星形成ゼミ
SFN #312 (59-67本目)
百瀬宗武（茨城大・理）詳細解説は以下の3本• #63: Detection of Nitrogen gas in the β Pictoris circumstellar disk (P.A. Wilson et al.
A&A in press)• #64: Does HL Tau Disk Polarization in ALMA Band 3 Come from Radiatively Aligned
Grains? (Haifeng Yang et al., MNRAS in press)•#66: Star-forming content of the giant molecular ﬁlaments in the Milky Way (M. Zhang
et al. A&A in press)
その他はひと言解説63. Detection of Nitrogen gas in the β Pictoris circumstellar
disk
P. A. Wilson et al. A&A in press
https://arxiv.org/pdf/1811.04927.pdf【内容】β Pic に対するfar-UVのスペクトルをHST’s Cosmic Origins
Spectrograph により取得。初めてNI triplet の吸収線を検出。モデリングにより円盤中のNアバンダンスを求め，過去から知られていたC, O richな
このデブリ円盤ガスの起源を議論した。
【背景】• 過去のFarUV のスペクトル観測 (e.g., Roberge+ 2006): C, O richなガス
成分が明らかになっていた。以下の2つの起源が提案(Xie et al. 2013)：【観測データと解析】• HSTのCosmic Origins Spectrograph により取得したfar-UVスペクトル（Feb. 2014 - May. 2018），1200Å近辺のNI triplet ラインを初検出• スペクトルの形をモデリングでフィッティング，MCMCで• ISM 成分と，デブリ円盤起源２成分（CS0とCSX）←１成分より著し
く良いフィット，３成分にしてもあまり良くないについても上限値を求めた• 同じ波長帯にあるSIII**, MnII
A&A proofs: manuscript no. N

MnII
NI

NI

MnII
NI SIII**SIII**(1) “Preferential production” : C, O-rich な物体からのnon-thermal
desorption による放出物 (UVによるガス放出，ダスト蒸発，Cometからの放出・蒸発)(2) “Preferential depletion”：普通のabundanceを持つガスから，
radiation force を受けにくいC, Oが残った• Nの定量ができれば両者を区別できる：• もしN/Feが(C, O同様)高ければ，Preferential depletionをサポート(radiation force を受けにくいと言う点でNはC, Oと共通)• もしN abundanceが普通なら，Preferential production をサポート（Cometの主成分はH2O, それに続きCO, CO2で，Nはマイナー）

Fig. 1. Measured flux as a function of wavelength (HST rest frame) for the NI lines at ⇠ 1200 Å. The black spectrum represents the combined datawith the thicker parts indicating the region used to fit the continuum which is shown as a black solid line. The coloured lines show the individualcomponents with the cyan coloured line showing the individual absorption profiles before they get convolved by the instrumental LSF.

values are likely caused by uncertainties in the wavelength solu（上）観測スペクトルとベストフィットの結果
tion.

To estimate the total column density of circumstellar NI gas

We initially fit the absorption lines using a two component
model consisting of one component representing the interstellar medium (ISM) and another the circumstellar gas disk. The
resulting fit was poor, suggesting the presence of a third component. This third component is added and named CSX , and its
inclusion decreased the value of the reduced 2 from 1.6 (with
10 free parameters) to 1.0 (with 15 free parameters). This deP. A. Wilson
et al.: Detectionof Nitrogenin thecreased the Bayesian information
criterion(Schwarz
et al. gas
1978)from 646 to 451 and the Akaike information criterion (Akaike1974) from 607 to 409. Adding a fourth component, however,
did not improve the fit, so we settle on this three-component
model. The CSX component, which was free to vary in radial
velocity space, gave the best fit close to the rest frame of Pic at20.0 km/s (Gontcharov 2006; Brandeker et al. 2004). The continuum was modelled using a second order polynomial.

【結果】

3.3.2. Selecting the free component parameters

In the absence of reliable lines for which to check the wavelength calibration locally, we take the liberty of not constraining the ISM (vISM ) and CS0 (vCS0 ) bulk velocities to their literature values. However, since the ISM component has been wellconstrained in previous studies to be o↵set by -10 km/s relative
to the star’s radial velocity component (Vidal-Madjar et al. 1994;
Lallement et al. 1995), we set this requirement and allow the twoparameters to vary together, provided that vCS0 vISM = 10 km/s
is maintained. Aside from that constraint, all parameters for the
ISM absorption component were kept fixed except for the ISM
nitrogen column density, log(NNI /1 cm2 )ISM . The fixed ISM parameters were T ISM = 7000 K (the temperature of the ISM) and⇠ISM = 1.5 km/s (the turbulent broadening of the ISM), both
values of which follow from studies observing the interstellar
medium towards Pic and other nearby stars, such as Bertin
et al. (1995); Lallement et al. (1995).
For both circumstellar components, the column density andturbulent broadening (⇠) were set as free parameters. The bulk
velocity of the CSX component was also allowed to vary freely.
The temperature of the CS gas is unknown. However, to avoid
the degeneracy introduced when modelling both the turbulent
velocity and the temperature simultaneously we fix the CS gas
temperature to 10 K for both CS components. The relationshipbetween the parameters are expressed mathematically as

Table 1. The medium values and uncertainties of the posterior probability distributions generating using the MCMC method.

Parameter

Valuelog(NNI /1 cm2 )ISM
log(NMnII /1 cm2 )ISM
Pictoris
T ISM circumstellar disk
bISM
vISM

13.8+0.2
0.3
 11.0+0.7
7000 K†
1.5 km/s†
13.3+1.8
3.0 km/s

Narrow absorption by gas at Pic system velocity, CS0log(NNI /1 cm2 )CS0log(NSIII⇤⇤ /1 cm2 )CS0log(NMnII /1 cm2 )CS0
bCS0
vCS0

14.9 ± 0.7
 11.6+0.4
 12.2+0.1
1.0+0.4
0.3 km/s
vISM + 10 km/s

Broad absorption by gas at Pic system velocity, CSX
log(NNI /1 cm2 )CSX
log(NSIII⇤⇤ /1 cm2 )CSX
log(NMnII /1 cm2 )CSX
bCSX
vCSX
†

indicates the fixed parameters.

14.04 ± 0.03
14.2 ± 0.1
 12.6+0.1
25.8 ± 1.7 km/s
25 ± 1 km/s

Carlo (MCMC) run using the emcee code described in ForemanMackey et al. (2013). We ran 200 MCMC walkers with a totalof 10,100 steps each, with 100 burn in steps. This resulted in a
total of two million steps, of which ⇠ 25 % were accepted. The
posterior probability distributions for the free model parameters
are shown in the corner plot (Foreman-Mackey 2016) in Fig. 3,
along with the marginalised 1D distributions which were used
to calculate the median values and the uncertainties on each freeparameter (see Table 1).

