SHAO(2021/7/22)

1. Exploring early universe with neutral hydrogen
@上海天文台（2021/7/22）
©Aman Chokshi
Hayato Shimabukuro(島袋隼士)
（云南大学・SWIFAR）
Aman Chokshi

2. •Born in Okinawa(冲绳)
•Ph.D from
Nagoya university(2016)
•Postdoc at
Paris observatory(2016-2018)
About me
•Postdoc at
Tsinghua University(2018-)

3. •Born in Okinawa(冲绳)
•Ph.D from
Nagoya university(2016)
•Postdoc at
Paris observatory(2016-2018)
About me
•Postdoc at
Tsinghua University(2018-)
•云南⼤学（2019ー）

4. Outline
• Introduction
• Basics of 21cm line
• Current 21cm cosmology status and future
• My works
• Challenge
• Summary

5. Introduction

6. Current universe
©Hubble space telescope

7. Current universe
Stars, galaxies, bright universe
©Hubble space telescope

8. Past universe

9. Past universe
No stars, galaxies, dark universe

10. Past universe
No stars, galaxies, dark universe
How did the universe evolve from dark ages to present universe?

11. The history of the universe
Present
Past
https://universe-review.ca/
Epoch of
Reionization
Dark ages
Dark Ages・・・No luminous object exists.
Epoch of Reionization(EoR)・・・UV photons by luminous objects ionize
neutral hydrogen in the IGM (z~6-15).
Cosmic Dawn・・・First stars and galaxies form (z~20-30).

12. The history of the universe
Present
Past
https://universe-review.ca/
Epoch of
Reionization
Dark ages
Dark Ages・・・No luminous object exists.
Epoch of Reionization(EoR)・・・UV photons by luminous objects ionize
neutral hydrogen in the IGM (z~6-15).
Cosmic Dawn・・・First stars and galaxies form (z~20-30).

13. （C)Kenji Hasegawa（Nagoya University）
Credit: M. Alvarez, R. Kaehler and T.Abel

14. （C)Kenji Hasegawa（Nagoya University）
Credit: M. Alvarez, R. Kaehler and T.Abel

15. Current observations for EoR
•Lyman alpha emitter galaxies（LAE） •Lyman alpha forest
Konno et al (2014)
(http://pages.astronomy.ua.edu/keel/agn/forest.html)
QSO
HI cloud
>The number of ionizing photons
Sensitive to neutral hydrogen fraction

16. Current observations for EoR
•Lyman alpha emitter galaxies（LAE） •Lyman alpha forest
Konno et al (2014)
(http://pages.astronomy.ua.edu/keel/agn/forest.html)
QSO
HI cloud
>The number of ionizing photons
Sensitive to neutral hydrogen fraction

17. Current observations for EoR
•Lyman alpha emitter galaxies（LAE） •Lyman alpha forest
Konno et al (2014)
(http://pages.astronomy.ua.edu/keel/agn/forest.html)
QSO
HI cloud
>The number of ionizing photons
Sensitive to neutral hydrogen fraction

18. Current observations tell us
(Greig et al 2017)
Constraints on average neutral(ionized) hydrogen fraction (Global history).

19. Current observations tell us
(Greig et al 2017)
Constraints on average neutral(ionized) hydrogen fraction (Global history).
Current observations tell us only global
history (at late stage of EoR).

20. We want to know EoR much more
(ex)
•EoR theory
•Morphology and topology of ionized bubble
•Ionizing sources
•Relation to galaxy formation and evolution
etc…

21. We want to know EoR much more
We should observe IGM at the EoR directly !
(ex)
•EoR theory
•Morphology and topology of ionized bubble
•Ionizing sources
•Relation to galaxy formation and evolution
etc…

22. We want to know EoR much more
We should observe IGM at the EoR directly !
(ex)
•EoR theory
•Morphology and topology of ionized bubble
•Ionizing sources
•Relation to galaxy formation and evolution
etc…

23. We want to know EoR much more
We should observe IGM at the EoR directly !
(ex)
•EoR theory
•Morphology and topology of ionized bubble
•Ionizing sources
•Relation to galaxy formation and evolution
etc…
Synergy with galaxy observation by ALMA, JWST, Subaru

24. We want to know EoR much more
We should observe IGM at the EoR directly !
(ex)
•EoR theory
•Morphology and topology of ionized bubble
•Ionizing sources
•Relation to galaxy formation and evolution
etc…
✕
Synergy with galaxy observation by ALMA, JWST, Subaru

