adsabs/WIESP2022-NER huggingface dataset:
Paper: 2018ApJ...860...20S (acknowledgments)
Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center. Results were partially obtained using the analysis software Pynbody ( https://github.com/pynbody/pynbody ). We thank the Fisk-Vanderbilt Masters-to-PhD Bridge program for the funding and support of this research. We also wish to thank the anonymous referee for their thorough reading of the manucript and their useful comments which greatly improved its quality. J.B. acknowledges generous support from the Helen Gurley Brown Trust. M.V. acknowledges support from NASA award ATP NNX10AC84G.
Paper: 2017ApJ...839L..24M (fulltext)
in Section 2.3.2 . 3.3. Gravitationally Unstable Disk Figure 3 (right) shows the simulated observations for a gravitationally unstable disk with Σ ∝ R −0.5 and T ∝ R −0.75 . The disk mass is 0.24 M ⊙ , leading to a disk-to-star-mass ratio of 0.49. Even with this relatively massive disk, the combined system mass lies within the limits discussed in Section 2.3.1 . The simulated unsharp masking observation reproduces the large-scale spiral arms, the dark crescents, and the bright inner ellipse, while the deprojected image shows two large-scale spirals analogous to Figure 1 (right). 4. Discussion The combination of our hydrodynamic modeling and simulated observations allows us to put strong constraints on the disk structure from which the submillimeter continuum emission originates. Throughout all of our models, we find that a steeply declining surface mass density beyond ≈300 au is key to producing a close match to the masked image. Figure 4 shows the scaled radial intensity profile of our successful self-gravitating disk and the radial intensity profile of the successful companion simulations compared to the observational data from Pérez et al. ( 2016 ) and the model of Andrews et al. ( 2009 ). The steep decline beyond ≈300 au in our simulation manifests itself in the form of a steep emission profile at large radii that turns over at approximately the right radius, matching the observed profile well. The modest scaling factor for the self-gravitating disk (∼1.5) is well within uncertainties associated with dust-to-gas ratios and/or grain opacities for circumstellar disks. Figure 4. Radial emission profiles for the successful gravitationally unstable disk simulation (red), which has been decreased by a factor of ∼1.5 (see the text) and the successful companion disk simulation (blue). Also shown are data from Pérez et al. ( 2016 ; black points) and the best-fit model from Andrews et al. ( 2009 ; black dashes). The steep decline beyond ≈300 au is key to matching the observed morphology in the simulated images. We note that the resulting Toomre profile dips marginally below 1 for a limited radial range in our successful self-gravitating disk. However, this disk shows no sign of fragmentation even though we evolve it for many dynamical times for this radial range. On the other hand, a companion beyond the spirals (≳300 au) is unlikely to have formed by core accretion. This suggests that, should the companion hypothesis be correct, this would hint that the Elias 2–27 disk may have formed a fragment by gravitational instability in the past. We also stress the importance of applying an unsharp mask to our simulated observations. While such a mask is primarily applied to increase the contrast of the image, subtle changes are introduced to the resulting image that allow us to remove models from consideration. Changes in the surface density profile affect the radial locations at which there is an excess or deficit with respect to a Gaussian mask. This
Paper: 2017ApJ...845...39O (acknowledgments)
We are grateful to the anonymous reviewer for constructive comments that helped to improve the manuscript. This work has extensively used NASA Astrophysics Data System, and the SIMBAD database, operated at CDS, Strasbourg, France. This publication made use of data products provided by the NASA/IPAC Infrared Science Archive. We are grateful to Dr. J Maíz Apellániz for kindly providing us with the optical spectrum of Cyg OB2 12 and to Dr. M Mapelli for a useful discussion on the dynamics of multiple systems. L.M.O. acknowledges support by DLR grant 50 OR 1302. A.S. is supported by the Deutsche Forschungsgemeinschaft (DFG) under grant HA 1455/26. D.P.H. was supported by NASA grant GO5-16009A. Facility: CXO (HETG/ACIS) .
