銀河進化と遠方宇宙 - 2019.3.11 - Kanagawa Univ

天体物理学的効果の中性水素のクラスタリングへの影響
Rika Ando1
Collaborators: Atsushi J Nishizawa1
Kenji Hasegawa1
Ikkoh Shimizu2
Kentaro Nagamine2
1Nagoya University, 2Osaka University

arXiv:1808.01116

Contents
1. Introduction• galaxy survey• 21cm line intensity mapping

2. HI bias
• BAO peak scale• scale dependence

3. Redshift space distortion of HI• theoretical model• measure using simulation data
• SKA

4. Summary!2 /26

宇宙の加速膨張と大規模構造
宇宙の加速膨張の起源(dark energy や modified gravity)
斥力を及ぼすエネルギー

一般相対論を拡張• 膨張率の変化• 密度ゆらぎの進化!3 /26

相
対
的
な
宇
宙
の
大
き
さ

credit: NASA

速

加

張

膨

現在
宇宙年齢/10億年

大規模構造の探査による制限→ パワースペクトル, 相関関数, BAO, RSD …

宇宙のものさしとしてのBAO!4 /26

Baryon Acoustic Oscillation (バリオン音響振動)
No. 2, 2005

3. THE REDSHIFT-SPACE CORRELATION FUNCTION
3.1. Correlation Function Estimation

In this paper, we analyze the large-scale clustering using thetwo-point correlation function ( Peebles 1980, x 71). In recent
years, the power spectrum has become the common choice onlarge scales, as the power in different Fourier modes of the linear
density field is statistically independent in standard cosmology
theories ( Bardeen et al. 1986). However, this advantage breaks
down on small scales due to nonlinear structure formation, whileon large scales elaborate methods are required to recover the statistical independence in the face of survey boundary effects (fordiscussion, see Tegmark et al. 1998). The power spectrum andcorrelation function contain the same information in principle,
as they are Fourier transforms of one another. The property of
the independence of different Fourier modes is not lost in real
space, but rather it is encoded into the off-diagonal elements ofFig. 2.—Large-scale redshift-space correlation function of the SDSS LRG
the covariance matrix via a linear basis transformation. One mustsample. The error bars are from the diagonal elements of the mock-catalog cotherefore accurately track the full covariance matrix to use thevariance matrix; however, the points are correlated. Note that the vertical axis
correlation function properly, but this is feasible. An advantage
logarithmic and linear scalings. The inset shows an expanded view with a
0.0 mixesof the correlation function is that, unlike in the power spectrum,
linear vertical axis. The models are !m h2 ¼ 0:12 (top line), 0.13 (second line),
and 0.14 (third line), all with !b h2 ¼ 0:024 and n ¼ 0:98 and with a mild nonsmall-scale effects such as shot noise and intrahalo astrophysics
linear prescription folded in. The bottom line shows a pure CDM model (!m h2 ¼
stay on small scales, well separated from the linear regime fluc0:105), which lacks the acoustic peak. It is interesting BAO
to note that although thetuations and acoustic effects.
data appear higher than the models, the covariance between the points is soft as
We compute the redshift-space correlation function using
regards overall shifts in "(s). Subtracting 0.002 from "(s) at all scales makes thethe Landy-Szalay estimator (Landy & Szalay 1993). Random
plot look cosmetically perfect but changes the best-fit #2 by only 1.3. The bumpat 100 h#1 Mpc scale, on the other hand, is statistically significant. [See the electronic
catalogs containing at least 16 times as many galaxies as the LRG
edition of the Journal for a color version of this figure.]
sample were constructed according to the radial and angular seMB
-0.5
C
lection functions described above. We assume a flat cosmology
sight direction than along the tangential direction. We sum thesewith !m ¼ 0:3 and !" ¼ 0:7 when computing the correlation
function. We place each data point in its comoving coordinate
four correlation functions in the proportions corresponding to
the fraction of the sphere included in the angular bin, thereby relocation based on its redshift and compute the comoving sepw
aration between two points using the vector difference. We use
covering the spherically averaged redshift-space correlation funcbins in separations of 4 h#1 Mpc from 10 to 30 h#1 Mpc andtion. We have not yet explored the cosmological implications of
the anisotropy of the correlation function ( Matsubara & Szalaybins of 10 h#1 Mpc thereafter out to 180 h#1 Mpc, for a total of
20 bins.
-1.0 2003).
We weight the sample using a scale-independent weighting
The resulting redshift-space correlation function is shown in
Figure 2. A more convenient view is shown in Figure 3, wherethat depends on redshift. When computing the correlation funcwe have multiplied by the square of the separation, so as to flattention, each galaxy and random point is weighted by 1/½1 þ n(z)Pw &(Feldman et al. 1994), where n(z) is the comoving number density
out the result. The errors and overlaid models will be discussed
peak, to be deand Pw ¼ 40;000 h#3 Mpc3 . We do not allow Pw to change withbelow. The bump at 100 h#1 Mpc is the acoustic
SNescribed in x 4.1.
scale so as to avoid scale-dependent changes in the effective bias
caused by differential changes in the sample redshift. Our choice
The clustering bias of LRGs is known to be a strong functionofof Pw is close to optimal at k ' 0:05 h Mpc#1 and within 5%-1.5
of luminosity (Hogg et al. 2003; Eisenstein et al. 2005; Zehavi
the LRG sample
volume-limited
the optimal errors for all scales relevant to the acoustic oscillations 0.0et al. 2005a),
0.1and while0.2
0.3is nearly 0.4
0.5(k P 0:15 h Mpc#1 ). At z < 0:36, nPw is about 4, while nPw ' 1
out to z ! 0:36, the flux cut does produce a varying luminositymat z ¼ 0:47. Our results do not depend on the value of Pw; changcut at higher redshifts. If largerm
scale correlations were preferentially drawn from higher redshift, we would have a differential
ing the value wildly alters our best-fit results by only 0.1 !.

