THE STAR FORMATIONNEWSLETTER
No. 320 (#36), No. 321 (#1-9)
塚越崇(NAOJ)
4 Oct. 2019

1. Northern Galactic Molecular Cloud Clumps in Hi-GAL: Clump andStar Formation within Clouds
2. HST spectra reveal accretion in MY Lupi
3. Gaia DR2 distances to Collinder 419 and NGC 2264 and new
astrometric orbits for HD 193 322 Aa,Ab and 15 Mon Aa,Ab
4. Inner rocky super-Earth formation: distinguishing the formation
pathways in viscously heated and passive discs
5. The First Detection of 13C17O in a Protoplanetary Disk: a Robust
Tracer of Disk Gas Mass
6. The fulcrum wavelength of young stellar objects – the case of LRLL 31
7. Radial Drift and Concurrent Ablation of Boulder-Sized Objects
8. The Structure of Dark Molecular Gas in the Galaxy – II. Physical Stateof “CO-Dark” Gas in the Perseus Arm
9. Stars and brown dwarfs in the sigma Orionis cluster. IV. IDS/INT andOSIRIS/GTC spectroscopy and Gaia DR2 astrometry
10.Dust accretion in binary systems: implications for planets andtransition discs

Northern Galactic Molecular Cloud Clumps in Hi-GAL: Clump and Star Formation within Clouds
Zetterlund, E., et al.

• Hi-GALデータとCOHRSデータを使った銀河面分子雲の調査• GMCとクランプ、SFRの関係性をglobalに調べる• GMCとclumpのmass fractionを用いて評価• 主にたくさんの結果を示している論文

• Mcloud - SFRの関係をdense substructureも念頭に入れて調べる• 2つの既存カタログをマッチングして使用• Recent star formation - 連続波(特に短波長)• HiGALのクランプカタログ [Ellsworth-Bowers+2013]+ distance determination tech. [Zetterlund+2017]• クランプの質量などを導出• Initial condition of star formation - CO
• CO High Resolution Survey (COHRS)のクラウドカタログ [Colombo+2019]• クラウドの質量やサイズ、ビリアル比等を導出• Clump formation fraction(efficiency)• 4704のHi-GAL clumpが1182のCOHRS cloudとマッチex)

stars. We estimate this quantity as ourraction,fails to exclude a few clouds with clump mass fractions over unity, but these• Clump mass fraction

tion =Mclump
MGMCM
åi clump, i.
=MGMC

(5 )

Clump>3’のもので評価
e •clump
masses contained in a cloud
mass,
where i indexes the individual• 平均で~0.2

rived from 12CO(3−2) emission were
GMC物理量(M,∑,α,v)との比較
et al. (2019) and are summarized here.
a cloud is calculated from its Gaussian

強い相関なし• GMC質量(面密度)と弱い相関• 1, 重いcloudほど多くのclumpを持つ• 2, 重いcloudほど重いclumpを持つ• Rgalにも非常に弱い相関がある=>環境効果

Figure 8. Distribution of clump mass fractions for the subset of clouds tha
have σmajor>3′. The red curve represents the lognormal ﬁt to the data, withparameters μ=−1.8 and σ=0.8.

virialized
non-virialized
To determine what properties of a GMC inﬂuence its CFE
5.3. Relations with Physical Properties

we plot clump mass fractions of clouds against various physica
properties (Figure 10). In examining cloud mass, surface massdensity, virial parameter, and line width we see no more thanslight correlations between clump mass fraction and thesecloud properties. In the case of cloud mass and cloud mass
surface density, we ﬁnd shallow power-law slopes of −0.14±0.03 and −0.13±0.05, respectively, with large dispersions. A
cloud with more mass will, on average, have a slightly lower
clump mass fraction. A cloud’s stability against collapse as awhole (see Section 8) does not inﬂuence the fraction of acloud’s mass that will collapse into denser clumps.
In these plots, red points correspond to non-virialized clouds(αGMC<2), that is, those unstable to gravitational collapse
This comprises ∼25% of our sample. Panel (c) shows that thenon-virialized clouds sample from the full distribution of clump
mass fractions, as do virialized clouds. As seen in panels (a)and (b), these potentially collapsing clouds are more likely tohave higher masses and surface mass densities. However, weknow that lower-mass clouds (M∼103 Me) can collapse toform stars (Enoch et al. 2008). These clouds are not absenfrom the COHRS catalog, but we are less likely to match HiGAL clumps to them. This may be due to the small clouds’n as
L (70)(erg s-1)
1SFR
(M: yr ) = Journal, 881:90. tdep,clump(12)=The Astrophysical(19pp),
2019 August
20 Mclump SFR,the
1.7 ´ 10 43(15) Zetterlund, Glenn, & Rosolowsky

