再電離シミュレーションコードの開発と初期成果
Kenji Hasegawa (Nagoya University)
collaborators:
Tomoaki Ishiyama (Chiba U.),
Hidenobu Yajima (Tohoku U.),
Akio Inoue (Osaka Sangyo U.),2017年1月7-9日

SKA研究会「銀河進化と遠方宇宙」2017 @ 阿蘇
1/19

Recombinationz~1100First Star
Formationz~10-30(First) galaxies& AGN
formation?
z~10

IGM isalmost ionized.
z~6IonUn ize diverse

CMB photons

DarkAgesﬁrst stars

再電離未解決問題• いつはじまりいつ終わったか?
• 時間的空間的にどう進んだか?
• 電離光子源は何だったか?
2

宇宙初期の天体形成史

再電離: 現状の理解(私見)Question 1: 始まりと終わり
z~6ではほぼ完全電離である. 始まりは不明. 積分値(τe)はCMB観測から制限

Question 2: Topology•観: 観測的にはほとんど制限なし(clusteringから弱い制限 eg Ouchi+2010).

•理: シミュレーションではほとんどがinside-out型を示唆(ただし、光源は星形成銀河を仮定)

Question 3: 電離光子源
銀河が見えているので最有力候補だが電離光子脱出割合はよくわからない.
• 初代星は理論的にはmassiveで再電離に効く可能性があるが観測的には未•3検出. =>SKAで検出?田中くんトーク• ClasicalにはAGNはほとんど効かないと思われていたが、Giallongoら(2015)が多くのくらいAGNの存在を示唆(これもSKAで検出?竹内くんトーク).
Giallogoの観測が本当であればAGNだけで再電離できる可能性(e.gYoshiura, KH+)=> Topologyにも影響

研究目的
SKA : 圧倒的高感度で再電離期 HI 21cm線の検出が期待=>中性水素の空間分布を3次元(x-y-z)情報を直接得られる.
時間進化はほぼ解決.しかし、Topologyや電離光子源の解明には他の観測+理論モデルが必要.
4

輻射輸送計算で再電離過程をシミュレートすることで観測と比較しうる理論モデルを構築

Radiative Transfer simulations
Cosmological Radiation Hydrodynamics (RHD) Simulations• 輻射輸送と流体計算をカップルする為、高分解能計算であれば輻射による影響下での星形成率、それに伴うIGM電離過程をconsinstentに解ける. (e.g., KH, Semelin 2013)• 計算領域を広げるのは大変なので、典型的電離史計算やPS解析、バブルカウントなどの統計的研究に不向き

Post-processing Radiative Transfer (RT) Simulations• 小スケールの情報は潰してしまう為、比較的計算量が軽く、大きな計算領域を取りやすい(Ilievらの仕事が有名).=>大規模サーベイなどの観測と直接比較しやすい• Feedback効果のようなややこしいものは自動的には考慮されない5輻射輸送計算• Radiative Transfer of UV photons•

主に電離、解離光子の輸送(加熱~104K, 水素分子=ガス冷却剤の破壊)•X-rayの場合、以下の近似はそのまま成り立たないこともある

emissivity

輻射輸送方程式
opacity

化学反応率
立体角積分 光加熱率
(近似: 流体,光源の変動,原子の反応速度との比較、ガスからのdiﬀuseな放射はその場で吸収される.)全ての吸収体の足し合わせ輻射力
流体+化学反応式とのカップル

輻射``流体’’計算
Radiation Hydrodynamics code START
SPH with Tree-based Accelerated Radiative Transfer(KH & Umemura 2010)• Hydrodynamics(+ Dark Matter Dynamics)
SPH (Smoothed Particle Hydrodynamics)

N-bodyConsistently solve
Radiative transfer ofUV photons from “ALLstellar particles”

chemistry• Non-equilibrium
Creation
Destructiondni= Ci (T, nj )dt

Di (T, nj )nie-, H+, H, H-, H2, H2+, He, He+, and He2+ , dust, metal7我々の数値計算戦略
小スケールの物理を考慮しつつ大領域の計算を実現し、観測の予言/比較に使用したい。

large scale N-bodysimulation
data (provided byIshiyama-san)Sub-grid models ofgalaxies and IGM
w/ feedback (fromRHD sim.)