Paper: 2017MNRAS.470.3095R (fulltext)
factor. This equation has the solution , where ‘en’ corresponds to the entry time of a perturbation mode into the horizon. Then, at the time at which a dark matter halo becomes non-linear (i.e. δ D ∼ 1), the density contrast of baryonic matter also approaches one. In the non-linear phase of structure formation, assuming a top-hat spherical model, each shell collapses without crossing the other shells and at the turnaround time structures start collapsing and finally virialize (Padmanabhan 1993 ). If we ignore the dissipation of baryonic matter at the first stage of virialization, then baryonic matter particles will have almost the same amount of kinetic and potential energy as dark matter particles and will virialize at the same time as dark matter fluid. Then, in the gravitational potential of dark matter, we expect that baryonic matter extends to the same scale as the dark matter structure. We can now calculate the density of baryonic matter in the dark matter halo from the following relation: where h ν 0 is the energy of CMB photons, m p is the mass of a proton and the ‘zero’ sub/superscript corresponds to the value of parameters at the present time. The important issue concerning the amount of baryonic matter within the gravitational potential of dark matter is the possibility of formation of baryonic structure. Formation of baryonic structure after the virialization of a halo is possible if plasma can cool and fall to the centre of the gravitational potential of the dark matter. The essential criterion is comparing the dynamical time-scale with the cooling time-scale of the baryonic matter. The dynamical time-scale for a test particle in the potential of dark matter is given by and, on the other hand, the cooling time-scale is where σ T is the Thomson cross-section and α is the fine-structure constant. For t cool t grav , we have a sufficient condition for the formation of baryonic structures. Substituting temperature from the virial condition, we get the simple result where baryonic and dark matter are enclosed within the same radius R . Integrating from equation ( 32 ) and equating it with equation ( 35 ), we obtain the following relation between the size of structure and the mass of baryonic matter in terms of η B : where η 10,B is the definition of η B normalized to 10 −10 . For a Galactic halo with mass of order of M D ≃ 10 12 M ⊙ , for η 10,B > 10 −5 , a structure with the mass of a globular cluster can form within this dark halo. Another lower value for the baryonic asymmetry could be η 10,B ≃ 10 −12 , where only one star with M min ∼ 0.1 M ⊙ condenses to form a single star within a 10 12 solar mass halo. We can think about another extreme case, having only one star within the cosmological horizon. In this case, we can write the η B parameter in terms of the minimum mass for a star and the mass of matter within the horizon (i.e. M H ), where m X and m p are the mass of a dark matter particle and the proton mass. Substituting the
Paper: 2016A&A...587A..32M (fulltext)
but it also reorganises the field topology, reducing the pinching of field lines close to the protostellar object, which also hinders the braking mechanism. Magnetic flux freezing and magnetic braking play a central role in the formation and development of the structures during the collapse. While in iMHD strongly amplified fields launch powerful magnetically supported outflows, these latter are much weaker or even disappear in niMHD. Misalignment between the initial rotation axis and the magnetic field direction does not appear to affect the niMHD results, showing that the physical flux dissipation due to ambipolar diffusion dominates the effects of initial configuration or numerical diffusion. For iMHD models, the additional mixing due to a tilted configuration also produces a diffusion plateau, similar to the ambipolar calculations. The disks that form in iMHD, characterised by strong magnetic support and an inflated shape (due to toroidal field lines loaded by infalling matter) strongly differ from the flat disks that form in niMHD. Formation and long-term evolution of disks in ideal MHD, however, are of dubious validity. Furthermore, the excessive magnetic braking generates unphysical counter-rotation inside the outflow or the magnetic tower. Interchange instabilities develop at the interface between the core and the disk, producing a redistribution of the flux and displacement of the