21-cm signature of the first sources in the Universe : prospects of detection with SKA
Raghunath Ghara
NCRA-TIFR [email protected]
February 12, 2016
Raghunath Ghara (NCRA-TIFR) Detecting early sources February 12, 2016 1 / 23
Plan of the talk
Efforts to detect and understand the early sources : 21-cm signal, JWST, TMT..
21-cm observation of the reionization :
Evolution of the global 21-cm signal, power spectrum, rms etc.. Detection of ionized bubble,isolated sourcein visibilityand image base techniques.
Plan of the talk
Efforts to detect and understand the early sources : 21-cm signal, JWST, TMT..
21-cm observation of the reionization :
Evolution of the global 21-cm signal, power spectrum, rms etc.. Detection of ionized bubble,isolated sourcein visibilityand image base techniques.
Raghunath Ghara (NCRA-TIFR) Detecting early sources February 12, 2016 2 / 23
Plan of the talk
Efforts to detect and understand the early sources : 21-cm signal, JWST, TMT..
21-cm observation of the reionization :
Evolution of the global 21-cm signal, power spectrum, rms etc.. Detection of ionized bubble,isolated sourcein visibilityand image base techniques.
Plan of the talk
Efforts to detect and understand the early sources : 21-cm signal, JWST, TMT..
21-cm observation of the reionization :
Evolution of the global 21-cm signal, power spectrum, rms etc..
Detection of ionized bubble,isolated sourcein visibilityand image base techniques.
Raghunath Ghara (NCRA-TIFR) Detecting early sources February 12, 2016 2 / 23
Motivation
Can we detect the first sources with radio interferometers like the SKA1-low? What informations can be obtained from that?
IGM properties: Neutral fraction Kinetic temperature Source properties:
Mass of the source Age
Escape fraction of UV photonsfesc
UV and X-ray luminosity etc..
Motivation
Can we detect the first sources with radio interferometers like the SKA1-low? What informations can be obtained from that?
IGM properties:
Neutral fraction Kinetic temperature Source properties:
Mass of the source Age
Escape fraction of UV photonsfesc
UV and X-ray luminosity etc..
Raghunath Ghara (NCRA-TIFR) Detecting early sources February 12, 2016 3 / 23
Possible sources: popIII stars, Galaxies, mini-QSO, HMXBs..
1022 1024 1026 1028
101 102 103
Lν (erg/s/Hz)
λ (Å) PopIII
Galaxy Mini−QSO HMXBs
HI Lyα
HeI
HeII100 eV
M? = 103 M for popIII
= 107 M for others.
Spectral indexα= 1.5 Ratio of X-ray and UV luminosity fX = 0.05 fesc = 0.1
tage = 20Myr
The stellar part of the source is generated using PEGASE code : Salpeter IMF with 1-100M population II stars, metallicity 0.001Z. Mini-QSO : Iq ∝E−α , PopIII : black-body spectrum, HMXBs : absorption of soft-X-rays in ISM (Fragos et al 2013)
Possible sources: popIII stars, Galaxies, mini-QSO, HMXBs..
1022 1024 1026 1028
101 102 103
Lν (erg/s/Hz)
λ (Å) PopIII
Galaxy Mini−QSO HMXBs
HI Lyα
HeI
HeII100 eV
M? = 103 M for popIII
= 107 M for others.
Spectral indexα= 1.5 Ratio of X-ray and UV luminosity fX = 0.05 fesc = 0.1
tage = 20Myr The stellar part of the source is generated using PEGASE code : Salpeter IMF with 1-100M population II stars, metallicity 0.001Z. Mini-QSO : Iq ∝E−α , PopIII : black-body spectrum, HMXBs : absorption of soft-X-rays in ISM (Fragos et al 2013)
Raghunath Ghara (NCRA-TIFR) Detecting early sources February 12, 2016 4 / 23
Simple Model
Rectangular simulation box.
Length of the box along the frequency direction is determined by the
observational band width.
We assume that the source is at the center of the simulation Box.
Simple Model
Solve 1-D radiative transfer equations, generate xHI andTK profiles.
Assume Lyα photon flux reduces as 1/R2 with radial distanceR.
Calculate the coupling coefficients and spin temperature (TS) profile.
