by the formation of CO 2 ice clouds and their corresponding climatic impact. For the Sun, Forget Pierrehumbert ( 1997 ) reported an outer HZ boundary of 2.4 AU for a planet fully covered with CO 2 clouds, which is far larger than the cloud-free value of 1.67 AU Kasting et al. ( 1993 ). The competing radiative cooling and heating effects are individually large, but partly balance each other. That means that small errors in the description of one of these radiative interactions can lead to large errors in a cloud’s net effect. So far, all previous studies on the climatic impact of CO 2 clouds used a simplified treatment for the numerical solution of the radiative transfer equation to determine the atmospheric and surface temperatures. In particular, two-stream
Paper: 2020MNRAS.494.4665P (fulltext)
implications for the proposed loose correlation between explosion energy and kick velocity (Bray Eldridge 2016 ; Janka 2017 ; Vigna-Gómez et al. 2018 ). Our results constitute further evidence that this correlation is not a tight one. More likely, the explosion energy only determines the maximum attainable kick velocity, below which one expects a distribution of kicks depending on the degree of unipolarity or bipolarity (Müller et al. 2019 ). This can be accounted for in a more general formulation than in Bray Eldridge ( 2016 ) by a factor that measures the explosion asymmetry (Janka 2017 ). The evolution of the spin-kick angle α in model m39 is noteworthy. Some observations have suggested that the birth spins and kicks of neutron stars tend to be aligned (Johnston et al. 2005 ; Ng Romani 2007 ; Noutsos et al. 2013 ). However, even though hydrodynamic mechanisms for spin-kick alignment have been proposed (Janka 2017 ), no trend towards spin-kick alignment has been observed so far in 3D CCSN simulations of non-rotating progenitors (Wongwathanarat et al. 2013 ; Müller et al. 2019 ). For our non-rotating explosion model y20, we also find a large angle α ≈ 70° between the spin and kick. For the rapidly rotating model m39, however, the spin-kick angle stays at about α ≈ 30°. In this case, spin-kick alignment comes about because the bipolar outflows are aligned with the initial rotation axis, which is not changed appreciably by asymmetric accretion on to the PNS. This suggests that progenitor rotation could play a role in explaining spin-kick alignment (provided that the observational evidence remains robust). However, even for model m39, the spin-kick alignment is not perfect, and is not clear whether the polar alignment of the outflows is a robust feature for rotating progenitors. In fact, some previous 3D supernova simulations of rotating progenitors rather find that the explosion develops preferably in the equatorial plane (Summa et al. 2018 ; Takiwaki Kotake 2018 ). Clearly, more simulations are required to determine the implications of rotation for the explosion morphology and spin-kick alignment. 6 GRAVITATIONAL WAVE EMISSION The gravitational-wave emission for our models, as measured by an observer at the pole and the equator, is shown in Fig. 6 . The high mass and rotation of model m39 results in high gravitational-wave amplitudes of up to 40 cm at the pole and over 100 cm at the equator. Model y20 reaches amplitudes of ∼10 cm at the pole, and ∼18 cm at the equator. Model s18np has a much lower amplitude of ∼5 cm at the equator, due to the lack of shock revival in this model, however its prompt convection signal in the direction of the equator reaches amplitudes as high as model y20. Figure 6. The gravitational-wave emission for our models as measured at the pole (left-hand panel) and the equator (right-hand panel). Top is model m39, middle is model s18np, and bottom is model y20. All models show the rise of gravitational-wave frequency
Paper: 2017ApJ...846L..18C (fulltext)
the total magnetic fluctuations and of the parallel electric fluctuations, and (top and bottom rows, respectively) for (left column) and β i = 0.2 (right column). A classical intermittency analysis has been performed on both simulations at about the peak of the nonlinear activity. In order to define the large-scale limit of the inertial range, we evaluated the perpendicular and parallel autocorrelation functions, respectively defined as and (Frisch 1995 ). We assumed isotropy in the perpendicular xy -plane, with the parallel direction along B 0 , i.e., along z . The e -folding length approximately gives the integral scale, which is about in the perpendicular direction (corresponding to ), for both regimes. The situation is different in the parallel direction, where the parallel correlation length is for β p = 0.2, while it is for β p = 1 (corresponding to and ∼0.5, respectively). This is in qualitative agreement with the features spotted in Figure 1 and quantitatively with the corresponding spectra (see Figure 4 ), indicating differences already in the large-scale properties of the fluctuations possibly due to a different decorrelation mechanism along the mean field. The level of intermittency can be better quantified by the probability distribution functions (PDFs) of the magnetic field increments at a given scale r , defined asWe show here the statistics of the perpendicular increments, namely, , spanning this increment from lengths larger than the correlation scale , down to the smallest available scale (Δ x ∼ 0.08 d p ). These distributions are reported in Figure 3 (a) for the β p = 0.2 regime for three cases, namely, and 0.08. These PDFs, as expected, become increasingly intermittent going toward smaller scales. In order to compare among cases, and among different times, we measured the scale-dependent kurtosis χ —the fourth-order moment of the increments in Equation ( 4 )—that can be measured asThis quantity is reported in Figure 3 (b), as a function of the perpendicular scale r , for the two values of β , at two distinct times. At large scales, for r > 5 d p , the distribution becomes Gaussian, where χ ∼ 3, in agreement with the computation of the correlation lengths. At small scales, in the inertial range of turbulence, there is an enhancement due to the intermittent nature of the cascade, due to the presence of coherent structures and nonlinear waves. At the smallest scales, a saturation of the multifractality is observed, in agreement with observations in the SW. In fact, the study of high-order structure functions up to the sixth moment and of their exponents, shows deviation from monofractality (not shown here). Here, this process of saturation might also be slightly affected by the presence of artificial dissipation. It is important to note that at scales in the inertial-dispersive range, the case with β p = 0.2 is more intermittent than the β p = 1 regime, indicating a higher degree of coherency in the small-scale fluctuations.
