The 3rd of June, 2016
銀河進化学研究会(2016a)
東北大学

ダスト形成を考慮した孤立系銀河シミュレーションと観測量との比較

青山尚平

SA et al. to be submitted.
大阪大学・宇宙進化グループ

Collaborators:
侯冠州(Kuan-Chou Hou)(ASIAA)、清水一紘(大阪大学)、平下博之(ASIAA)、
Keita Todoroki(Kansas U.)、Jun-Hwan Choi(U. Texas, Austin)、
長峯健太郎(大阪大学)

Introduction: cosmic dust (dust)• Dust consists of heavy elements such as carbon and silicate, floating in theinterstellar medium.
• It is generated in the nucleosynthesis of heavy elements
at the end of the massive stars.
http://www.drcom.co.jp/blog/wpcontent/uploads/2013/12/zz3.png• Dust plays important role in ISM as follows:
1. Highly efficient catalyst of H2 formation, necessary for star formation.
2. Absorption of the UV light and reemitting in the infrared (IR).
dust
UV light

IR light

Introduction: previous works• Yajima et al.(2015) MNRAS, 451, 418
Cosmological zoom-in simulation(z=199→6)
Radiation transfer is calculated with dust.
Constant dust-to-metal mass ratio.

Yajima et al (2015) [1411.2626]• Bekki (2015) MNRAS, 449, 1625
Dust particles are included in SPH simulation.
The formation, growth, and destruction
by AGB stars, supernovae (SNe) and ISM are included.
Some of interactions of dust (coagulation, shattering) has
not been included yet.

Bekki (2015) [1501.05459]

Hirashita (2015) 2-component model [MNRAS, 447, 2937]
Hirashita categorizes dusts into two sizes:
large / small dusts( a > 0.03μm , a < 0.03μm ).
a=0.03μmaHirashita’15

In this work, we use
the GADGET3-Osaka SPH code
(Springel ‘05 + modification).
atoms,moleculesi-th SphL↗

SN shocks
L→×, S→×

Mg, Zi,Ti,ψi etc.
grain growthS↗

dust

SNe IIL↘:-(ML/Mg)ψ
S↘:-(MS/Mg)ψ

coagulation

shattering

Figure credit :AsanoInitial condition• AGORA initial condition (Kim et al. 2014 )• Mgas=8.6×109 M☉• Ngas =105

Type Total Mass

# of particles

Gas

8.6×109 M☉

105

Halo

1.3×1012 M☉

105

Disk

4.3×1010 M☉

105Bulge

5.4×109 M☉
0Stars

1.25×104
0 Distribution of Gas particles

log10 ( T [K] )Sub-grid model for accretion• Resolution of our simulation (~ 80pc ) istoo low to treat the physical processes
in molecular clouds (e.g. accretion).
• We assume that the 10% of mass ofSPH particles is molecular clouds with T=50K-3] )log(n[cm10and n=103 cm-3.
• In addition, the accretion occurs only in50K
this molecular cloud.
Hirashita (2015)
103cm-3
Hirashita&Kuo(2011)[1105.4930]

10%80pc

Sub-grid model for collisional processes• Coagulation / shattering [collision]←σ=πa2
process
We fix the velocity to
10 km/sec.

Dust species representative
radiuscoagulation

Small

0.005 μm

shuttering

Large

0.1 μmSub-grid model for collisional processes
50K
103cm-3• Shattering (significant only in diffuse gas)nSph < 1 cc-1 : τ = τcoll(L)nSph > 1 cc-1 : τ = ∞ [ No reaction ]• Coagulation (significant only in dense medium)
TSph > 100 K : τ = 0.5 × τcoll(S)(n=103 cc-1, T=50 K )TSph < 100 K : τ = τcoll(S)(nSPH, TSPH)

50%

80pc

100 %

Small/Large dust distribution (z-projection map)
We redistribute dust and metal
to neighboring SPH particles
with the Kernel weightat each time step.

Data points:
Remy-Ruyer et al. (2014)
A&A, 563, A31

Total dust-to-gas ratio vs metallicity

log10( Dtot )• t ≲ 0.2 Gyr, Dtot ∝ Z,i.e. fixed dust-to-metal mass ratio isgood approximation.

log10( Z/Z☉ )Data points:
Remy-Ruyer et al. (2014) A&A, 563, A31• T ≳ 0.2 Gyr, accretion becomes significant
and the previous approx. is no longer valid.
• T ≳ 1.0 Gyr, coagulation and shattering
is in balance. Many data points can beexplained by this snapshot.

Small to large grain ratio vs metallicity

log10( DS / DL )• t ≲ 0.1 Gyr, small grain is only created
via shattering and the abundance is small.
• t ~ 0.2 Gyr, accretion comes in, and small
grain abundance dramatically increase
due to accretion.

• t ≳ 1.0 Gyr, coagulation and shattering isin balance, and the small abundance issuppressed due to coagulation ( S -> L ).

log10( Z/Z☉ )log10( sSFR [Gyr-1] )Time evolution ofSpecific Star formation Rate (sSFR)• In our simulation, sSFR ~ 1 Gyr-1
when age is 1 Gyr.

Class I

• We categorize the galaxies
according to sSFR :Class I, II and III

Class III• We assign the simulation results
whose age are 0.3, 1.0, 3.0 (10) Gyrto the classes, respectively.

log10( t [Gyr] )Comparison with observational result 1.
Dust abundance log10 (Dtot)

Data points Mattsson et al. (2012b) [1201.3374]
The observed radial profiles of dust abundance approximately agree with our simulations.

Comparison with observational result 2.
Depletion : log10(Dtot/Z)

Data points Mattsson et al. (2012b)[1201.3374]
The observed radial profiles of depletion also approximately agree with our simulations.

Conclusions• We investigate the time evolution and spatial distribution oflarge and small dust grain in an isolated galaxy
based on Hirashita (2015) 2-component dust model using GADGET3-Osaka.
• We have implemented sub-grid models for coagulation, shatteringand accretion.
• Our simulation can reproduce observational results such asradial profile of total dust abundance and depletion (Dtot/Z).
• Dynamical evolution of dust properties• Some issues remain (e.g. metal/dust diffusion).

Back upEstimation of R25 from a simulation.
• The R25 is related to Rd Elmegreen(1998)
R25 ≃ 4 Rd .
• This relation can be checked by the data
shown in de Vaucouleurs & Pence (1978).
• Rd is easily obtained by fitting
the radial profile of stars.