星形成ゼミ 論文紹介 2012/11/16
Star Formation Newsletter No.238
担当：小屋松1. The Protocluster G18.67+0.03: A Test Case for Class I CH3OH Masers as Evolutionary
Indicators for Massive Star Formation
C.J. Cyganowski, C.L. Brogan, T.R. Hunter, Q. Zhang, R.K. Friesen, R. Indebetouw, C.J. Chandler【目的】Class I メーザーは大質量星の進化の指標として使えるか？
【観測】SMA および VLA によるミリ波観測
・G18.67+0.03 ̶EGOs サーベイで 3 つの Class I CH3OH メーザー源(EGO, UCHII, NEMS)【結果】・3 つすべてのメーザー源に 13CO アウトフローが付随
Cyganowski et al.
・EGO, NEMS
6.7GHz Class II CH3OH メーザー, SiO(5–4)放射→活発なアウトフローにより Class I メーザーが励起
・UCHIIClass II メーザー, SiO 放射ともになし→13CO はアウトフローの残骸【結論】Class I CH3OH メーザーは若い領域(hot core)と進化の進んだ領域(UCHII)の両方で励起される

The Astrophysical Journal Letters, 759:L5 (6pp), 2012 November 1＋：Class I メーザー ◇：Class II メーザー

59:L5 (6pp), 2012 November 1

Ellingsen et al.

Three color Spitzer image (RGB:µm) of G18.67+0.03; positions of CH3 OH masers from Cyganowski et al. (2009) are
Table8.0,4.5,3.6
1
arked with ! (Class II) and + (Class I). In all panels, the synthesized beam(s) are shown at lower left. (a) SMA pointings (dashed yellow circles)
II Methanol
Transitions
d contours of BGPS 1.1 Classmm emission(white)Maser
and VLA
3.6 cm emission (blue; Cyganowski et al. 2011b) are overlaid. Contour levels: BGPS:−10,20)×σ, σ =0.03 Jy beam ; VLA: (4,40,120)×σ, σ =3.06E-5 Jy beam−1 . (b) Contours of SMA 1.3 mm continuum emission (gray) and MIPS 24
Figure 3. SMA molecular gas kinematics. (a) DCN(3-2) first moment map. (b) Zoom view of CM1-UCHII H2 CO(30,3 -20,2 ) velocity fi
Transition
Series
G 345.01+1.79
memission (yellow). Levels: SMA:
(3,5,10,20,40,60,120)×σ, σ Discovery=0.00145 Jy beam−1 . MIPS: 600,1200,1800
MJy sr−1 . (c-e): Zoom views of maser(moment
1, colorscale),overlaid with contours of VLA 1.2 cm continuum emission (black) and blue/red-shifted 13 CO(2-1) emission. (c) SMA
urces, with SMA contours (black) as in (b). In (d), VLA 1.2 cm
continuum contours (blue) are also overlaid(levels (5,10,25,50)×σ,
σ =7.4E-5
Jy
Reference
Reference
mm continuum (colorscale) overlaid with contours of VLA 1.2 cm continuum (black) and composite maps of blue/red-shifted 13 CO(2-1) emissiam−1 ).

gure 1.

2. Discovery of Two New Class II Methanol Maser Transition in G 345.01+1.79
S.P. Ellingsen, A.M. Sobolev, D.M. Cragg, and P.D. Godfrey