core and disrupting the top-bottom symmetry in the system. Mesh resolution is found to strongly affect the simulation results in iMHD. None of these effects is observed in the niMHD simulations if the resolution is high enough. Disks with Keplerian velocity profiles around the protostar form in all our niMHD simulations for all different magnetisations and inclination angles. Their size and mass, however, is significantly reduced (by a factor ) in the more magnetised case () because of the increased braking. Such a magnetisation value seems to be typical of most molecular clouds. Aligned and misaligned initial configurations have no consequence on the disk properties in niMHD and yield disks with very similar properties. Magnetic flux diffusivity due to ambipolar diffusion thus appears to play a dominant role during the first protostellar collapse and the formation of the first Larson core and its surrounding disk, and it appears to dominate processes such as magnetic field and rotation axis orientations. Flux diffusion during the collapse allows the formation of quasi-Keplerian disks, solving the “disk formation crisis” found in ideal MHD. The mass, size, and magnetic properties (plasma ) of these disks, however, strongly depend on the initial magnetisation ( parameter) of the cloud, and in all cases the disks are significantly smaller and less massive than those found in pure hydrodynamics calculations. Characterisation of this plasma is of major importance to characterise viscous transport in disks, notably in the MRI. To complete our study, we will
Paper: 2016A&A...585A..51D (fulltext)
For Ion2 , the observed ratio is 15 making Ion2 an outlier in the oxygen abundance vs. the [O iii ]/[O ii ] ratio relation and the EW(H) (i.e., sSFR) vs. the [O iii ]/[O ii ] ratio (Fig. 2, Stasińska et al. 2015 ); the Ion2 ratio is higher by 0.6 dex for the observed EW(H) (Table 1 ) and the ratio is higher by 1 dex than galaxies in the SDSS sample with similar metallicities. The Ion2 [O iii ]/[O ii ] ratio is also higher than expected for the derived stellar mass, SFR, and sSFR ( Nakajima Ouchi 2014 ). Therefore, we conclude that the extreme [O iii ]/[O ii ] ratio is due to unusual physical conditions (density-bounded nebula), which imply a low column density of neutral gas, and so favor leakage of ionizing photons ( Nakajima Ouchi 2014 ). 3.3. Physical properties derived from the photometry While the emission lines highlight Ion2 ISM physical properties, we also use the photometry to confirm findings such as the large [O iii ] emission and derive other physical parameters. From Fig. 8 , the jump in the -band is evident, while the continuum level in the adjacent bands, , and IRAC Channel 1 is 24.15. The magnitude in the HAWKI -band corresponds to an additional flux of erg/s/cm, which corresponds to an observed equivalent width of 6700 Å (1600 Å rest-frame). The total flux derived for H+[O iii ] from the MOSFIRE spectrum (see Table 1 ) is fully compatible with the flux estimated from the -band excess (after correcting for slit losses for the three lines, see above). The derived + [OIII] equivalent width is one of the largest ever observed at . The measured line ratios among the H+ [O iii ] suggest the [O iii ] rest-frame equivalent width is 1100 Å, with a similar value to the few extreme cases reported in the literature at ( Atek et al. 2011 ; Amorín et al. 2014b ; Maseda et al. 2014 ). The [O iii ]/H ratio is also higher than the value reported in Holden et al. (2014) for LBGs at , while the ratio is higher in this sample than in the local Universe ( Brinchmann et al. 2004 ). At large equivalent widths of H+[O iii ] have also been reported, measured through photometric excess detected in the Spitzer /IRAC channels (e.g., Finkelstein et al. 2013 ; Smit et al. 2014 ; Oesch et al. 2015 ). While these cases can be spectroscopically investigated only with future facilities, such as the James Webb Space Telescope (JWST) and Extremely Large Telescope class, in our case the MOSFIRE near-infrared spectroscopy has allowed us to access the details of the lines. Fig. 7 Comparison of the metallicity and ionization parameter () between the mean sample properties from Nakajima Ouchi (2014) and Ion2 with 1 uncertainties. Ion2 is compared to local galaxies from the SDSS survey, a galaxy sample at , a Lyman break galaxy (LBG) sample at , a Lyman alpha emitter (LAE) sample at , local Lyman break analogues (LBAs), LyC emitters, and Green Peas (GPs). See Nakajima Ouchi (2014) and references therein for a complete description of these samples. We derive the SFR