BAO (rh~100Mpc/h)comoving separation[Mpc/h]→ DA→ H(z)

563

correlation function ξ(s)• 宇宙初期に物質の分布に刻印されたゆらぎ• 特徴的な振動スケールの値は精密に測定

regime by a factor of !4. The LRG sample should therefore outperform these surveys by a factor of 2 in fractional errors on large
scales. Note that quasar surveys cover much more volume thaneven the LRG survey, but their effective volumes are worse, evenon large scales, due to shot noise.

θEisenstein et al. 2005

DETECTION OF BARYON ACOUSTIC PEAK

→ 宇宙論パラメータの制限

Kowalski et al. 2008

w

状態方程式

pde = w ρde

Ω

2.

1.

1.

0.

0.

RSDによる重力理論の検証!5 /26

Redshift Space Distortion (赤方偏移空間歪み)• 天体の特異速度によって赤方偏移空間における相関関数に歪み(非等方性)が生じる• RSDの観測より、密度ゆらぎの成長率 f へ制限
Publications of the Astronomical Society of Japan (2016), Vol. 68, No. 3

f(z)σ8(z)近年のRSDの観測によるfσ8への制限

38-17

ΛCDM
GR+(w=-1)z→ 重力理論の検証

過去
Okumura et al. 2016

Fig. 17. Constraints on the growth rate f (z)σ 8 (z) as a function of redshift at 0 < z < 1.55. The constraint obtained from our FastSound sample at
1.19 < z < 1.55 is plotted as the big red point. The previous results include the 6dFGS, 2dFGRS, SDSS main galaxies, SDSS LRG, BOSS LOWZ,
WiggleZ, BOSS CMASS, VVDS, and VIPERS surveys at z < 1. A theoretical prediction for fσ 8 from "CDM and general relativity with the amplitude
determined by minimizing χ 2 is shown as the red solid line. The data points used for the χ 2 minimization are denoted as filled-symbol points while

Downloaded from https://academic.oup.

