Title: NonGaussian signatures in cosmic shear fields
1Non-Gaussian signatures in cosmic shear fields
Masahiro Takada (Tohoku U., Japan)
Based on collaboration with Bhuvnesh Jain
(Penn) (MT Jain 04, MT Jain 07 in prep.)
Sarah Bridle (UCL) (MT Bridle 07,
astro-ph/0705.0163) Also see the poster of
Nobuhiro Okabe (Tohoku) for the observational
results for cluster lensing using Subaru data
July 6th 07 _at_ IAP
2Outline of this talk
- What is cosmic shear tomography?
- Non-Gaussian errors of cosmic shear fields and
the higher-order moments - Parameter forecast including non-Gaussian errors
- Combining WLT and cluster counts
- Summary
3Cosmological weak lensing cosmic shear
- Arises from total matter clustering
- Not affected by galaxy bias uncertainty
- well modeled based on simulations (current
accuracy, lt10 White Vale 04) - A level effect needs numerous (108) galaxies
for the precise measurements
zzs
past
zzl
observables
Large-scale structure
z0
present
4Weak Lensing Tomography
(e.g., Hu 99, 02, Huterer 01, MT Jain 04)
- Subdivide source galaxies into several bins based
on photo-z derived from multi-colors (e.g.,
Massey etal07) - ltzigt in each bin needs accuracy of 0.1
- Adds some depth information to lensing
improve cosmological paras (including DE)
?m(z)
5Tomographic Lensing Power Spectrum
- Tomography allows to extract redshift evolution
of the lensing power spectrum. - A maximum multipole used should be like
l_maxlt3,000
6Tomographic Lensing Power Spectrum (contd.)
- Lensing PS has a less feature shape, not like CMB
- Cant better constrain inflation parameters (n_s
and alpha_s) than CMB - Need to use the lensing power spectrum amplitudes
to do cosmology the amplitude is sensitive to
A_s, ?de0 (or ?m0), w(z).
7Lenisng tomography (condt.)
- WLT can be a powerful probe of DE energy density
and its redshift evolution. - Need 3 z-bins at least, if we want to constrain
DE model with 3 parameters (?_de,w0, wa) - Less improvement using more than 4 z-bins, for
the 3 parameter DE model
8Non-linear clustering
- Most of WL signal is from small angular scales,
where the non-linear clustering boosts the
lensing signals by an order of magnitude (Jain
Seljak97). - Large-scale structures in the non-linear stage
are non-Gaussian by nature. - 2pt information is not sufficient higher-order
correlations need to be included to extract all
the cosmological information - Baryonic physics lgt103
Non-linear clustering
l_max3000
9Non-Gaussianity induced by structure formation
- Linear regime O(?)ltlt1 all the Fourier modes of
the perturbations grow at the same rate the
growth rate D(z) - The linear theory, based on FRW GR, gives
robust, secure predictions - Mildly non-linear regime O(?)1 a mode coupling
between different Fourier modes is induced - The perturbation theory gives the specific
predictions for a CDM model - Highly non-linear regime a more complicated mode
coupling - N-body simulation based predictions are needed
(e.g., halo model)
- Correlations btw density perturbations of
different scales arise as a consequence of
non-linear structure formation, originating from
the initial Gaussian fields - However, the non-Gaussianity is fairly accurately
predictable based on the CDM model
10Aspects of non-Gaussianity in cosmic shear
- Errors in cosmic shear are non-Gaussian
- Including non-Gaussian errors degrade the
cosmological constraints? - Realize more realistic ability to constrain
cosmological parameters - The dependences for survey parameters (e.g.,
shallow survey vs. deep survey) - Yet, adding the NG information, e.g. carried by
the bispectrum, is useful?
11Covariance matrix of PS measurement
(MT Jain 07 in prep.)
- Most of lensing signals are from non-linear
scales the errors are non-Gaussian - PS covariance describes correlation between the
two spectra of multipoles l1 and l2 (Cooray Hu
01), providing a more realistic estimate of the
measurement errors - The non-Gaussian errors for PS arise from the
4-pt function of mass fluctuations in LSS
l1
l1
12Correlation coefficients of PS cov. matrix
w/o shot noise
- Diagonal Gaussian Off-diagonal NG, 4-pt
function - 30 bins 50ltllt3000
- If significant correlations, r_ij?1
- The NG is stronger at smaller angular scales
- The shot noise only contributes to the Gaussian
(diagonal) terms, suppressing significance of the
NG errors
with shot noise
13Correlations btw Cls at different ls
- Principal component decomposition of the PS
covariance matrix
14Power spectrum with NG errors
- The band powers btw different ells are highly
correlated (also see Kilbinger Schneider 05) - NG increases the errors by up to a factor of 2
over a range of l1000 - elllt100, gt104, the errors are close to the
Gaussian cases
15Signal-to-noise ratio SNR
- Data vector power spectra binned in multipole
range, l_minltlltl_max, (and redshifts) - In the presence of the non-Gaussian errors, the
signal-to-noise ratio for a power spectrum
measurement is - For a larger area survey (f_sky ) or a deeper
survey (n_g ), the covariance matrix gets
smaller, so the signal-to-noise ratio gets
increased S/N
16Signal-to-ratio SNR(contd.)