Paper: 2020ApJ...892L...1L (fulltext)
of AT2019DSG, the S/N is too low (3), hence the polarization no longer follows a Gaussian distribution, but a Rice distribution instead (Plaszczynski et al. 2014 ). To obtain a robust estimate of the upper limit, we used the formulation by Plaszczynski et al. ( 2014 ). More specifically, for a 68% confidence level (corresponding to 1 σ ), the upper limit can be estimated as:We thus obtained an upper limit of 2.7% at the 1 σ level for the second epoch of AT2019DSG. It appears that AT2019DSG exhibits a polarization of ∼2% at the later epoch. However, we also need to take into account the interstellar polarization (ISP), which comes from the line-of-sight dust contributed by the Milky Way (MWG) and the host galaxy. By checking the extinction map, the line-of-sight MWG extinction— E ( B – V )—is ∼0.088 from Schlafly Finkbeiner ( 2011 ) and 0.102 from Schlegel et al. ( 1998 ). According to the empirical upper limits from Serkowski et al. ( 1975 ), this can translate into P as high as ∼1%. Another way to measure line-of-sight MWG dust polarization is to use field stars. In this regard, we also measure the polarization of a bright field star ∼1′ west of AT2019DSG. The field star polarization is at 0.5% level, consistent with the empirical upper limits from Serkowski et al. ( 1975 ). In addition to line-of-sight MWG dust polarization, there can also be polarization coming from the host. To constrain it, we used multiband photometry from Pan-STARRS (Chambers et al. 2016 ) and fit the host galaxy spectral energy distribution (SED) with LePhare (Arnouts et al. 1999 ; Ilbert et al. 2006 ). This gives an E ( B – V ) of 0.05, relatively small compared to the line-of-sight MWG extinction, hence the host galaxy plays an insignificant role in contributing to the polarization. This suggests that the high polarization (∼9%) in the optical in the earlier epoch cannot be explained by the MWG dust extinction alone. This is different from the case of Swift J164449.3+573451, where there was no polarization in the radio wavelength, and Wiersema et al. ( 2012 ) attributed the high linear polarization in the near-infrared to the dust induced polarization by the host galaxy. Table 2 Polarization Measurements We also include a light curve of AT2019DSG from the alerts issued by the public ZTF survey, aggregrated by the community broker ANTARES 8 8 https://antares.noao.edu (Saha et al. 2014 , 2016 ; Narayan et al. 2018 ) in both g and r bands, as shown in Figure 3 . With the light curve in hand, we can also check whether the TDE faded significantly between the first and second epoch, and whether the polarization signal is diluted (hence reduced) by the light from host galaxy. As can be seen in Figure 3 , the light curve indicates that the brightness of the TDE decreased from 17.87 ± 0.06 mag to 18.46 ± 0.10 mag in the g band between the two epochs. We note that the ZTF measurement is based on difference imaging, meaning that the photometry is solely from the light of
Paper: 2017MNRAS.464.3108G (acknowledgments)
The authors thank Michael Cooper, Marla Geha, Coral Wheeler, Jose Oñorbe, Ferah Munshi, Erik Tollerud, Frank van den Bosch, Andrew Wetzel, Massimo Ricotti, Phil Hopkins, Justin Read, and the anonymous referee for valuable comments that have improved the manuscript. We also thank Aaron Dutton for providing the NIHAO data. Support for SGK was provided by NASA through Einstein Postdoctoral Fellowship grant number PF5-160136 awarded by the Chandra X-ray Center, which is operated by the Smithsonian Astrophysical Observatory for NASA under contract NAS8-03060. MBK acknowledges support from the National Science Foundation (grant AST-1517226) and from NASA through HST theory grants (programmes AR-12836 and AR-13888) awarded by the Space Telescope Science Institute (STScI), which is operated by the Association of Universities for Research in Astronomy (AURA), Inc., under NASA contract NAS5-26555. We also acknowledge the support of the Greenplanet cluster at UCI, where much of the analysis was performed. This work also made use of matplotlib (Hunter 2007 ), astropy (Astropy Collaboration et al. 2013 ), numpy (van der Walt, Colbert Varoquaux 2011 ), scipy (Jones et al. 01 ), and ipython (Perez Granger 2007 ). This research has made use of NASA's Astrophysics Data System.
