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- Wallström, Sofia, 1988, et al.
(författare)
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ALMA Compact Array observations of the Fried Egg nebula: Evidence for large-scale asymmetric mass-loss from the yellow hypergiant IRAS 17163-3907
- 2017
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 597, s. A99, pp. 1-10
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Tidskriftsartikel (refereegranskat)abstract
- Yellow hypergiants are rare and represent a fast evolutionary stage of massive evolved stars. That evolutionary phase is characterised by a very intense mass loss, the understanding of which is still very limited. Here we report ALMA Compact Array observations of a 50??-mosaic toward the Fried Egg nebula, around one of the few Galactic yellow hypergiants IRAS 17163-3907. The emission from the 12CO J = 2-1 line, H30? recombination line, and continuum is imaged at a resolution of ~8??, revealing the morphology of the molecular environment around the star. The continuum emission is unresolved and peaks at the position of the star. The radio recombination line H30? shows unresolved emission at the star, with an approximately Gaussian spectrum centered on a velocity of 21 ± 3km s-1 with a width of 57 ± 6km s-1. In contrast, the CO 2-1 emission is complex and decomposes into several components beyond the contamination from interstellar gas in the line of sight. The CO spectrum toward the star is a broad plateau, centered at the systemic velocity of +18 km s-1 and with an expansion velocity of 100 ± 10km s-1. Assuming isotropic and constant mass-loss, we estimate a mass-loss rate of 8 ± 1.5 × 10-5M? yr-1. At a radius of 25?? from the star, we detect CO emission associated with the dust ring previously imaged by Herschel. The kinematics of this ring, however, is not consistent with an expanding shell, but show a velocity gradient of vsys ± 20km s-1. In addition, we find a puzzling bright feature radially connecting the star to the CO ring, at a velocity of +40 km s-1 relative to the star. This spur feature may trace a unidirectional ejection event from the star. Our ACA observations reveal the complex morphology around IRAS 17163 and illustrate the breakthroughs that ALMA will bring to the field of massive stellar evolution.
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| 2. |
- Bender, P., et al.
(författare)
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Distribution functions of magnetic nanoparticles determined by a numerical inversion method
- 2017
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Ingår i: New Journal of Physics. - : IOP Publishing. - 1367-2630. ; 19:7
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Tidskriftsartikel (refereegranskat)abstract
- In the present study, we applied a regularized inversion method to extract the particle size, magnetic moment and relaxation-time distribution of magnetic nanoparticles from small-angle x-ray scattering (SAXS), DC magnetization (DCM) and AC susceptibility (ACS) measurements. For the measurements the particles were colloidally dispersed in water. At first approximation the particles could be assumed to be spherically shaped and homogeneously magnetized single-domain particles. As model functions for the inversion, we used the particle form factor of a sphere (SAXS), the Langevin function (DCM) and the Debye model (ACS). The extracted distributions exhibited features/peaks that could be distinctly attributed to the individually dispersed and non-interacting nanoparticles. Further analysis of these peaks enabled, in combination with a prior characterization of the particle ensemble by electron microscopy and dynamic light scattering, a detailed structural and magnetic characterization of the particles. Additionally, all three extracted distributions featured peaks, which indicated deviations of the scattering (SAXS), magnetization (DCM) or relaxation (ACS) behavior from the one expected for individually dispersed, homogeneously magnetized nanoparticles. These deviations could be mainly attributed to partial agglomeration (SAXS, DCM, ACS), uncorrelated surface spins (DCM) and/or intra-well relaxation processes (ACS). The main advantage of the numerical inversion method is that no ad hoc assumptions regarding the line shape of the extracted distribution functions are required, which enabled the detection of these contributions. We highlighted this by comparing the results with the results obtained by standard model fits, where the functional form of the distributions was a priori assumed to be log-normal shaped.
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