4. Results
2kT
b =
+ ⇠2
m
2

(2)

values are likely caused by uncertainties in the wation.
To estimate thePic測定値，total column density of circum（黒）：β
we add the two circumstellar components togethe

Absorption by the ISM

4.1. Saturated NI lines

The results from the best fit (and MCMC) show that the CS0
where b is the width of the lines, T the temperature, k, the Boltz- component is completely saturated (seen by the cyan colouredmann constant, m the mass of the considered species and ⇠ the lines which reach a flux of 0 in Fig. 1). The ISM component isturbulent broadening (also sometimes referred to as microturbu- partially saturated. The saturation leads to larger uncertainties on
2
Fig. 3.
A corner plot showing the one and two dimensional projections of the posteriorlog(Nprobability
distributions
for the freeaparameters.
Theuncertainty
blue
lent
velocity).
/1cm)
reaching
magnitudeof 0.7. ThisNICS
0dashed lines indicate the mean of the distribution. The black dashed lines in each of the 1D histograms represent the 1 deviations (68 % of the
becauseincreasein column
doesn’t make the abmass) with the central dashed line indicating the median value. The solid black lines inis
eachof the 2Dan
histograms
represent
the 1, 2 densityand 3 levels
signaturemuch
deeper,butonlyinsteadrespectively (with 1 = 39.3 % of the volume). The red dashed lines indicate the modesorptionof the distribution.
For theparameterswhich
have anwidens the absorp3.4.
Fit
to
the
data
upper uncertainty, the uncertainty was calculated using assuming a truncated Gaussiantion
distribution.
profile which is then partially absorbed by the CSX com⇤⇤
We fit the NI triplet in conjunction with the MnII and SIII lines ponent. This is seen by the broad posterior distribution of ⇠CSX⇤⇤
with
MnII overlapping
the blueside
bluestNI line. We
doMnII
valuesshown
in distributions
Fig. 3. Interestingly,
although
4.3. Column
density estimatesfor MnII
andofSIIIof thecolumndensityand find them
to be the CS is free tolog (Abundance) relative to Fe

3.3.1. Choosing the number of model components

Fig. 1. Measured flux as a function of wavelength (HST rest frame) for the NI lines at ⇠ 1200 Å. The black spectrum represents thewith the thicker parts indicating the region used to fit the continuum which is shown as a black solid line. The coloured lines show
components with the cyan coloured line
the individual absorption profiles before they get convolved by the instrumental【アバンダンス(relative
to showingFe)比較】

Brandeker et al. (2016)

4

Nに対するのがこの仕事⇣
2
NI /1 cm
NI
/1 c
log(N
/1
cm
)
=
log
10
+
10
NI
CS
（赤△）：CI コンドライト= 14.9 ± 0.7（橙⦿）：Sun
We compare the ratio of the N/Fe column densit
to Si) with solar abundances, CI chondrites and（青□）：ハレー彗星ダスト
CS02
Present work

0

2

CSX

Fig. 2. It shows that the NI abundance is consistentHalley dust abundances, yet is inconsistent with C

2
H

CNO

Si

Ca

Fig. 2. The abundances of the Pic gas disk (black circles) comparedto solar abundances (orange Sun symbols), CI chondrites (red triangles)
and Halley dust (blue squares). The abundances are given relative to iron(Fe) and the figure is adapted from Fig. 2 from (Roberge et al. 2006).
The OI detection by Brandeker et al. 2016 who used the Herschel telescope, represents a range of possible values which depend on the spatial
distribution of the O gas in the CS disk. The OI column density estimate
by Roberge et al. 2006 (represented by the black circle) could represent
a lower column density limit due to challenges associated with measuring optically thick OI lines (see Brandeker 2011 and Fig. S1 in Roberge
et al. 2006). The CI chondrites consistently show low abundances forthe volatile elements H, C, N, O which is expected as they were in agaseous state when the meteorite formed and did thus not condense or
accrete.

4.2. An indirect estimate of the H column densit
in the direction of Pic

Using the HST and the Goddard High Resolution
C, Oのように異常に高い(GHRS),
Meyer et al. (1997) conducted observat
terstellar NI and found a value for the mean in
アバンダンスではなかった
phase
N/H abundance at (7.5 ± 0.4) ⇥ 10 5 . Furt
reported no statistically significant variations in
N abundances from sight↓ line to sight line and ndensity-dependent nitrogen depletion from the gas
timatethe total hydrogenproduction
column density in the I
Preferential
value for the NI ISM column density calculated
and assuming N(NI)⇡N(Nを示唆
total ). From the NI ISM
sity we calculate that the HI ISM value in the dir
is log(NHI /1 cm2 )ISM = 17.9+0.2
0.3 . This is consisten
et al. (2017) where this value was found to be 18.2

Article number, page 4 of 8

【そのほかの議論】• CS0 (Narrow absorption by disk gas)：bCS0(線幅)~ 1km/s →比較外側の，stable に回転できるバンド領域からの放射• CSx (Broad absorption by disk gas)：bCSX(線幅)~ 26km/s →内側の領域から？

比較的 gas richなexocomets がたくさん来て溜まったNI成分？

64. Does HL Tau Disk Polarization in ALMA Band 3 Comefrom Radiatively Aligned Grains?

H. Yang et al.

Haifeng Yang et al., MNRAS in press
https://arxiv.org/pdf/1701.05953【今回の問題提起】
よく考えると，Band3はRadiative Alignmentと２つの点であってない(1) Elliptical vs. Circular

Dec (asec)

Dec (asec)