25. We want to know EoR much more
We should observe IGM at the EoR directly !
(ex)
•EoR theory
•Morphology and topology of ionized bubble
•Ionizing sources
•Relation to galaxy formation and evolution
etc…
✕
Synergy with galaxy observation by ALMA, JWST, Subaru

26. Basics of 21cm line

27. 21cm line
•21cm line radiation : Neutral hydrogen atom in IGM emits the
radiation due to the hyperfine structure.
z=6 → 1.5m or 202 MHz
z=20 → 4.4m or 68MHz
Radio wavelength.
We have yet to observe 21cm signal at EoR and cosmic dawn!
We can map neutral hydrogen atom in the IGM.
However…

28. 21cm line
•21cm line radiation : Neutral hydrogen atom in IGM emits the
radiation due to the hyperfine structure.
z=6 → 1.5m or 202 MHz
z=20 → 4.4m or 68MHz
Radio wavelength.
We have yet to observe 21cm signal at EoR and cosmic dawn!
We can map neutral hydrogen atom in the IGM.
However…
We have not observed 21cm line at
high redshift yet !

29. Spin temperature
n""
n"#
= 3 exp
✓
h⌫21cm
kTS
◆
Key quantity in 21cm line physics
T 1
S =
T 1
CMB + xcT 1
K + x↵T 1
c
1 + xc + x↵
Spin temperature is determined by
•interaction with CMB photons
•collision with hydrogen atoms
•interaction with Ly-alpha photons
(TCMB)
(TK, xc)
(Tc ⇠ TK, x↵)
Properties of X-ray sources (e.g.
spectral energy distribution (SED))
Relevant astrophysics
Properties of first stars (e.g.
Initial mass function)

30. Mesinger et al 2010
heating
WF effect
Wouthuysen-Field(WF) effect
Spin temperature couples to
IGM kinetic temperature via
Ly-alpha photons from first
stars.
Thermal history
X-ray heating
X-ray photons drastically heat
kinetic temperature of the IGM
Spin temperature
Kinetic temperature
CMB temperature

31. Wouthuysen Field (WF)effect
•The spin temperature couples Lyman-alpha color temperature (and also kinetic
temperature) (Wouthuysen 1952,Field 1959).
•The hyperfine state is changed through 2P state by Lyman-alpha photons (121.6nm)
Solid lines : allowed path
Dashed lines : not allowed path
•Lyman alpha photon is emitted from first stars

32. 21cm line signal
Red : cosmology Blue : astrophysics
Global signal has characteristic peaks
and troughs according to key epochs
Tb =
TS T
1 + z
(1 exp(⌧⌫))
⇠ 27xH(1 + m)
✓
H
dvr/dr + H
◆ ✓
1
T
TS
◆ ✓
1 + z
10
0.15
⌦mh2
◆1/2 ✓
⌦bh2
0.023
◆
[mK]
Brightness temperature
Global signal (sky averaged brightness temperature)
*We actually observe brightness temperature

33. Images by 21cm line
Mellema et al (2013)
We can see how ionised regions are distributed by 21cm image.
xi = 0.8
xi = 0.5
Ionised regions
However, it is difficult to observe 21cm image by current observations due to specification…

34. 21cm power spectrum (PS) :
Scale dependence
Pober et al (2014)
EoR
X-ray
heating
WF
effect
z
Redshift dependence
21cm power spectrum
h Tb(k) Tb(k
0
)i = (2⇡)3
(k + k
0
)P21
We first try to detect the 21cm line signal statistically with ongoing telescopes.

35. Current 21cm cosmology
status and future project

36. 1. Theoretical studies

37. 21cm statistical approaches
Greig & Mesinger (2016), Park et al (2018)
•EoR parameter estimation with Bayesian
statistics
•21cm signal analysis with machine learning
Shimabukuro & Semelin (2017), Schmit et al (2018)
•21cm higher order statistics
(bispectrum, skewness)
Shimabukuro et al (2015,2016,2017), Yoshiura et al (2015)
Watkinson et al (2017), Majumadar et al (2018)
Constraints on EoR models
Park et al 2018
Shimabukuro & Semelin (2017)

38. Morphology of ionized bubble
•Minkowski functionals
•Betti number
•Granulometry
Gleser et al (2006),Lee et al (2008), Friedrich et
al (2011),Hong et al (2014),Yoshiura et al (2017)
Giri et al (2021), Kapahtia et al (2021)
Kakiichi et al (2017)
Gleser et al (2006)
Giri et al (2021)
Evaluate ionized bubble topologically and morphologically
•Artificial neural network
Shimabukuro & Semelin al (2020),Yoshiura et
al (2021)

39. First luminous object & EoR
•21cm line signal from first stars
Yajima & Li (2013),Tanaka et al (2018)
•Galaxy formation & EoR
Yajima & Li (2013)
Yajima & Li (2013)
Hasegawa & Semelin (2013), Hutter et al (2020)
How do first luminous objects affect EoR?