1-D δTb profile used to generate δTb map in the simulation box.
Raghunath Ghara (NCRA-TIFR) Detecting early sources February 12, 2016 6 / 23
Signal
Differential brightness temperature :
δTb(~θ, ν)∼27×xHI(x,z) [1+δB(x,z)]
1 +z 10
1/2
1− Tγ(z) TS(x,z)
mK, (1)
Neutral fraction of hydrogen
Spin temperature (depend on CMBR, Collisional, Lyα coupling and TK )
δT
bprofiles
1022 1024 1026 1028
101 102 103
Lν (erg/s/Hz)
λ (Å) PopIII
Galaxy Mini−QSO HMXBs
HI Lyα
HeI
HeII100 eV
−300
−250
−200
−150
−100
−50 0 50
10−1 100 101 102
δTb (mK)
R (cMpc) PopIII Galaxy Mini−QSO HMXBs
Signals are different around different type of sources. Redshift = 15
δTb pattern around a source :
Hii region at the center (δTb= 0), Emission region (δTb>0),
Absorption region (δTb<0), Signal vanishes at far away region.
Raghunath Ghara (NCRA-TIFR) Detecting early sources February 12, 2016 8 / 23
δT
bprofiles
1022 1024 1026 1028
101 102 103
Lν (erg/s/Hz)
λ (Å) PopIII
Galaxy Mini−QSO HMXBs
HI Lyα
HeI
HeII100 eV
−200
−150
−100
−50 0 50
10−1 100 101 102
δTb (mK)
R (cMpc) Mini−QSO
Signals are different around different type of sources. Redshift = 15 δTb pattern around a source :
Hii region at the center (δTb= 0), Emission region (δTb>0),
Absorption region (δTb<0),
Visibility
Differential brightness temperature :
δTb(~θ, ν)∼27xHI(x,z) [1+δB(x,z)]
1 +z 10
1/2
1− Tγ(z) TS(x,z)
mK,
Direct measurable quantity is visibility.
V(U~, ν) = Z
d2θ Iν(~θ) A(~θ) ei2π~θ·U~, (2)
Sky specific intensity : Iν(~θ) = 2kcB2ν2δTb(~θ, ν)
Primary beam pattern
Raghunath Ghara (NCRA-TIFR) Detecting early sources February 12, 2016 9 / 23
Signal Visibility
−300
−250
−200
−150
−100
−50 0 50
10−1 100 101 102
δTb (mK)
R (cMpc) PopIII Galaxy Mini−QSO HMXBs
10−6 10−4 10−2 100
10 100 1000
|S(U, νc)| mJy
U PopIII
Galaxy Mini−QSO HMXBs
Redshift = 15.
M? = 103 M for popIII
= 107 M for others.
α= 1.5,fX = 0.05 ,fesc= 0.1,tage = 20Myr, density contrastδ= 0
Noise
Signal with system noise and foregrounds.
V(U~, ν) =S(U~, ν) +N(U, ν~ ) +F(U~, ν), (3) S(U~, ν) is the 21-cm signal visibility
N(U~, ν) is the system noise F(U~, ν) foreground contributions
The system noise at different baselines and frequency channels are expected to be Gaussian random variables with zero mean.
rms noise :
q
hN2i=
√
2kBTsys
Aeff√
∆νc ∆tc, (4)
rms noise can be reduced over long observation time tobs (by a factor of p
∆tc/tobs).
Raghunath Ghara (NCRA-TIFR) Detecting early sources February 12, 2016 11 / 23
Noise
Signal with system noise and foregrounds.
V(U~, ν) =S(U~, ν) +N(U, ν~ ) +F(U~, ν), (3) S(U~, ν) is the 21-cm signal visibility
N(U~, ν) is the system noise F(U~, ν) foreground contributions
The system noise at different baselines and frequency channels are expected to be Gaussian random variables with zero mean.
rms noise :
q
hN2i=
√
2kBTsys
Aeff√
∆νc ∆tc, (4)
rms noise can be reduced over long observation time tobs (by a factor of p
∆tc/tobs).
