63

Dynamics of a massive binary at birth・大質量星の形成はなぜ難しいか？
球対称の仮定では、Mstar>20Msunで、輻射圧>重力になって降着が止まる。
解決案1：そもそも降着率が大きければいい→観測的にも高い降着率が示唆される(10^4Msun/yearとか)Show affiliations• Zhang, Yichen; Tan, Jonathan C.; Tanaka, Kei E. I.; De Buizer, JamesM.; Liu, Mengyao; Beltrán, Maria T.; Kratter, Kaitlin;Mardones, Diego; Garay,
Guido
Abstract*解決案2：円盤を通した非軸対称降着ならもうちょい小さな
Almost all massive stars have bound stellar companions, existing in binaries orhigher-order multiples1-5. While binarity is theorized to be an essential feature
降着率でもいいof how massive stars form6, essentially all information about such properties isderived from observations of already formed stars, whose orbital properties may
have evolved since birth. Little is known about binarity during formation stages. ・高降着率だと何が起こるか？
Here we report high-angular-resolution observations of 1.3 mm continuum and円盤が分裂してバイナリーを作るだろう
H30α recombination line emission, which reveal a massive protobinary with
→高分解能で大質量原始星周りの円盤を観測しapparent separation of 180 au at the centre of the massive star-forming regionて確かめたいIRAS 07299-1651. From the line-of-sight velocity diﬀerence of 9.5 km s-1 of thetwo protostars, the binary is estimated to have a minimum total mass of 18 solar
masses, consistent with several other metrics, and maximum period of 570 yr,
・これまでの観測
assuming a circular orbit. The H30α line from the primary protostar shows
kinematics consistent with rotation along a ring of radius of 12 au. The
赤外線観測、赤外干渉計、センチ波などでバイナ
observations indicate that disk fragmentation at several hundred astronomical
リーの距離を調べてた。
units may have formed the binary, and much smaller disks are feeding the
IRAS 20126+4104: 850 au, G35.20-0.74: 800 au,
individual protostars.
NGC 7538IRS1: 430 au, IRAS 17216-3801: 170 au

見た目の軌道間隔だけではなくて、軌道の運動なども知りたい。
https://ui.adsabs.harvard.edu/abs/2019NatAs...3..517Z/abstract

・本観測1 ALMA1.3mm観測・本観測2: H30α再結合線大きいマップ：low resolution (0.22 0.15秒角=370au 250au )の1.3連続波マップ(streaming structure, 3.8­8.0M⊙ )A,Bそれぞれから検出した。
*主量子数n=1に遷移してくるのがライマン系
列、n=2がバルマー系列で、これがn=30。

LETTERS

a

E

100 b
Declination offset (mas)W
S

Source A

50
Source B

0

Declination offset (mas)

0

–5
5

0

200

–100

20
100 au

100

c

A

25
B

–100

6

–5

b

30

A

0

4
Intensity (K)

1,000
500

400
200
0
–200
–400
400

Source B

300

50

–50

Source A

010
5100 au

20

200
100
0

50
0
–50

2,000 au
2

1,500

50

200 150 100 50
0 –50 –100
Right ascension offset (mas)

0

400

–50

–150

1.68kpc away

2,000

100

–150

2,500

800
Intensity (K)N

Intensity (K)aM (M⊙)

Declination offset (arcsec)

NATURE ASTRONOMY

Intensity (K)

右上：(0.035
10
0.029= 59 au 49
au)->180au 離れた2つの電波源を見つけた。
5(51 and 18 mJy)->明るい方をA, 暗い方をBと呼ぶ

NATURE ASTRONOMY

8

–10

–50

0

50

100

–1

VIsr (km s )Fig. 2 | H30α line spectra at the continuum peak positions. a, At the peak
position of Source A. b, At the peak position of Source B. The r.m.s. noiselevels are marked by the error bar in each velocity channel. The red solid
curves are fitted Gaussian profiles with the central velocities indicatedby the red dashed lines. The residual differences between the observed
spectra and fitted Gaussian profiles are also shown below the spectra. The
grey shaded regions indicate the 3σ noise levels.

Right ascension offset (arcsec)
6

tre of mass vof binary forsecondary gr
is further fro
high-mass stformation ev
state, is unlik
few protostel
Discussion aforming starcore accretio
magnetic fiel
formed centr
to produce t
tional instabi
current circu
earlier disk.
if the region iin competitiv
There arethe disk fragmisalignmen
ture around S(Methods). F
scale structur
ture around
Such misalig
fragmentatioby changes ingas at these v
components
the infall env
structured an
so disk orien
Misalignmen
been indicate
sources19,23. F
scenario by dnot. Finally, l
to determine
formation.

・とにかく質量を知りたい
1.3 mm 電波連続波からの見積もり→周り(>500 au)がoptically thinだと思って見積もると周りのガスはだいたい 3.8­8M⊙ くらい。
*ただし、干渉計観測なので広がった成分は見えていない。これは下限値

H30α観測分光からの質量の見積もり
スペクトルの中心が15.5 1.1km/s (A) と 25.0 1.6km/
s(B)と、ちょっと違う。差が9.5 1.9km/s。これをバイナ
リーの軌道が原因だと思って質量を見積もる→まず円軌道だと思うと、total system mass がM0>18.4 7.4M⊙*離心率もいろいろ変えて考えては見た。右下の図

計全体の速度がVsys=16.5‒18kms­1 とわかっているので、バイナリーの重心がこの速度だと思うとbinary
mass ratio
は AS
NATURELETTERS
<0.7
10

a

N
100
E

Declination offset (mas)W
S

5

Source A

50
Source B

0
–50

50

–100

20
100 auDeclination offset (mas)

100

c

A

50

25
B

–100
100 au200 150 100 50
0 –50 –100
Right ascension offset (mas)2,000 au
0

5

2

0

4
Intensity (K)6–5Right ascension offset (arcsec)

30

A

0
–50

10
5

–150

–5

200
100

–150

0

400

8

–10

20

M (M⊙)

Declination offset (arcsec)*ZAMSじゃないと思うと、8­19M⊙(A) , 7­17M⊙ (B)800bIntensity (K)H30α観測からの見積もり
Zero-Age主系列星(ZAMS)の星のモデルを仮定し、制動放射の強さから星の質量を見積もる。
連続波を引き去って、free-free成分が39mJy and 4mJy だとわかった。そこから→12.5M⊙ (A) and 10M⊙ (B)議論
Aの周りの円盤（リング）の軌道運動から見積もった質量(6Msun)がなんかちっちゃい。

H30α分光データからAの周りのガスの回転
分光データのうち、狭い速度範囲ごとにmapを書いたchannel mapsを見て各ピークを取って一枚の絵にする（図４）*free-freeから見積もった系全体が18.4 7.4M⊙ なので、これの一番小さい質量(11 Msun)を等質量バイナリーだと思った時5.5
Msunのときとconsistent→おおよそ場所ごとの速度成分がわかる→これがケプラー回転するリングだと思うとRring = 7 1 mas = 12 au,
中心の質量が6 2M⊙→回転がケプラーより遅い？

LETTERS

NATURE ASTRONOMY
a

b

10

c

50

1.5

Centroid intensity

VIsr (km s–1)

20
10
0

–5

1.0

10

0.5

0

5

0

–5

Right ascension offset (mas)

–10

–20

d

20

c

–10
–10
10

a

VIsr (km s–1)

Declination offset (mas)

30

0

b

30

40
5

少し広い領域を見ると、コンパクトソースはあんまり多くない。rich clusterでの星形成という可能性は低い→でかい分子雲コアが収縮して、形成された円盤が分裂した可能性が高い。

e

0.0
0

2

4

6

8

10

12

–20

–10

0

10

20

30

40

50

VIsr (km s–1)