Dec (asec)【内容】ALMAで得たHL
ng disk.
Soon after the appearance of theTauの多波長偏光イメージ(850μmと3mm)は，
theory3.1 mm (ALMA Band 3)
millimeter polarization through dust self-scattering
Radiative Alignmentではpol. vectorと直交する向きに
1.5
ka et al.
2015), it became clear that the CARMA
ob大きく異なるPolarization
patternを示しており，850μmが散乱偏光が卓0.14
Polarization from Radiative Alignment 3
pattern in HL Tau is more consistent with scattering中心星がいるはず（Circular）だが，観測はellipticalなパターン
1.0
polarizationin an inclined disk (Yang et al. 2016a;
越しているのに対し，後者が(散乱偏光の影響が小さくなって)Radiative
0.12
orbit the central star at di↵erent speeds1 ) than by radiaa et al. 2016) than that produced by grains aligned
Elliptical Pattern
Circular Pattern
0.5
widelyexpected toroidal magnetic fields, although
tive alignment and that both alignment mechanisms are exalignmentが見えてきたと理解されて来た。λ=3mmの結果を定量的に注
0.10
ignment with more complex magnetic fields cannot
pected to produce pronounced azimuthal variation in polar0.0 ized intensity that shouldd out意深く見ると単純なRadiative(Stephens et al. 2014; Matsakos et al. 2016;
be easily observable. We computealignmentとは合わない。”Goldalignment”
0.08
Alves et al. 2018 for the case of BHB07-11). With
the expected ALMA Band 3 polarization
patterns for HL
0.5
etric (ガスとダストの相対速度差に基づく整列)
observations by the Atacama Large MillimeTau disk based on the radiative and aerodynamic alignment
を自己散乱などと組み合わせ
millimeter Array (ALMA), spatially resolved polar0.06finite telescope beam,
mechanisms taking into account of thehas been
detected in an increasing number of circum1.0
ることが必要？
and compare them with (a)the observational data in Sec. 4.
disks, especially at ALMA Band 7/6 (0.87 mm/1.3
We find that both mechanisms fail0.04
to match the polarizao date, the majority of the observed patterns are con1.5
tion
data
and0.0are thus
disfavored.
In Sec. 4.3, we stress the
1.5
1.0
0.5
0.5
1.0
1.5
with thatfrom
self-scattering,
e.g.,
HL
Tau
(Stephens【HL Tau ALMAの結果】Kataoka et al. (2017) importance& Stephenset al.
(2017)
oftakingintoaccount beam-averaging in comRA (asec)
017, Band 7), IM Lup (Hull et al. 2018 Band 7), IRS
paring model predictions and observational data and explore
Figure 2. Elliptical vs circular polarization pattern. The red solid
ovoy et al. in prep, Band 6), HH212 (Lee et al. 2018;
3.1(Girart
mm (ALMA
Band
3)line segments are for polarization orientations, and green dashedplausible
to improve
0.87
mmways(ALMABand the7) model predictions. Additional), and HH80/81
et
al.
2018,
Band
6).
1.5
1.5 challenges of aligned grain models in explaining the multiline segments for the direction of the required radiative flux pro0.14
sides magnetically aligned grains and dust selfjected into the sky plane in the case of radiative alignment.
wavelength observations of the HL3.0
Tau disk are briefly disng, there
are
other
mechanisms
forproducingmil1.01.0 cussed. Our main results are summarized in Sec. 5.
/submillimeter polarization. One of such mecha0.12
2.5
adiative0.5
alignment, was recently proposed by Tazaki
0.5
the short axis of the projected grain shape in the sky plane017), based on the earlier work by Lazarian & Hoang
0.10
2.0
remains aligned with a radial line that passes through the. Within the framework of grain alignment by ra0.0
0.0 2 POLARIZATION ORIENTATION
center (see the green dashed line segments in the right panel
torque, radiative alignment could happen when the
ダストの整列0.08
1.5
ic field is weak. In this case, grains will align withof Fig. 2 for illustration). To visualize the situation better,
2.1
Polarization
patternfromradiativealignment
0.5
0.5
ng axes perpendicular to the local radiation flux, or
it is again helpful to go to theor
extremecase, where
the e↵ec異方性を特徴付けるもの（磁場輻射fluxor
ガスとの相対速度）
inaninclineddisk
iscircular,notelliptical
1.0
0.06
ction of the local radiation anisotropy, rather thantively oblate grains are infinitely thin “disks” (or “flakes”). In
1.0
1.0
gnetic field. The mechanisms of radiative(a)alignment
A major reason that thepolarization in ALMA
this case, it is easy
to /showthat,
whenのいずれかが平行になる
projected to the sky(b) HL Tauとダストのshort
axis
long
axis
0.5
st self-scattering have in common that they both
0.04
Band 3 was attributed to radiative alignment was that theplane, the “disks” become “ellipses” with their short axes
1.5
1.5 polarization vectors appear to follow the elliptical contours
the anisotropy in the radiation field incident onalong the radial direction in ↓the sky plane and long axes
1.5 1.0 0.5 0.0 0.5 1.0 1.5
1.5 1.0 0.5 0.0 0.5 1.0 1.5
t grain to produce polarization. Nevertheless, theyof constantRA
brightness
dust
perpendicular to the radial direction, producing a circular
RA (asec)(asec) (which are the circles of constant 円盤を斜めから見ると，PAごとで自然と偏光効率が変わり↵erent dependence on wavelength and disk orientaemission in the disk plane projected onto the sky plane; seepolarization pattern as illustrated by the red solid line seghich makes them distinguishable, especially through0.87 mmobservations(ALMA Band7) withFig. 1a) and the radiative alignment was thought to proments in the right panel of Fig. 2. This is consistent with theavelengthpolarization
and
in
disks
（見えるダストの断面形状が変わるため）偏光率にPA依存性が
自己散乱
1.5 Radiative Alignment
duce such an elliptical pattern (see Fig. 3b of Kataoka et al.
well-known result of the polarization orientation from mage inclinations (i.e., edge-on).
Figure 1. HL Tau
disk polarization
detectedby ALMAin Band
3.02017).
The
expectation
would
be
true
if the grains have their
netically aligned grains in (optically thin) molecular clouds,（seeTazakietal.
2017）??
date, the1.0
strongest support for the mechanism of ra~ are100μm）
出るはずだが，観測はそこまで顕著なPA依存性がない
3 (panel a)（ダストサイズ
and Band 7 (b). The panels
adopted from Kataoka(2) 偏光度のPA依存性（詳しい図は次頁）

shortest axes aligned by radiative flux along the radial di-which is always perpendicular to the B-field component in【マンガでわかるダスト整列偏光：
Polarizationfrom Radiative
Alignment
Polarization
from
Radiative
Alignment
7【整列機構ごとでの偏光効率の(PA, i) 依存性】

7

ほぼedge on 円盤のPA依存性】

2.00

“棒”を
正面から
見る

1.25
1.00
0.75
0.50
0.25

Major axis

1.50
Minor axis

Polarization degree (%)

