ALMA による原始惑星系円盤の観測シミュレーション

Presentation on theme: "ALMA による原始惑星系円盤の観測シミュレーション"— Presentation transcript:

1 ALMA による原始惑星系円盤の観測シミュレーション
京都大学 ALMA による原始惑星系円盤の観測シミュレーション I am Shigehisa Takakuwa from ALMA-J Project Office. I guess you must be very hungry or sleepy, So I have to finish my talk quickly. The title of my talk is scientific role of ACA for low-mass star-formation study. 高桑　繁久 & 黄　郁恵 (ASIAA, Taiwan)

2 1. Introduction ACA (Japan)
ALMA: Atacama Large Millimeter and submillimeter Array Atacama Desert at Northern Chile, International Project, 0.01 arcsec (~ 1 AU) resolution, 30 times better sensitivity than SMA 12-m Array (U.S., Europe) 50 12-m antenna ACA (Japan) 4 12-m Total Power (Single-Dish) Array m Array Let me start with introduction. ALMA, we all know what is ALMA. Here, I would like to remind you that ALMA consists of two components. One is so-called 12-m array, which consists of m antennas, and will be constructed by the U.S. and European group. The other component is ACA, Atacama Compact Array. ACA consists of

3 ALMA は原始惑星系円盤の理解を どれだけ推し進めるのか？あるいは ALMA の限界は？ それをどのように定量的に評価？？

4 Theoretical Disk Images @ 230, 350, 460, 690 GHz
Theoretical Physical Parameters of the Disk (中本さん、野村さん) Radiative Transfer Code Theoretical Disk 230, 350, 460, 690 GHz 比較せよ !! ALMA Observing Simulation Science Power of ALMA ``Observed’’ Disk Images Our strategy of simulations is like this. First, we make scientific models in collaboration with theoretical astronomers. Here, these images have physical basis, not just simple shape. Then, we make imaging simulations of the theoretical images with Miriad. Now, you can estimate the observed physical parameters from the simulated observational images. We compare our observed physical quantities to those in the theoretical image, and then we can study how ACA reproduce science, and we can verify the scientific imporatnce of ACA. 2 SED fitting ``Observed’’ Physical Parameters of the Disk

5 ALMA 観測シミュレーションパラメータ Using Miriad Declinations: -23° (zenith)
Hour Angle: (hour) for both 12 m and ACA Synthesized Beam: 1.2 x 1.1 arcsec (P.A. = -87 deg) Primary Beam: ~ 18 arcsec (12-m Array) @ 350 GHz Error: Thermal Noise only (Tsys = 250 GHz) Here is a summary of our simulations. Using Miriad

6 ``観測’’ 結果の定量的評価 ---> Introducing ``Fidelity’’
At each image pixel (i, j); abs[ Model (i, j) ] Fidelity (i, j) = abs[Model (i, j) - Simulated (i, j)] However, we need to evaluate the imaging quality in a quantitative way. How can we do it ? Here, we introduce the value of Fidelity. At each image pixel (I,j), Fidelity is expressed in this Formula, that is, model over the difference between the model and the simulated images. Fidelity can be calculated in each image pixel, and we can make the image of fidelity. We usually take median values in the entire image pixels with lower cutoff level. Futhermore, this fidelity can also be defined in the uv domain, and we call it uv fidelity.

7 2. Simulated Disk Images Model
12-m array only All Obs. Model Fidelity @freq350GHz Peak 9.36E+02 Peak 2.2E+03 Inclusion of ACA provides a better imaging result. Peak 9.36E+02 Peak 2.2E+03 All: 12-m Array +ACA (7-m Array +Single-Dish) Inclusion of ACA provides a better imaging result

8 @230GHz @350GHz Intensity 12m Array Intensity 12m Array all all Model Model radius (arcsec) radius (arcsec) Intensity Intensity all all Model Model 12m Array 12m Array radius (arcsec) radius (arcsec) @460GHz @665GHz Without ACA, we cannot reproduce the radial intensity distribution @high Freq. properly.

9 7-Point Mosaic with the 12-m Array
Single-Field Mosaic Obs. Model Fidelity @freq350GHz Peak 9.36E+02 Peak 2.51E+03 Mosaicking provides a better imaging result. Peak 9.36E+02 Peak 2.2E+03 All: 12-m Array +ACA (7-m Array +Single-Dish) Inclusion of ACA provides a better imaging result

10 List of Fidelities With or witout ACA, Single-dish ---> ACA required With or without mosaic of the 12-m array ---> Mosaicking Better

11 3. 円盤の物理量の導出 (Still Preliminary….)
F(r) = (r) P (Tdust (r) ) (r)Ωk(r) mmH (r) Through the SED fitting at each radius, we can derive Tdust (r),  (r), and r NH2 = 6.5 × 1022 (cm-2), Td = 38 K, &  = 1.7 k(r) = kmm (1.2 /  )r kmm = cm2 g-1 (Crapsi et al. 2004)

12 Derived Physical Parameters from the Simulated Images (All: 12-m array + ACA)
正解 Radius (AU) 正解は ~ 5× AU, 200 AU, 350 GHz よさそうにみえる….

13 Derived Physical Parameters (cont.)
Tdust (r) r 正解は AU それ以降ほぼ一定 正解はr = 2 (constant) Radius (AU) まあ正しい？？

14 今後の課題: 詳細な答え合わせ 理論イメージを構築する、 円盤の``正しい’’ 物理パラメータ 理論イメージに対して
SED フィットして求めた 円盤の物理パラメータ 観測シミュレーションのイメージに SED　フィットをして導出した ``観測された’’ 物理パラメータ ３者の詳細な比較が必要、物理パラメータの ``Fidelity’’, ALMA 観測はどれだけ円盤の物理モデルに制限を与えられるか？

15 4. Summary: 原始惑星系円盤の理論イメージを用いた ALMA 観測のシミュレーション
ACA, あるいは mosaic 観測により 観測のイメージの質の向上 SED fitting による円盤の物理パラメータの導出 ALMA がどれだけ原始惑星系円盤の物理に迫れる のかを定量的に評価するため、 理論の ``正しい’’ 物理パラメータとの詳細な比較が必要

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