Paper: 2016MNRAS.463..205B (fulltext)
before the analyses pipelines were finalized. Our decision to focus on the NGC exclusively did come after a comparison with S16 had occurred, though we believe that we are well justified in our choice. S16 provide the current best weak lensing mass calibration of redMaPPer clusters, and they discuss in detail how their mass calibration compares to others in the literature. While the constraints on the slope of the mass–richness relation are in good agreement between the two works, there is mild tension on the recovered amplitude assuming our fiducial cosmology, with the clustering-derived constraints preferring a somewhat higher amplitude. At the richness pivot point used in this work, λ 0 = 35, S16 predict log 10 ( M /M ⊙ ) = 14.43 ± 0.04, while our constraints yield log 10 ( M /M ⊙ ) = 14.62 ± 0.08; this discrepancy corresponds to roughly 2.2σ tension. Because the clustering analysis prefers a slightly lower value of α than the weak lensing analysis, this tension is reduced for λ > 35. For λ 35, the tension remains roughly the same since the error bars increase as one moves away from the λ pivot point. We postpone a discussion of the origin of this tension, and a more detailed comparison of the two results, to future work. That is, our current results reflect our best understanding of both the weak lensing and clustering analysis prior to the comparison of the two works. We have also considered a power-law bias–richness relation as per equation ( 10 ). This model has five parameters: A λ , α λ , β λ and two bias parameters for 5 λ 20 clusters in the two redshift bins. Fitting this model to the data, we find A λ = 3.54 ± 0.13, α λ = 0.57 ± 0.08 and β λ = 2.0 ± 1.1 with χ 2 /d.o.f. = 57.7/75. 7 CHARACTERIZING THE UNCERTAINTY IN THE MASS–RICHNESS RELATION The uncertainties on the mass–richness parameters presented in Fig. 6 and Table 1 receive contributions from several sources: statistical noise in the measurement of the angular correlation functions, uncertainty on the parameters of the line-of-sight projection model, uncertainty on the parameters of the assembly bias model and scatter around the b ( M ) relation from Tinker et al. ( 2010 ). In addition to these sources of scatter that are explicitly included in our model, it is also possible that our measurement is affected by systematic biases that we have not modelled. Below, we determine the approximate contributions of both modelled sources of scatter and unmodelled systematic errors to the uncertainty budget of our parameter constraints. 7.1 Statistical noise in the correlation function measurement We first investigate how statistical noise in the measurement of w αβ (θ) contributes to our parameter uncertainties. The contribution of statistical noise to our parameter uncertainties can be determined by setting the parameters of the line-of-sight projection model, the parameters of the assembly bias model and b scaling to constant values rather than allowing these parameters to vary.