Offset (mas)Fig. 4 | Distributions of the H30α emission centroids in Source A and comparison with the model. a, Spatial distribution of the H30α emission centroids
in Source A in each velocity channel. The centroids (triangles with error bars) are determined by a two-dimensional Gaussian fit to the H30α emissionin each channel. The error bars show 1σ uncertainties from two-dimensional Gaussian fitting. Only channels with peak H30α intensities higher than 20σ(1σ!=!1.8!mJy!beam−1) are included. The right ascension and declination offsets are relative to the continuum peak position. Line-of-sight velocities are shown by thecolour scale. The coloured circles are the predicted centroid distribution of the best-fit model of an inclined rotating ring. The actual projected shape of the best-fit
ring is shown by the black ellipse, where the emission comes from the eastern half (the solid half). The centre of the fitted ring is marked by the star. b, Distancesof the centroids from the continuum peak position with their line-of-sight velocities, compared with the best-fit model. The meaning of the symbols are same as
those in a. c, Scaled centroid intensities and scaled 1σ noise (triangles with error bars) compared with the prediction of the best-fit model (solid curve).
or different HRLs of same source have central velocities different26 by ~5 km s−1,
while some studies show that multiple HRLs have same central velocities which
are consistent with the source velocity based on modelling13. However, there wasno mm HRL observation with a spatial resolution <100 au previously. With suchby the approximately Gaussian profiles of the observed H30α spectra), the ratio
between H30α peak intensity and free-free continuum intensity is derived to be29
TH30α

6 ⎛ Te ⎞−1−1⎛ Δv ⎞ ⎡⎛ Te ⎞−1⎤ ⎡N (He+) ⎤−1

Supplementary Figure 5: Compact continuum sources identified in the high-resolution data.
a: continuum map of the region < 1000 from the central sources, with the crosses marking theidentified continuum sources. b e: Zoom-in views of the identified continuum sources.

64

Physical Properties of Large-scale Galactic Filaments
Show affiliations• Zucker, Catherine; Battersby, Cara; Goodman, Alyssa
Abstract
The characterization of our Galaxy’s longest filamentary gas features has been the subjectof several studies in recent years, producing not only a sizable sample of large-scalefilaments, but also confusion as to whether all these features (e.g., “Bones,” “Giant
Molecular Filaments”) are the same. They are not. We undertake the first standardized
analysis of the physical properties (H2 column densities, dust temperatures,morphologies, radial column density profiles) and kinematics of large-scale filaments inthe literature. We expand and improve upon prior analyses by using the same data sets,techniques, and spiral arm models to disentangle the filaments’ inherent properties fromselection criteria and methodology. Our results suggest that the myriad filament-finding
techniques are uncovering diﬀerent physical structures, with length (11-269 pc), width(1-40 pc), mass (3× {10}3 {M}☉ {--}1.1× {10}6 {M}☉ ), aspect ratio (3:1-117:1), and highcolumn density fraction (0.2%-100%) varying by over an order of magnitude across the
sample of 45 filaments. We develop a radial profile-fitting code, RadFil, which is publicly
available. We also perform a position-position-velocity (p-p-v) analysis on a subsample
and find that while 60%-70% lie spatially in the plane of the Galaxy, only 30%-45%
concurrently exhibit spatial and kinematic proximity to spiral arms. In a parameter space
defined by aspect ratio, dust temperature, and column density, we broadly distinguishthree filament categories, which could indicate diﬀerent formation mechanisms or
histories. Highly elongated “Bone-like” filaments show the most potential for tracing grossspiral structure (e.g., arms, spurs), while other categories could be large concentrations ofmolecular gas (giant molecular clouds, core complexes).

https://ui.adsabs.harvard.edu/abs/2018ApJ...864..153Z/abstract

・銀河系の大スケールフィラ
メント
銀河系スケールに、大きなスケールで細いのフィラメント構造が見つかってきている。
文献によって調べ方はまちまちなので、統一的な手法で系統的に調べたい- 80pc 0.5 pcの速度成分が連続したinfrared dark

ネッシーの発見
The Astrophysical Journal, 797:53 (13pp), 2014 December 10

cloudを見つけた(Nessie) Jackson et al. 2010
- その後、この構造はもっと広がっていることがわかった。下図。Goodman et al. 2014
- しかも、これは銀河重力によってできたフィラメント
Goodmanetal.
で初めて見つかった構造かもしれない？

Figure 1. “Nessie Classic”, “Extended”, and “Optimistic”. It is recommended that this high-resolution figure be viewed electronically, as zooming and panning arenecessary to reveal the structures discussed. Background imagery is a three-color image constructed from Spitzer where red shows MIPS 24 µm, green IRAC 8.0 µm,
and blue IRAC 5.8 µm. The image (brightness/contrast) adjustment used emphasizes Nessie and also makes the image look a bit greener than is “natural.” Yellow
horizontal lines show b = 0◦ and b = − 0.◦ 5. Small white numbers show galactic longitude (l) in degrees. A non-annotated high-dynamic-range view of this Spitzer
image is available as a supplement to this paper at http://hdl.handle.net/1902.1/22050. (Note that related figures below show less exaggerated contrast and zoom in on
the central portions of Nessie.).
(A color version of this figure is available in the online journal.)
Goodman et al. 2014

The Astrophysical Journal, 864:153 (34pp), 2018 September 10

Zucker, Battersby, & Goodman

Figure 1. Various selection criteria employed for major large-scale fIlament catalogs included in this study, taken from their original publications (Ragan et al. 2014;
Wang et al. 2015, 2016; Zucker et al. 2015; Abreu-Vicente et al. 2016).

The Astrophysical Journal, 864:153 (34pp), 2018 September 10

Zucker, Battersby, & Goodman

Figure 13. Top: l–v diagram of the spiral arm models and large-scale ﬁlaments in a section of the ﬁrst Galactic quadrant. The MST “Bones” based on the catalog data
are shown, but the tracks for the MST “Bones” based on the continuum data are functionally equivalent. Background grayscale shows 12CO emission from the Dameet al. (2001) survey, integrated between −1°<b<1°. Spiral arm traces are taken from Reid et al. (2016) and include the Local Spur (LoS), the Aquila Rift (AqR),
the Aquila Spur (AqS), the Sagittarius Near arm (SgN), the Sagittarius Far arm (SgF), the Scutum Near arm (ScN), and the Norma arm (Nor). The colored dots
correspond to the four different large-scale ﬁlament catalogs included in this study, derived through Gaussian ﬁtting of the ﬁlament’s CO emission in 0°. 1 longitudeintervals (see Section 3.6). Bottom: plane-of-the-sky map of the same section of the ﬁrst Galactic quadrant. Background grayscale also shows the 12CO emission fromthe Dame et al. (2001) survey, now integrated between 0 and 110 km s−1. The ﬁlament masks are overlaid to scale and color-coded according to ﬁlament catalog. The
same spiral arm models are shown as in the top panel.

determine the central velocities of our ﬁlaments at evenly spaced

plane-of-the-sky map over an identical longitude range (weThe Astrophysical Journal, 864:153 (34pp), 2018 September 10

Zucker, Battersby, & Goodman

45個のlarge-scale ﬁlamentについて同じ手法でのデータ解析をやった•まずvariationが大きい。大きさ(11-269 pc), 幅(1-40pc), 質量 3e3-1.1e6Msun, アスペクト比(3:1-117:1), 線質量 80-6300Msun/pc, mediancolumn density (1e21-1e22 cm-2)
Figure 10. Length, linear mass, width, and aspect ratio box-and-whisker plots for the four different ﬁlament classes in our sample. All four are plotted in logarithmic
scale. In each box plot, the solid line indicates the median of the distribution while the dashed line indicates the mean. The bottom and top edge of each box denote theend of the ﬁrst and third quartiles of the distribution, while the end of the “whiskers” enclose all of the data points that are not considered outliers, which are plotted as
individual dots. We ﬁnd signiﬁcant variation in large-scale ﬁlament properties both among and between classes, with length, width, linear mass, and aspect ratio
varying by one to two orders of magnitude from one end of the ﬁlament spectrum to the other. In the ﬁrst and second panels, we show two distributions for the MST“Bone” lengths and linear masses—one from our catalog-based MST “Bone” deﬁnition (dark orange) and the other from the continuum-based MST “Bone” deﬁnition(light orange). In the third and fourth panels, only the continuum-based MST “Bone” widths and aspect ratios are available. Further, we additionally show in gray theextinction-derived widths and aspect ratios of the Milky Way Bone catalog, which are all originally identiﬁed as IRDCs.