r about this relation is ∼0.2 dex, or about 60%.
where SFR is the star formation rate measured for the cloud inthis calibration was developed using individual
bothcases.ofInvestigatingthese normalized quantities, we see noth typical scalesof hundredsparsecs and it will being
le for individual GMCs. At this wavelength, thecorrelation
between SFR and clump mass fraction. On the otherfor light fromraces
stars of ages 0–100 Myr, but thehand,
positivession-contributing
stellara age
is 5 Myr. correlation, partially driven by clouds witholeur clouds are deﬁned in PPV space, we are using aextreme
clump
fractions,is seen between tdep,clump andthetracer to measurestar formation.
We mass
control for
thiste our uncertainties
due massto this mismatch
as follows.
clumpfraction(Figure 15, center). This implies that onple,
the ﬂux densities required for conversion to SFRs,
Figure 15. Left:starformation
rate /M
derivedHi-GAL
70 μm
as a functionof が大きいclump massfraction.
Center:clumpmass
depletion(see=>Mが大きいところでM
The AstrophysicalJournal,
881:90 (19pp),
2019 Augusttime
20
clumpGMC
averageeitherclumpmassisemission
higherinclumpcloudswithhigher
ved
ateEquation
the ﬂux
densityfoundwithin
thefromvelocity(15)) as a function of clump mass fraction. Right: clouds’ total mass in clumps as a function of clump mass fraction. Red points indicate clouds with virial
COHRS
We account for background ﬂux
parametersmask.
αvir<2.
emission by creating a “rind” around the mask with a12mass fractions–1.5
resolution
elements,
processofclumpor mimicking
the SFR in theclumps
is smaller
in clouds
hotometry but for irregular ISM structures. We ﬁt awith greater clump mass fractions. Figure 15 (right)
GMCshows that
it is the former: clump masses tend to be larger in clouds withgreater clump mass fractions. Figure 15 also•showsthat clumps
Lada+2010と異なる結果Zetterlund, Glenn, & Rosolowsky
with lower virial parameters tend to have higher SFRs (left) andThe Astrophysical Journal, 881:90 (19pp), 2019 August 20
Figure 18. Left: distribution of log (t /t ) for clouds. The mean value is 2.81±that more massive clumps tend to have smaller virial
Clump
has formed in a simulation, as per Figure 17, a dispersion
parameters (right). While the scatter is verylarge, taken
consistent with observations should be included also.
The Astrophysical Journal, 881:90 (19pp), 2019 August 20
Zetterlund, Glenn, & Rosolowskytogether these weak correlations are consistent with an
7. SFR Densities Compared to the Kennicutt–Schmidt Law
evolutionary trend in which clumps and clump mass fractions
The Kennicut–Schmidt (KS) law relates the SFR surface
density (Σ ) to the surface mass density of gas (Σ ) throughgrow within clouds over time, become increasingly gravita⎞⎛ S(16)
S= A⎜⎟ ,tionally unstable, and have correspondingly increased SFRs.
⎝ 1 M pc ⎠Figure 16 shows that more massive clouds host more star
where A=(2.5±0.7)×10M yr pc and N=1.4±0.15 is the power-law exponent (Kennicutt 1998). In Figure 21,formation. This behavior has been seen before in other studies,Figure 18. Left: distribution of log (t /t ) for clouds. The mean value is 2.81±0.61.
Right: same
above, butThe lawmean(shownvalue is 2.43±0.65.
we compare
ouras cloud
datafortoclumps.
the KS
as a thickgrayline).
Our
dataﬁtthelaw
remarkably
well,although with aincluding the Gould Belt clouds in the solar neighborhoodhas formed in a simulation, as per Figure 17, a dispersion signiﬁcantwith molecularclouds
overalongpath
length,averagingff There are a few clouds
degree of dispersion.
withconsistent with observations should be included also.
multiple star-forming regions along the line of sight. All theseabnormally low Σvalues. We ﬁnd no other abnormalities in(Lada et al. 2010) and H II regions in the nearby galaxies NGC
systematic effects could easily account for the differences in thetheseclouds,
observed
KS andlaw theyindex.fall within the overall scatter of SFRs
300 (Faesi et al. 2014) and NGC 628 (Kreckel et al. 2018),7. SFR Densities Compared to the Kennicutt–Schmidt Law calculatedusing alternative calibrations from 24 μm emission
The Kennicut–Schmidt (KS) law relates the SFR surface
et al. 2009) andinfraredemission (Hao et al. 2011;
8. total
VirialParameters
εff,clump=0.37%
among other work. We place these other data on Figure 16,density (Σ ) to the surface mass density of gas (Σ ) through (RiekeMurphy et•al. 2011).
In thefocusedscalingsof clump
Weﬁt previous
Equationsections,(16) to wethesedata onandtheﬁndparametersof⎞⎛ S
alongside our own. The work of Lada et al. (2010) argued thatand cloud properties and theformation
properties.
A=(2.3±1.1)×10
M resulting
yr pcstar andN=2.0±0.1.
(16)
S= A⎜
⎟ ,εff,GMC=0.15%•However,in Figures
7, 11,13, 15, 17,19,dex.
andOur21, ﬁtweslopehaveThe
1σ dispersion
about
this12,regression
is 0.6⎝ 1 M pc ⎠the local molecular clouds followed a linear correlation<2areto caveatsdetermine
whether they
thoseKS.
cloudswith α there
isindicatedsteeper thanHowever,to applying
the相関

