[P-CG24] アルマによる惑星科学の新展開

[PCG24-09] The Synthetic ALMA Multiband Analysis of the Dust Properties of the TW Hya Protoplanetary Disk

*Seongjoong Kim¹、Hideko Nomura¹、Takashi Tsukagoshi²、Ryohei Kawabe^2,3,4、Takayuki Muto⁵ (1.Department of Earth and Planetary Sciences, Tokyo Institute of Technology、2.National Astronomical Observatory of Japan、3.The Graduate University for Advanced Studies (SOKENDAI)、4.Department of Astronomy, School of Science, University of Tokyo、5.Division of Liberal Arts, Kogakuin University)

キーワード：methods: observational, protoplanetary disks, stars: individual (TW Hydrae)

Analyzing multiband observations of dust continuum emission is one of the useful tools to constrain dust properties which help us to understand the physical properties of the disks. We perform the synthetic ALMA multiband analysis to find the best ALMA band set for constraining the dust properties of the TW Hya protoplanetary disk. We find that the Band [10,6,3] set is the best set among the possible combinations of ALMA Band [3,4,5,6,7,8,9,10]. We also find two conditions for the good ALMA band sets providing narrow constraint ranges on dust properties; (1) Band 9 or 10 is included in the band set and (2) Enough frequency intervals between the bands. These are related with the conditions which give good constraints on dust properties: the combination of optically thick and thin bands are required, and large β (β is the power-law index of dust opacity, κν ∝ νβ) and low dust temperature are preferable. To examine our synthetic analysis results, we apply the multiband analysis to ALMA archival data of the TW Hya disk at Band 4, 6, 7, and 9. Band [9,6,4] set provides the dust properties close to the model profile, while Band [7,6,4] set gives the dust properties deviating from the model at all radii with too broad constraint range to specify the accurate values of dust temperature, optical depth, and β. Since these features are expected by the synthetic multiband analysis, we confirm that the synthetic multiband analysis is well consistent with the results derived from real data.