The Astrophysical Journal, 864:153 (34pp), 2018 September 10

Zucker, Batteanalyses—including a jupyter notebook that users can run
Several studies (Juvela et al. 2012b; Smith et al. 2014b) haveshown that the best-ﬁt radial column density proﬁle values arethemselves—is publicly available online as part of the RadFil
17
intimately dependent on background subtraction and Zucker,
ﬁtting radius.
The RadFil
and its2018
functionality
package.
The AstrophysicalJournal,package
864:153 (34pp),
September 10is
Battersby, & Goodman
As
such,
we
providealternative
Gaussian-based
widthsfor
ourdescribed in Zucker & Chen 2018 and more information isﬁlaments using different background subtraction and ﬁtting radii
provided in Appendix A.8.
in Table 4. The impact of ﬁtting parameter variation is discussed
Our ﬁrst estimate of the width involves taking perpendicular
at length in Appendix A.8, but the average FWHM typicallycuts across the spine, determining where the cut touches the edgechanges by a few tenths of a parsec for a reasonable range ofof the mask on either side of the spine, and taking the medianﬁtting parameters. The process of building and ﬁtting a radial
length of these cuts as the mask-based ﬁlament width (see the thincolumn density proﬁle for Filament 2 is shown in Figure 9 andred cuts across the spine in the bottom panel of Figure 9(a)). Thisoutlined in more detail in Appendix A.8.
mask-based width was determined for every ﬁlament in the sample
Box-and-whisker plots for the length, linear mass, width, andand is given in Column (6) of Table 3. For our second estimate of
aspect ratio distributions are shown as side-by-side panels in
the width, we ﬁt a Gaussian function to the radial column density
Figure 10. As seen in the leftmost panel of Figure 10, theproﬁles of a subset of ﬁlaments whose quantitative boundaries are
median lengths of the four different ﬁlament classes spandeﬁned via the Hi-GAL column density maps (the Zucker
approximately a factor of 3, with the GMFs having the highest
et al. 2015 Bones and Wang et al. 2015 Large-scale Herschelmedian length (94 pc), followed by the Large-scale Herschelﬁlaments). The Gaussian-based width was not determined for the(50 ispc),
the asMilky
Way Bonespc),lengthand andthe width
MST as summarized in
Figureand15. Idealizedcomparisonof thedifferent large-scaleﬁlamentthe
catalogs.ﬁlaments
Each ﬁlament
shown
a rectangle,
with the(36same
GMF
MST “Bone”
samples.
Speciﬁcally,
we determine
Figure 12. Galactic plane separation (left panel) and absolute position angle (right panel) box-and-whisker plots for the four different ﬁlament clas
“Bone”
ﬁlaments(31 pcangle,
for thecatalog-based
method,273,pc
Table
3
and
shown
in
Figure10.
Theheight
above
or
below
the
Galacticplane,
as
well
as
the
position
are
the
same
as
given
in
Table
exceptthe absolute
pixel with the maximum column density value along each of theonly
the distribution for the MST “Bones” based on the catalog data is shown, but the tracks for the MST “Bones” based on the continuum dafor the continuum-based method).
value is not taken.
equivalent (see Table 3). In each box plot, the solid line indicates the median of the distribution while the dotted line indicates the mean. The bottom
perpendicular cuts and build a radial column density proﬁle along
In the middle-left panel of Figure 10, we see that the median each box denote the end of the ﬁrst and third quartiles of the distribution, while the end of the “whiskers” enclose all of the data points that are not ceach cut with respect to this pixel. We then ﬁt a Gaussian to thelinear masses for the four classes vary by a factor of 4: the which are plotted as individual dots. In the background, we also overlay the expected plane separation and position angles of a random control s
altitudes)
are common,
lying density“in an proﬁlesarm” ofgiven
the byGalaxy(being inentireensembleof radial column
these set
GMFs have the highest linear mass (≈1500 Me pc−1), with the Monte Carlo analysis (light-colored box-and-whisker plots). This is akin to what the distributions would look like if ﬁlaments with lengths typica
thecuts.
plane
additionally
being
a
of
OurandGaussianmodel has
two kinematically
free parameters consistent(amplitude, with average
MST “Bone” linear mass about half that value dropped randomly in a box with the stipulation that each ﬁlament must be completely“observed” given the boundaries of current Galactic plane-r 2
purportedspiralarm)
israrer.
standard deviation) and is given by N (r ) = aexp 2s 2 , where a(≈700–800 Me pc−1). The Milky Way Bones and the Largescale Herschel ﬁlaments have the lowest linear masses, withis the amplitude, and σ is the standard deviation. We ﬁrst subtract a( )•Solid:median, dashed: mean
•濃いボックス：下から1/4と3/4のところ•薄いボックス：ランダムだと思った時の分布•今回提案するフィラメントのカテゴリー分けの手法•Cold and high column density fraction•H2 column density >1022 cm­2
•dust temperature < 20 K
•Aspect ratio• *simulationsは銀河の渦状腕にある背骨のような構造は、ひしゃげてかつ高面密度を持つことを示唆(Smith et al. 2014)。なのでcolumn
densityとaspect比を用いる。 Boneは進化の早い段階なので低温度が期待される。

その結果以下の3つのカテゴリーができた。
a. large scale ﬁlament: GMFs
b. elongated dense corec. highly elongated high column density ﬁlaments (Bone of the
The Astrophysical Journal,
864:153 (34pp), 2018 September 10
Zucker, B
Galaxy)Figure 17. We summarize the characteristic aspect ratios and cold and high column density fractions for the multimodal ﬁlament population p

Figure 16. Top: the distribution of cold and high column density fraction vs.

CO-dark gas in the Milky Wa

議論- GMF？aspect比は他に比べて低いが(8:1)、
普通のGMC(例えば1.5:1)よりは高い。GMF
はただのkinny subset of GMCか？

- MST Bone?円柱のソーセージ不安定？あるいは、GMC内でﬁlamentaryな構造が暴走的に成長した？

- Bone candidates? large-scale gravityが必要？最も長くて密なBone-likeなフィラメントは銀河系の重力によって作られ維持されている？

COのデータのある22/45 のフィラメントについて、position-position-velocityの解析をした。近場のスパイラル構造と同じところにいるか調べた。
->35%のフィラメントがスパイラルと同じ場
所(<20 pc,<10 km/s)だとわかったが、残り65%はそうじゃない