40. Synergy between 21cm & other lines
Kubota et al (2018)
•21cm line and Lyman-alpha galaxies
Yoshiura et al (2018), Kubota et al (2018)
Moriwaki et al (2019)
Yoshiura et al (2019)
Cross-correlation between 21cm line and other lines. Reducing systematic errors
Ma et al (2018)
Yoshiura et al (2019)
•21cm line and[OIII] galaxies
•21cm line and CMB
•21cm line and X-ray background

41. 21cm absorption lines (21cm forest)
•Dark matter, inflation and other cosmology
Shimabukuro et al (2014,2019,2020a), Villanueva &
Ichiki (2021), Kawasaki et al (2020)
21cm forest is powerful tool for EoR, cosmology and galaxy formation
•Thermal state of the IGM
Furlanetto & Loeb (2002), Ciardi et al (2015),
Semelin (2015)
•Galaxy formation
Xu et al (2011), Aditya et al (2021)

42. 2. Observational status

43. Current 21cm experiments
MWA LOFAR HERA
GMRT
Radio interferometer
•Array of radio telescope
antennas
•Measure time delay
between antennas
•Work together as a single
telescope

44. Current upper limits on 21cm PS
HERA collaboration 2019
Current 21cm experiments put upper limit of the 21cm line power spectrum 2-3 order
of magnitude higher than theoretical expectation.
Challenges: ionosphere, RFI, foreground, etc

45. EDGES (Bouman et al 2018)
Too deep trough
Too flat
We detected the 21cm line signal?
Very strange result ! Need exotic physics?
mis-calibration? unknown systematics?

46. Did we detect the 21cm global signal ?
EDGES (Bouman et al 2018)
Too deep trough
Too flat
We detected the 21cm line signal?
Very strange result ! Need exotic physics?
mis-calibration? unknown systematics?

48. 2021/6/29

49. 2021/6/29

50. 2021/6/29

51. SKA-Low
•Frequency 50-350MHz(z=3~27)
•Resolution : ~3.3-23 arcsec
•FoV :~ tens -a few hundreds of square degree
•Effective collecting area : ~300’000 m2
•China is a membership of SKA
High resolution
&
High sensitivity
Wide FoV
&

52. Images by 21cm line
Mellema et al (2013)
•~ a few arc-minutes resolution •~ a few degree FoV
(Minimum) required specification for imaging
xi = 0.8
xi = 0.5
•Enough sensitivity

53. Images by 21cm line
Mellema et al (2013)
•~ a few arc-minutes resolution •~ a few degree FoV
(Minimum) required specification for imaging
xi = 0.8
xi = 0.5
SKA can do !
•Enough sensitivity

54. My works

55. What I have done so far
•Cosmology at small scales with 21cm forest (Warm dark
matter, axion dark matter and so on)
[Shimabukuro et al.(2014), Shimabukuro, Ichiki & Kadota
(2020a,2020c)]
•21cm statistics (bispectrum, one point statistics)
[Shimabukuro et al.(2015), (2016), (2017a)]
•21cm signal analysis with artificial neural network (ANN)
[Shimabukuro & Semelin (2017b), Shimabukuro, Mao & Tan
(2020b)]

56. What I have done so far
•Cosmology at small scales with 21cm forest (Warm dark
matter, axion dark matter and so on)
[Shimabukuro et al.(2014), Shimabukuro, Ichiki & Kadota
(2020a,2020c)]
•21cm statistics (bispectrum, one point statistics)
[Shimabukuro et al.(2015), (2016), (2017a)]
•21cm signal analysis with artificial neural network (ANN)
[Shimabukuro & Semelin (2017b), Shimabukuro, Mao & Tan
(2020b)]

57. What I have done so far
•Cosmology at small scales with 21cm forest (Warm dark
matter, axion dark matter and so on)
[Shimabukuro et al.(2014), Shimabukuro, Ichiki & Kadota
(2020a,2020c)]
•21cm statistics (bispectrum, one point statistics)
[Shimabukuro et al.(2015), (2016), (2017a)]
•21cm signal analysis with artificial neural network (ANN)
[Shimabukuro & Semelin (2017b), Shimabukuro, Mao & Tan
(2020b)]

58. We want to know EoR much more
We should observe IGM at the EoR directly !
(ex)
•EoR theory
•Morphology and topology of ionized bubble
•Ionizing sources
•Relation to galaxy formation and evolution
etc…
✕
Synergy with galaxy observation by ALMA, JWST, Subaru