13
CO is integrated over the indicated velocity ranges, optimized for each source. Contour levels (Jy beam−1 km s−1 ): EGO: blue: 1,2,3,4,5; r
5r 1Array–60 A+(SMA)7 study of the
1 mm-wavelength
Menten(1991b) Wang et al. 2012).Norris
et al. (1993)
dust conTo provide
kinematic
information
for blue: 2,3; red: 2,3,5,7. NEMS: blue: 2,4,6; red: 2,4,6,8. MIRS: blue: 1.5,2,3,4; red: 1.5,2,3,4. (d) SiO(5-4) integrated inten
1,2,3,4.
CM1-UCHII:
20 –3−1andE molecular line emission
2
Batrla et al. (1987)the ionized gas, weNorriset al.complementary(1988)
nuum
toward G18.67+0.03,
include1.3 cm KarlFigure 1.contours
Spectra(white).
of the 104.1
GHz (13E) (left)
216.9ofGHz(51 –4−3 –122map (moment
0, colorscale), overlaid with VLA 1.2 cm continuum
VLA contour
levelsas −4
in Figure
1. andPositions
CH3 OHmas
2constrain
Wilsonet al. (1985)
Ellingsen
et al.
(2004)hydrogen
the evolutionary3states of the maser
sources
G. Jansky
Array
(VLA)
recombi-et al. (2009) are marked with ! (Class II) and + (Class I). Synthesized beam(s) are shown at lower left in each panel.
3 Very Large
1 –30 E
from Cyganowski+ndthepresence/absenceofactiveoutflows.
The
SMA
nationline
andcm
continuum
observations.
92 –101 A
4
Wilson et al. (1984)
Cragg et al. (2004)
3.3. Ionized Gas Properties
2011). If bulk motions (e.g. expansion) dominate t
for deciphering
82well-suited–91 A−
4 MYSO relative
Wilsonevoluet al. (1993)
moder
states (Beuther et al.
al. 2009;
linewidth, this could explain the low derived Te ; howev
2. OBSERVATIONS
7onary5 2009; Zhang etHaschicket al. (1989)
Ellingsen
et al. (2011)
We detect the H63α and H64α recombination lines−2 –8−1 E−+
the RRL emission is too weak to investigate thisstudyi
possib
SMA observations
at 1.3mm
obtained
on 18
June
7 The
–5
/A
Haschicket al. (1989)
Ellingsen
et al.3were(2011)
towards
G18.67+0.03-CM1(Cyganowski et al. 2011b).
3 A Submillimeter
Array is a 6
joint project between
the Smithpresen
ity. The cm-wavelength spectral index is consistentw
in good−1
AstrophysicalObservatory5and the AcademiaCragg
SinicaetInsti6nianal. (2001)2010 with 7 antennas
Cragginetcompactal. (2001)configuration,
−2 –7
−1 E
The
fittedRRL
velocity(77.3±0.9kms)isconsiste of Astronomy
and Astrophysics and is funded by the Smithweather (τ225GHz ∼0.07). A three-pointing mosaic was
optically thin free-free emission, and the ionizing
phot−(Salii3 clump–63 A/A+ and the Academia
6 Sinica.
Cragg et al. (2001)
Cragg et al. (2001)
tent
with
the1).molecular-gas velocity. From the line-tonian
Institution
47 −1
used
to
cover
the
extentofthe(sub)mm(Fig.
flux (∼1×10 s , calculated as in Cyganowski
et31 –40 A+
1
Val’tts et al. (1995)
Caswell et al. (2000) continuum ratio of 0.48, the fitted FWHM linewidth of
216.9
2011b) corresponds to a single ionizing star of spect
00 –1−1 E
2Val’tts et al. (1999)
Val’tts et al. (1999)
27.0 km s−1 , and the fitted source size of 0."" 63 (from2003Atype B0.5V (Smith et al. 2002).
50 –15−1 E
7Salii & Sobolev (2006)
Salii & Sobolev (2006) the continuum image), we derive an electron temperareport21 –30 A+
1
Slysh et al. (1995)
Caswell et al. (2000) ture of ∼5100 K and density of ∼1.9×104 cm−3 (followdensit–J−1 E group7
Slysh et al. (1995)
Slysh et al. (1995)
ing the method of e.g. Garay et al. 1986; Sewi!lo et al.
-3Salii et al.
-4(2003)–J0 E group
8
Salii et al. (2003)
with th102 –93 A−
6
Salii & Sobolev (2006)
Salii & Sobolev (2006)
the 21【目的】新たな Class I CH OH メーザーの遷移を発見する【観測】Swedish ESO Submillimeter Telescope (SEST)・G345.01+1.79 ̶Class II CH OH メーザー源
・既知 7 本+予測 6 本の Class II CH OH メーザー遷移【結果】13 本中 9 本の遷移を検出
・2 本が初検出
13 –12 E …104.1 GHz
5-1–42 E…216.9 GHz→Class
II CH
OH
メーザーのシリーズが10 個
have been rounded at the 100 kHz
significance level.
The G
345.01+1.79
reference is the most sensitive3
available for the specific transition.
遷移が 18 本にそれぞれ増えた

high-brightness temperaturesdels successfully predict masions for which it has been obconditions implied are much
97b). So the presence of multhin one source can, throughto constrain the physical conder the assumption that thehe same location).