The Astrophysical Journal, 864:153 (34pp), 2018 September 10

Zucker, Battersby, & Goodman

were then derived via the morphology of the low-density
tracing 13CO emission enveloping these dense ﬁlamentarycomplexes. Ragan et al. (2014) and Abreu-Vicente et al. (2016)
conﬁrmed velocity contiguity by collapsing the 13CO cubes inlatitude bounds around the ﬁlament and ensuring that the p –v
diagram exhibits unbroken emission. Together, Ragan et al.
(2014) and Abreu-Vicente et al. (2016) identiﬁed 16 GMFs
(9 claimed to be associated with spiral arms), all of which areincluded in this study.
Wang et al. (2015) undertook a search for the coldest anddensest ﬁlaments (“Large-scale Herschel ﬁlaments”) by visuallyinspecting Herschel Hi-GAL images of the inner galaxy (Molinari
et al. 2010) and conﬁrming velocity contiguity via a custom 13CO
p –v slice taken along the ﬁlament. Wang et al. (2015) uncovered
nine ﬁlaments with typical lengths on the order of 40–100 pc,
column densities ≈1×1021–2×1022 cm−2, and dust temperatures 17–21 K. Seven of these are claimed to be associated withspiral arms, and all nine ﬁlaments listed in Table 2 from Wanget al. (2015) are included in this study.
Next, Zucker et al. (2015) carried out a by-eye search of themid-IR GLIMPSE and MIPSGAL surveys (Carey et al. 2009;
Churchwell et al. 2009) speciﬁcally for Nessie analogs—the“Bones of the Milky Way.” Zucker et al. (2015) cataloged
Figure 2. Top-down artist’s conception view of the Milky Way Galaxy
highly elongated extinction features (typical lengths 20–60 pc)(courtesy of Robert Hurt, NASA). The longitude range of the full sample isthat lie parallel and in close proximity to the plane-of-the-sky
shown as a yellow arc (with the radius of the arc set by the farthest ﬁlamentdistance, ≈10 kpc; see Table 1). Every ﬁlament we consider lies in this area. In
projections of known spiral arms. Zucker et al. (2015)13
orange we show the range of longitudes covered by the GRS survey of CO in
identiﬁed 10 candidates and developed a set of Bone criteria
the ﬁrst quadrant (Jackson et al. 2006), which we use to perform a kinematic(with prescriptions for aspect ratio, spatial and kinematic
analysis on a subset of the ﬁlaments as discussed in Section 3.6 and Figure 13.
proximity to spiral arms, and velocity contiguity) intended todifferentiate features most likely to form due to the Milky
Way’s global spiral potential. To conﬁrm velocity contiguity,
2. Sample Selection
Zucker et al. (2015) took a custom 13CO p –v slice along theWe draw our selection of large-scale ﬁlaments from several
ﬁlament and ensured that dense gas catalog sources tracing theexisting catalogs. To be included in Figure
this analysis,ﬁlamenta gradient<3thekmhighlys−1 per
10 pc. section
Six of tenof disc in the Milky Way simulati
2. Mapa of
total columnﬁlamentdensity exhibitof hydrogen
nucleioffor
resolvedof themust be at least 10 pc long, stated to becontiguous
inthese
met arms,
all Bone
criteria (withthe otherfour failinggasvelocity
has a rangeof morphologies,
fromﬁlaments
dense spiralto filamentary
spurs,
to diﬀuse
inter-arm regions.
3the original paper presenting it, and be part of a catalog whose
the aspect ratio criterion ), and we include all 10 listed in Table
members are purported to lie near or be associated with some2 from Zucker et al. (2015), plus Nessie (Goodman et al. 2014),
aspect of spiral structure. Filaments that satisfy these criteria
in this study (hereafter the “Milky Way Bone” catalog).
dure
do not aﬀect
the results, we have calculated t
3 (GMFs)RESULTS
MILKY
WAY
include the Giant Molecular Filamentsfrom FROM
Ragan THEFinally,Wang
et al. (2016) produced
a populationof MSTjecteddensities for two 700 pc by 700 pc subSIMULATION
et al. (2014) and Abreu-Vicente et al. (2016),
the Large-scaleﬁlaments by applying an MST algorithm
to surface
dense molecularof the grid at ten times higher resolution (i.e. a pi
Herschel ﬁlaments from Wang et al. (2015), the Milky Way

参考：Smith et al. 2014, simulations, AREPO

65

Mapping Distances across the Perseus Molecular Cloud Using CO
Observations, Stellar Photometry, and Gaia DR2 Parallax Measurements
Show affiliations• Zucker, Catherine; Schlafly, Edward F.; Speagle, Joshua S.; Green, Gregory M.; Portillo, Stephen K.
N.; Finkbeiner, Douglas P.;Goodman, Alyssa A.
Abstract
We present a new technique to determine distances to major star-forming regions across the Perseus
Molecular Cloud, using a combination of stellar photometry, astrometric data, and 12CO spectral-line
maps. Incorporating the Gaia DR2 parallax measurements when available, we start by inferring the distanceand reddening to stars from their Pan-STARRS1 and Two Micron All Sky Survey photometry, based on atechnique presented by Green et al. and implemented in their 3D “Bayestar” dust map of three-quarters of
the sky. We then refine their technique by using the velocity slices of a CO spectral cube as dust templates
and modeling the cumulative distribution of dust along the line of sight toward these stars as a linear
combination of the emission in the slices. Using a nested sampling algorithm, we fit these per-star distancereddening measurements to find the distances to the CO velocity slices toward each star-forming region.
This results in distance estimates explicitly tied to the velocity structure of the molecular gas. We determine
distances to the B5, IC 348, B1, NGC 1333, L1448, and L1451 star-forming regions and find that
individual clouds are located between ≈275 and 300 pc, with typical combined uncertainties of ≈5%.
We find that the velocity gradient across Perseus corresponds to a distance gradient of about 25 pc, withthe eastern portion of the cloud farther away than the western portion. We determine an average distance tothe complex of 294 ± 17 pc, about 60 pc further than the distance derived to the western portion of thecloud using parallax measurements of water masers associated with young stellar objects. The method we
present is not limited to the Perseus Complex, but may be applied anywhere on the sky with adequate COdata in the pursuit of more accurate 3D maps of molecular clouds in the solar neighborhood and beyond.
https://ui.adsabs.harvard.edu/abs/2018ApJ...869...83Z/abstract

The Astrophysical Journal, 869:83 (27pp), 2018 December 10

Zucker et al.

The Astrophysical Journal, 869:83 (27pp), 2018 December 10

The Astrophysical Journal, 869:83 (27pp), 2018 December 10

Zucker et

Zucker et al.

Figure 2. Cartoon line-of-sight reddening proﬁle assuming a model with a single velocity slice v1 (where the cloud can be described by a single distance componentd1). Such a reddening proﬁle is deﬁned by the free parameters dfore (foreground cloud distance), Efore (foreground cloud reddening), d1 (distance modulus to single
velocity slice), and c1 (gas-to-dust conversion coefﬁcient in single velocity slice). The quantity Ij,1 constitutes the CO emission for star i lying in pixel j in the single
velocity slice v1. The reddening proﬁle is overlaid on an idealized joint posterior on distance and reddening (grayscale ellipsoid) for individual star i lying in CO pixel
j. The star’s likelihood is simply the integral over μ following the reddening proﬁle (solid red line); the dashed red lines are excluded from the integration. In Section 6
the likelihood from this star would be multiplied together with the likelihoods of thousands of other stars to get the total likelihood contribution (see Equation (4)).

parameterize the foreground dust cloud as lying at a distance
dfore, and with a reddening contribution in ΔEB−V given by
Efore. For a star i in CO pixel j, the reddening proﬁle isparameterized as follows:

In Figure 2, we show a cartoon line-of-sight reddening
proﬁle for a very simple one-slice model (lying at velocity v1),
where the CO emission toward our region of interest is
described by a single distance component d1. In such a model,
we can parameterize the total line-of-sight reddening proﬁle as
EB - V (mi ; a) = EB - V (mi ; d fore, Efore, {d1, d2 ... dn},having a jump in reddening Efore at distance dfore, plus a second{I j,1, I j,2, ¼I j, n}, {c1, c2, ¼cn}) ,(5 )jump in reddening at distance d1, the magnitude of which is
given by the CO emission in slice v1 coincident with the star,
where our free parameters are dfore, Efore, {d1, d2, K, dn}, andmultiplied by some gas-to-dust coefﬁcient c1. The free{c1, c2, K, cn}. The proﬁle takes the form of a step function.
parameters deﬁning our reddening proﬁle are dfore, Efore, d1,
Assuming that our velocity slices are ordered by distanceand c1, which are ﬁxed across all stars. The only variation in(d1<d2< K<dn), the total line-of-sight reddening out to a
the reddening proﬁle from star to star stems from the magnitude
distance d for a single star, coincident with CO pixel j, wouldof the reddening jump at distance d1, which is dependent on the
CO pixel j coincident with each star on the plane of the sky.
beThis single-template model is similar to the one implemented in⎧0
d - d fore
Schlaﬂy et al. (2014), with the exception that they use the⎪Ed fore - d - d1
angular distribution of the Planck emission (Planck Collabora⎪ foretion et al. 2011) instead of CO velocity slices as their dust
d1 - d - d2 ...
EB - V = ⎨ E fore + I j,1 c1
templates and ﬁx dfore to 0 pc. In comparison to Planck, ourn⎪⎪E fore + å I j, k ck
d > dn.
more complex multi-slice CO velocity model is better able to⎪⎩k= 1
trace the underlying molecular H2 and probe the structure of thecloud along the line of sight.
The assumption of the velocity slices increasing monotonically
There are a number of limitations to our model, most notably
in distance (such that v1<v2< K<vn, so d1<d2that intensity structures in position–position–velocity (p–p–v)< K<dn) is only for notational purposes above, and is not
space do not necessarily correspond to physical density
Figure 5.
Line-of-sight
reddeningfor the B5ourstar-forming
region.
TheInfull proﬁleis integrated
out to μ=19 mag (see Figures(p–p–p)
2 and 3), space
but for illustrative
actually
imposedwhenproﬁlewe perform
line-of-sightﬁts.
structuresin position–position–position(see
purposesactuality,
we only showthereddening
proﬁle
in
the
range
4
mag<μ<10
mag.
The
red
line
indicates
thereddening
proﬁleparameterizedbythemedianthe velocity slices have the freedom to switch their
Beaumont et al. 2013). As discussed in Beaumont et al. (2013),of thesamples for each parameter (summarized in the table above the ﬁgure), derived from our dynesty run. Since the magnitude of the reddening jump depends on theorder.
two wayslack toofB5.
one-to-one
correspondence
amount of
CO emission, we have taken the average of the CO emission in each slice tothere
obtain are
an estimateof thethis
reddening
The blue lines
are random samples

from the same chain used to derive the median. In the background grayscale, we show distance–reddening stellar posteriors used in the parameter estimation (seeG18), stacked on top of one another. We plot the most probable distance–reddening6position for each star as a lime green scatter point, obtained by extracting the cellwith the maximum probability in each of the gridded stellar posteriors. These lime green points are shown only for reference and are not used in the ﬁt, which always
integrates through the full posterior for each star.

7.38+0.03, and 7.45+0.04 mag, respectively. This corresponds to(≈280–300 pc), we ﬁnd that the ﬁrst slice, at the lowest

Figure 11. (a)Combined 12CO (red) and 13CO (blue) integrated intensity map of Perseus (Ridge et al. 2006). The boundaries we deﬁne for each region (same as
Figure 1(b)) are shown in black. The centroid of each polygon is marked with a different colored point. (b)An R.A.–velocity diagram of Perseus, with the same coscale as panel (a). The colored points show the peak-reddening velocity (dark points) and average-reddening weighted velocity (light points) as a function of R.A.
each cloud. The error bars in R.A. show the horizontal extents of the polygons overlaid in panel (a). (c)Average reddening-weighted distance to each region asfunction of R.A. (d)A velocity–decl. diagram of Perseus, with the same color scale as panel (a). The colored points show the decl. as a function of peak-reddeni
velocity (dark points) and average-reddening weighted velocity (light points). The error bars in decl. show the vertical extents of the polygons overlaid in panel ((e)The average reddening-weighted distance to each region as a function of its peak-reddening velocity (dark points) and average reddening-weighted velocity (ligpoints). We ﬁnd that the cloud distances tend to increase with both average reddening-weighted velocity and R.A. In total, the velocity gradient of ≈5 km s−1 maps
a distance gradient of about 25 pc. The uncertainty provided on distance accounts only for the statistical uncertainty and does not include any systematic uncertain

66

RadFil: A Python Package for Building and Fitting Radial
Profiles for Interstellar Filaments
Show affiliations• Zucker, Catherine; Chen, Hope How-Huan
Abstract
We present RadFil, a publicly available Python package that gives users fullcontrol over how to build and fit radial profiles for interstellar filaments. RadFilbuilds filament profiles by taking radial cuts across the spine of a filament,
thereby preserving the radial structure of the filament across its entire length.
Pre-existing spines can be inputted directly into RadFil, or can be computed
using the FilFinder package as part of the RadFil workflow. We provide
フィラメントをフィットするためのソ
Gaussian and Plummer built-in fitting functions, in addition to a background
フトウェアパッケージの解説
subtraction estimator, which can be fit to the entire ensemble of radial cuts oran average radial profile for the filament. Users can tweak parameters like theradial cut sampling interval, the background subtraction estimation radii, and
the Gaussian/Plummer fitting radii. As a result, RadFil can provide treatment of
how the resulting filament properties rely on systematics in the building andfitting process. We walk through the typical RadFil workflow and compare ourresults to those from an independent radial profile code obtained using thesame data; we find that our results are entirely consistent. RadFil is open source
and available on GitHub. We also provide a complete working tutorial of thecode available as a Jupyter notebook, which users can download and run
themselves.

https://ui.adsabs.harvard.edu/abs/2018ApJ...864..152Z/abstract

1

A sensitive λ 3 mm line survey of L483. A broad view of
the chemical composition of a core around a Class 0
objectShow affiliations• Agúndez, M.; Marcelino, N.; Cernicharo, J.; Roueﬀ, E.; Tafalla, M.
Abstract
An exhaustive chemical characterization of dense cores is mandatory to our understanding of chemical compositionchanges from a starless to a protostellar stage. However, only a few sources have had their molecular composition
characterized in detail. Here we present a λ 3 mm line survey of L483, a dense core around a Class 0 protostar, which
was observed with the IRAM 30 m telescope in the 80-116 GHz frequency range. We detected 71 molecules (140including diﬀerent isotopologs), most of which are present in the cold and quiescent ambient cloud according to theirnarrow lines (FWHM 0.5 km s-1) and low rotational temperatures (≲10 K). Of particular interest among the detected
molecules are the cis isomer of HCOOH, the complex organic molecules HCOOCH3, CH3OCH3, and C2H5OH, awide variety of carbon chains, nitrogen oxides like N2O, and saturated molecules like CH3SH, in addition to eight newinterstellar molecules (HCCO, HCS, HSC, NCCNH+, CNCN, NCO, H2NCO+, and NS+) whose detection has alreadybeen reported. In general, fractional molecular abundances in L483 are systematically lower than in TMC-1 (especiallyfor carbon chains), tend to be higher than in L1544 and B1-b, and are similar to those in L1527. Apart from theoverabundance of carbon chains in TMC-1, we find that L483 does not have a marked chemical diﬀerentiation withrespect to starless/prestellar cores like TMC-1 and L1544, although it does chemically diﬀerentiate from Class 0 hot
corino sources like IRAS 16293-2422. This fact suggests that the chemical composition of the ambient cloud of someClass 0 sources could be largely inherited from the dark cloud starless/prestellar phase. We explore the use of
potential chemical evolutionary indicators, such as the HNCO/C3S, SO2/C2S, and CH3SH/C2S ratios, to trace theprestellar/protostellar transition. We also derived isotopic ratios for a variety of molecules, many of which show
isotopic ratios close to the values for the local interstellar medium (remarkably all those involving 34S and 33S), while
there are also several isotopic anomalies like an extreme depletion in 13C for one of the two isotopologs of c-C3H2, adrastic enrichment in 18O for SO and HNCO (SO being also largely enriched in 17O), and diﬀerent abundances for thetwo 13C substituted species of C2H and the two 15N substituted species of N2H+. We report the first detection in
space of some minor isotopologs like c-C3D. The exhaustive chemical characterization of L483 presented here,
together with similar studies of other prestellar and protostellar sources, should allow us to identify the main factorsthat regulate the chemical composition of cores along the process of formation of low-mass protostars. A copy of the
reduced spectrum (FITS file) is available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/625/A147Based on observations carried out with
the IRAM 30 m Telescope. IRAM is supported by INSU/CNRS (France), MPG (Germany) and IGN (Spain).