Baseline distribution
10−7 10−5 10−3 10−1 101
102 103
nB(U, ν)
U ν = 90 MHz
SKA1−low MWA GMRT LOFAR
10−1 100 101 102
102 103
σ(U, ν) mJy
U
BaselineU =dant/λ. dant is the distance between the antenna pair andλobservational wavelength.
nB(U, ν) is the number of antenna pairs having same baselineU at frequency ν.
rms noise can be further reduced by a factor of 1/p
2πnB(U, ν)U∆U
Raghunath Ghara (NCRA-TIFR) Detecting early sources February 12, 2016 12 / 23
Visibilities
−300
−250
−200
−150
−100
−50 0 50
10−1 100 101 102
δTb (mK)
R (cMpc) PopIII Galaxy Mini−QSO HMXBs
10−4 10−2 100
10 100 1000
|S(U, νc)| mJy
U
SKA1−low
PopIII Galaxy Mini−QSO HMXBs
Redshift = 15, νc = 90 MHz,Bν = 16 MHz, ∆νc = 50 kHz, tobs = 1000 h.
Signal is detectable at the low baselines for the fiducial galaxy, mini-QSO and HMXBs.
Visibilities : mini-QSO
10−5 10−2 101
10 100 1000
|S(U, νc)| mJy
U
SKA1−low
106 MO· 107 MO· 108 MO· 109 MO·
10−5 10−2 101
10 100 1000
|S(U, νc)| mJy
U
SKA1−low
fX=0.05, α=1.5 fX=0.10, α=1.5 fX=0.05, α=0.5
Redshift = 15, νc = 90 MHz,Bν = 16 MHz, ∆νc = 50 kHz, tobs = 1000 h.
Position of the first zero crossing shift towards lower baselines as mass increases.
Visibilities at low baselines are insensitive to fX andα.
Raghunath Ghara (NCRA-TIFR) Detecting early sources February 12, 2016 14 / 23
Visibilities : mini-QSO
0 0.1 0.2 0.3 0.4 0.5
−8 −6 −4 −2 0 2 4 6 8 |S(U, νc)| mJy
∆ν (MHz)
U = 10 U = 50 U = 100 NS
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
−8 −6 −4 −2 0 2 4 6 8 |S(U, νc)| mJy
∆ν (MHz) U = 10 20 Myr1 Myr
100 Myr NS
Redshift = 15, νc = 90 MHz,Bν = 16 MHz, ∆νc = 50 kHz, tobs = 1000 h.
Visibility peaks at the central frequency channel at the position of the centre of the source.
Signal to noise ratio
SNR :
SNR= 1 σN
R d2UR
dν nB(U, ν) S(U, ν~ ) R d2UR
dν nB(U, ν) , (5) where
σN =
√
2kBTsys
Aeff
ptobs Bν Nant(Nant−1)/2. (6)
10−5 10−3 10−1 101
10 100 1000
|S(U, νc)| mJy
U
SKA1−low
Mini−QSO
Raghunath Ghara (NCRA-TIFR) Detecting early sources February 12, 2016 16 / 23
SNR
20 40 60 80 100 120 140 160 180 200
6 7 8 9
SNR
log (M★/MO· ) 2 3 4 5 6 7 8 9 10
0 0.2 0.4 0.6 0.8 1 fesc
8.6 8.8 9 9.2 9.4
0 0.05 0.1
fX
8 8.5 9 9.5 10 10.5 11 11.5 12
0.5 1 1.5 2
SNR
2 4 6 8 10 12
20 40 60 80 100 5 10 15 20 25 30 35 40 45 50
10 15 20
Fiducial mini-QSO : SNR ∼9 for tabs = 1000 h, ∆ν = 50 kHz.
SNR depend on the source properties, in particular on the mass and age of the source and the escape fraction of ionizing photons.
SNR weakly depend on the X-ray properties.
SNR decrease with increasing redshift.
Overlap between sources
10−3 10−2 10−1 100
100 1000
|S(U, νc)| mJy
U Overlapped Massive−halo Isolated Analytical
Noise 10−1
100 101
−10 −5 0 5 10
|S(U=20, ν)| mJy
∆ν (MHz)
Overlapped: Minimum halo mass∼4×109 M. Massive-halo: Minimum halo mass∼2×1010 M. Isolated: Single source at the center of FOV.