ATIONS

using the Swedish ESO
between 2000 June 22 anddifferent methanol transiass II methanol maser tranwhich are predicted class II
olev et al. 1997b). The frens range from 84 to 265 GHz.

Table 2
Summary of Lines Observed toward G 345.01+1.79
Transition

ν
(MHz)

rms
(Jy)

Tsys
(K)

13−3 –14−2 E
6−2 –7−1 E
72 –63 A−
72 –63 A+
13−3 –12−4 E
31 –40 A+
00 –1−1 E
21 –30 A+
70 –7−1 E
51 –42 E
102 –93 A−
102 –93 A+
42 –51 A−

84423.769
85568.084
86615.578
86902.956
104060.647
107013.812
108893.948
156602.413
156828.533
216945.600
231281.100
232418.590
234683.390

0.4
0.4
0.3
0.3
0.7
0.7
0.3
1.3
2.3
0.8
1.5
1.6
1.3

143
160
149
140
254
265
166
600
1015
203
267
329
315

Integration Peak Flux Velocity(minutes)(Jy)(km s−1 )
50
54
42
60
30
56
60
56
54
60
42
30
50

<1.9
10.9(1.9)
7.2(0.6)
6.8(0.5)
2.8(1.1)66(8)8.3(0.4)
27.6(1.2)
45.0(1.8)
4.2(0.8)
<7.5
<7.8
<6.4

−22.1
−22.3
−22.1
−22.3
−21.9
−21.7
−21.8
−21.7
−22.5

Note. The rest frequencies for transitions <200 GHz are from Tsunekawa et al.
(1995) and the remainder are from Sastry et al. (1984).

Figure 2. Spectra of the detected class II methanol maser transitions towardG 345.01+1.79.

signifiobservin Salintensdrama
variatimaser
pointivariati
Sali
231.3
peak flour SEsignifi
Salii &Weand (w
results
sitions
adequrable w