現在

重力理論モデル従来の銀河サーベイ
http://www.sdss.org/science/!6 /26銀河をトレーサー大規模構造の探査
メリット• 銀河の3次元分布が得られる• 理論モデルが確立されている
デメリット• 遠方の銀河の赤方偏移の観測が困難※点は銀河

ダークマターの新たなトレーサーとしての中性水素(HI)21cm線 intensity mapping!7 /26銀河を分解せずにHIから放射された21cm線強度を観測→ 中性水素の3次元分布
intensity mapping
中性水素p• 広い領域• より遠方まで• 高い周波数分解能e21-cm線λobs = λ21cm(1+z)

研究の目的: HIの理論モデルの構築!8 /2621cm線intensity mappingによる宇宙論モデルへの制限
先行研究:線形モデルを用いた将来観測による制限予測

Measuring BAO with future SKA surveys

Philip Bull

SKA2 galaxy survey
Euclid galaxy survey

wa

Bull et al. 2015

w0

Figure 4: Forecast constraints on (w0 , wa ) for several SKA configurations and Euclid, in combination with
Planck and BOSS. All other parameters have been marginalised, including WK , and the bias is free per z bin.

状態方程式 pde = w ρdew = w0 + (1 − a) wa

Expected constraints on the dark energy equation of state parameters (Eq. 2.3) are shown in
Fig. 4 for a subset of these configurations, combined with forecast Planck CMB and BOSS low
redshift BAO constraints.2 Forecasts for a future Euclid galaxy survey are shown for comparison,also with Planck+BOSS included. While unable to match Euclid on raw figure of merit3 (FOM =69, versus 129 for Euclid), the Phase 1 IM survey has a highly complementary redshift range andwide survey area (with potentially ⇠ 100% overlap), and should be completed in the early 2020’s,
making it the low redshift dataset of choice for joint analyses with Euclid and other high redshift
experiments like WFIRST and DESI. Combining surveys will be important for pinning-down thenature of dark energy in the medium term, as “Stage IV” galaxy surveys may not offer sufficientprecision on their own to discriminate between most dark energy models (Marsh et al. 2014). In
the longer term, the galaxy survey with SKA2 will be able to achieve a substantially larger FOM
of around 310.

5. Conclusions
The Baryon Acoustic Oscillations imprint a distance scale into the distribution of matter on large
scales that can be used to constrain the expansion history and geometry of the Universe. In turn,this can be used to constrain key cosmological parameters, potentially allowing us to answer fundamental questions about the nature of dark energy such as whether it evolves with time. The BAO

PoS(AASKA14)024

intensity mappingではdark energyのパラメータへの強い制限が期待研究の目的: HIの理論モデルの構築!8 /2621cm線intensity mappingによる宇宙論モデルへの制限
先行研究:線形モデルを用いた将来観測による制限予測

Measuring BAO with future SKA surveys

Philip Bull

SKA2 galaxy survey
Euclid galaxy survey

wa

Bull et al. 2015

w0

Figure 4: Forecast constraints on (w0 , wa ) for several SKA configurations and Euclid, in combination with
Planck and BOSS. All other parameters have been marginalised, including WK , and the bias is free per z bin.

状態方程式 pde = w ρdew = w0 + (1 − a) wa

Expected constraints on the dark energy equation of state parameters (Eq. 2.3) are shown in
Fig. 4 for a subset of these configurations, combined with forecast Planck CMB and BOSS low
redshift BAO constraints.2 Forecasts for a future Euclid galaxy survey are shown for comparison,also with Planck+BOSS included. While unable to match Euclid on raw figure of merit3 (FOM =69, versus 129 for Euclid), the Phase 1 IM survey has a highly complementary redshift range andwide survey area (with potentially ⇠ 100% overlap), and should be completed in the early 2020’s,
making it the low redshift dataset of choice for joint analyses with Euclid and other high redshift
experiments like WFIRST and DESI. Combining surveys will be important for pinning-down thenature of dark energy in the medium term, as “Stage IV” galaxy surveys may not offer sufficientprecision on their own to discriminate between most dark energy models (Marsh et al. 2014). In
the longer term, the galaxy survey with SKA2 will be able to achieve a substantially larger FOM
of around 310.

