des collaboration meeting – dec. 11, 2006 1 dark energy survey science proposal josh frieman

1DES Collaboration Meeting – Dec. 11, 2006

Dark Energy Survey Science Proposal

Josh Friemanhttp://astro.uchicago.edu/~frieman/DES/proposal/proposal.pdf


Context: Dark Energy Task Force (DETF)

Report Recognized 4 promising Dark Energy probes familiar to DES Defined Figure of Merit (FoM) for Dark Energy experiments Envisioned staged approach to DE based on FoM & scale: Stage III: near-term, intermediate-scale projects; FoM~3-5 Stage IV: longer-term, large-scale: LST, JDEM, SKA; FoM~5-10 Recommended immediate start to a Stage III project Considered 8 `generic’ Stage III projects, 6 of them essentially identical to DES Proposal should make the case that DES satisfies requirements for a DETF Stage III project, and that multiplicity of methods & control of systematics should yield results toward optimistic end of the Stage III FoM.

3DES Collaboration Meeting - Dec. 11, 2006

Science Proposal Team

Clusters: Mike Gladders, Tim McKayWeak Lensing: Bhuv Jain, Sarah BridleSupernovae: Bob Nichol, Masao Sako, w/input from Gajus Miknaitis, Ramon Miquel, Rick KesslerBAO: Will Percival, Enrique Gaztanaga, Wayne HuOther DE Probes: Scott DodelsonSimulations: Gus Evrard, Paul Ricker, Andrey KravtsovPhoto-z’s: Huan Lin, Ofer LahavFisher Matrix Mavens: Wayne Hu, Gary Bernstein, Jochen Weller, Scott Dodelson, Zhaoming MaReviewers: Joe Mohr, Ramon Miquel, Chris Smith, Gary & Rebecca Bernstein, David Weinberg

building on NOAO Proposal (2004) and DETF White Papers (2005)


Schedule

Oct. 18: letter from DOE & NSF Late Oct: Science proposal team formed Phone meetings: 11/3, 11/10, 11/17, 11/28, 12/7 First drafts compiled ~11/27 Revised drafts sent to reviewers 12/2 Reviews received 12/6 Final sections due 12/11 PM Completed science section delivery 12/13 Proposal submission 12/20


DES Forecasts: Power of Multiple Techniques

Ma, Weller, Huterer, etal

Assumptions:Clusters: SPT-selected,8=0.75, zmax=1.5,WL mass calibration(no clustering self-calibration)

BAO: lmax=300WL: lmax=1000(no bispectrum or galaxy-shear)

Statistical+photo-z systematic errors only

Spatial curvature, galaxy biasmarginalized

Planck CMB prior

w(z) =w0+wa(1–a) 68% CL

geometric

geometric+growth

Clustersif 8=0.9


I. Clusters and Dark Energy

•Requirements1.Understand formation of dark matter halos 2.Cleanly select massive dark matter halos (galaxy clusters) over a range of redshifts 3.Redshift estimates for each cluster 4.Observable proxy that can be used as cluster mass estimate: g(O|M,z)

Primary systematics: Uncertainty in g (bias & scatter)Uncertainty in O selection fn.

€

dN(z)dzdΩ

= dVdz dΩ

n z( )


Cluster Cosmology with DES

• 3 Techniques for Cluster Selection and Mass Estimation:• Optical galaxy concentration• Weak Lensing • Sunyaev-Zel’dovich effect (SZE)

• Cross-compare these techniques to reduce systematic errors

• Additional cross-checks: shape of mass function; cluster correlations (self-calibration)


Statistical Weak Lensing CalibratesCluster Mass vs. Observable Relation

Hansen etal Johnston, Sheldon, etal, in preparation


SZE vs. Cluster Mass: Progress in Simulations

Integrated SZE flux decrement depends only on cluster mass: insensitive to details of gas dynamics/galaxy formation in the cluster core robust scaling relations

Nagai

SZE

flux

Adiabatic∆ Cooling+Star Formation

small (~10%) scatter


Observer

Dark matter halos

Background sources

Statistical measure of shear pattern, ~1% distortion Radial distances depend on geometry of Universe Foreground mass distribution depends on growth of structure