2

Federrath & Klessen2011) regulate star formation. In this picture, turbulent
number have the strongest influence on the SFR, causenergy stabilizes the clouds on large scales, but at theing variations by more than an order of magnitude, whilesame time, supersonic turbulence induces local compresmagnetic fields can account for reductions of the SFR bysions,Formation
producing filaments
and ofcores,
which are theMagnetizedproa factor oftwo.
3. The Star
Rate
Turbulent
Clouds:Comparing Theory,
genitors of stars. Eventually, both turbulence and magIn Section 2, we introduce and discuss the six anaSimulations,andnetic fields
playObservations
their parts; the only question is: whichlytic theories for the SFR, based on the turbulent density
is the dominant
controlling
factor of star formation?
PDF, derive and discuss their dependencies, add magChristoph one
Federrath,and Ralf
S. Klessen
The aim of this paper is to advance our understanding
netic fields to the theories that did not include magnetic【目的】星形成率を決めるパラメータは何か？
of the relevant physical processes and their parameters
field e↵ects in previous derivations, and compare them
controlling the conversion of dense gas into stars, and towith each other in detail. We then test the analytic【手法】・星形成率の6つの理論モデル
explain the observed variations of the SFR column dentheories with numerical simulations of supersonic, magsity. We
develop andnetized turbulence by varying the sonic Mach number
Krumholz& compare
McKeesix predictive theories —the original Krumholz & McKee (KM), Padoan & Nord(M = 3–50), the forcing of the turbulence (solenoidal,
Padoan & Nordlun
lund (PN), and Hennebelle & Chabrier (HC) theories,
mixed, compressive), and the magnetic-field strength
Hennebelle& Chabrierand multi-freefall
versionsof theses three —, which are(yielding Alfvén Mach numbers MA = 1.3–1) to cover
all based on integrals over the turbulent density probaa comprehensive range of cloud parameters. The simuの
3
つとこれらのmulti-freefall
版
bility distribution function (PDF), explained in detail inlation methods and setups are explained in Section 3.
the next section.
We extend the KM and HC theories, as
A detailed time-evolution analysis of column density,
・MHD
シミュレーション
well as all the multi-freefall theories to include magnetic
magnetic-field morphology, and fragmentation proper・系内の分子雲の観測値
fields. We evaluate the relative importance of turbulence,ties is presented in Section 4. In Section 5, we comits forcing characteristics, and magnetic fields in controlpare the SFRs measured in the magnetohydrodynamic
を比較
ling the SFR and show that the SFR depends on the(MHD) simulations with the six theoretical models, andfollowing four basic
parameters:
determine the best-fit theory parameters that are uni【結果】・星形成率は
4 つのパラメータに依存versally applicable and fit all our simulations simultane1. virial parameter ↵vir = 2Ekin /|Egrav |,ously. Section 6 presents a comparison of SFR column
densities in the simulations with observations of Galac2. sonic Mach number M = V /cs ,tic clouds. We discuss limitations of the theoretical andnumerical models, as well as limitations in the compar3. turbulent forcing parameter b, with purely
ison with observations in Section 7. Finally, we list oursolenoidal (divergence-free) forcing parameterized
conclusions and summarize the most important resultsby b = 1/3, mixed forcing by b = 0.4 and purely
in Section 8. Here, we study the SFR in detail, while incompressive (curl-free) forcing by b = 1, andPaper II (Federrath & Klessen 2012), we concentrate on
the star formation efficiency (SFE).
4. the ratio of thermal to magnetic pressure=
2M2A /M2 with the Alfvén Mach number MA .
2. THE SFR FROM THE STATISTICS OF SUPERSONICMAGNETIZED TURBULENCE
We test all six theories with numerical simulations of・パラメータの分散により観測の分散が説明できる
supersonic, magnetized turbulence including self-gravity
2.1. The Density PDF
・マッハ数と乱流の強さが最も重要なパラメータand sink particles to capture dense, collapsing, starThe probability density function (PDF) of the gas denforming gas. We find that the multi-freefall KM and PN
sity in a turbulent medium—such as a molecular cloud—・磁場も二次的に効いてくる
modelsfits to & Klessen
26 including magnetic fields provide the bestFederrathis the key ingredient for analytic models of star formaour numerical simulations with typical uncertainties oftion. A log-normal density PDF has been used to exless than a factor of two. This is an encouraging agreeplain the mass distribution of cores and stars, the corement, given that the SFR varies by two orders of magmass function (CMF) and the stellar initial mass function
nitude in the simulations, depending on the four basic(IMF) (Padoan & Nordlund 2002; Hennebelle & Chabriercloud parameters listed above.
2008, 2009; Elmegreen 2011; Veltchev et al. 2011; Donkov
Comparing our numerical experiments with SFRs meaet al. 2012; Parravano et al. 2012; Hopkins 2012), thesured in Galactic star-forming regions, we find that for
Kennicutt-Schmidt relation (Krumholz & McKee 2005;
typical star formation efficiencies of SFE = 1%–10%, theTassis 2007), the SFE (Elmegreen 2008), and the SFR
best-fit local efficiencies due to radiative and mechanical(Krumholz & McKee 2005; Padoan & Nordlund 2011;
feedback from jets, winds, expanding shells or outflows
Hennebelle & Chabrier 2011). Here we concentrate on
driven by young stellar objects are ✏ = 0.3–0.7 with a
the SFR and derive its basic dependencies.
best-fit value of ✏ ⇡ 0.5 for SFE = 3%. This suggests
The log-normal PDF of the gas density is defined as,that a fraction ✏ ⇡ 0.3–0.7 of all the infalling gas onto✓◆a typical protostellar core is accreted by the protostar,1(s s0 )2ps (s) = p
exp
,
(1)
while a fraction (1 ✏) ⇡ 0.3–0.7 is re-injected into the
2 s2
2⇡ s2
interstellar medium by jets, winds, and outflows. We
find good agreement between the numerical simulations
expressed in terms of the logarithmic density,and Galactic observations, suggesting that the observed
variations in ⌃SFR with ⌃gas are a result of di↵erent coms ⌘ ln (⇢/⇢0 ) .
(2)binations of the four basic parameters controlling the
SFR: ↵vir , M, b, and , as listed above. Since molecThe PDF is a normal (Gaussian) distribution in s, meaning it is a log-normal distribution in ⇢. The quantities
ular clouds are often characterized by virial parametersof order unity, we conclude that the degree of compres⇢0 and s0 denote the mean density and mean logarithsion induced by the turbulent forcing and sonic Machmic density, the latter of which is related to the standard