Paper: 2018MNRAS.473...59A (acknowledgments)
Acknowledgements We thank the staff of the GMRT who have made these observations possible. The GMRT is run by the National Centre for Radio Astrophysics of the Tata Institute of Fundamental Research. NK acknowledges support from the Department of Science and Technology via a Swarnajayanti Fellowship (DST/SJF/PSA-01/2012-13). We thank an anonymous referee for a very helpful report on an earlier draft that significantly improved the quality of this paper.
Paper: 2015ApJ...814...93S (acknowledgments)
We thank the anonymous referee for a careful review and valuable comments. We appreciate Y. Fujita and Y. Ohira for helpful discussion. This work is partially supported by the Grant-in-Aid for Scientific Research, No. 25400227 from the MEXT of Japan (KA).
Paper: 2016ApJ...820..113J (acknowledgments)
We wish to thank Marc De Rosa for contributing the PFSS library to SolarSoft, and for helpful reponses to questions about the software. We also wish to acknowledge Figen Oktem for useful discussions regarding regularization in optimization problems, and Leon Ofman for similarly useful discussions of coronal MHD simulations.
Paper: 2018ApJ...859..127B (fulltext)
range. Figure 2. Normalized (see Equations ( 1 )–( 3 )) power spectral densities observed by MMS1 at MHD scales in the quasi-perpendicular MSH during the time interval 07:00–08:00 UT on 2017 January 8. The parallel and perpendicular magnetic-field components measured by FGM are shown in red and dark blue, respectively. The parallel and perpendicular electric-field components measured by EDP are shown in orange and light blue, respectively. The density measured by FPI is displayed in green. The associated black solid lines represent the slope of the observed spectra. The vertical dashed line displays the electron gyrofrequency, while the dotted and dashed–dotted lines show the electron gyroradius and inertial length, respectively, estimated using Taylor’s hypothesis. The insert shows the anisotropy A at different frequencies. 3. Kinetic-scale Turbulence In order to study magnetic fluctuations in the sub-ion range, the burst-mode magnetic waveforms from FGM and SCM instruments are merged using an FIR filter (see, e.g., Breuillard et al. 2016 ), and B 0 and n 0 are defined as low-pass, filtered fluctuations at 0.1 Hz (i.e., below the frequency range of interest). Spatial and temporal scales are again determined as described in Section 1 ; however, as we will see below, intense whistler turbulence is detected in the quasi-perpendicular MSH, which might violate Taylor’s hypothesis. This is discussed in the next two sections. 3.1. Quasi-parallel Magnetosheath In this case, we have v bulk / v A > 3 and v bulk / v ms > 2 (see Table 1 , case 3), thus the Taylor hypothesis should not be significantly violated, and the frequency shift and flattening of the spectrum should be negligible (see Section 1 ). Figure 3 shows that at sub-ion scales (i.e., below the largest electron scale being f ρe here) the anisotropy of magnetic fluctuations is much smaller (here A ≈ 1) than in the MHD range, as noted in the previous section. Both perpendicular and parallel magnetic spectra follow the classical power law, f −2.8 , which is expected by KAWs and whistler turbulence. In this range, both parallel and perpendicular electric fluctuations follow an f −0.8 power law, i.e., , as expected from theoretical models (see Section 4 ). However, if the density spectrum also roughly follows an f −2.8 power law, , as in the MHD range, which is not expected from any of the models cited above. We note here that the density spectrum is affected by Poisson noise (for more details, see Gershman et al. 2015 ) above 10 Hz (not shown) and the flattening of the spectrum is not physical. Figure 3. Normalized (see Equations ( 1 )–( 3 )) power spectral densities observed by MMS1 at kinetic scales in the quasi-parallel MSH during the time interval 00:16–00:18 UT on 2017 January 18. The parallel and perpendicular magnetic-field components measured by FGM are shown in red and dark blue, respectively. The parallel and perpendicular electric-field components measured by EDP are shown in
Paper: 2019ApJ...875...27C (acknowledgments)
We gratefully acknowledge the Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO) for the support of the FELIX Laboratory. This work is supported by the European MCSA ITN network “EUROPAH” (grant No. 722346) and the NWO Dutch Astrochemistry Network (DAN-II, grant No. 648.000.030). For the computational work, we acknowledge support by NWO under the “Rekentijd” program (grant No. 17603) and the SurfSARA staff.