Yun Wang (on behalf of the Euclid Galaxy Clustering SWG)

1. Cosmic Expansion History from Euclid BAO Measurements Yun Wang (on behalf of the Euclid Galaxy Clustering SWG) Euclid Galaxy Clustering SWG Meeting London, March 21, 2012

2. Euclid Consortium Galaxies Microwave background Galaxy Clustering: Baryonic Acoustic Oscillations (BAO) as standard ruler (WMAP, e.g. Komatsu et al. 2009) Percival et al. (2009, 2010)

3. Reconstructing power spectra to 1% 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) Euclid ESA HQ Paris Sept. 12, 2011 Euclid ESA HQ Paris Sept. 12, 2011 Euclid SPR Jan. 19, 2012

4. Euclid Consortium w(z) from Baryonic Acoustic Oscillations SDSS LRGs at z~0.35 The largest volume of the Universe currently mapped Total effective volume Veff = 0.26 Gpc3h-3 20% of the Euclid slitless data at z~1 Total effective volume (of Euclid) Veff = 19.7 Gpc3h-3 L1L2PRR Meeting ESTEC 27 May 2011

5. The unique power of Euclid: w(z) Euclid Consortium 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

6. GC-1-1 and WL-1-1 optimal sky coverage ,fixed-length survey Consortium 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 Euclid ESA HQ Paris Sept. 12, 2011 Euclid SPR Jan. 19, 2012

7. Planck+Euclid+simulation: FoM L0 requirement met (WL+GC) (WL+GC)+ CL+ISW (Euclid All) Euclid ESA HQ Paris Sept. 12, 2011 Euclid ESA HQ Paris Sept. 12, 2011 Euclid SPR Jan. 19, 2012

8. DE 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 Yun Wang, 3/21/2012

9. Two Approaches: • “Full P(k)” method: parametrize P(k) using [H(zi), DA(zi), (zi), G(zi), Pshoti, nS, mh2, bh2] • BAO “wiggles only”: P(k)  P(k0.2,|z)[sin(x)/x]·exp[-(ks)1.4-k2 nl2/2] x=(k2s2+ k//2s//2)1/2 p1=ln s-1=ln(DA/s); p2=ln s//=ln(sH); Yun Wang, 3/21/2012

10. Yun Wang, 3/21/2012 Figure of Merit vs Redshift Accuracy Assuming Euclid Red Book Baseline:  15,000 (deg)2  0.65<z<2.05  e(f,z) *Updated from Wang et al. (2010)

11. Yun Wang, 3/21/2012 Expansion History H(z): BAO vs P(k) xh(z)=H(z)s xd(z)=DA(z)/s *Updated from Wang et al. (2010) for Euclid RB baseline *Based on Wang (2012)

12. Yun Wang, 3/21/2012 Constraints on Growth Rate *Based on Wang (2012)

13. Yun Wang, 3/21/2012 DE FoM vs Information Used xh(z)=H(z)s xd(z)=DA(z)/s pNL=50% *Updated from Wang et al. (2010) for Euclid RB baseline *Based on Wang (2012)

14. Yun Wang, 3/21/2012 •  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. Space/Ground Complementarity