本研究の目的PoS(AASKA14)024

intensity mappingではdark energyのパラメータへの強い制限が期待
HIの時間発展には複雑な天体物理が寄与

中性水素を用いた宇宙論解析のための理論的枠組みの構築

5. Conclusions

The Baryon Acoustic Oscillations imprint a distance scale into the distribution of matter on large
scales that can be used to constrain the expansion history and geometry of the Universe. In turn,this can be used to constrain key cosmological parameters, potentially allowing us to answer fundamental questions about the nature of dark energy such as whether it evolves with time. The BAO

先行研究におけるHIの取り扱い!9 /26

ダークマターのハロー質量に応じてHIの分布を計算
Sarkar et al.2018, Wang et al. 2019
N体シミュレーション
ダークマターの重力相互作用のみを計算

Mhalo-MHI
モデル
を仮定

HIの
密度場
Mpc

Figure 1. Shown in this figure are the matter (left panels), halo (central panels) and H I (right panels) density contrasts [δ(x, t) = δρ(x, t)/ρ̄(t)], respectively,
at three different redshifts 6, 3 and 1 (from top to bottom). First we calculate the over densities on the grid positions using cloud in cell (CIC) interpolation
scheme. We prepare the two-dimensional density plots by collapsing a layer of thickness 5.6 Mpc along one direction to calculate the average density contrast
on a plane. Different colours indicate the values of density contrast on each of the pixels as shown by the colour bar.

バリオン物理を計算していない
Mhalo-MHIモデルに依存

high-resolution simulation (referred to as HRS) with [2, 144]3 particles in a [4, 288]3 regular cubic grid of spacing 0.035 Mpc, the total
simulation volume remaining the same as earlier. The lower-masslimit for the halo mass is 108.1 M⊙ in the HRS, well below Mminin the entire redshift range. The HRS requires considerably larger
computational resources compared to the other simulations, and wehave run only a single realization for which we have compared theresults with those from the earlier lower resolution simulations.
3 R E S U LT S

at three different redshifts, viz. 6, 3 and 1. It can be seen that thecosmic web is clearly visible in all three components even at thehighest redshift z = 6, though it is somewhat diffused for the matterat this redshift. Observe that the basic skeleton of the cosmic web isnearly the same for all the three components, and the basic skeleton
does not change significantly with redshift. We see that for all thethree components the cosmic web becomes more prominent withdecreasing redshift. Considering the matter first, the density contrast
grows with decreasing redshifts due to gravitational clustering. The
haloes are preferentially located at the matter density peaks, and it
is evident that the haloes have a higher density contrast. We see thatthe structures in the halo distribution are more prominent comparedto the matter, particularly at high redshifts. The H I closely follows
the halo distribution at z = 6. However, in contrast to the matter• HIバイアスのモデル化• HIのRSDの測定

Fig. 1 provides a visual impression of how the matter, the haloes
and the H I are distributed at different stages of the evolution. We
show this by plotting the density contrasts δ(x, t) = δρ(x, t)/ρ̄(t)Downloaded from https://academic.oup.com/mnras/article-abstract/460/4/4310/2609038
by Nagoya University user
on 20 March 2018

