Yun Wang

(on behalf of the Euclid Galaxy Clustering SWG)

Euclid Galaxy Clustering SWG Meeting London, March 21, 2012

Cosmic Expansion History from Euclid BAO Measurements

EuclidConsortium

Galaxy Clustering: Baryonic Acoustic Oscillations (BAO) as standard ruler

GalaxiesGalaxiesGalaxiesGalaxies Microwave Microwave backgroundbackgroundMicrowave Microwave backgroundbackground

(WMAP, e.g. Komatsu et al. 2009)Percival et al. (2009,

2010)

Instrument Overall WP Breakdown VG :3

EuclidConsortiumReconstructing power spectra to 1%

Euclid ESA HQ Paris Sept. 12, 2011 Euclid ESA HQ Paris Sept. 12, 2011 Euclid SPR Jan. 19, 2012

Simulated of the Euclid spectro. survey : 100 deg2: effect of redshift errors (red dots). (A. Merson and C. Baugh mocks)

GC redshift-survey: Power spectrum reconstruction with 20% of the Euclid data.(W. Percival)

L1L2PRR Meeting ESTEC 27 May 2011

EuclidConsortiumw(z) from Baryonic Acoustic Oscillations

20% of the Euclid slitless data at z~1

Total effective volume (of Euclid)Veff = 19.7 Gpc3h-3

20% of the Euclid slitless data at z~1

Total effective volume (of Euclid)Veff = 19.7 Gpc3h-3

SDSS LRGs at z~0.35

The largest volume of the Universe currently mapped

Total effective volumeVeff = 0.26 Gpc3h-3

SDSS LRGs at z~0.35

The largest volume of the Universe currently mapped

Total effective volumeVeff = 0.26 Gpc3h-3

EuclidConsortiumThe unique power of Euclid: w(z)

FoM > 400 (e.g. wp~0.016 and wa~0.16)

In this case a cosmological constant is favoured by more than 100:1 over model M: "decisive" statistical evidence in favour of the simplest model, in Bayesian terms

A less precise experiment will not have enough statistical power to favour a cosmological constant over the more complex alternative

Instrument Overall WP Breakdown VG :6

EuclidConsortiumGC-1-1 and WL-1-1 optimal sky coverage ,fixed-length survey

Euclid ESA HQ Paris Sept. 12, 2011 Euclid SPR Jan. 19, 2012

With 15,000 deg2 for for GC and WL: optimisation for a fixed time survey.Most efficient survey, allowsto do WL and GC simulatenously on the same area

Consortium

Instrument Overall WP Breakdown VG :7

EuclidConsortium

Modified Gravity

Dark MatterInitial Conditions

Dark Energy

Parameter mν/eV fNL wp wa FoM

Euclid Primary 0.010 0.027 5.5 0.015 0.150 430

Euclid All 0.009 0.020 2.0 0.013 0.048 1540

Euclid+Planck 0.007 0.019 2.0 0.007 0.035 4020

Current 0.200 0.580 100 0.100 1.500 ~10

Improvement Factor

30 30 50 >10 >40 >400

Planck+Euclid+simulation: FoM L0 requirement met

Euclid ESA HQ Paris Sept. 12, 2011 Euclid ESA HQ Paris Sept. 12, 2011

(WL+GC)

(WL+GC)+CL+ISW

(Euclid All)

Euclid SPR Jan. 19, 2012

Yun Wang, 3/21/2012

DE Forecasting from GCDE Forecasting from GC• Propagate the measurement errors in lnPg(k) into measurement

errors for the parameters pi:

lnPg(k) [Veff(k)]-1/2

=k·r/kr

3

3

)2(2

d)(

)(ln)(lnmax

min k

kkk

effj

g

i

gk

kij V

pP

pP

F

surveyg

g

g

geff

VknP

knP

kPn

kPndV

2

23

1),(

),(

1),()(

),()()(

r

rrk

Yun Wang, 3/21/2012

Two Approaches:Two Approaches:

• “Full P(k)” method:

parametrize P(k) using [H(zi), DA(zi), (zi), G(zi), Pshot

i, nS, mh2, bh2]

• BAO “wiggles only”:

P(k) P(k0.2,|z)[sin(x)/x]·exp[-(ks)1.4-k2 nl2/2]

x=(k2s2+ k//

2s//2)1/2

p1=ln s

-1=ln(DA/s); p2=ln s //=ln(sH);

Yun Wang, 3/21/2012

Assuming Euclid Red Book Baseline:

(deg)2

0.65<z<2.05 e(f,z)

*Updated from Wang et al. (2010)

Figure of Merit vsRedshift Accuracy

Figure of Merit vsRedshift Accuracy

Yun Wang, 3/21/2012

xh(z)=H(z)sxd(z)=DA(z)/s

*Updated from Wang et al. (2010) for Euclid RB baseline*Based on Wang (2012)

Expansion History H(z):BAO vs P(k)

Expansion History H(z):BAO vs P(k)

Yun Wang, 3/21/2012

*Based on Wang (2012)

Constraints on Growth Rate

Constraints on Growth Rate

Yun Wang, 3/21/2012

xh(z)=H(z)sxd(z)=DA(z)/s

pNL=50%

*Updated from Wang et al. (2010) for Euclid RB baseline

*Based on Wang (2012)

DE FoM vs Information Used

DE FoM vs Information Used

Space/Ground Complementarity

Ongoing ground-based surveys (WiggleZ, BOSS) enable better understanding of galaxy clustering, and improved modeling of systematic effects, which benefit Euclid.

Overlaps in redshift range (BOSS, BigBOSS, and Euclid) enable clustering statistics using multiple tracers (LRG, OII3727, and H emitters), which improves DE constraints and the modeling of systematic effects.

Yun Wang, 3/21/2012