Photo-z for LRGs, DES, DUNE and the cross talk with Dark Energy

Ofer Lahav,University College London

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 LahavUniversity College London

“Evidence” for Dark Energy

Observational data• Type Ia Supernovae • Galaxy Clusters• Cosmic Microwave Background• Large Scale Structure• Gravitational Lensing

Physical effects: • Geometry • Growth of StructureBoth 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 Universem =0.3

LCDMa = 1 (t= 13.5 Gyr)

OCDMa = 1 (t= 11.3 Gyr)

LCDMa = 6 (t= 42.4 Gyr)

OCDMa = 6 (t= 89.2 Gyr)

Hoffman, OL, Yepes & Dover 2007

Imaging Surveys Survey Sq. Degrees Filters Depth Dates Status

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 approvedVST/KIDS/

VISTA/VIKING 1700 4+5 moderate 2007-2010? 50%approved

DES (NOAO) 5000 4 moderate 2008-2012? proposedPan-

STARRS ~10,000? 5? moderate 2006-2012? ~funded

LSST 15,000? 5? deep 2014-2024? proposed

JDEM/SNAP1000+ (space)

9 deep 2013-2018? proposed

VST/VISTA

DUNE

5000? 2010-2015?moderate 4+5 proposed

20000? (space) 2+1? moderate 2012-2018? proposed

Y. Y. Mellier

Photo-z / Cosmology Synergy

Large Scale Structure

Clusters of Galaxies

Simulations

Photo-z

Gravitational Lensing

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)

Blanco 4-meter at CTIO

300,000,000 photometric redshifts within a volume of 23 (Gpc/h)^3, out to z = 2

DES Organization

SupernovaeB. NicholJ. Marriner

ClustersJ. MohrT. McKay

Weak LensingB. JainS. Bridle

Galaxy ClusteringE. GaztanagaW. Percival

Photometric RedshiftsF. CastanderH. Lin

SimulationsA. KravtsovA. Evrard

Science Working Groups

DES:UK consortium:

UCL, Portsmouth, Cambridge, Edinburgh, Sussex

Over 100 scientistsin 17 institutionsIn the US, UK, Spain and Brazil

DES Status

• 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

•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

DETF FoM

DES Forecasts: Power of Multiple Techniques

FoM factor 4.6 tigther compared to near term projects

w(z) =w0+wa(1–a) 68% CL

Ma, Tang, Weller

Sources of uncertaintiesin measuring Dark Energy

• Theoretical (e.g. the cosmological model)

• Astrophysical (e.g. galaxy and cluster properties)

• Instrumental (e.g. image quality)

Photometric redshifts

• Probe strong spectral features (e.g. 4000 break)

z=3.7z=0.1

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

• Photo-z mocks and algorithms

• Spetroscopic training sets

• MegaZ-LRG (DR6)

• DES

• VISTA

• 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

Output:redshift

Input:magnitudes

Collister & Lahav 2004http://www.star.ucl.ac.uk/~lahav/annz.html

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

Blake, Collister, Bridle & OL; astro-ph/0605303

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Halo fit to MegaZ-LRG

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Blake, Collister,OL0704.3377

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Excess Power on Large Scales?

Blake et al. 06 Padmanabhan et al. 06

The Dark Energy Survey

DES+VISTA would improve photo-z by a factor of 2 for z> 1What is the effect on WL, BAO, SNIa Science? Banerji, Abdalla, OL, Lin et al.

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DES (5 filters) vs. DES+VISTA(8 filters)

DES+VISTA: Galaxy Power Spectrum

DES grizY DES grizY + VISTA JHK

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*22 kPzbzDznnP

zndz

dVf

dz

dN

nPVP

mgal

sky

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⎛ +∝For the same clipping

threshold, we can measure the power spectrum accurately to higher redshifts using the DES+VISTA data.

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

Back of the envelope: improved by sqrt (volume) => Sub-eV from DES(OL, Abdalla, Black, Kiakotou; in prep)

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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

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Abdalla, Amara, Capak, Cypriano, OL , Rodes astro-ph/0705.1437

DE FoM for DUNE with and without NIR

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NIR will improve FoM by 1.3-1.7

DE FOM vs number of spectra needed

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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