MNRAS 460, 4310–4319 (2016)※HIバイアス: HIとダークマターの密度分布のずれ

本研究の特色: 流体シミュレーション!10 /26

宇宙論的流体シミュレーションを使用• ダークマターだけでなく中性水素の時間発展も同時に計算
より現実に近い理論モデルの構築

本研究の特色: 流体シミュレーション!10 /26

宇宙論的流体シミュレーションを使用• ダークマターだけでなく中性水素の時間発展も同時に計算
より現実に近い理論モデルの構築

銀河スケール以下の物理モデルの不定性が存在
星形成や銀河からの質量放出

物理モデルの異なる2つのシミュレーションを使用
HIの宇宙論的なスケールのクラスタリングへの影響を調べる
e.g. BAOのスケール rh~100Mpc/h

2つのシミュレーションと天体物理学的効果 !11 /26
小スケールの天体物理のモデルが異なる(星形成活動、超新星・AGN feedbackなど)

Illustris simulation

Osaka simulation

moving mesh code AREPO

N-body/SPH code Gadget-3

ボックスサイズ : (75 cMpc/h)3

ボックスサイズ: (85 cMpc/h)3

粒子数 : 2*4553

粒子数 : 2*5123

強い AGN feedback

AGN feedback を含まない

minimum softening[ckpc/h]
particle mass [Msun/h]: gravity : ~6
, baryon : ~0.6
: DM
: ~6*107 , baryon : ~3*108

Vogelsberger et al.(2014), Nelson et al.(2015)

Aoyama et al. 2017, Shimizu et al. 2019

※Uniform UVB model, 宇宙論パラメータや粒子解像度はほとんど同じ密度ゆらぎ 1+δ map!12 /26

ガス(baryon w/o star,BH)とHIの密度map
Illustris HI

Osaka HI

Illustris gas

Osaka gasρi
= 1 + δiρ̄i

(i=gas,HI)HI bias
1. Introduction• galaxy survey• 21cm line intensity mapping

2. HI bias
• BAO peak scale• scale dependence

3. Redshift space distortion of HI• theoretical model• measure using simulation data

4. Summary!13 /26

バイアスのBAO振動スケールへの影響!14 /26

観測から得られるBAOの振動スケールは線形理論から予言される値からずれる※イメージ(計算にはCAMB使用)• 重力の非線形性• バイアスのスケール依存性δHI = bHI(k) δm

P/Pno-wiggle

ピーク位置がシフトする例) b(k)=1+0.5k

k[h/cMpc]
ρ
密度ゆらぎ：δ = ρ̄ − 1

線形 mater
非線形 matter
バイアスを持つトレーサー

HIバイアスのスケール・赤方偏移依存性!15 /26

密度場からHIとダークマターのパワースペクトルを測定
dark matter

1+δ =

ρX
ρ̄X

HI

z=1
z=5

method:1<z<5のパワースペクトルの比をとることでHIバイアスを測定・モデル化

PHI−mb(k) =Pm
HI バイアスHI-matter 相互相関
matter 自己相関z=3

HI バイアス

点PHi mb(k) =
Pm

Illustris (w/ AGN)

: simulation data

曲線: b(k)=b0+b1k!16 /26

Osaka (w/o AGN)
z=5

z=4

中
性
水
素
バ
イ
ア
ス

z=3

z=2
z=1

Large-scale

Small-scale

波数

Large-scale

Small-scale

波数

2
kmax
6⇡ 2

Z kmax0

dk P lin (k, z) = C ⇠ 0.7

HI バイアス

点PHi mb(k) =
Pm

Illustris (w/ AGN)

: simulation data

曲線: b(k)=b0+b1k!16 /26

Osaka (w/o AGN)
z=5

中
性
水
素
バ
イ
ア
ス

z=4
z=3

z=2

kmax
z=1

Large-scale

Small-scale

波数

Large-scale

Small-scale

波数b(k) = b0 + b1k
スケール依存性

2
kmax
6⇡ 2

Z kmax0

dk P lin (k, z) = C ⇠ 0.7

スケール依存性と天体物理の影響
バ
イ
ア
ス
パ
ラ
メ
|
タ

b(k) = b0 + b1k!17 /26

大スケールのHI バイアスは(例. k<0.5 h/Mpc @ z=3)

