1Massive Outflows
Driven by Magnetic Effects
in Star Forming Clouds
with High Mass Accretion Rates
YUKO MATSUSHITA / Masahiro Machida: Kyushu University
Yuya Sakurai / Takashi Hosokawa: The University of Tokyo / Kyoto University
DTA 2016/11/24-25@Mitaka

2

Motivationv Massive stars ( > 8Msun )formation process is no clearly
understandv Massive stars significantly affectthe evolution of the universe•••

stellar radiation feedback
inject kinetic energy, thermalenergypolluted gas into interstellar
space / stellar wind /supernova explosion

http://www.nao.ac.jp/gallery/weekly/2014/20141216-w3-main.html

Clarifying Massive stars formation process isimportant in astrophysical study !!!

3Previous Worksv Krumholz / Kuiper→ stellar radiation feedback→ magnetic outflow

v Hennebelle, Commercon
v Seifried→ stellar radiation feedback→ magnetic outfow

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4M [Msun]

Fco [Msun km/s /yr]

Introduction
Massive outflows arescaled-up versionsof low-mass outflow ?

Beuther et al. (2002)

L [Lsun]Maud et al. (2014)

Lm [Lsun]

L [Lsun]Wu, Y. et al.
(2004)Wu, Y. et al.
(2004)

L [Lsun]5

Introduction
What’s the Magnetic Outflow ?
→ transfer angular momentum

by magnetic and rotation effects

Strong magnetic fieldobserved in massive
star forming regions(Li et al. 2015 / Falgarane etal. 2008)

Li et al. (2015)

6

Introduction■

Angular momentum problem
specific angular momentum
should decrease a factor of 10-5

Goodman et al. (1993), Williams &Cieza (2011),Mathieu (2004)

Low-mass Stars: Jet, Outflow can transfer
angular momentum ~99.9%(Tomisaka 2000)→ How are massive stars ?

7Methods
Bonnor-Ebert density profile

Resistive-MHD eq

barotropic eq : p = p(⇢)

Protostar is formed→ remove the gas n > nthr
in r < rsink
sink radius : 1AU
central density：3.8×10-19gcm-3
isothermal temperature：40K(Machida & Hosokawa. 2013)

8Methods

ratio of thermal to gravitational energy

accretion rate

SmallLarge

prepared 6 modelcontrols the cloud mass, initial cloud stability• mass accretion rate is large in an initially thermallyunstable cloud• magnetic field strength：B0 is adjusted to µ = 2→each model has different magnetic field strengths

9Results : Mass accretion rate against protostellar mass
A (α0=0.5)
B (α0=0.2)
C (α0=0.08)
D (α0=0.04)
E (α0=0.02)
F (α0=0.01)

initially moreunstable cloud→ higheraccretion rate

dMps /dt [Msun yr-1]

1
10-1
10-2
10-3
10dMps /dt [Msunyr-1]

F (α0=0.01)

10-2

depend on
first core-4

10-510-1

oscillation is causedby GI of Disk

0.1

averaged mass accretion rates for 0 < tps < tend
averaged mass accretion rates for 0 < tps < 2tff

1Mps [Msun]

102x10-5 α0−3/2

averaged mass accretion ratein each model corresponds tothe theoretical prediction

10-3

A (α0=0.5)

10-40.01

α00.1

1

10Results : Outflow of each model
log n [cm-3]
891012Mps = 0.01 [Msun]

400

200

200

200

0-200

0-200-400
400-2000x [AU]200400

400

400

400

200

200200100 yr

t = 43940.7 [yr]-200tps = 129.1 [yr]0-200-400
400-2000x [AU]200400t = 44813.4 [yr]4004004002002002001000 yr

tps = 1001.8 [yr] Mps = 1.5 [Msun]-400

t = 241122.8 [yr] tps = 1088.9 [yr] Mps = 1.1 [Msun]

00-200-200

200-2000x [AU]200400

400

400

400

200200200

5000 yrt = 48848.1 [yr]tps = 5036.5 [yr] Mps = 2.9 [Msun]

0-200-200-400-2000x [AU]2004001100104400

de Villiers etal. (2014)-2000x [AU]200400(3Massive outflow !
> 20 Msun : Outflow mass102-200t = 16102.8 [yr]0x [AU]

200400tps = 2227.8 [yr] Mps = 39.4 [Msun]

higher accretion rate shortens
10 the lifetime of first core
101001049

color: density(c)arrows : velocity-400-400time [yr](b)tps = 1047.2 [yr] Mps = 14.3 [Msun]-200-400-400

1010-400t = 245172.5 [yr] tps = 5138.6 [yr] Mps = 1.3 [Mun]0200-400-400400z [AU]0x [AU]

0x [AU]

0z [AU]-200-200t = 14922.2 [yr]z [AU]-400400-200-400-400200-400-400z [AU]200z [AU]0x [AU]

0x [AU]

tps = 144.2 [yr] Mps = 1.0 [Msun]

0z [AU]-200

A (α0=0.5)
B (α0=0.2)
C (α0=0.08)
D (α0=0.04)
E (α0=0.02)
F (α0=0.01)-200-400-400-200

Mps = 0.1 [Msun] t = 14019.1 [yr]((a)102-400t = 240228.8 [yr] tps = 194.9 [yr] Mps = 0.1 [Msun]