1.75

Aerodynamic
Radiative
Magnetici = 30i = 45i = 60i = 85

Aearodynamic

“棒"を
横から見る
Radiative

“碁石”を
横から見る

“碁石”を
正面から見る

Figure 8. Large di↵erence in not only polarization orientation
Figure 8. Largedi↵erencein notonly polarization
orientation
0.00
but also
azimuthalvariationof polarization
degree between the
0
20
40
60
80
but also azimuthal
variationof polarization
degree between
aerodynamic(upperpanel) and radiative(lower) thealignment for
Azimuthal angle sky (degree)
aerodynamica(upperalignment
nearly panel)edge-onand
diskradiative(with an (lower)
inclination
angle i for= 85 ). Sucha nearly edge-on(with suitedan inclination
angle i =). alignmentSuchdisks disk
are ideallyfor distinguishingthe85two
mechFigure 7. Polarization degree as a function of the azimuthal
disks are ideallysuited for distinguishing the two alignment mechanisms.
Figure 7. Polarization
degreeas a functionof the azimuthal
angle in thesky plane✓sky for di↵erentalignment mechanisms
anisms.
anddi↵erent
inclination
The polarization
angle in the sky
plane✓sky fordi↵erentangles.
alignment
mechanisms degrees fromthe magneticalignmentline) andaerodynamicalignment
and di↵erent inclination
angles.
The (dottedpolarization
degreesfrom
4 HL TAU BAND 3 POLARIZATION(solid) havea similar
dependence,both peaking on
the
Aearodynamic
は longaxisがガス流と平行 ＝ Prolate (needle) でモデル化
the magnetic alignment(dottedline) angularand aerodynamicalignment
4 HL TAU BAND
3 POLARIZATION
minor axis(✓skydependence,= 90 ). This bothis opposite
to on
thattheof the radiative(solid) have a similar
angularpeaking
4.1 The model
Radiative
は short axisが輻射flux と平行 = Oblate (flake)でモデル化(dashed),which topeaks
axis (✓sky4.1=
0 )The model
minor axis (✓skyalignment= 90 ). Thisis opposite
thatonof thethe major
radiative
Of the three grain alignment mechanisms discussed in
instead.
Di↵erent
anglesare(✓represented
by di↵erentalignment (dashed),
which
peaksinclinationon the major
axis
sky = 0 )last
section,magneticalignment discussed
is the leastinlikely poscolors.
Note thatthe arepolarization
degreethe minor axis deOf the the
three
grain
alignment
mechanisms
instead. Di↵erent
inclination
anglesrepresented
by on
di↵erent
creasesmonotonicallywith onincreasing
inclination
sibility
for producing
the Band3leastpolarization
observed inthethelast section,
magneticalignmentisthelikelyposcolors. Note thatthe polarization
degreethe minor
axis de- angle for
円盤全体で空間的に平均化した時，偏光ベクトルが長軸に沿うか
caseofradiativealignment(dashedlines),
vanishingcompletely
HL Tau disk
shown
in Fig. 1a) observed
because itinpredicts a
creases monotonically with increasing inclination angle for thesibility for producing
the(andBand
3 polarization
the edge-on(dashedcase with
i = 90.
polarization
orientation
perpendicular,rather thancase of radiativein alignment
lines),
vanishingcompletely
HL Tau短軸に沿うかで区別がつくはず（少なくともPA依存性が出るはず）
disk(and shownin Fig. 1a)because it predicts
a parallel,
the ellipticalcontours of rather
iso-intensity.
For the radiativein the edge-on case with i = 90 .
polarizationtoorientation
perpendicular,
than parallel,alignment,
we of
have
already pointed
outradiative
one of its potento the ellipticalcontours
iso-intensity.
For thetial problems: it predicts a circular, rather than elliptical

【モデルとの比較】
8

H. Yang et al.

(1) 空間分解能

Dec (arcsec)

1.0

無限大の場合のPolarization pattern と PI

Radiative alignment

Aerodynamic alignment
100

100

10 1

10 1

10 2
1.0
1.0

10 2

Band 3で観測されたPol. Vectorの向きのパターンとしてはAerodynamic alignment の方が合っているがPol. FractionのPA依存性はどちらとも合わない

0.5
0.0

Band 7で観測されたPol. Vectorの向き・Pol. Fractionとも合わせる必要がある

0.5
1.0
1.0

0.5

0.0
0.5
RA (arcsec)

0.5

0.0
0.5
RA (arcsec)

1.0

Aerodynamic な alignment + 自己散乱で説明できる？
詳細なシミュレーションはfuture work

Polarization from Radiative Alignment 9
Figure 9.
The modeled
polarization without
telescope beam convolution. The color map represents the polarized intensity (with arbitrary
(2)
空間分解能
観測ビームでなました時の比較（本論文では，定性的な理解を得るためのunits). The vectors with uniform length show the orientation of the polarization. The di↵erences between these two mechanisms are clear.
Radiative alignment produces a circular polarization pattern with a stronger polarization along the major axis. Aerodynamic alignment
produces an elliptical polarization pattern with a stronger polarization along the minor axis.

1.5

Data

0.14

Dec (asec)

These two1.0
orientations are the same along the major and
0.12
minor axes, and the di↵erence becomes bigger at intermediate azimuthal
0.5 angles. On the other hand, polarized intensity
is concentrated along the major axis for radiative alignment,
0.10
which is the opposite to that for aerodynamic alignment.
4.2

0.0

0.08

Neither
0.5 radiative nor aerodynamic alignment

0.06
The models in Fig. 9, generated from the ALMA Band
1.0 observation of unpolarized continuum
3 long-baselineemis(a)sion of ALMA Partnership et al. (2015), have a much higher
0.04
1.5
spatial resolution than Band 3 polarization observation by
1.5(2017).
1.0 To0.5compare
0.0 with
0.5 real
1.0 data,
1.5 a teleKataoka et al.
(asec)
scope beam convolution is RA
needed.
We convolve the modeled Stokes I, Q, U map separately with the beam used for
the Band 3 polarization observation (000· 445 ⇥ 000· 294). The
results are shown in Figs. 10 and 11.

1.5

Radiative alignment

0.14

1.0

0.12

0.5

0.10

0.0

現象論的なモデル計算を示しているが割愛）
0.14

1.0

0.12

0.5

0.10

0.0
0.08

0.5
1.0

1.5

Aerodynamic alignment

0.06
(b)

1.5
1.5 1.0 0.5 0.0 0.5 1.0 1.5
RA (asec)

0.04

0.08

0.5
1.0

0.06
(c)

1.5
1.5 1.0 0.5 0.0 0.5 1.0 1.5
RA (asec)

0.04

66. Star-forming content of the giant molecular filaments in
the Milky Way
M. Zhang et al. (A&A,in press)
https://arxiv.org/pdf/1811.02197.pdf

母サンプル 121 GMFs with the length of > 10 pc(identified by Ragan et al. (2014), Wang et al. (2015), Zucker et al.
(2015), Abreu-Vicente et al. (2016), Li et al. (2016), and Wang et al.
(2016).)【内容】天の川中のGiant Molecular Filaments (GMFs)を統一的な方法で解CO Data あり (FCRAO あるいは Mopra サーベイ)

析。過去論文から抽出した57のGMFsでサンプルを構成し，それらに含まれ

self-absorption あるものと13COでカバーされているYSOs と 分子ガスを一貫した手法で解析し，その統計的な性質を調べた。

ないもの，redundantのものを除去
57 GMFs が最終的に対象として残る【解析】

Fig. 9. Overview of GMF 54 (GMF341.9-337.1). Others are same as Fig. 3.

A&A proofs: manuscript no. draft_v0• nIR - fIR で点源抽出，コンタミを除いてYSOs候補同定• 前景減光を補正後，Tbol元にClass 0/I, Flat, II, III区分(右カラムFig. 11)• Class IIのKsバンド絶対等級(MKs)分布から，Orion(L1641N)での MKs vs.