We ensure that the maximum source mass in the box is 107 M and the source is at the center of the FOV.
Raghunath Ghara (NCRA-TIFR) Detecting early sources February 12, 2016 18 / 23
Foregrounds
10−4 10−2 100 102 104 106
10 100 1000
|V(U, νc)| mJy
U Signal
NS FG
10−4 10−2 100 102 104 106
−8 −6 −4 −2 0 2 4 6 8
|V(U=10, ν)| mJy
ν (MHz)
Foregrounds contribution is very large compared to the signal and the system noise.
Foregrounds : Galactic synchrotron radiation.
One can try to remove the foregrounds from the total signal by
Using a filter
Signal estimator:
DEˆ E
= Z
d2U Z
dν S(U, ν~ )Sf?(~U, ν) nB(U, ν~ ) (7) Noise :
D
(∆ ˆE)2E
NS=ANS Z
d2U Z
dν |Sf(U~, ν)|2 nB(U~, ν) (8) where,
ANS= DNˆ2
E 2 Nant(Nant−1)
∆νc
Bν
(9) Foregrounds : (Datta et al 2007)
D
(∆ ˆE)2E
FG= Z
d2U Z
dν1 Z
dν2 2KB
c2 2
(ν1ν2)2
×nB(U, ν~ 1) nB(U~, ν2) C2πU(ν1, ν2)
×Sf?(U~, ν1)Sf(~U, ν2) (10)
Raghunath Ghara (NCRA-TIFR) Detecting early sources February 12, 2016 20 / 23
Using a filter
−15
−10
−5 0 5
−8 −6 −4 −2 0 2 4 6 8 sT (µJy)
ν(MHz) Bf
10−5 10−4 10−3 10−2
0 0.5 1 1.5 2
<E>
Bf (MHz) Signal
NS
FG 34
5 6 7 8 9 10 11
0 0.5 1 1.5 2
2 11 22 33 44
SNRE
Bf (MHz) r (cMpc)
Filter :
Sf(U, ν~ ) = ν
νc
2
[ST(U~, ν,Bf)−Θ(1− |ν−νc|/B0) B0
×
Z νc+B0/2
ν −B0/2
ST(U~, ν0,Bf) dν0] (11)
Conclusions
We investigate the detectability of early sources like popIII stars, mini- QSO, galaxy and HMXBs, by comparing the 21-cm visibility signal with the system noise appropriate for a telescope like the SKA1-low.
Upon integrating the visibility around a typical source over all
baselines and over a frequency interval of 16 MHz, we find that it will be possible make a ∼9σ detection of the isolated sources like PopII galaxies, mini-QSOs and HMXBs at z ∼15 with the SKA1-low in 1000 hours.
The exact value of the signal to noise ratio (SNR) will depend on the source properties, in particular on the mass and age of the source and the escape fraction of ionizing photons.
The predicted SNR decreases with increasing redshift.
We can use filters to detect the sources while the signal is much weaker than the system noise and foregrounds.
Thank you
Raghunath Ghara (NCRA-TIFR) Detecting early sources February 12, 2016 22 / 23
Conclusions
We investigate the detectability of early sources like popIII stars, mini- QSO, galaxy and HMXBs, by comparing the 21-cm visibility signal with the system noise appropriate for a telescope like the SKA1-low.
Upon integrating the visibility around a typical source over all
baselines and over a frequency interval of 16 MHz, we find that it will be possible make a ∼9σ detection of the isolated sources like PopII galaxies, mini-QSOs and HMXBs at z ∼15 with the SKA1-low in 1000 hours.
The exact value of the signal to noise ratio (SNR) will depend on the source properties, in particular on the mass and age of the source and the escape fraction of ionizing photons.
The predicted SNR decreases with increasing redshift.
We can use filters to detect the sources while the signal is much weaker than the system noise and foregrounds.
Thank you
Including the light-cone effect
10−3 10−2 10−1 100
100 1000
|S(U, νc)| mJy
U Overlapped Massive−halo Isolated Analytical
Noise 10−1
100 101
−10 −5 0 5 10
|S(U, νc)| mJy
∆ν (MHz)
Raghunath Ghara (NCRA-TIFR) Detecting early sources February 12, 2016 23 / 23