Transcript From Galaxy Surveys to Dark Matter and Dark Energy: UCL

Photo-z for LRGs, DES, DUNE and the
cross talk with Dark Energy
1. The Dark Energy Survey
2. Photo-z methodology
3. Photo-z and probes
4. Applications: LRGs, DES, DUNE
mainly with Filipe Abdalla and Manda Banerji
Ofer Lahav,
Ofer Lahav
University College London
University College London
“Evidence” for Dark Energy
Observational data
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Type Ia Supernovae
Galaxy Clusters
Cosmic Microwave Background
Large Scale Structure
Gravitational Lensing
Physical effects:
• Geometry
• Growth of Structure
Both depend on the Hubble expansion rate:
H2(z) = H20 [M (1+z) 3 + DE (1+z) 3 (1+w) ]
(flat)
Dark Energy: back to Newton?
F = -GM/r2 + /3 r
X
*
“I have now explained the two principle cases of
attraction…
which is very remarkable”
Newton, Principia
The Future of the Local Universe
m =0.3
LCDM
a=1
(t= 13.5 Gyr)
OCDM
a=1
(t= 11.3 Gyr)
Hoffman, OL, Yepes & Dover 2007
LCDM
a=6
(t= 42.4 Gyr)
OCDM
a=6
(t= 89.2 Gyr)
Imaging Surveys
Survey
Sq. Degrees
Filters
Depth
CTIO
75
1
shallow
published
VIRMOS
9
1
moderate
published
COSMOS
2 (space)
1
moderate
complete
DLS (NOAO)
36
4
deep
complete
Subaru
30?
1?
deep
2005?
observing
CFH Legacy
170
5
moderate
2004-2008
observing
RCS2 (CFH)
830
3
shallow
2005-2007
approved
VST/KIDS/
VISTA/VIKING
1700
4+5
moderate
2007-2010?
50%approved
DES (NOAO)
5000
4
moderate
2008-2012?
proposed
Pan-STARRS
~10,000?
5?
moderate
2006-2012?
~funded
LSST
15,000?
5?
deep
2014-2024?
proposed
9
deep
2013-2018?
proposed
4+5
moderate
2010-2015?
proposed
2+1?
moderate
2012-2018?
proposed
VST/VISTA
1000+
(space)
5000?
DUNE
20000? (space)
JDEM/SNAP
Dates
Status
Y. Mellier
Photo-z / Cosmology Synergy
Large Scale Structure
Photo-z
Gravitational Lensing
Simulations
Clusters of Galaxies
The Dark Energy Survey
The Dark Energy Survey
• Study Dark Energy using
4 complementary techniques:
I. Cluster Counts
II. Weak Lensing
III. Baryon Acoustic Oscillations
IV. Supernovae
• Two multi-band surveys
5000 deg2 g, r, i, z
40 deg2 repeat (SNe)
• Build new 3 deg2 camera
and data management system
Survey 2010-2015 (525 nights)
300,000,000 photometric
redshifts within a volume of
23 (Gpc/h)^3, out to z = 2
Blanco 4-meter at CTIO
DES Organization
Over 100 scientists
in 17 institutions
In the US, UK, Spain
and Brazil
Science Working Groups
Clusters
J. Mohr
T. McKay
Supernovae
B. Nichol
J. Marriner
Weak Lensing
B. Jain
S. Bridle
Galaxy Clustering Photometric Redshifts
E. Gaztanaga
F. Castander
W. Percival
H. Lin
DES:UK consortium:
UCL, Portsmouth, Cambridge, Edinburgh, Sussex
Simulations
A. Kravtsov
A. Evrard
DES Status
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Low-risk, near-term (2010-15) project with high discovery potential
Survey strategy delivers substantial DE science after 2 years
Synergy with SPT and VISTA
Precursor to LSST, DUNE and JDEM
Total cost is relatively modest (~ $20-30M)
 STFC approved £1.7M for the DES optical corrector, subject to
funding in the US
 Glass ordered by UCL in Sep 07 (funds from 5 universities)
 DES in the US President budget request for FY08
 DOE CD1 approved; CD2/CD3 in Jan 08
 NSF contribution to data management
DES Forecast
Constraints
DETF FoM
•DES+Stage II combined = Factor 4.6 improvement over Stage II combined
•Consistent with DETF range for Stage III DES-like project
•Large uncertainties in systematics remain, but FoM is robust to uncertainties
in any one probe, and we haven’t made use of all the information
DES Forecasts:
Power of Multiple Techniques
w(z) =w0+wa(1–a)
68% CL
Ma, Tang, Weller
FoM factor 4.6 tigther compared to near term projects
Sources of uncertainties
in measuring Dark Energy
• Theoretical (e.g. the cosmological model)
• Astrophysical (e.g. galaxy and cluster
properties)
• Instrumental (e.g. image quality)
Photometric redshifts
z=0.1
•
Probe strong
spectral features
(e.g. 4000 break)
z=3.7
Photo-z –Dark Energy
cross talk
• Approximately, for a photo-z slice:
(w/ w) = 5 (z/ z) = 5 (z/z) Ns-1/2
=> the target accuracy in w
and photo-z scatter z dictate the number of required
spectroscopic redshifts
Ns =105-106
Cosmology from
photo-z surveys
• Optimization of Photo-z for
cosmic probes
• MegaZ-LRG (DR6)
• Photo-z mocks and
algorithms
• VISTA
• Spetroscopic training sets
• DES
• DUNE
• other surveys
BAO, WL, neutrino mass, ISW,
halo parameters,…
Photo-z Challenges
• Optimizing hybrid methods
- errors
- pdf
- ‘clippping’
• Optimal filters
• Spetroscopic training sets
• Field vs cluster photo-z
• Synergy with BAO and WL
• “Self calibration” and “colour tomography”
Photo-z Methods
• Template fitting (e.g. Hyper-z)
• Bayesian methods (e.g. BPZ, Zebra)
• Training-based methods (e.g. ANNz)
ANNz - Artificial Neural Network
Input:
magnitudes
Collister & Lahav 2004
http://www.star.ucl.ac.uk/~lahav/annz.html
Output:
redshift
MegaZ-LRG
*Training on ~13,000 2SLAQ
*Generating with ANNz
Photo-z for ~1,000,000 LRGs
over 5,000 sq deg, 2.5 (Gpc/h)^3
z = 0.046
Collister, OL et al.
LRG - photo-z code comparison
M. Banerji, F. Abdalla F., V. Rashkov, OL et al
photo-z bins
Collister et al.
Baryon oscillations from MegaZ-LRG
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
Blake, Collister, Bridle & OL; astro-ph/0605303
Halo fit to MegaZ-LRG
QuickTi me™ and a
TIFF (Uncompressed) decompressor
are needed to see this pi cture.
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
Blake, Collister,OL
0704.3377
Excess Power on Large Scales?
Blake et al. 06
Padmanabhan et al. 06
The Dark Energy Survey
DES (5 filters)
vs. DES+VISTA(8 filters)
Quic kTime™ and a
TIFF ( Unc ompres s ed) dec ompr ess or
are needed to s ee this pic ture.
DES+VISTA would improve photo-z by a factor of 2 for z> 1
What is the effect on WL, BAO, SNIa Science?
Banerji, Abdalla, OL, Lin et al.
DES+VISTA: Galaxy Power
Spectrum
For the same clipping
threshold, we can measure the
power spectrum accurately to
higher redshifts using the
DES+VISTA data.
DES grizY
P
1 
1 
1 