Table 2. Summary of giant filaments identified with di↵erent dataset and criteria.
Filament

Identification

Velocity coherence confirmation

samples

Datasetresolution

Criteria

NH2 regime

DatasetGiant Molecular
Filament (GMF)

GLIMPSE,UKIDSS-GPS,
2MASS⇠1-200visual inspection for longabsorption or extinction feature,projected length > 1 ,allowing for gaps

AV &10GRS,
ThrUMMSvisual inspection for ‘skinnylong’ emission feature,aspect ratio 10,
lower temperature thansurroundings

AV ⇠ 5Spectral lines

13

CO

Reference

Criteria

continuous velocity variations,
without steep velocity jumps

1, 4

M★関係(検出限界を見積もる)とUniversal IMF (Kroupa 2001)を使ってCO

continuous velocity,
without velocity broken

2

Class IIの星の数に焼き直す

3

could giant filament(CGF)

Milky Way bone(bone)

Herschel Hi-Gal

GLIMPSE,MIPSGAL⇠25-35⇠2-60000

visual inspection for ‘largely
continuous filamentary
extinction features’,parallel to Galactic plane,
within 20 pc of mid-plane,
aspect ratio>50

AV ⇠ 20

GRS

13

HOPS,
MALT90,BGPS,
GRS,ThrUMMS

NH3 ,N2 H+ ,
HCO+ ,
13COv < 3 km s 1 per 10 pc

ATLASGAL
follow-up
molecularline
observationsb

NH3 ,N2 H+ ,
CS,
13
CO

1
betweenv < 10 km sconnected compact sources

5

BGPS

N2 H+ ,HCO+

v < 2 km s 1 between
connected clumps

6• Class I に関しても，Kryukova et al. (2012)で求められていた統計的な

ATLASGAL
filament (AF)ATLASGAL⇠2000

extracting skeletons with
DisPerSEa ,aspect ratio > 3

AV &10

MST algorithm,
projected length > 10 pc,
linearity > 1.5

AV & 10Luminosity分布関数を元に検出限界を見積もり，それを補正してClass Iの星の数に焼き直す

MST filament (MF)

BGPS

⇠3300

• 以上を通じ，GMFs ごとに>0.08M⦿ のYSOs の総質量や分布を得る。

References. (1) Ragan et al. (2014); (2) Wang et al. (2015); (3) Zucker et al. (2015); (4) Abreu-Vicente et al. (2016); (5) Li et al. (2016); (6) Wanget al. (2016).
Notes. (a) Sousbie (2011). (b) Please see the Table 3 of Li et al. (2016) for the complete velocity references.

GMF 39 の例
左がAv Map (13COに基づく)
図中の赤と緑がそれぞれClass I, II
Fig. 10. the H

K s versus J

H color–color diagram for the YSOs

Fig. 11. The de-reddened ↵ and T bol of YSOs in the GMF 39(CFG047.06+0.26). The dashed lines show the boundaries of YSO classification schemes (Greene et al. 1994; Chen et al. 1995).

サンプルの物理量の分布
M. Zhang et al.: Star-forming content of the giant molecular filaments in the Milky Way

星形成率 (SFRs)，星形成効率 (SFEs)，
単位面積あたりの星形成率 (SFRs)分布
Fig. 19. Two-point correlation functions for the Class I sources in 6 GMFs. The title on each panel corresponds to the ID number of Table 4. The
red solid lines show the linear fits to the roughly straight line part of the data and the fitting slopes are labeled in each panel.

Fig. 20. Probability distributions of (a) star formation rate; (b) star formation efficiency; (c) surface density of star formation rate for 34 GMFs
with the distances of <5.5 kpc. The red vertical lines show the median values of SFE and ⌃SFR that are re-estimated with Class I+Flat+II sourcesin the nearby star-forming regions (see the text for details).

in the range of 0.06 3.88 M Myr 1 pc 2 with a median value8of 0.9 M Myr 1 pc 2 . The SFEs obtained in five nearby starforming clouds by Evans et al. (2009) are ⇠3 6%, with a median value of ⇠5%. Based on a larger sample, Evans et al. (2014)
found that SFEs in nearby star-forming regions are in the rangeof [0.2%, 7.8%], with a median value of 1.8%. At a first glance,the ⌃SFR and SFEs of the GMFs are on average significantly
lower than that of the molecular clouds in the Gould Belt. However, we must remind that there is a systematic di↵erence between the SFRs obtained in the GMFs and nearby star-forming
regions due to the di↵erent methods that are used to estimate the
SFRs.

Evans et al. (2009) and Evans et al. (2014) use all YSOs detected in the nearby star-forming regions to estimate the SFRs,
including Class I, Flat, Class II, and Class III sources. However,
due to the lack of strong infrared excess, the Class III sources
could be incomplete in some clouds. Moreover, the optical spectroscopical observations in Serpens and Lupus found that ⇠40100% of Class III sources are actually background AGB stars(Oliveira et al. 2009; Romero et al. 2012). Considering the highcontamination fraction in the Galactic plane, we only use Class
I+Flat and Class II sources detected in the GMFs to estimate thetotal number of YSOs.
To compare the GMFs with nearby star-forming regions, were-calculate the SFRs of the nearby clouds based on the latest
version of YSO samples in the c2d and Gould Belt surveys
presented by Dunham et al. (2015). We obtain the extinction
map for each nearby molecular cloud with 2MASS (Skrutskie

近傍のStar Forming regions のメジアン値（赤）を中心に分布：GMFsといえど，SF活動性は大差ない？

Fig. 17. Distributions of (a) filament length; (b) heliocentric distance; (c) logarithm of cloud mass Mcloud ; (d) line width v; (e) logarithm of gas
surface density ⌃gas ; (f) logarithm of dense gas mass Mdense ; (g) free-fall time obtained based on spherical morphology; (h) aspect ratio; and (i)logarithm of dense gas mass per unit length.

⇠170 M pc 2 ; Solomon et al. 1987). Note that we use the extinction contour of AV = 3 mag to estimate the cloud mass, whichis inclined to underestimate the total mass of the GMFs.
In Fig. 18, we show the line widths ( v) versus the sizes (R)and masses (Mcloud ). Here the size is the equivalent radius ob-

gression coefficients using the Bayesian method developed by
Kelly (2007) that allows the inclusion of uncertainties along bothaxes during the fitting process. Note that the fitting routine requires symmetric uncertainties; for asymmetric uncertainties we
simply use the maximum of the two asymmetric errors. Based on

8

We have excluded the nearby star-forming clouds with ⌃SFR = 0 during the statistics. Thus this value of 0.9 is significantly higher than thevalue of 0.48 o↵ered in Table 1 of Evans et al. (2014).