• スケール依存性を持つ
at z>3• 小スケールの天体物理への依存性が弱い(星形成, 超新星/AGNフィードバック)● filled: Illustris (w/ AGN)
○ open: Osaka (w/o AGN)

Redshift Space Distortions of HI
1. Introduction• galaxy survey• 21cm line intensity mapping

2. HI bias
• BAO peak scale• scale dependence

3. Redshift space distortion of HI• theoretical model• measure using simulation data

4. Summary!18 /26

RSDのふるまいと理論モデル
非等方パワースペクトルの理論モデル(kµfµ = kk /k = cos ✓= f /bHi!19 /26f : 線形成長率2)v

PHi (k, µ) = eb2Hi (1 + µ2 )2 Pm (k)赤方偏移空間 Finger of God Kaiser
実空間抑制
上昇 でのmatter
でのHI

Finger of God

Kaiser

小スケール

大スケール

特異
速度
実空間
赤方偏移空間非線形な
ランダム運動Jackson et al. 1972

高密度領域に落ち込む
Kaiser et al .1987

RSDモデルの整備と手法!20 /26

特異速度 → 視線方向の距離 → 相関関数の非等方性
simulation box

s3

HIのRSDに適用できる理論モデルを検証

method: 赤方偏移空間における粒子の位置
s2

s1

v3
(s1, s2, s3) = (x1, x2, x3 +aH )赤方偏移空間

実空間

での位置

での位置

天体の
特異速度

where A10 is the Einstein coefficient for emission, and WHI (z) istoday, rc,0 , in neutral hydrogen. Assuming that HI is a linearly
density field, we can relate fluctuations in the brightness!2temper
1 /26
redshift-space matter density perturbation,

SKAによる21cm線intensity mapping

1 2 2
大規模電波干渉計のSKAによるintensity
mapping2
d Tb = T b dHI (k) = T b (bHI + f µ )e 4 k sNL

観測量: 輝度温度

3
2
hc
A
3
z) to RSDs and non-linear g
where the anisotropic
terms
are+due
10 (1δTb =the 3D redshift-space
ρ̄
δ
HI
HI
measurematterpower
spectrum,
hd
(k)d
2
M
32π kBmpν21 H(z)by mapping out the brightness temperature distribution in angle a

https://www.skatelescope.org/
SKA Organisation

Bull et al.2015

Tinst [K]zmin
zmax
nmin [MHz]nmax [MHz]Ddish [m]d n [kHz]
Wsur [103 deg2 ]Ndish ⇥ Nbeam

SKA1-MID
Band 1 Band 2
28
20
0.35
0.00
3.05
0.49
350
950
1050
1760
15
15
50
50
25
25
254 ⇥ 1 254 ⇥ 1

SK
Band
50
0.58
3.05
350
900
12
50
25
60 ⇥

0<z<3周波数分解能: 50kHz

SKAの分解能
角度方向の密度ゆらぎは均される干渉計モード

角度方向の

空間分解能
Osaka simulation

reality
視
線
方
向
角度方向

単一鏡モードinterferometer

single-dish~2cMpc/h @z=1

~65cMpc/h @z=1

赤方偏移空間における 1+δHI map at z=3!22 /26

0<z<3周波数分解能: 50kHz

SKAの分解能
角度方向の密度ゆらぎは均される干渉計モード

角度方向の

空間分解能
Osaka simulation

reality
視
線
方
向
角度方向

単一鏡モードinterferometer

single-dish~2cMpc/h @z=1

~65cMpc/h @z=1

赤方偏移空間における 1+δHI map at z=3
interferometer!22 /26

0<z<3周波数分解能: 50kHz

SKAの分解能
角度方向の密度ゆらぎは均される干渉計モード

角度方向の

空間分解能
Osaka simulation

reality
視
線
方
向
角度方向

単一鏡モードinterferometer

single-dish~2cMpc/h @z=1

~65cMpc/h @z=1

赤方偏移空間における 1+δHI map at z=3
interferometer
single-dish!22 /26

Osaka simulationから測定したP2D!23 /26

P2D 等高線 at z=3
実空間
赤方偏移空間
赤方偏移空間(干渉計)