相関無相関

• M

はSFRとnon-linear• M

はConstant SFE

10 depff

SFRgasgas

SFR-2:−1010 dep

Ne−1−2• SFE/t がGMCとff

clumpで異なる
SFR

SFR

gas

SFRN

gas

:

-2−11e

vir

−1−2

その他

(19pp), 2019 August 20• K-S lawと比較

Zetterlund, Glenn, & Rosolowsky• ややsteep• ビリアル比• poor indicator of clump(つまり星形成)• GMCとclumpの視線速度差• clumpはGMC(spiral arm)に
uniformに分布

The First Detection of 13C17O in a Protoplanetary Disk: a Robust Tracer of Disk Gas Mass
Booth, A.S., et al.

• 13C17Oを原始惑星系円盤で初検出(HD163296)• 光学的に薄いのでガス質量を出せる• CO同位体を合わせるようにガス質量を推定=> 今まで考えられていた質量より2-6倍重い• ALMA cycle3 data (Notsu et al. 2019)• HD163296 (d=101.5pc,ただし論文では122pcを使用)• resolution: 0.87”x0.51”• S/N=7で13C17O(J=3-2)検出• そのほかのCO同位体データ• CO, 13CO, C18O (J=2-1)• CO, C17O (J=3-2)• optically thinを仮定して柱密度導出• 7.1x1015 cm-2 (<50au, 50K assumption)• C18Oから求めた柱密度との比~2.5=> C18Oはoptically thick• もしoptically thinなら比 ~100

• Qi+2011のモデルをベースに放射輸送計算+擬似観測• 13C17O以外のCOを再現する円盤モデル• CO depletion入り• 試したモデル• Model 1: モデルそのままで一定のX(13C17O) = 5.39x10-10• Model 2: ガス質量全体を増やす(目で合わせて3.5倍とした)• Model2の方が合う• Model1だと13C17Oを過小評価• total disk mass: 0.31M⦿
• g2d~260• これまでの見積もりより2-6倍重い• 光学的に厚いCOで求めていたせい• ISMの同位体比でフィットできている• selective photo-dissociationは起きていない？
• C18Oでも光学的に厚いので、rare COの高感度観測が必要• CO snow line?