P
nP 
V 
dN
dV
 f sky
n( z )
dz
dz
nPgal  n( z )[D( z )]2 [b( z )]2 Pm (k* )

DES grizY + VISTA JHK
DES+VISTA : Effect of Reddening
Plots generated using JPL mocks (P.Capak)
which include the effects of reddening
DES z=0.8 photo-z shell
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
Back of the envelope: improved by sqrt (volume) => Sub-eV from DES
(OL, Abdalla, Black, Kiakotou; in prep)
DUNE: Dark UNiverse
Explorer
Mission baseline:
• 1.2m telescope
• FOV 0.5 deg2
• PSF FWHM 0.23’’
• Pixels 0.11’’
• GEO (or HEO) orbit
Surveys (3-year initial programme):
• WL survey: 20,000 deg2 in 1 red broad band,
35 galaxies/amin2 with median z ~ 1, ground
based complement for photo-z’s
• Near-IR survey (J,H). Deeper than possible
from ground. Secures z > 1 photo-z’s
Optical and Optical+NIR
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
Abdalla, Amara, Capak, Cypriano, OL , Rodes astro-ph/0705.1437
DE FoM for DUNE
with and without NIR
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
NIR will improve FoM by 1.3-1.7
DE FOM vs
number of spectra needed
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
Abdalla et al.
Photo-z Challenges
• Optimizing hybrid methods
- errors
- pdf
- ‘clippping’
• Optimal filters
• Spetroscopic training sets
• Field vs cluster photo-z
• Synergy with BAO and WL
• “Self calibration” and “colour tomography”
The END