Article number, page 17 of 70

with possibility that there is a correlation between ⌃SFR and fDG ⌃gasg), for GMFs.
byいわゆるKS則Overall, the star formation rate per free-fall time of GMFs
al.
is in the range of 0.002 0.05 with a median value of 0.02,
ense
which is roughly consistent with the results of Krumholz et al.
to(2012). However, the large uncertainties of ⌃SFR , ⌃gas , fDG ⌃gas ,stiand ⌃gas /t↵ do not allow us to obtain any robust conclusion about
tor,
whether there are correlations between these parameters; for thisthepurpose, more accurate measurements of SFR and gas mass areadaneeded. Covering wider dynamic ranges of the parameters would
malso be helpful in studying the relationships. However, we de) if
tect a significant correlation between SFR and Mdense for GMFs,
hat
which indicates that the gas mass above a visual extinction of 7
A&A proofs: manuscript
0.8
mag can be used as a predictor of SFR.
enThisisshallower
thantheapproximately
linearrelationshipprot
gas
found in the nearby clouds (Lada et al. 2010) A&A proofs: manuscript
extinnds; 5.2. What controls SFRs of the molecular clouds?
clou
1
the
Fig. 22. SFR and ⌃SFR as a function of (a) dense gas mass; (b) cloud mass;fDG ⌃gasfor GMFs.
Note
the GMFs
original
SFR
Myr) = 0.046M(M from), di↵erent(2) proto
Lada
dense
distr
Thisandis(c)(Mshallower
than
the thatapproximately
linear relationshipidentification publications are marked with di↵erent symbols. The abbreviations correspond to the column one of Table 2. The straight lines
We foundintheprevious
sectionastrongcorrelation
between
struc
found
in
the
nearbyclouds
(Lada
et
al.
2010)
extin
represent Lada’s equation (green solid line, Lada et al. 2010), the relation
from
WuGalactic
et al. (2005)(blue dashedline),
fitting
resultfrom Evans et al.
or
in
the
dense
cores
(Wu
et
al.
2005)
So- SFR and(2014)
abovgas (redmass
forline),
GMFs.
regression
cloud
dottedand our The
linear Bayesianfitting results linear
without considering
uncertainties (black1 solid line). The Pearson correlation coefficients
SFR
(M
Myr
)
=
0.046M(M),(2)
the di↵erent sets of parameters obtained without
considering
uncertainties
aremarkedontopregionofeachpanel.
The
insert
plots
in
1
Lada
dense
we gives thebetween
etadistrirelationshipA&A proofs:
manuscript
no.
draft_v0
SFR
(M
Myr
)
=
0.012M(M).
(3)
Wu slopes, and intrinsic scattersdense
each panel show the probability distributions of correlation coefficients (r), fitting( ) obtained with Bayesian linear
substructheregression method by Kelly (2007).
or in the Galactic dense cores (Wu et al. 2005)
ers "The slope we derive is closer to that derived by Evans et al. abov, it This is shallower than the approximately linear relationshipprotostars
iscorrelated
with
the
area
of
the
cloud
above
a
(黒実線；本
(青：Wu
et
al.
2005
(0.66±0.12)
1
1
ing
s
et
al
(2014),
who Myrre-investigatedthedense
SFRsin0).the nearby star-forming
SFR
(M
)
=
0.012M(M
SFR (M
Myr
)
/
M
(M
).
(1)
the found
0(3)
Wu
dense
in the nearby clouds (Lada et al. 2010)
extinction A , denoted as S (A ). Obviously, S (A ) refle

K sub-s
Galactic
dense ofcores)
furth
regions with a uniformK YSO sample. TheyKobtained
a relation
cloud
structure.
Kainulainenetal.
(2014)
used
the
prob
ers
"
The
slope
we
deriveisclosertothatderived
by
Evans
et
al.
(緑：Ladaetal.
(赤点線：Evanset1
Articlenumber,
page
19
of
70
1
0.89
SFRLada (M Myr ) = 0.046Mdense (M ),
(2)
SFR
(M
Myr
)
=
0.041M). the(4)interna
ing sI
Evanswho
distributionsofgas
densityasmeasureofthe(2014),
re-investigated
the
SFRs
in
the
nearbystar-forming
dense (M2010 近傍雲)
al. 2014 近傍SFRs)

研究の結果)

A&A proofs:
manuscript no. draft_v0
フィラメント単位長さ当たりのSFRがGMFs線密度と良い相関？

SFR/Mdense vs. Mdense
A&A proofs: manuscript no. draft_v0

Fig. 23. SFR/Mdense as a function of dense gas mass for the GMFs.
Fig. 23. SFR/Mdense as a function ofNote
dense
gasthemass
for from
the GMFs.
that
GMFs
di↵erent original identification publications
Note that the GMFs from di↵erent originalidentification
publications
are marked
with di↵erent
symbols. The abbreviations correspond to theare marked with di↵erent symbols. The
abbreviations
to thecolumnone of correspond
Table 2. The
Pearson r obtained without consideringcolumn one of Table 2. The Pearsonuncertainties
r obtained without
considering
is marked on the top of the figure. The insert plots show
uncertainties is marked on the top of the figure. The insert plots show
the probability distributions of correlation coefficient and fitting slope
the probability distributions of correlation coefficient and fitting slope
obtained with Bayesian linear regression method by Kelly (2007).
obtained with Bayesian linear regression method by Kelly (2007).

Negative Correlation= SFR vs. MdenseがSub-linear なことの別表現

Fig.
24. per
SFR
perlength
unit forlength vs. dense gas mass per unit length for
Fig. 24. SFR per unit length vs. dense gas
mass
unit
that the GMFs
GMFs. Note that the GMFs from di↵erentGMFs.
originalNote
identificationpub- from di↵erent original identification publications
are markedcorrewith di↵erent symbols. The abbreviations correlications are marked with di↵erent symbols.
The abbreviations
to thecolumnone of Table 2. The black line shows the linear
spond to the column one of Table 2. The spondblack lineshows
the linear
fittings obtained
without
fittings obtained without considering uncertainties.
The Pearsonr ob-considering uncertainties. The Pearson r obtained
without
consideringtained without considering uncertainties is also
markedon thetop of the uncertainties is also marked on the top of the
figure. The insert plots show the probabilityfigure.
distributionsof correlation
The insert
plots show the probability distributions of correlation
coefficient and fitting slope obtained withcoefficient
Bayesian linear
regression
and fitting
slope obtained with Bayesian linear regression
method by Kelly (2007).
method by Kelly (2007).

59

Non-thermal emission from massive star forming regions: A possible SNR candidate
G351.7–1.2?

59 V. S. Veena , S. Vig , B. Sebastian , D. V. Lal , A. Tej and S. K. Ghosh
1

1

2

2

1

3

1

Indian Institute of Space science and Technology (IIST), India; 2 National Centre for Radio Astrophysics (NCRATIFR), India; 3 Tata Institute of Fundamental Research (TIFR), India
E-mail contact: veenavs.13 at iist.ac.in
We present low frequency wide band observations (300 − 500 MHz) of the star forming complex G351.7–1.2 using
upgraded Giant Metrewave Radio Telescope (uGMRT), India. Combining this with the optical, infrared and submillimeter data, we analyse the large scale diﬀuse radio emission associated with the region that exhibits a broken shellmorphology. The spectral index of the emission in the shell is −0.8, indicating non-thermal emission. Hα emissionthat mimics the morphology of the radio shell on a smaller scale is also detected here. Based on the non-thermal
emission from the radio shell and the presence of its optical counterpart, we classify G351.7–1.2 as a candidate SNR.
A γ-ray source detected by F ermi LAT (1FGLJ1729.1–3641c) is located towards the south-west of the radio shell andcould have a possible origin in the interaction between high velocity particles from the SNR and the ambient molecular
cloud.
Accepted by MNRAS
https://arxiv.org/pdf/1811.01666