• これまでのモデル• 1, 155au at 19K (Qi+2011); 2, 90au at 25K (Qi+2015)• 今回の観測は前者でフィットできるが、もっと高感度の観測が必要• 重力不安定?
thin, CO isotopologues, or by detecting molecules that,due to chemistry, peak in abundance at a location re• 最小となるQでも~6(110au)くらい
lated to the snowline. Qi et al. (2011) use observations
CO and put the snowline at 155 au at 19 K: follow up=>”今は”安定•

work suggested that the snowline was instead at 90 au
and 25 K (Qi et al. 2015). Out of these two scenarios
質量降着率から初期の円盤質量を概算すると
our 13C 17O observations fit best with the former option
given the data in hand. The relationship between the0.1Myrで1.33M
⦿cations, DCO+ (ring from 110 and 160 au) and N2 H+(inner edge of the ring at 90 au), and the location of the=>円盤初期では不安定
midplane CO snowline is not trivial, but both species
have been detected in this disk (Mathews et al. 2013;
Qi et al. 2015). Our analysis shows that the C 18O emission in both models tested is optically thick, and thus

Dust accretion in binary systems: implications for planets and transition discs
Chachan, Y. et al.

• 連星系惑星の観測• 連星系のdynamical stability limitのすぐ外側で見つかる傾向• そこで作られた？or 別の場所で作られて移動した？
• 前者はbinaryの影響が大きく難しい。
• 後者の方が優勢。truncated edgeでのdust trappingで作る• ただ現行の計算では観測のlocationはまだ再現出来ていないらしい
Dust accretion in binary systems

3

trappingが起き、惑星がで• q~0.1くらいのCircumbinary diskでdustTable 1. Simulations Parameters

Here, dust and gas particles have masses md and mg ,ties ⇢d and ⇢g , and local velocities vd and vg respecy. P is gas pressure, (~r) is the gravitational potential
e binary (see appendix B) and avisc is acceleration due
tificial viscosity (see Springel 2005). In our simulations
ompute the drag coefficient assuming
constant Stokes
pber, S t = t s ⌦(r), where ⌦(r) = GM/r3 , the Keplerian
lar frequency due to the total mass of the binary, M.
• GADGET-2
The binary orbits in an anticlockwise direction and has
ss ratio q •= M
2 /M1 , total mass M = M1 + M2 , semi-major
ガス+ダストa, and eccentricity e. The simulations are run in the inframe centredon theregime
binary’s centreof mass. The stars(q<0.1)• stellar
reated as sinks and particles that come within 0.01a ofr star are• accreted
onto regime
it (Bate et(q<0.01)
al. 1995). The biplanetaryparameters are assumed to be constant over the duraof the simulationand the stellar gravitational
softeningdiskの観点• pre-transitional
h is set to 0.001a, chosen to be small enough to ensure
the circumstellar discs are not a↵ected by the softenWe do not include the e↵ects of disc self-gravity or the-reaction of the disc on the binary in our simulations. A

きるかどうか？を検証する• SPHによる計算

Parameter

Description

ValueMa⌦bcsTotal Mass
Binary semi-major axis
Binary orbital frequency
pSound speed (normalised to GM/a)
Gas injection radiuse < 0.3(in units of a)e = 0.3
Dust injection radiuse < 0.3(in units of a)e = 0.3
Stokes number
Gas injection rate (per tdyn = 1)
Dust injection rate (per tdyn = 1)
Artificial viscosity parameter
nominale = 0.0, q = 0.4
Injection angulare = 0.2, q = 0.1
momentum for gas
e = 0.2, q = 0.4, 0.7
e = 0.3, q = 0.1
e = 0.3, q = 0.4, 0.71.0
1.0
1.0
0.05
1020
7
100.1
500
100
1.5
1.2
1.3
1.25
1.4
1.4
1.5

Rin j
Rin j,dust
StṄ
Ṅdust↵S PHjin jq=0.01のケース•The circumstellar disc masses are est
the mass within the Hill radius that
We convolve with a Gaussian kernel
move high frequency noise in (Mdisc
ある程度の時間でCBdiskにダ
its gradient with time to determine th
simulation is allowed to run for either
スト(St=0.1)がたまり、セカン
accretion onto the binary ceases. We ocretion rates from roughly 30torb ⇠ 200
ダリへの降着はpuregasになるinclude the results obtained
after stetablished (as in Young et al. 2015). To
時間はeに依存•of dust and gas to the primary andthe fractional accretion rate onto the=ṀprimaryṀprimary + Ṁsecondary.