100
視
線
方
向
の
波
数

FoG効果
Kaiser・FoG 効果を

300

Kaiser効果

Large-scale

PHI(k) においても確認

Small-scale多重極パワースペクトル
シミュレーション vs 理論

model:

free parameters2(kµf
PHi (k, µ) = Wbeam (k, µ) e

v)

2

2
bHi (1 +f 2 2µ ) Pm (k)bHi+ TNS 補正項
Taruya et al. 2010(s)kPl (k)点!24 /26: Osaka simulation

曲線: 理論モデル (TNS)
monopole

with best-fitting parameters

quadrupole
2
kmax
6⇡ 2

Z kmax0

dk P lin (k, z) = C ⇠ 0.7

多重極パワースペクトル
シミュレーション vs 理論

model:

free parameters2(kµf
PHi (k, µ) = Wbeam (k, µ) e

v)

2

2
bHi (1 +f 2 2µ ) Pm (k)bHi+ TNS 補正項
Taruya et al. 2010(s)kPl (k)点!24 /26: Osaka simulation

曲線: 理論モデル (TNS)
monopole

with best-fitting parameters銀河サーベイに用いられている
RSDの理論モデルがHIに適用できた
quadrupole
2
kmax
6⇡ 2

Z kmax0

dk P lin (k, z) = C ⇠ 0.7

推定値の比較: HIバイアス
2
PHi (k, µ) = Wbeam(k, µ) e (kµf実空間PHI-m/Pm (this work)
RSDから推定(this work)

実空間PHI-m/Pm (先行研究)
Mhalo-MHIモデルを使用
Sarkar et al. 2018v)

2

!25 /26

b2Hi (1 +f 2 2µ ) Pm (k)bHi+ TNS 補正項
Taruya et al. 2010

推定値の比較: HIバイアス
2
PHi (k, µ) = Wbeam(k, µ) e (kµf実空間PHI-m/Pm (this work)
RSDから推定v)

2!25 /26

b2Hi (1 +f 2 2µ ) Pm (k)bHi+ TNS 補正項
Taruya et al. 2010

(this work)

実空間PHI-m/Pm (先行研究)
Mhalo-MHIモデルを使用
Sarkar et al. 2018

銀河サーベイのRSDモデルでHIバイアスの値を正しく推定推定値の比較: HIバイアス
2
PHi (k, µ) = Wbeam(k, µ) e (kµf実空間PHI-m/Pm (this work)
RSDから推定v)

2!25 /26

b2Hi (1 +f 2 2µ ) Pm (k)bHi+ TNS 補正項
Taruya et al. 2010

(this work)

実空間PHI-m/Pm (先行研究)
Mhalo-MHIモデルを使用
Sarkar et al. 2018

銀河サーベイのRSDモデルでHIバイアスの値を正しく推定

ハローとHIの質量の正しい関連付けが必要

まとめ
目的: 中性水素(HI)を用いた宇宙論解析のための理論的枠組みの構築

手法: 2つの宇宙論的流体シミュレーションを用いてHIバイアスとHIの赤方偏移空間歪み(RSD)を測定
結果 実空間で測定したHI bias

• スケール依存性 (at z>3)
• 銀河スケール以下の物理モデルの不定性の影響は小さい
e.g. 星形成や超新星/AGN フィードバック

結果 赤方偏移空間歪み(RSD)• 銀河サーベイで用いられる理論モデルをHIにも適用可能• ハローとHIの質量の関係のより詳細な調査が必要!26 /26

Thank you for listening
arXiv:1808.01116