59. We want to know EoR much more
We should observe IGM at the EoR directly !
(ex)
•EoR theory
•Morphology and topology of ionized bubble
•Ionizing sources
•Relation to galaxy formation and evolution
etc…
✕
Synergy with galaxy observation by ALMA, JWST, Subaru

60. 21cm signal analysis with
machine learning

61. 1.EoR parameter estimation
with ANN

62. Statistical challenge in 21cm cosmology
(Mesinger 2018)
Cosmology
CMB map (angular) power spectrum cosmological parameter
21cm
21cm 3D map 21cm power spectrum astrophysical parameter
Based on Bayesian inference

63. Statistical challenge in 21cm cosmology
(Mesinger 2018)
Cosmology
CMB map (angular) power spectrum cosmological parameter
21cm
21cm 3D map 21cm power spectrum astrophysical parameter
Based on Bayesian inference
We proposed alternative method.

64. Artificial Neural Network (ANN)
An ANN is a mathematical
model of human brain network.
ex.) Rumelhart et. al (1986)
LeCun et. al (1989)
Recently, it has been applied to
field of astronomy.

65. Artificial Neural Network (ANN)
•Training network with training
dataset, ANN can approximate any
function which associates input and
output values.
y = f(x)
• Applying trained network to unknown
data for prediction.
yANN = f(xtest)
• ANN consists of input layer, hidden
layer and output layer. Each layer has
neurons.
Regression Problem

66. Dataset
⇣ : the ionizing efficiency.
: the minimum viral temperature of halos producing ionizing
photons
: the mean free path of ionizing photons through the IGM
(Maximum HII bubble size)
Tvir
Rmfp
~
d = [P(k), ~
✓]
21cm power spectrum (input)
EoR parameter (output)
EoR Parameter
✓EoR = f(P21)

67. z=11, PS without any noise
Reconstructed by 21cmPS at z=11
10
20
30
40
50
60
10 20 30 40 50 60
R
mfp,ANN
[Mpc]
Rmfp,true[Mpc]
z=12
10
20
30
40
50
60
10 20 30 40 50 60
ANN
true
z=12
1
10
100
1 10 100
T
vir,ANN
[K/10
3
]
Tvir,true[K/103
]
z=12
14 neurons, 100’000 iterations
• True value .vs. Reconstructed value
•The scatter of is large.
Rmfp ⇣
Tvir
•Other reconstructed parameters match
true one relatively well.
Shimabukuro &
Semelin (2017)
Rmfp

68. z=11, PS without any noise
Reconstructed by 21cmPS at z=11
10
20
30
40
50
60
10 20 30 40 50 60
R
mfp,ANN
[Mpc]
Rmfp,true[Mpc]
z=12
10
20
30
40
50
60
10 20 30 40 50 60
ANN
true
z=12
1
10
100
1 10 100
T
vir,ANN
[K/10
3
]
Tvir,true[K/103
]
z=12
14 neurons, 100’000 iterations
• True value .vs. Reconstructed value
•The scatter of is large.
Rmfp ⇣
Tvir
•Other reconstructed parameters match
true one relatively well.
Shimabukuro &
Semelin (2017)
Rmfp

69. z=9, 10, 11. PS with thermal noise and cosmic variance
Reconstructed by 21cm PS at z=9,10,11
Rmfp ⇣
Tvir
10
20
30
40
50
60
10 20 30 40 50 60
R
mfp,ANN
[Mpc]
Rmfp,true[Mpc]
10
20
30
40
50
60
10 20 30 40 50 60
ANN
true
1
10
100
1 10 100
T
vir,ANN
[K/10
3
]
Tvir,true[K/10
3
]
Red : z=9,10,11
Blue : z=9
The parameters obtained by the ANN
match true values. ANN work well !

70. 2.Recovering HII bubble size
distribution with ANN

71. Bubble size distribution (BSD)
''How large bubbles are distributed ?’'
Giri 2019
What can we learn from BSD?
Giri et al 2017
•EoR source (galaxy or AGN?)
•ionizing efficiency, recombination, radiative feedback.
(ex.)

72. BSD from 21cm observation
Kakiichi et al 2017
IFT
21cm Image BSD
Incomplete IFT due to limited number of antenna in interferometer.
visibility
We do not observe 21cm image directly by radio interferometer!
We first observe visibility and perform Inverse Fourier
Transformation (IFT) to obtain 21cm image. Then, compute BSD.