https://ui.adsabs.harvard.edu/abs/2019A%26A...625A.147A/abstractM. Agúndez et al.: A 3 mm line survey of L483

(a few 104 yr; André et al. 2000) evolutionary stage like theClass 0 one remains unclear. This may be related to the way theswitch on of the protostar affects the ambient cloud. In somesources the cloud would preserve much of the characteristics of
A&A 625, A147 (2019)the starless/prestellar phase, displaying high C4 H/CH3 OH ratios
and being rich in carbon chains, while in others the chemical
content of the ambient cloud would be strongly processed by
the injection of energy from the protostar, thus showing low
C4 H/CH3 OH ratios and abundant COMs (hot corinos). However,a deeper understanding of why this would happen is still lacking.
A possible explanation of the chemical differentiation between
Class 0 sources rich in carbon chains and rich in COMs (hot corinos) has been suggested by Sakai et al. (2008a). These authors
proposed that sources rich in carbon chains would have had ashort lifetime of the prestellar collapse, in which case ices would
be rich in CH4 and the evaporation of these during the switch onof the protostar would lead to the formation of carbon chains by
gas phase chemistry. On the other hand, hot corinos would result
from a longer prestellar collapse phase, meaning that ices would
be rich in CO, which upon hydrogenation and further processing driven by protostar heating would lead to abundant COMs
in the gas phase. Chemical models following this idea have been
carried out (Aikawa et al. 2008, 2012; Hassel et al. 2008, 2011)
but still a definitive theoretical validation of the chemical differentiation between Class 0 sources rich in carbon chains and hot
corinos is lacking. More recently, a survey of the C2 H/CH3 OH
in 36 Class 0/I protostars by Higuchi et al. (2018) pointed tothe environmental effect of the dense core being located ina more inner or outer region of the molecular cloud comFig. 6. Column density of C4 H represented as a function of the column density of CH3 OH (leftpanel), HCOOCH (middle panel), and CH OCH3
plex as a possible driver3 of the diversity of C2 H/CH33OH ratios(right panel) in various starless/prestellar cores, Class 0 sources, and hot corinos. All column
densities are beam-averaged values obtained withobserved.
single-dish telescopes. See references in the caption of Fig. 5 for the column densities of C4 H We
andalsoCHinvestigatedL1527.
whetherL1544,
the use B1-b,of moreandspecific
prox3 OH in TMC-1,
of COMs
likelimits),
HCOOCH, ratherthan
Column densities of HCOOCH3 and CH3 OCH3 are taken from Marcelino et al. (in prep.) for ies
TMC-1(upperJiménez-Serra
et3al.
(2016)
forthe3 and CH3 OCH
generic
CH3 OH,
could provide
insightfor
into
L1544, Cernicharo et al. (2012) for B1-b, and Yoshida et al. (2019) for L1527 (upper limits). more
For thethreeone
hotofcorino
sources,columnsome
densities
the chemicaldifferentiation
between starless/prestellar and proC4 H are from Sakai et al. (2009a), for CH3 OH from Maret et al. (2005), and for HCOOCH3 andCH3 OCH
3 from Cazaux et al. (2003) (values havetostellar sources. Therefore, in the middle and right panels of
been averaged for a 1000 source size) and from Bottinelli et al. (2007).
Fig. 6 we show the column density of C4 H versus that of
HCOOCH3 and CH3 OCH3 , respectively, for the same sources
considered before. We see that the Class 0 sources B1-b, L1527,
at the Class 0 stage. We however warn that this interpretation is other type of chemicalthat is,movingfromanyasoftheand L483family;
cluster aroundthewhensame region
in thediagramstarless/prestellar
sources,
they canbe clearly differennot sufficiently robust because of the low statistics of sources these two sourcesto L483, there
is nowhileobviousdifferentiation
inFig. 7. Some column density ratios which are potentially good chemical evolutionary indicators of the prestellar/protostellar transition. The
upper limit to the column density of CH3 SH in TMC-1 is taken fromMarcelino et al. (in prep.).

4.5. Isotopic ratios

The high sensitivity of the line survey permitted us to detect agood number of isotopologs substituted with rare isotopes (D,13
C, 15 N, 18 O, 17 O, 34 S, and 33 S), and even some doubly substituted species. Isotopolog abundance ratios have been obtained
from the column densities derived and are presented in Tables 2
and 3. The uncertainties in these ratios are estimated to be 30%.
We note that although the estimated uncertainties in the column
densities are of the order of 50% (see above in Sect. 4.2), we
can reasonably expect lower uncertainties for isotopic ratios. An
important part of the uncertainty that affects the determinationof a column density is dominated by the error in the rotationaltemperature, which becomes less important when computing
column density ratios between different isotopologs of a given
molecule because these are expected to have similar excitation
conditions. This latter statement has been verified in the few
cases in which we have enough lines to estimate the rotationaltemperature for different isotopologs of the same molecule. For
example, for c-HCC13 CH and c-C3 HD we derive rotational temperatures of 4.1 ± 0.3 and 4.1 ± 0.2, respectively (see Table 1).

58

Fates of hydrous materials during planetesimal collisions
Wakita, Shigeru; Genda, Hidenori
Abstract
Hydrous minerals are found on the surfaces of asteroids, but their origin is notclear. If their origin is endogenic, the hydrous minerals that were formed in the
inner part of a planetesimal (or parent body) should come out on to the surface
without dehydration. If their origin is exogenic, the source of hydrous minerals
accreting onto asteroids is needed. Collisions in the asteroid belt would be related
to both origins because collisions excavate the surface and eject the materials.
However, the fate of hydrous minerals in large planetesimals during the collisional
process has not been well investigated. Here, we explore planetesimal collisions
by using the iSALE-2D code, and investigate the eﬀect of an impact for the target
planetesimal containing hydrous minerals. Our numerical results for the fiducial
case (5 km/s of the impact velocity) show that hydrous minerals are slightly
heated during the collisions. This moderate heating indicates that they can avoid
the dehydration reaction and keep their original composition. Some hydrous
minerals have larger velocity than the escape velocity of the collision system. Thismeans that hydrous minerals can escape from the planetesimal and support thetheory of exogenic origin for the hydrous minerals on asteroids. Meanwhile, thevelocity of other hydrous minerals is smaller than the escape velocity of thesystem. This also indicates the possibility of an endogenic origin for the hydrous
minerals on asteroids. Our results suggest that hydrous minerals on asteroids canbe provided by planetesimal collisions.

・含水鉱物の起源
小惑星の表面に水を含んだ鉱物が見つかっている。
表面にあるためには
母天体内側で作って、水と反応せずに表面に出てくる？
表層にあとから降り積もる？
→２つの微惑星の衝突計算で調べる→若干加熱されるだけなのでdehydrationを回避できて、original compositionを維持できる。
,FDUXV  ²

S. Wakita and H. Genda

Fig. 1. Hugoniot curve for serpentine with the corresponding impact velocity
vimp.

https://ui.adsabs.harvard.edu/abs/2019Icar..328...58W/abstract

once the S of hydrous materials exceeds Sdehyd, we deﬁne it as a dehydrated part. We do not switch the EOS from serpentine to dunite in
the collisional simulations. This is because we focus on the occurrenceof the dehydration reaction and what occurs after the dehydration reaction is irrelevant to this study.
Fig. 1 shows the Hugoniot curve for serpentine derived from ANEOStable in iSALE code which is based on Brookshaw (1998). When theimpact velocity exceeds 6 km/s, S also exceeds Sdehyd. Therefore, for apurely hydrodynamic case, the typical impact velocity (∼5 km/s) of
asteroids in the current main asteroid belt (Bottke et al., 1994; Farinella
and Davis, 1992) cannot cause a signiﬁcant dehydration reaction.
However, a recent study considering material strength (Kurosawa andGenda, 2018) reports that frictional heating during an impact increases
enormously S. Numerical simulations with the strength model areneeded for precise evaluation of the dehydration reaction during planetesimal collisions. Note that the dehydration reaction would be an
endothermic reaction (Wakita and Sekiya, 2011). The main purpose ofthis study is to understand whether or not planetesimal collision would
trigger the dehydration reaction. Thus, we do not take into account theheat consumption in this work due to the dehydration reaction.