Fig. 11.— (a): Star formation rate column density ⌃SFR vs. gas column density ⌃gas measured in the GRAVTURB simulations listed inTable 2 for a star formation efficiency SFE = 1% (blue) and SFE = 10% (red), respectively. Two contour lines for each SFE are drawn. The
thick contours enclose 50% of all (⌃gas , ⌃SFR ) simulation pairs, centered on the peak of the distribution, while the thin contours enclose
99%. (b): Same as (a), but only the contours of the simulations are drawn, and observational data of Galactic clouds from Heiderman
et al. (2010) are superimposed. The individual data points are labeled in the legend of the bottom panels (Taurus: filled black box, Class I
YSOs and Flat YSOs: green and red stars and upper-limits shown as downward-pointing triangles, HCN(1–0) Clumps: golden diamonds,
and C2D+GB Clouds: dark blue boxes). The simulation data in panels (a) and (b) are plotted for a local core-formation efficiency ✏ = 1,
the value expected without any local feedback from YSOs. (c): Same as (b), but the simulation data were transformed to ✏ = 0.5 using
Equations (47), which changes the GRAVTURB contours compared to (a) and (b). The value ✏ = 0.5 was determined by fitting thesimulation data to the observational data using Equation (48), suggesting local efficiencies of ✏ ⇡ 0.3–0.7 for an assumed SFE ⇡ 1%–10%
in the observed clouds. (d): Same as (c), but for the simulation maps smoothed to 4⇥ coarser resolution, demonstrating the e↵ect ofobserving the simulated clouds with reduced telescope resolution.

because more gas is accreted by sink particles and thus
removed from the gas phase at higher SFE. If we wereto fit power laws to the distributions, the slopes would
be in the range 1–2, i.e., ⌃SFR / ⌃1–2
gas with somewhat
flatter slopes at higher SFE.
6.2. Galactic Observations of ⌃gas and ⌃SFR
To compare the simulation data with observations, we
add data of Galactic clouds from Heiderman et al. (2010)in panel (b) of Figure 11, superimposed on the simulation contours. The observational data are from Galactic
observations of clouds and YSOs identified in the Spitzer
Cores-to-Disks (C2D) and GB surveys (Evans et al. 2009)of massive dense clumps (Wu et al. 2010), and of the
Taurus molecular cloud (Pineda et al. 2010; Rebull et al.
2010). The simulation data indicated by the same con-

Koenigl 1993; Konigl & Pudritz 2000; Beuther et al.
2002; Pudritz et al. 2007; Peters et al. 2011; Seifried et al.
2011a). Hence, only a fraction ✏ < 1 of the in-falling gas
actually ends up on the protostar.
The local core-formation efficiency is parameterized by
the factor ✏ in Equation (7), from which all the SFR↵ models in Section 2 were derived. Since there is no feedback in our simulations, ✏ = 1 by definition. However,
we can devise a correction to account for ✏ < 1. For this,we simply have to multiply the original ⌃SFR for ✏ = 1
by a given ✏ < 1. To conserve mass, we also have to account for the fact that a fraction (1 ✏) was not accreted
and remained in the gas phase due to local feedback.
This means we have to increase ⌃gas according to the
reduction of ⌃SFR , such that ⌃tot = ⌃gas + ⌃SF with
⌃SF = ⌃SFR tSF is conserved. Given our simulation data⌃gas and ⌃SFR with ✏ = 1, we can compute values ⌃0SFR

4. Evidence for Grain Growth in Molecular Clouds: A Bayesian Examination of theExtinction Law in Perseus
Jonathan B. Foster, Kaisey S. Mandel, Jaime E. Pineda, Kevin R. Covey, Héctor G. Arce, Alyssa A. Goodman【目的】減光則をよりよく求める【手法】Megacam r, i, z-band と UKIDSS J, H, K-band を組み合わせて背景光の色を測定
階層ベイズ統計モデル
・測定値の誤差
・もともとの色のばらつき
・スペクトル型
・ダスト赤化を考慮して個々の星と集団の特徴のパラメータを同時に推定【結果】減光 AV と減光則の傾き RV とに強い相関
他の領域と同じ傾向→ダスト成長はユニバーサルな過程である