73. BSD from 21cm PS
Kakiichi et al 2017
21cm power spectrum BSD
visibility
We can directly compute 21cm power spectrum from visibility
without Inverse Fourier Transformation.
Avoid information loss by incomplete IFT.

74. BSD from 21cm PS
Kakiichi et al 2017
21cm power spectrum BSD
visibility
We can directly compute 21cm power spectrum from visibility
without Inverse Fourier Transformation.
Can we recover BSD from 21cm PS ?
Avoid information loss by incomplete IFT.

75. 21cm power
spectrum
Input Output
ionised bubble size
distribution
Our datasets consist of 21cm power spectrum as input data and bubble
size distribution as output data.
Our strategy
We try to recover ionised bubble size distribution from 21cm PS

76. Recovered BSD
Black: Distribution obtained
by 21cm 3D image directly.
Red: Distribution obtained
by ANN.
xHI = 0.39

77. Different stage of reionization

78. Effect of thermal noise
21cm PS with thermal
noises (SKA level)
Errors are estimated
by 10 realizations
thermal noises
xHI = 0.39

79. Challenging issue

80. Foreground problem
Jelic et al 2008
The 21cm signal is buried under strong foreground !
Remove foreground ?
or
Avoid (strong)foreground?
Santos 2005
~8 order
Dillon et al 2013

81. Take home messages of my talk are…

82. Take home messages of my talk are…
•The epoch from the Dark Ages to cosmic reionization is the
frontier in the history of the universe.

83. Take home messages of my talk are…
•The epoch from the Dark Ages to cosmic reionization is the
frontier in the history of the universe.
•21cm signal is a promising tool to study this epoch.

84. Take home messages of my talk are…
•The epoch from the Dark Ages to cosmic reionization is the
frontier in the history of the universe.
•21cm signal is a promising tool to study this epoch.
•SKA will bring us fruitful information on the epoch
through Dark Ages to EoR

85. Take home messages of my talk are…
•The epoch from the Dark Ages to cosmic reionization is the
frontier in the history of the universe.
•21cm signal is a promising tool to study this epoch.
•SKA will bring us fruitful information on the epoch
through Dark Ages to EoR
•We proposed a method based on machine learning to
analyze the 21cm line signal.

86. •"21cm cosmology" (Prithcard & Loeb, astro-ph/1109.6012)
Textbook
Review paper
•"Cosmology at low frequencies" (Furlanetto et al, astro-ph/0608032)
•''In the beginning : the first sources of light and the deionization of the
universe” R,Bakana & A,Loeb (astro-ph/0010468)
References

87. bakcup

88. Accuracy for all test data
Relative error between two size
distributions at fixed bubble
radius for all test data.
Good recovery for all test data.

89. n""
n"#
= 3 exp
✓
h⌫21cm
kTS
◆
The spin temperature is determined by following equilibrium
T 1
S =
T 1
CMB + xcT 1
K + x↵T 1
c
1 + xc + x↵
de-excitation rate by collision
de-excitation rate by UV
photons
excitation rate by UV
photons
excitation rate by collision
Stimulated by CMB photons
Spontaneous de-
excitation with Einstein
coefficient

90. Wouthuysen Field (WF)effect
•The mechanism that couples the spin
temperature of neutral hydrogen atom to
Lyman-alpha photons(Wouthuysen
1952,Field 1959)
•The hyperfine state is changed via 2P state
Solid lines : allowed path
Dashed lines : not allowed path

91. 21cm PS with SKA
SKA covers wide epoch and range of the 21cm PS !!
Redshift evolution Scale dependence
z=8.95
z=15.98
Koopmans et al. (2014)
Pritchard et al. (2014)

92. • 1000 EoR models
• 48000 training datasets (20% of which is used for validation)
• 2000 test datasets
• 21cm PS is ranged from k=0.11/Mpc to 1.1/Mpc with 14 bins
• 5 hidden layers
• 212 neurons at each hidden layer
• 2000 iterations
Setup

93. Evaluate accuracy: noise
We evaluate accuracy of obtained parameters by chi-square. Smaller
chi-square means better accuracy.
single z
As expected, accuracy becomes worse if we add noise to 21cm
power spectrum.
without noise with noise

94. Evaluate accuracy: redshift
We evaluate accuracy of obtained parameters by chi-square. Smaller
chi-square means better accuracy.
multiple z
The accuracy of parameter estimation is improved when we
consider redshift evolution of 21cm power spectrum.
Single z
Both include noise

95. (Ex.) Emulator
EoR parameters 21cmPS
ANN MCMC
Before : 2.5days on 6 cores
After: 4minutes
speed up by 3 orders of magnitude
(Schmit et al 2018)
(input) (output)