60

Deep, multi-band photometry of low-mass stars to reveal young clusters: a blind studyof
theForming
NGC Complex
2264 region
G351.7-12 の長波長電波マップ（NT emission）がメイン• Star1,2
1
1L.
Venuti,F.
Damiani,andL.
Prisinzano• Fermi LAT で検出された γ線源とradio shellが対応，SNRと分子雲との相互作用の現場？
1

INAF – Osservatorio Astronomico di Palermo G. S. Vaiana, Piazza del Parlamento 1, 90134 Palermo, Italy; 2Eberhard Karls Universität, Institut für Astronomie und Astrophysik, Sand 1, 72076 Tübingen, Germany

https://arxiv.org/pdf/1811.01666

60

Deep, multi-band photometry of low-mass stars to reveal young clusters: a blind studyof the NGC 2264 region

60 L. Venuti , F. Damiani , and L. Prisinzano
1,2

1

1

1

INAF – Osservatorio Astronomico di Palermo G. S. Vaiana, Piazza del Parlamento 1, 90134 Palermo, Italy; 2Eberhard Karls Universität, Institut für Astronomie und Astrophysik, Sand 1, 72076 Tübingen, Germany
E-mail contact: laura.venuti at astro.uni-tuebingen.deWe aim to test a purely photometric approach to statistically identify a young clustered population embedded in alarge population of field stars, with no prior knowledge on the nature of stars in the field. We conducted our blind
test study on the NGC 2264 region, which hosts a well-known young cluster. We selected a large (4 deg2 ) area aroundthe NGC 2264 cluster, and assembled an extensive r, i, J catalog of the field from pre-existing large-scale surveys.
We then mapped the stellar color locus on the (i − J, r − i) diagram to select M-type stars, which: i) comprise asignificant fraction of the Galactic stellar population; ii) exhibit the strongest luminosity evolution from the PMS to
the MS; iii) have r, i, J color properties that provide a direct and empirical estimate of AV . A comparative analysisof the photometric and spatial properties of M-type stars as a function of AV enabled us to probe the structureand stellar content of our field. We could identify two distinct populations: a diﬀuse field population and a clusteredpopulation. The presence of occulting material, spatially associated with the clustered population, allowed us to derive
an estimate of its distance (800–900 pc) and age (∼0.5–5 Myr), consistent with the literature parameters for the NGC
2264 star-forming region. The extracted clustered population exhibits a hierarchical structure, in excellent agreementwith the NGC 2264 subregions reported in the literature. Our selection of clustered members is coherent with theliterature census of the NGC 2264 cluster for about 95% of the objects in the inner regions of the field, where thecontamination rate by field stars in our sample is only 2%. The method tested here can be readily applied to surveys
like Pan-STARRS and the future LSST to undertake a first complete census of low-mass, young star populations down
to distances of several kpc across the Galactic plane.
Accepted by A&A
http://arxiv.org/pdf/1811.02731

61

A simpleapproach to CO
cooling in molecular clouds
dataだけに基づき，young
cluster の同定する方法をテストした• 純粋にPhotometry
A. P. Whitworth1 and S. E. Jaﬀa1
1

http://arxiv.org/pdf/1811.02731

61

61

A simple approach to CO cooling in molecular clouds
A. P. Whitworth1 and S. E. Jaﬀa1
1

School of Physics & Astronomy, Cardiﬀ University, Cardiﬀ CF24 3AA, UK

E-mail contact: ant at astro.cf.ac.uk
Carbon monoxide plays an important role in interstellar molecular clouds, both as a coolant, and as a diagnostic
molecule. However, a proper evaluation of the cooling rate due to CO requires a determination of the populations
33
of many levels, the spontaneous and stimulated radiative de-excitation rates between these levels, and the transferof the emitted multi-line radiation; additionally, this must be done for three isotopologues. It would be useful tohave a simple analytic formulation that avoided these complications and the associated computational overhead; this
could then be used in situations where CO plays an important role as a coolant, but the details of this role are not
the main concern. We derive such a formulation here, by first considering the two asymptotic forms that obtain in
the limits of (a) low volume-density and optical depth, and (b) high volume-density and optical depth. These forms
are then combined in such a way as to fit the detailed numerical results from Goldsmith & Langer (1978; hereafterGL78). The GL78 results cover low temperatures, and a range of physical conditions where the interplay of thermaland sub-thermal excitation, optical-depth eﬀects, and the contributions from rare isotopologues, are all important.
The fit is obtained using the Metropolis-Hastings method, and reproduces the results of GL78 well. It is a purely local
and analytic function of state — specifically a function of the density, ρ, isothermal sound speed, a, CO abundance,
XCO , and velocity divergence, ∇ · υ. As an illustration of its use, we consider the cooling layer following a slow steadynon-magnetic planar J-shock. We show that, in this idealised configuration, if the post-shock cooling is dominated by
CO and its isotopologues, the thickness of the post-shock cooling layer is very small and approximately independentof the pre-shock velocity, υo , or pre-shock isothermal sound speed, ao .
Accepted by Astronomy & Astrophysics
http://arxiv.org/pdf/1811.06814• CO回転遷移の冷却率を幅広い範囲で解析的に求めるformalizmを開発

Bipolar Hii regions produced by cloud/cloud collisions

• Goldsmith & Langer (1978)との比較

Fig. 1. The continuous curves give the total CO cooling rate, as predicted by the approximate analytic formulation derived here (Eqns. 15 through18). The di↵erent panels correspond to (a) T = 10 K; (b) T = 20 K; (c) T = 40 K;n and (d) T = 60 K (these temperatures
are given in the top lefthandocorner of each panel). The di↵erent curves represent di↵erent values of log10 XCO (|r · |/3 km s 1 pc 1 ) 1 = 8, 7, 6, 5 and4 (thesevalues are given down
margin of each panel). The rates obtained by the detailed computations of GL78 are given at discrete values
n the righthandoof the density, log10 nH2 /cm 3 = 1, 2, 3, 4, 5, 6 and 7; plus signs, stars, open circles, crosses and open squares correspond respectively to
n
o
1
1 1
log10 XCO (|r · |/3 km s pc ) = 8, 7, 6, 5 and 4.