Gaussian
- Multipole range 50ltlltl_max
- Non-gaussian errors degrade S/N by a factor of 2
- This means that the cosmic shear fields are
highly non-Gaussian (Cooray Hu 01 Kilbinger
Schneider 05)
Non-Gaussian
50ltlltl_max
17The impact on cosmo para errors
- We are working in a multi-dimensional parameter
space (e.g. 7D)
error ellipse
?_de
w_0
w_a
n_s
.
- Volume of the ellipse VNG?2VG
- Marginalized error on each parameter ? length of
the principal axis ?NG2(1/Np)??G (reduced by
the dim. of para space) - Each para is degraded by slightly different
amounts - Degeneracy direction is slightly changed
?_mh2
?_bh2
18 An even more direct use of NG bispectrum
Bernardeau97, 02, Schneider Lombardi03,
Zaldarriaga Scoccimarro 03, MT Jain 04, 07,
Kilbinger Schneider 05
given as a function of separation l
given as a function of triangles
19A more realistic parameter forecast
MT Jain in prep. 07
WLT (3 z-bins) CMB
- Parameter errors PS, Bisp, PSBisp
- G ?(?_de)0.015, 0.014, 0.010 ? NG 0.016(7),
0.022(57), 0.013(30) - ?(w0) 0.18, 0.20, 0.13 ? 0.19(6), 0.29(45),
0.15(15) - ?(wa) 0.50, 0.57, 0.38 ? 0.52(4), 0.78(73),
0.41(8) - The errors from Bisp are more degraded than PS
- Need not go to 4-pt!
- In the presence of systematics, PSBisp would be
very powerful to discriminate the cosmological
signals (Huterer, MT 05)
20WLT Cluster Counts
MT S. Bridle astro-ph/0705.0163
- Clusters are easy to find from WL survey itself
mass peaks (Miyazaki etal.03 see Hamana sans
talk for the details) - Synergy with other wavelength surveys (SZ,
X-ray) - Combining WL signal and other data is very useful
to discriminate real clusters from contaminations - Combing WL with cluster counts is useful for
cosmology? - Yes, would improve parameter constraints, but how
complementary? - Cluster counts is a powerful probe of cosmology,
established method (Kitayama Suto 97
Meneghetti05)
Angular number counts
w0-1 ? w0-0.9
21Mass-limited cluster counts vs. lensing-selected
counts
Hamana, MT, Yoshida 04
Halo distribution
Convergence map
2 degrees
- Mass-selected sample (SZ) vs lensing-based sample
22Redshift distribution of cluster samples
23Cross-correlation between CC and WL
Cluster
A patch of the observed sky
Shearing effect of background galaxies
- If the two observables are drawn from the same
survey region, the two probe the same cosmic mass
density field in LSS - Around each cluster, stronger shear signal is
expected up to 10 in induced ellipticities,
compared to a few for typical cosmic shear - A positive cross-correlation is expected
Clusters happen to be less/more populated in a
given survey region than expected, the amplitudes
of lt???gt are most likely to be smaller/greater
24Cross-correlation btw CC and WL (contd.)
1014ltM/M_slt1015
- Shown is the halo model prediction for the
lensing power spectrum - A correlation between the number of clusters and
the ps amplitude at l103 is expected.
25Cross-covariance between CC WL
- Cross-covariance between PS binned in l and z and
the cluster counts binned in z - The cross-correlation arises from the 3-pt
function of the cluster distribution and the two
lensing fields of background galaxies - The cross-covariance is from the non-Gaussianity
of LSS - The structure formation model gives specific
predictions for the cross-covariance
26SNR for CCWL
- The cross-covariance leads to degradation and
improvement in S/N up to ?20, compared to the
case that the two are independent
27Parameter forecasts for CCWL
lensing-selected sample
mass-selected sample
WL
CCWL
CCWL with Cov
- Lensing-selected sample with detection threshold
S/N10 contains clusters with gt1015Msun - Lensing-selected sample is more complementary to
WLT, than a mass-selected one? Needs to be more
carefully addressed
28HSCWLS performance (WLTCCCMB)
- Combining WLT and CC does tighten the DE
constraints, due to their different cosmological
dependences - Cross-correlation between WLT and CC is
negligible the two are considered independent
approximately
29Issues on systematics self-calibration
- If several observables (O1,O2,) are drawn from
the same survey region e.g., WLPS, WLBisp, CC, - Each observable contains two contributions (C
cosmological signal and S systematics) - Covariances (or correlation) between the
different obs. - If the systematics in different obs are
uncorrelated - The cosmological covariances are fairly
accurately predictable - Taking into account the covariances in the
analysis could allow to discriminate the
cosmological signals from the systemacs
self-calibration - Working in progress
30Summary
- The non-Gaussian errors in cosmic shear fields
arise from non-linear clustering in structure
formation - The CDM model provides the specific predictions,
so the NG errors are in some sense accurately
predictable - Bad news the NG errors are very important to be
included for current and, definitely, future
surveys - The NG degrades the S/N for the lensing power
spectrum measurement up to a factor of 2 - Good news the NG impact on cosmo para errors are
less significant if working in a
multi-dimensional parameter space - 10 for 7-D parameter space
- WLT and cluster counts, both available from the
same imaging survey, can be used to tighten the
cosmological constraints