5. The Absence of Cold Dust around Warm Debris Disk Star HD 15407A
Dideaki Fujiwara, Takashi Onaka, Satoshi Takita, Takuya Yamashita, Misato Fukagawa, Daisuke Ishihara, Hirokazu
Kataza, and Hiroshi Murakami【目的】デブリ円盤の冷たいダストの量を求める【観測】Herschel/PACS 70µm, 100µm, 160µm および AKARI/FIS WIDE-S(90µm)【結果】MIR のフィットの外挿で FIR 超過も説明できる→FIR の起源は内側の温かいダスト(~500–600K)で外側の冷たいダスト(~50–130K)は存在しない
Ldust/L*~0.005 は大きすぎて定常モデルでは説明できない
・2 つの非定常メカニズム
Late Heavy Bombardment (LHB)
Two-body Impact
たくさんの衝突天体を要する LHB シナリオでは冷たいダストが受かるはず
The AstrophysicalJournal Letters, 759:L18(5pp), 2012 November 1
Fujiwara et al.
→LHB
では HD15407Aのデブリ円盤を説明できない
10

Flux Density (Jy)

1

2MASS
WISE
AKARI/IRC
Subaru/COMICSAKARI/FIS
Herschel/PACS
IRAS
Spitzer/IRS
Star
Star+BB(505K)

0.1

0.01

1

10
Wavelength (µm)

100Figure 1. NIR–FIR SED of HD 15407A. The black crosses indicate the 2MASS photometry, which determines the photospheric contribution of the star (Kurucz
1992) shown as the gray solid line. The purple, blue, green, and yellow filled circles, and black open circles indicate the photometric data of WISE, AKARI/IRC,
Subaru/COMICS, and AKARI/FIS, and IRAS, respectively. The red open and filled circles indicate the photometric measurements from individual images taken with
Herschel/PACS and their weighted-average of photometry for each band, respectively. All of the flux densities are not color-corrected. The vertical and horizontal
bars of the photometric data show the flux density errors and the bandwidths, respectively. The orange solid and gray dashed lines indicate the Spitzer/IRS spectrum
and the estimated continuum level of the excess emission, respectively, taken from Fujiwara et al. (2012a).

3.2. Mass of Warm Debris around HD 15047A
Fujiwara et al. (2012a) estimated the mass of fine warm dust
around HD 15407A to be 7 × 1017 kg ∼10−7 M⊕ from thedust model fitted to the band features seen in the Spitzer/IRS
spectrum at 5–35 µm. This value does not include the mass ofthe blackbody dust, which consists of large (!10 µm in size)
grains and rubble.
Assuming that the continuum component of the observed
excess emission at MIR and FIR wavelengths is attributable toblackbody grains of 505 K at Rdust = 0.6 AU, as suggested by
Fujiwara et al. (2012a) and this work, and that its flux density
is proportional to the sum of geometrical cross sections of thedust with the grain size distribution of n(a) ∝ a −3.5 , we could
estimate the total mass of large debris dust as
!
"!
"!
"1
MtotalLdustρamin 2= 2.7 × 10−4M⊕L∗
2.5 g cm3µm
" 12 !
"2!

∼5×10−5 M⊕ ∼ 3×1020 kg assuming amax = 1 mm. Assuming
amax = 1 km, the total mass is estimated to be ∼0.05 M⊕∼3 × 1023 kg, corresponding to a few lunar masses or about
half of Mars’ mass.
An upper limit on the mass of cold dust (∼50 K at Rdust =60 AU) around HD 15047A could also be estimated in thesame manner from the upper limit on the fractional luminosity
Ldust /L∗ " 2 × 10−6 set by the present work. Assuming thesame grain size distribution (n(a), amin , amax ) as that of warm
dust, an upper limit on the mass of cold dust is given as just a
few times of the mass of warm dust as estimated above.
3.3. NIR Excess
As mentioned in the previous subsection, no debris material colder than ∼500 K is suggested by the MIR–FIR SED
of HD 15407A. On the other hand, photometry at 4.6 µm in
the WISE W2 band shows excess over the estimated continuum
component of blackbody (Figure 1), suggesting the presence