62

62

Bipolar Hii regions produced by cloud/cloud collisions
A. Whitworth1 , O. Lomax1 , S. Balfour1 , P. Mége2 , A. Zavagno2 and L. Deharveng2
1

School of Physics & Astronomy, Cardiﬀ University, Cardiﬀ CF24 3AA, UK; 2 Aix Marseille Univ, CNRS, LAM,
Laboratoire d’Astrophysique de Marseille, Marseille, France
E-mail contact: ant at astro.cf.ac.uk
We suggest that Bipolar Hii Regions may be the aftermath of collisions between clouds. Such a collision will produce
a shock-compressed layer, and a star cluster can then condense out of the dense gas near the centre of the layer. If
the clouds are suﬃciently massive, the star cluster is likely to contain at least one massive star, which emits ionisingradiation, and excites an Hii region, which then expands, sweeping up the surrounding neutral gas. Once most of
the matter in the clouds has accreted onto the layer, expansion of the Hii Region meets little resistance in directions
perpendicular to the mid-plane of the layer, and so it expands rapidly to produce two lobes of ionised gas, one oneach side of the layer. Conversely, in directions parallel to the mid-plane of the layer, expansion of the Hii Region
stalls due to the ram-pressure of the gas that continues to fall towards the star cluster from the outer parts of thelayer; a ring of dense neutral gas builds up around the waist of the Bipolar Hii Region, and may spawn a second
generation of star formation. In this paper we present a dimensionless model for the flow of ionised gas in a Bipolar
Hii Region created according to the above scenario, and predict the characteristics of the resulting freefree continuum
and recombination-line emission. This dimensionless model can be scaled to the physical parameters of any particularsystem. Our intention is that these predictions will be useful in testing the scenario outlined above, and thereby
providing indirect support for the role of cloud/cloud collisions in triggering star formation.
Accepted by• タイトルの通りの内容• 論文というよりアイディアのメモっぽい
Detection of Nitrogen gas in the β Pictoris circumstellar disk
http://arxiv.org/pdf/1811.06828

63

P.A. Wilson1,2,3,4, R. Kerr5 , A. Lecavelier des Etangs3,4 , V. Bourrier3,4,6 , A. Vidal-Madjar3,4 , F. Kiefer3,4 ,https://arxiv.org/pdf/1811.11897

65
65

Physical properties and chemical composition of the cores in the California molecular
cloud
Guo-Yin Zhang1,2 , Jin-Long Xu1 , A. I. Vasyunin3,4 , D. A. Semenov5,6 , Jun-Jie Wang1 , Sami Dib6,7 ,Tie Liu8,9 , Sheng-Yuan Liu10 , Chuan-Peng Zhang1,6 , Xiao-Lan Liu1 , Ke Wang11,12 , Di Li1,13 , Zhong-Zu
Wu14 , Jing-Hua Yuan1 , Da-Lei Li15 and Yang Gao16
1

National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, PR China; 2 University ofChinese Academy of Sciences, Beijing 100049, PR China; 3 Ural Federal University, Ekaterinburg, Russia; 4 Engineer35
ing Research Institute Ventspils International Radio Astronomy Centre of Ventspils University of Applied Sciences,
In?enieru 101, Ventspils 3601, Latvia; 5 Department of Chemistry, Ludwig Maximilian University, Butenandtstr. 513,81377 Mnchen, Germany; 6 Max Planck Institute for Astronomy, Knigstuhl 17, 69117, Heidelberg, Germany; 7 Niels
Bohr International Academy, Niels Bohr Institute, Blegdamsvej 17, 2100 Copenhagen , Denmark; 8 Korea Astronomy
and Space Science Institute, 776 Daedeokdaero, Yuseong-gu, Daejeon 34055, Republic of Korea; 9 East Asian Observatory, 660 N. Aohoku Place, Hilo, HI 96720, USA; 10 Institute of Astronomy and Astrophysics, Academia Sinica. 11F
of Astronomy-Mathematics Building, AS/NTU No.1, Sec. 4, Roosevelt Rd, Taipei 10617, Taiwan; 11 Kavli Institutefor Astronomy and Astrophysics, Peking University, 5 Yiheyuan Road, Haidian District, Beijing 100871, PR China; 12European Southern Observatory (ESO) Headquarters, Karl-Schwarzschild-Str. 2, 85748 Garching bei Mnchen, Germany; 13 CAS Key Laboratory of FAST, NAOC, Chinese Academy of Sciences, Beijing 100101, PR China; 14 Collegeof Physics, Guizhou University, Guiyang 550025, PR China; 15 Xinjiang Astronomical Observatory, CAS, 150, Science
1-street, Urumqi, Xinjiang 830011, PR China; 16 School of Physics and Astronomy, Sun Yat-Sen University, Zhuhai,
519082, Guangdong, PR China
E-mail contact: zgyin at nao.cas.cn
We aim to reveal the physical properties and chemical composition of the cores in the California molecular cloud(CMC), so as to better understand the initial conditions of star formation. We made a high-resolution column densitymap (18.2”) with Herschel data, and extracted a complete sample of the cores in the CMC with the fellwalker algorithm.
We performed new single-pointing observations of molecular lines near 90 GHz with the IRAM 30m telescope along
the main filament of the CMC. In addition, we also performed a numerical modeling of chemical evolution for the cores
under the physical conditions. We extracted 300 cores, of which 33 are protostellar and 267 are starless cores. About
51% (137 of 267) of the starless cores are prestellar cores. Three cores have the potential to evolve into high-mass stars.
The prestellar core mass function (CMF) can be well fit by a log-normal form. The high-mass end of the prestellar
CMF shows a power-law form with an index α = −0.9 ± 0.1 that is shallower than that of the Galactic field stellar
mass function. Combining the mass transformation eﬃciency (ε) from the prestellar core to the star of 15 ± 1% andthe core formation eﬃciency (CFE) of 5.5%, we suggest an overall star formation eﬃciency of about 1% in the CMC.
In the single-pointing observations with the IRAM 30m telescope, we find that 6 cores show blue-skewed profile, while
4 cores show red-skewed profile. [HCO+ ]/[HNC] and [HCO+ ]/[N2 H+ ] in protostellar cores are higher than those inprestellar cores; this can be used as chemical clocks. The best-fit chemical age of the cores with line observations is∼ 5 × 104 years.
Accepted by Astronomy & Astrophysics (A&A)
https://arxiv.org/pdf/1810.09522• カリフォルニア分子雲（巨大分子雲クラスだが星形成効率があまり活発でない）に対する包括的な調査• CMFやgas chemistry を星あり vs. 星なし
コア同士で比較http://arxiv.org/pdf/1811.02197

67

67 B. Zuckerman

The Nearby, Young, Argus Association: Membership, Age, and Dusty Debris Disks
1

1

Department of Physics and Astronomy, University of California, Los Angeles, CA 90095, USA

E-mail contact: ben at astro.ucla.edu
The reality of a field Argus Association has been doubted in some papers in the literature. We apply Gaia DR2 data
to stars previously suggested to be Argus members and conclude that a true association exists with age 40–50 Myr
and containing many stars within 100 pc of Earth; β Leo and 49 Cet are two especially interesting members. Based on
youth and proximity to Earth, Argus is one of the better nearby moving groups to target in direct imaging programsfor dusty debris disks and young planets.
Accepted by ApJ
http://arxiv.org/pdf/1811.01508• GAIAデータを元に，Argus Associationが幻でないことを検証，Debris 円盤探査の良い対象

Abstracts of recently accepted major reviews