Paper: 2020MNRAS.491.2465K (fulltext)
however, need to find more stars with similar travel times as S5-HVS1. It is remarkable that the age of S5-HVS1 ejection is close to both the age of the disc of young stars around the GC (Lu etal. 2013 ) and the age of the Fermi bubbles (Bland-Hawthorn Cohen 2003 ; Su, Slatyer Finkbeiner 2010 ) which have been potentially associated with the recent accretion event in the GC (Zubovas, King Nayakshin 2011 ; Guo Mathews 2012 ), thus potentially linking these different astrophysical objects. An alternative scenario that would naturally produce a time-variable HVS spectrum is that involving an Intermediate Mass Black Hole (IMBH) orbiting the GC (Yu Tremaine 2003 ; Levin 2006 ). In this mechanism, during the inspiral of the IMBH, the HVS production rate peaks and then subsides due to dynamical friction around the SMBH (Baumgardt, Gualandris Portegies Zwart 2006 ; Darbha etal. 2019 ), with the fastest HVS being ejected in the final phase of the in-spiral. This mechanism produces a strongly anisotropic distribution with the fastest stars in the orbital plane of the IMBH (Rasskazov etal. 2019 ). There is also some indication that the HVSs produced by this mechanism tend to have higher velocities and a flatter velocity spectrum than the classical Hills mechanism (Sesana, Haardt Madau 2007 ). While there is currently not much evidence for the presence of an IMBH in the GC (Gualandris Merritt 2009 ) other than a shallow stellar density slope that can be produced by an IMBH scattering (Baumgardt etal. 2006 ), if an IMBH inspiral happened a few Myr ago, then it would produce an excess of nearby and fast HVSs with a narrow range of ejection times. To test for this possibility we need to search for other nearby HVS and see if there is an excess of stars that were ejected at roughly the same time as S5-HVS1 (5Myr ago), are strongly anisotropic and that have a velocity spectrum inconsistent with the Hills mechanism. An interesting consequence of the fact that S5-HVS1 has lower mass than most other HVS in the halo is that its expected lifetime given the stellar mass of 2.3M is quite long around a 1Gyr. By the end of its life the star would have travelled a distance of 2Mpc, traversing a large fraction of the Local Group. This suggests that searching for such ejected stars at large distances from the MW or Andromeda (Sherwin, Loeb OLeary 2008 ) is quite promising. On top of being well separated in colourmagnitude space from other contaminants, an S5-HVS1-like star would eventually evolve on to the red giant branch and thus be detectable much more easily. Searches for S5-HVS1-like stars within the whole Local Group will be possible with upcoming deep imaging surveys like LSST (LSST Science Collaboration etal. 2009 ). In this paper, we tried to use the positionvelocity information on S5-HVS1 to constrain the distance from the Sun to the GC and the Galactic Solar velocity. We have not been able to constrain those simultaneously, mainly due to the precision of
Paper: 2021ApJ...908..219H (fulltext)
of this procedure at z = 6 (red) and z = 7 (blue) in Figure 4 as obtained by changing only the outflows (left) or changing only the column density (right). While both scenarios produce stacks that have consistent FWHM values with observations at z = 6, the changing outflows scenario yields also a consistent FWHM with z = 7 measurements. This also confirms that changing the column density predicts very high FWHM >400 km s −1 at z = 7. As quoted in the legend for changing the outflows scenario (left), z = 6 lines are broader than those at z = 7, and consistent with Pentericci et al. ( 2018 ). The lines are highly asymmetric with extended red wings. The blue peaks disappear due to the poor resolution. Figure 4. Example for stacks of randomly selected 52 mock spectra at z = 6 (red) and 19 mock spectra at z = 7 (blue) with f esc ( z = 7) ≈ 0.5 f esc ( z = 6) in agreement with the measured drop of X Ly α . We assembled the stacks following the method outlined in Pentericci et al. ( 2018 ) with spectral resolution R = 1390 (corresponding to Δ = 216 km s −1 ). All these spectra are either obtained by changing only outflows while keeping the column density N H I fixed (left) or changing only the column density N H I while keeping outflows fixed. In all cases, dust is kept fixed. In either scenario, the FWHM of stacks at z = 6 is consistent with values reported in Pentericci et al. ( 2018 , FWHM( z ∼ 6) = 300 ± 30). The FWHM of stacks obtained by changing outflows at z = 7 is also consistent with Pentericci et al. ( 2018 ) measurements (FWHM( z ∼ 7) = 220 ± 25) while those produced by changing the column density N H I are not, and hence indicating that changing the outflow can naturally lead to a higher Ly α escape as well as broader lines at lower redshifts as observations indicate. To quantify the width using the above recipe, we generate randomly 10,000 combination of stacks at z = 6 and z = 7 from the total number of model combinations (i.e., 143 and 201) in each scenario and compute their widths. We show the resulting width distribution at these redshifts in Figure 5 . Results from changing outflows and changing column density scenarios are presented by dashed and solid lines. Shaded red and blue areas show Pentericci et al. ( 2018 ) measurements at z ∼ 6 and z ∼ 7, respectively. From this exercise alone, we constrain the FWHM, using changing column density scenario, to 261.7 ± 14.3 km s −1 at z = 6 and 434.9 ± 47.8 km s −1 at z = 7, and using changing outflows scenario, to 291.5 ± 7.9 km s −1 z = 6 and 224.6 ± 22.8 km s −1 at z = 7. It is evident that, over all possible combinations and the prior range assumed, the changing outflows scenario produces consistent width distribution within the 1 σ level of Pentericci et al. ( 2018 ) measurements. This confirms that changing the column density predicts inconsistent width distributions. It might be noteworthy that while we use the Pentericci et al. ( 2018 ) results in this section, other studies of