We also use the ratio ṀD / ṀG to studyof dust and gas accretion rates withratio.
ṀD Ṁprimary,dust + Ṁsecondary,dust=,ṀG
Ṁprimary,gas + Ṁsecondary,gas

where each Ṁ is normalized to the inticles.

3

DUST ACCRETION

3.1

Planetary regime

We begin by considering a binary wi

include the results obtained
tablished (as in Young et alof dust and gas to the prim
the fractional accretion rat• ~15%のCB diskのガスがprimaryに入る• eに依存せず=• λdustは減少を続ける(e=0.2)

でprimaryとsecondaryへ
Young&Clarke(2015)を再現• ギャップが開くとダスト降着は止まる
λ=>pressure maximumにダストが堆積しているか調べる
pressure max.にある要素の近星点半径を指標とする.

ṀD Ṁprimary,dust + Ṁseconda=ṀGṀprimary,gas + Ṁseconda• 最初, ダスト(St=0.1)はガスと同じ比率•Ṁprimary + Ṁsecondary

We also use the ratio ṀD / Ṁof dust and gas accretion rratio.

Y. Chachanet al.
Stellarregime(q=0.1)のケース•Ṁprimary

where each Ṁ is normalized
ticles.
Y&& (2015)
0.5
Figure 3. The
gas and dust (for e = 0.2) accreted
Stfraction= 0. 1ofDust

onto the primary, , plotted as a function of time. After an initialtransient phaseGDs(⇠ 200tdyn , greyedfor gasACCRETION
settles to a value3 out),
DUSTof ⇠ 0.15. for dust can only be properly quantified for e = 0.2 as0.4
dust accretion rate is too low for for lower eccentricites. There is
3.1 Planetary regimea clear decline in for dust, implying that the amount of dust
accreted onto the binary (Figure 2) as well as onto the primary
0.3
We begin by considering ais going down with time.

0.2
0.1
0.00.00.2(i.e. a 10 MJ planet for a sknown that companions ondust in pressure maxima t
as is suspected to be thePinilla et al. 2012; Zhu et aFigure 1, it is clear that d0.4
0.60.8trappedefficiently
for comp0Dss 5DtiR (q)• 近星点距離がバイナリ間隔の2.2-2.8倍になるとダスト降着が止まる• qが大きくなると降着を止めるには大きな近星点距離が必要• 実際のCB cavityは大きいのでCBで惑星を作る説が優勢かも• とはいえ観測されているplanet locationにはmigrationが必要• planetary mass regimeの結果について• eが大きければ降着が止まるまで時間がかかる(>300orbits)が、内側で惑星を作る時間(~Myr)より短い• そういう系にあるhot Jupiterはin situ formationではなさそう• eの大きいplanetary mass companionの存在は、pre-transitional diskの解釈になるかも• 複数の重い惑星がなくても良い

HST spectra reveal accretion in MY Lupi
Alcala, J.M., et al.

Gaia DR2 distances to Collinder 419 and NGC 2264 and new astrometric orbits for HD 193322
Aa,Ab and 15 Mon Aa,Ab
Apellaniz, J.M.

Inner rocky super-Earth formation: distinguishing the formation pathways in viscously heated andpassive discs
Bitsch, B.

The fulcrum wavelength of young stellar objects – the case of LRLL 31Bryan, G.R., et al.

Radial Drift and Concurrent Ablation of Boulder-Sized Objects
Burn, R., et al.

The Structure of Dark Molecular Gas in the Galaxy – II. Physical State of “CO-Dark” Gas in thePerseus Arm
MBusch, M.P., et al.

Stars and brown dwarfs in the sigma Orionis cluster. IV. IDS/INT and OSIRIS/GTC spectroscopy andGaia DR2 astrometry
Caballero, J.A., et al.