Post-processing
Radiative Transferfor ionizing
photons

光源モデル: 銀河ハロー質量 vs. 電離光子数( = SFRと電離光子脱出割合の積にほぼ比例), IntrinsicなLya光度の情報、(今の所使っていないが)DustからのIR放射情報(unresolved) IGMモデル: 加熱でsmoothingされる効果込みの再結合率補正モデル
8Which are galaxies responsible for reionization?
Intrinsic ionizing photon Emissivity [Mpc-3s-1]
Low-mass range:銀河はたくさんいるが、UV/SN feedbackに敏感な為、寄与は小さい
High-mass range: 大質量ほどSFRが高いが、数自体も少なくこれらが相殺

z=6z=7z=89

Which are galaxies responsible for reionization?
Ionizing photon Emissivity with escape fraction
大質量ほどfescが小さく、結果として大質量銀河の寄与はさらに小さく

z=6z=7z=8Red line
Black line
= fescGalaxies with ~109Msun are responsible for reionization
10¥40963 particles for N-body(Mh,min=2.5×107Msun)
2563 grids for RT(dx=0.6Mpc)

11

12

Number density nH [cm-3]

HI fraction

Gas temperature Tg[K]21cm differential brightness
temperature δTb [mK]13

Comparison : Simulations and Observations:
Constraint by QSO spectra

Thomson Opt. Depth

Fan et al. 2006

• 今のところ、z=6でのHI fractionやトムソン散乱の光学的的厚みなどは観測とconsistent
14

LAE modeling
Hyper Suprime-Cam (HSC):=> Large Sample of high-z Lyman Alpha Emitters (LAEs)
Prime Focus Spectrograph (PFS):=> Resolve Lyα profile of each LAE
Theoretical modeling for LAEs
1. RHDシミュレーションの結果から直接Lya光子生成量を評価 (therecombination and collisional excitation processes in the ISM) =>Mhalo-Lα relationを取得
2. 単純な過程でLyα輻射をといてintrinsicなprofile形を計算(so far withan expanding cloud model, NHI=1019cm-2, voutflow=150km)
3. 再電離シミュレーションのIGM情報からすべてのLya candidatesに対してtransmissionを計算し、observableなLAEの情報を取得
15

without transmission

Considering transmission

LAEs are clearly obscured by neutral IGM
16

Lyα LF: Simulation vs. Observation
Simulated LFs at z~6-7 are well consistent with obs.
• Observed LF indeed indicates that the mean neutralfraction increases with redshift.
•Santos et al. 2016

Matthee et al. 2015

Intrinsic
Late reion.
Fiducial

17

Konno et al. 2014

Lyα profiles inform sizes of HII bubbles?
dense HI gas•

Lya profileの形(ピークシフト/Skewness)は、LAEが存在するバブルのサイズを反映• もし観測される場所ごとにprofileの違いが見られれば、``Patchy’’ reionizationの間接的証拠 => PFSに期待
18

Summary
再電離シミュレーションコードの開発=> ``長谷川モデル”での計算は可能•

21cmシグナル解析(PS, bubble count)LAE観測との比較に使用可能•

21cm-LAE cross correlation解析(SKA, MWA) => 久保田君トーク

今後•使い方を簡略化し、好きな銀河モデル(SFR, fesc)、AGNからの放射込みで計算で誰でも計算できるように調整.

•

電離光子源モデルと観測量との対応(e.g. LAE LF/clustering, HII
バブルサイズ分布, HI(3HeII) fine structure line PS, HI21cm-LAE相互相関)の解明
19

Obtaining the map of HI fraction(Coarse-grained cell size is set to be 10Mpc)

ionization degree
1-xHI (answer)

HI 21cm signal
differential Tb [K]160Mpc160Mpc•@z=7.321cm signal map (that will be obtained by the SKA phase 2)
well correlates with the true HI map.

Obtaining the map of HI fraction(Coarse-grained cell size is set to be 10Mpc)@z=7.3ionization degree
1-xHI (answer)

HI 21cm signal
differential Tb [K]fLyα=nLAE/nall,gal

160Mpc160Mpc160Mpc•21cm signal map (that will be obtained by the SKA-2) wellcorrelates with the true HI map.