Fig. 2. Snapshot of a planetesimal collision between anhydrous impactor andhydrous target for the ﬁducial case (Rimp = 20 km, Rtar = 100 km andRhyd = 90 km with vimp = 5 km/s) at 0 (top) and 3 (bottom) ts. Color represents
peak pressure on the left sides and the speciﬁc entropy at each position. White
dotted lines denote material boundary. (For interpretation of the references tocolor in this ﬁgure legend, the reader is referred to the online version of thischapter.)

3. Results

59

The Astrophysical Journal, 875:153 (10pp), 2019 April 20

Walther & Geballe

New Near-infrared Imaging and Spectroscopy of NGC 2071-IR
Show affiliations• Walther, D. M.; Geballe, T. R.
Abstract
We present high-resolution images of NGC 2071-IR in the J, H, and K bands and in theemission at 2.12 μm of the v = 1─0 S(1) line of molecular hydrogen. We also present
moderate-resolution K-band spectra of two young stellar objects, IRS 1 and IRS 3, within
NGC 2071-IR, that are candidate sources of one or more of the outflows observed in theregion. Two of the eight originally identified infrared point sources in NGC 2071-IR are
binaries, and we identify two new sources, one coincident with the radio source Very
Large Array-1 and highly reddened. The H2 Q(3)/S(1) line intensity ratios at IRS 1 and IRS
3 yield high and very high extinctions, respectively, to them, as is implied by their nearinfrared colors and K-band continuum slopes. The spectra also reveal the presence ofhot, dense circumstellar molecular gas in each, suggesting that both are strong
candidates for having energetic molecular outflows. We agree with a previous suggestionthat IRS 1 is the likely source of an east─west-oriented outflow and conclude that thisoutflow is probably largely out of the plane of the sky. We also conclude that if IRS 3 isthe source of the large-scale northeast─southwest outflow, as has been previously
suggested, its jet/wind must precess in order to explain the angular width of that outflow.
We discuss the nature of the point sources and their possible contributions, if any, to thecomplex morphology of the H2 line emission.

https://ui.adsabs.harvard.edu/abs/2019ApJ...875..153W/abstract

Figure 3. Continuum-subtracted image of NGC 2071-IR in the 1−0 S(1) line of H2. The positions of most of the known (proto)stars are marked, along with theoutﬂow regions IA-III designated by E00. The arrows denote the directions of the E- and NNE-pointing ionized jets from IRS 1 and IRS 3, respectively, as determinedfrom radio continuum measurements by T98, S02, TRR09, and CG12.

remarkably great. Both IRS 1 and IRS 3 lie between these twoemission lobes, and as noted by several previous investigators,
are possible sources of this wind. Source VLA-1 also is locatedbetween the lobes.
Walther & Geballe
Considerable H2line emission is present in Figure 3 outsideof IA and IB. Much of this was described by E00, but thepresent higher-resolution images reveal additional detail. In
particular, the morphology between those two lobes is highly
complex, especially to the east. Knots of bright H2line
emission are present to the east of IRS 1, VLA-1, and IRS3,extending as far as 40″ from them, and are collectively called
Outﬂow IIA by E00. Approximately 15″ to the west of thesesources a bright arc of emission is present within a larger regionof lower surface brightness, which E00 labeled IIB. Lying

3.2. Molecular Hydrogen Image
Figure 3 is a continuum-subtracted image of the H21−0 S(1) line at 0 35 resolution, covering ∼60%of the full extent ofThe
Astrophysical Journal,
875:153 (10pp),
2019 April
NE–SW-oriented
line emission(designated
IA 20
and IB in theﬁgure, following E00) detected by earlier observers at lower
angular resolution and imaged in full by E00 using a camera
with 0 81 pixels in unspeciﬁed seeing conditions. Figure 4 is amore detailed view, in contours of intensity, of the central 45″.
Outside of the central 30″ many of the brightest emitting
regions are located on the outer edges of the NE and SW lobes,
suggesting that they are regions where an outﬂowing windfrom a star is colliding with and shocking the surrounding
cloud. Although these edges appear to be sharp, especially in
the NE lobe (IA), the non-uniformity in surface brightness is
4

Figure 4. Contour map of H21–0 S(1) line emission in the central region of Figure 3. The locations of point sources are denoted by yellow stars. Also shown are theorientations of the disks of IRS 1 and IRS 3 (orange rectangles), as determined from observations of H2O maser spots by T98, and TRR09, and their ionized jets (bluearrows), as determined from radio continuum measurements by T98, S02, TRR09, and CG12.

60

Sheets, filaments, and clumps - high-resolution simulationsof how the thermal instability can form molecular clouds

Name
Paper IV HD(Wareing et al. 2018)
Model 1Model 2Model 3Model 4Clump

Domainpc on a sideG0
# of cells

Levelsof AMR

tstart(Myr)

Resolution
(pc)

HD
/MHD?

Cooling? Heating? G

300

8×8×8

8

0.0

0.29

HD

Y

Y

100
100
100
100
10

10 × 10 × 10
10 × 10 × 10
10 × 10 × 10
10 × 10 × 10
10 × 10 × 10

6
7
8
9
7

16.2
21.7
21.7
22.8
44

0.3125
0.156
0.078
0.039
0.0156

HD
HD
HD
HD
HD

Y
Y
Y
Y
Y

Y
Y
Y
Y
Y

Show affiliations• Wareing, C. J.; Falle, S. A. E. G.; Pittard, J. M.
Abstract
This paper describes 3D simulations of the formation of collapsing cold clumps via
thermal instability inside a larger cloud complex. The initial condition was a diﬀuse
atomic, stationary, thermally unstable, 200 pc diameter spherical cloud in pressure
equilibrium with low-density surroundings. This was seeded with 10 per cent density
perturbations at the finest initial grid level (0.29 pc) around nH= 1.1 cm-3 and evolved
with self-gravity included. No magnetic field was imposed. Resimulations at a higher
resolution of a region extracted from this simulation (down to 0.039 pc) show that thethermal instability forms sheets, then filaments, and finally clumps. The width of
the filaments increases overtime, in one particular case from 0.26 to 0.56 pc.
Thereafter, clumps with sizes of around 5 pc grow at the intersections of filaments. 21
3. Evolution of the diffuse cloud into a complex of clumps shrinking through gravitational collapse. Six time snapshots from Model 3 are
distinct clumps, with properties similar to those observed in molecular clouds, are Figure
in a box with sides of length 50 pc. Each snapshot shows a 3D isosurface rendering of density, with 10 isosurfaces shown at density levels ranging ln = 100 cm . Isosurface opacity increases with density, reaching high opacity by n = 10 cm , sharper and coloured green (digital-ofound using the FellWalker algorithm to find minima in the gravitational potential. Not upthe tofigure.
Lower density more translucent isosurfaces are diffuse and bluer in colour (digital-only), indicating the extent of unstable material (1< 10 cm ). The isosurfaces have been created from Silo datafiles using thetoolkit. Movie and Silo format raw data files are available
https://doi.org/10.5518/483.
all of these are gravitationally bound, but the convergent nature of the flow andincreasing central density suggest they are likely to form stars. Further simulation of the mass and volume filling fractions of cold gas, are relatively 4 R E S U LT I N G E VO L U T I O N O F T H E C L O U
to the choice of cooling function. On the other hand,
The evolution of the cloud and the properties of the structure fo
the most massive clump shows the gravitational collapse to a density >106 cm-3. insensitive
the cloud morphology and the large-scale velocity distribution ofacross the cloud complex are discussed in this Section. In partthe gas do strongly depend on the cooling function. They alsoof properties and derived statistics as well as
These results provide realistic initial conditions that can be used to study feedback ininvestigated the properties of the dense clumps formed within their time-variation
snapshots of slices, projections, and isosurface plots reveal
cloud. They found that the majority of these clumps are not selfproperties. Plotting mechanisms within the MG code areindividual clumps, interacting clumps, and the entire molecular cloud complex.
gravitating, suggesting that some form of large-scale collapse of the(VisIt Collabo
as well as the visualization software
H