0103-400-400z [AU]200z [AU]0x [AU]

Mps = 0.1 [Msun]

0z [AU]-200

tps = 27.8 [yr]-200-400-400

unstablet = 13902.7 [yr]z [AU]

tps = 3.0 [yr]400z [AU]t = 43814.5 [yr]400z [AU]Mps = 0.01 [Msun]= 10 [km s-1]

13Model F

~10 yrt = 240039.6 [yr] tps = 5.7 [yr]11

Model C

Mout [Msun]

stable7

Pout [Msun km s-1]

6Model A

-400-200

0x [AU]

20040048(

11Discussion : Comparison with Observations
104

102

← Mout - Lbol

100

10-1 2
10Beuther+02
Zhang+05
Wu+08
Maud+15

Observation data isa little high101103

104
Lbol [Lsun]

105

Pout – Lbol →Simulation data agree with
Observations
Lbol = L + G

M Ṁ
R106

103
Pout [Msun km s-1]

Mout [Msun]

103

A (α0 = 0.50)
B (α0 = 0.20)
C (α0 = 0.08)
D (α0 = 0.04)
E (α0 = 0.02)
F (α0 = 0.01)
Zhang-data
Maud-data
Wu-data102

A (α0 = 0.50)
B (α0 = 0.20)
C (α0 = 0.08)
D (α0 = 0.04)
E (α0 = 0.02)
F (α0 = 0.01)
Zhang-data
Maud-data

101

100 210103

104
Lbol [Lsun]10512Discussion : Comparison with Observations
dMout/dt [Msun yr-1]

10-2

10-3

A (α0 = 0.50)
B (α0 = 0.20)
C (α0 = 0.08)
D (α0 = 0.04)
E (α0 = 0.02)
F (α0 = 0.01)
Zhang-data
Maud-data
Beuther-data← Outflow rate – Lbol

Simulation data almost
agree with Observation.
Observation is a little low.

10-4102103

104
Lbol [Lsun]

105
1047

Eout – Lbol →Zhang+05
Wu+08
Maud+15

Eout [erg]Simulation agree withObservation
Beuther+021046

1045

A (α0 = 0.50)
B (α0 = 0.20)
C (α0 = 0.08)
D (α0 = 0.04)
E (α0 = 0.02)
F (α0 = 0.01)
Zhang-data
Maud-data

1044

1043 210103

104
Lbol [Lsun]

105

13

Discussion : Comparison with Observations
103

101

Simulation and
Observation are almost
the same

100

10-1

10-2 2
10103

Beuther+02
Zhang+05
Wu+08
Maud+15← Lkin – Lbol

104
Lbol [Lsun]

105

F – Lbol →Simulation date is high.
Caused by estimate of tdyn ?

106
10000
F [10-4 Msun km s-1 yr-1]

Lkin [Lsun]

102

A (α0 = 0.50)
B (α0 = 0.20)
C (α0 = 0.08)
D (α0 = 0.04)
E (α0 = 0.02)
F (α0 = 0.01)
Lkin=Lbol
Wu-data
Maud-data

1000

A (α0 = 0.50)
B (α0 = 0.20)
C (α0 = 0.08)
D (α0 = 0.04)
E (α0 = 0.02)
F (α0 = 0.01)
Wu-data
Maud-data
Zhang-data
Beuther-data

100

10121010310
Lbol [Lsun]

4105

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Now analyzing… “ Failed Outflow”↑ Driveprepared 6 model
controls
initial cloud stability
central density：3.8×10-19gcm-3
isothermal temperature：20K↑ Fail↑ No Drive

set up Mass-to-Flux ratio
2, 3, 5, 10change Magnetic strength

15

Even if magnetic field is weak,
Outflow can drive whenaccretion rate is small.

Results100Aαalpha10-1

10-2

mass accretion
rate Large
10-3

100

B
C
D
EF
2

3

5µmu

outflow
outflow
failed
faild
nono

10101

Magnetic field
StrongEven if magnetic field is strong,
Outflow cannot drive when accretion
rate is extremely Large.

16Conclusion & Future Works
ü investigate the relation between mass accretion onto theprotostar and the magnetically driven outflow
ü When the i nitial prestellar cloud has a strong magnetic field,
the outflow is powerful at any accretion rateü The physical quantities derived from our simulations
favorably agree with observation in massive outflow.
outflow mass / momentum / kinetic energy /outflow rate / kinetic luminosity / momentum flux /ü Both low- and high-mass stars form by a common
fundamental mechanism→ must ultimately consider various physical effects.
turbulence / radiation effects / etc…

17Conclusion & Future Works
Change mass accretion rate
and magnetic strength→ Even if magnetic field isweak, Outflow can drive whenaccretion rate is small.
Like low-mass stars.
→Even if magnetic field isstrong,Outflow cannot drive whenaccretion rate is extremely
Large.

ü Compare magnetic
pressure to rampressure→ if magnetic pressure
strong, outflow driven?
ü angular momentum
transfer→ What is the mostefficient ?

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19

Methods : “ Failed Outflow”
prepared 6 model
controls
initial cloud stability

set up Mass-to-Flux ratio
2, 3, 5, 10change Magnetic strength