Local fLya seems to correlate inversely with 21cm signal.
=> Will be a nice cross-check for HI mapping•21cm-LAE cross correlation
Preliminary results (by K. Kubota, & S. Yoshiura)

21cm-LAE cross power spectrum

21cm-LAE cross correlation function

Anticorrelation inthe vicinity ofLAE

see also e.g., Lidz+09, Park+13, Hutter+16, Sobacchi+16,

21cm-LAE cross correlation
Galaxy dominant Scenario

AGN dominant Scenario?

?
?

21cm-LAE cross correlation
Galaxy dominant Scenario

AGN dominant Scenario?

?

* Feasibility study for MWASubaru observation. (by K. Kubota)* If AGNs largely contribute toreionization, how is its impact
imprinted on the cross-correlation
function?

?

Summary•••

Constructed the models of galaxies and IGM that include
feedback effects.
Our simulation with the models well reproduces observations(reionization and LAEs).
Synergy with Subaru will provide fruitful information on thereionization process.
Future Work••Implement X-ray model (Yoshiura,KH+) in the RT simulation=> Create 21cm-LAEs cross-correlation templates for varioussituations
Synergy SKA(21cm) + Subaru(LAE) + WFIRST(LBGs, AGNs)(discussions with Masami Ouchi & Takahiro Sumi)=> cross-correlations 21cm & (LAE/LBG/AGN),

backup slides

Snapshot @ z=7.3

HI fraction

21cm differential brightness
temperature δTb [mK]

Number density nH [cm-3] Gas temperature Tg[K]27Comparison : RHD model vs. Simple model
Galaxy model

Clumping factor model

constant
vsMh-dependent

Uniform (C=3 const)
vsdensity-dependent

With our fesc model, the averaged• With our C model, reionization
fesc evolves from 0.3 to 0.2. Since
proceeds slowly at earlier
less massive galaxies with high fescstages.
are dominant at higher redshifts.
• Then catch up later.
• Thus, it becomes extended
reionization history.
•Modeling LAEs
Lyα depending on Mhalo

Lyα profile
Lyα attenuation by the IGM# Intrinsic Lya luminosity
via recombination +collisional excitation# Ly α escape fraction
fαesc=30%(e.g., Yajima et al. 2015)

LAE
asymmetricshape

Lya radiative transfer insimplified model :NHI=1019cm-2,
v_outflow=150 km/s

Lyα photons

Evaluate the transmissionrate, by performing raytracing along the line ofsight through thesimulated IGM in the
Hubble flow

Key Quantities for understanding Reionization
Ionizing photon emissivity vs. recombination rate (e.g., Madau+99)
Ṅion > ↵B (T )hne nHII i ⇡ ↵B (T )hn2HII i = ↵B (T )hnHII i2 CHII
αB:recombination rate

Clumpingfactor

Key Quantities are:1) Intergalactic medium (IGM) clumping factor
2) Number of ionizing sources (including faint galaxies)
3) Ionizing photon emissivity per one ionizing source(closely related to SFR, escape fraction fesc)

IMPORTANT:
These quantities are severely affected by radiative feedback.

UV feedback on galaxies and IGM
Photoionization: Heating gas up to ~104K
Photodissociation: Decreasing coolants.

on Galaxies

Internal (from stars) and external radiation
affects SFR and escape fraction (e.g., Susa
Umemura 04 Wise & Cen 09, Umemura, KH+12, KH, Semelin 2013).

on IGM

Uniform heating casew/o photoheating

w/ photoheating

UVあり=> Reduce the number of galaxies
during the EoR (e.g., Finlator+13,Wise+14)

Clumping factor is decreased byphotoheating (e.g., Pawlik+ 09)=> averaged clumping factor
corresponds to ~2-4.

Models of Galaxies and Clumping factor

1+δ

xHII=0.005-1

SEDs of simulated galaxies(KH+ 16, arXiv:1603.01961)

Feedback
regulated SFR+ Escape fraction= Halo massdependent SED.

high z=6z=7z=8low
Clumping factor decreases with increasing local
ionization degree and decreasing local density.

Make a look -up
table of clumping
factor as afunction of local
density andionization degree.

UV(1500Å) Luminosity Function (LF): Sim. vs. Obs.
←bright faint ->←bright faint ->←bright faint ->w/oFeedback
w/Feedback
Dashed : HR &small box run
Solid : LR &large box run• Feedback effects suppress SF activities.
• Simulated UVLFs are consistent with observed LFs. (Henceconsistent cosmic star formation density.)• Predict flattening of faint-end LF at MUV -13 ~ -14.