−3

−3

https://ui.adsabs.harvard.edu/abs/2019MNRAS.485.4686W/abstract

cloud may be required in order to produce gravitationally unstableclumps and hence stars. It remains to be explored in future work theextent to which different heating and cooling prescriptions affectthis work. The prescriptions used herein, which study precisely sucha large-scale collapse as referred to by Micic et al., are appropriate
for the column density of the initial diffuse atomic cloud in our
simulations.

MNRAS 485, 4686–4702 (2019)

H

−3

VISIT

VISIT

2012).
4.1 The dynamic evolution of the cloudFig. 3 provides an overview of the evolution of the cloud, fromthe first condensations cause steep density increases at t = 2

2484

N. J. Wright et al.

61

0
−1

RV
−1

+0.34
−0.30
+0.34
−0.34

+0.24
−0.22
+0.40
−0.37

α0

−1

µα

−1

+0.044−0.045+0.045−0.043

δ0

−1

µδ

−1

+0.036−0.038+0.038−0.036

Figure 6. Kinematics of our sample of 889 young stars across the Lagoon Nebula projected on to an inverted VPHAS + H α image. Top: Spatial distributionof 404 sources colour-coded by their RV in the range −8 < RV/km s−1 < 8 (sources outside this range are coloured by the limiting values of the colour bar).
The 485 sources without RVs are shown as empty circles. Bottom: Spatial distribution of 761 sources with vectors showing their PMs over 0.05 Myr, relative
to the median PM of (µα , µδ ) = (1.27, −1.98) mas yr−1 . The PM vectors are colour-coded by their PM position angle, as indicated by the colour wheel in thelower right corner. The 128 sources without usable PMs are shown as empty circles.

12

MNRAS 486, 2477–2493 (2019)−1−1

https://ui.adsabs.harvard.edu/abs/2019MNRAS.486.2477W/abstract

To sample the posterior distribution function we use the affineinvariant MCMC ensemble sampler (Goodman & Weare 2010)
EMCEE (Foreman-Mackey et al. 2013) and compared the model tothe observations using an unbinned maximum-likelihood test, which
is made efficient by the smooth velocity distributions modelled. For
the MCMC sampler we used 1000 walkers and 2000 iterations,discarding the first half as a burn-in. The six parameters were

Figure 11. PM position angle distribution plotted as a circular histogramwith north up and east to the left.

Downloaded from https://academic.oup.com/mnras/article-abstract/486/2/2477/5420

Show affiliations Show all authors• Wright, Nicholas J.; Jeﬀries, R. D.; Jackson, R. J.; Bayo, A.; Bonito, R.; Damiani,F.; Kalari, V.; Lanzafame, A. C.; Pancino, E.;Parker, R. J.; Prisinzano, L.; Randich,S.; Vink, J. S.; Alfaro, E. J.; Bergemann, M.; Franciosini, E.; Gilmore, G.; Gonneau,
A.;Hourihane, A.; Jofré, P. ; ...
Abstract
2488
N. J. Wright et al.
The combination of precise radial velocities from multi-object spectroscopy and highly
Table 3. Central velocities and velocity dispersions for the entire Lagoon Nebula population and the subsets of NGC 6530, M8E, and thesubgroup.
Velocity dispersions are not calculated for the latter two as they are not sufficiently well sampled. The north-western
accurate proper motions from Gaia DR2 opens up the possibility fornorth-westerndetailed
3D
subgroup lacks any sources with spectroscopy and so its RV is not known.
kinematic studies of young star-forming regions and clusters. Here, we perform such
SampleRVσµσµ
σ
an analysis by combining Gaia-ESO Survey spectroscopy with Gaia astrometry for(km s )(km s )
(mas yr )(mas yr )(mas yr )(mas yr )Lagoon Nebula
members)
0.08
2.12
1.19 ± 0.05
0.644
−1.94 ± 0.04
0.443
̃900 members of the Lagoon Nebula cluster, NGC 6530. We measurethe(all3D
velocity
NGC 6530 (r < 2.5 arcmin)
0.82
1.80
1.21 ± 0.04
0.251
−2.00 ± 0.03
0.216
dispersion of the region to be 5.35^{+0.39}_{-0.34} km s-1, which isM8E
large
enough to 0.75 ± 0.72
(r < 2 arcmin)–
1.78 ± 0.23–
−2.14 ± 0.34–
North-western group (r < 1––
1.77 ± 0.20–
−1.50 ± 0.17–
suggest the region is gravitationally unbound. The velocity ellipsoid arcmin)is anisotropic,
implying that the region is not suﬃciently dynamically evolved to achieve isotropy,
use the luminosity-weighted average of the two as the photocentre
though the central part of NGC 6530 does exhibit velocity isotropy
that suggests
RV, which is then added to the modelled RV.
we add measurement
uncertainties for the RVs and PMs
suﬃcient mixing has occurred in this denser part. We find strong Finallyevidencethat thefor each star, randomly sampling these from the observed uncerdistributions andstellar population is expanding, though this is preferentially tainty
occurringininclude
the the correlated PM uncertainties
quoted in Gaia DR2 (random sampling of uncertainties is necessary
declination direction and there is very little evidence for expansion
in therightbecause the modelled
population
is significantly larger than theobserved population). This model has 6 free parameters, the velocity
ascension direction. This argues against a simple radial expansion
pattern, as
dispersion and central velocity in each dimension. Wide and uniform
priorswere used for eachofthese context
parameters covering 0–100 km s
predicted by models of residual gas expulsion. We discuss thesefindings
inthefor the velocity dispersions and −100 to +100 km s for the central
velocities.
of cluster formation, evolution, and disruption theories.

Downloaded from https://academic.oup.com/mnras/article-abstract/486/2/2477/5420759 by National AstronomicalObservatory, Japan user on 14 June 2019

The Gaia-ESO Survey: asymmetric expansion of the Lagoon
Nebula cluster NGC 6530 from GES and Gaia DR2

62

Parallaxes for Star-forming Regions in the Inner
Perseus Spiral Arm
Show affiliations• Zhang, Bo; Reid, Mark J.; Zhang, Lian; Wu, Yuanwei; Hu,
Bo; Sakai, Nobuyuki; Menten, Karl M.; Zheng, Xingwu;Brunthaler,
Andreas; Dame, Thomas M.; Xu, Ye
Abstract
We report trigonometric parallax and proper motion measurementsof 6.7 GHz CH3OH and 22 GHz H2O masers in eight high-massstar-forming regions (HMSFRs) based on Very Long Baseline Array(VLBA) observations as part of the Bar and Spiral Structure Legacy(BeSSeL) Survey. The distances of these HMSFRs combined with
their Galactic coordinates, radial velocities, and proper motions,allow us to assign them to a segment of the Perseus arm with ℓ ≲70°. These HMSFRs are clustered in Galactic longitude from ≈30°
to ≈50° neighboring a dearth of such sources between longitudes≈50° to ≈90°.

https://ui.adsabs.harvard.edu/abs/2019AJ....157..200Z/abstract

８個の大質量形成領域で6.7 GHzメタノールメーザーと22GHz
水メーザーを用いて、parallaxとproper motionを決めた。