II. Weak Lensing: Cosmic Shear


•Cosmic Shear Angular Power Spectrum in Photo-z Slices

•Shapes of ~300 million galaxies median redshift z = 0.7

•Primary Systematics: photo-z’s, PSF anisotropy, shear calibration, intrinsic alignments

Weak Lensing Tomography

DES WL forecasts conservatively assume 0.9” PSF = median delivered to existing Blanco camera: DES should do better & be more stable

Huterer

Statistical errorsshown


Reducing WL Shear Systematics

DECam+Blancohardwareimprovements that will reduce raw PSF anisotropy

Include Bispectrum and Galaxy-shear: robustness against systematics

Red: expected signal

Results from 75 sq. deg. WLSurvey with Mosaic II and BTCon the Blanco 4-mBernstein, etal

DES: comparable depth: source galaxies well resolved & bright:low-risk

(improved systematic)

(signal)

Shear systematics should be under control at level needed for DES

(old systematic)

Cosmic Shear


III. Supernovae• Strawman Strategy: Repeat

observations in riz of 40 deg2

`wide & shallow’: ~2600 well-measured SN Ia lightcurves, 0.05 < z < 0.8

• Alternative Strategy: `Deep & narrow’ riz of 9 deg2, spectroscopic follow-up concentrated on Ia’s in ellipticals (lower extinction, better photo-z’s):

~200+800 Ia’s to z~1

• Larger sample, improved z-band response compared to ESSENCE, SNLS

• Issue: what fraction spectroscopic follow-up for distances & sample purity


IV. Baryon Acoustic Oscillations & Large-scale Structure

CMBAngularPowerSpectrum

SDSS galaxycorrelation function

Acoustic series in P(k) becomes a single peak in (r)

Bennett, etal

Eisenstein etal


BAO in DES: Galaxy Angular Power Spectrum

Probe substantially larger volume and redshift range than SDSS

Systematics:

photo-z’s, photometric errors,Non-linearity, Scale-dependent bias

Controls:

Calibration, bispectrum

Wiggles due to BAO


Photometric Redshifts• Measure relative flux in four filters griz: track the 4000 A break

• Estimate individual galaxy redshifts with accuracy (z) < 0.1 (~0.02 for clusters)

• Precision is sufficient for Dark Energy probes, provided error distributions well measured.

• Note: good detector response in z band filter needed to reach z>1

Elliptical galaxy spectrum

DES Collaboration Meeting – Dec. 11, 2006

Spectroscopic Redshift Training Sets for DES

Redshift Survey Number of Redshifts Overlapping DES

Sloan Digital Sky Survey 70,000, r < 20

2dF Galaxy Redshift Survey

90,000, bJ<19.45

VIMOS VLT Deep Survey ~60,000, IAB<24

DEEP2 Redshift Survey ~30,000, RAB<24.1

Training Sets to the DES photometric depth in place (advantage of a `relatively’ shallow survey)


DES Cluster Photometric Redshifts: Simulations & SDSS Results


DESgriz filters10 Limiting Magnitudes g 24.6 r 24.1 i 24.0 z 23.9 +2% photometric calibrationerror added in quadrature

Key: Photo-z systematic errors under control using existing spectroscopic training sets to DES photometric depth: low-risk

Galaxy Photo-z Simulations

+VHS JK

Improved Photo-z & Error Estimates and robust methods of outlier rejection

DES

Cunha, etal

DES + VHS on

ESO VISTA 4-menhances science reach

+Y


Variance and Bias of Photo-z Estimates

Cunha etal

Variance Bias


Weak Lensing & Photo-z Systematics

Ma

(w0)/(w0|pz fixed) (wa)/(wa|pz fixed)


BAO & Photo-z Systematics

Ma

(w0)/(w0|pz fixed)(wa)/(wa|pz fixed)


• Will measure Dark Energy using multiple complementary probes, developing these techniques and exploring their systematic error floors

• Survey strategy delivers substantial DE science after 2 years• Relatively modest, low-risk, near-term project with high discovery potential

• Scientific and technical precursor to the more ambitious Stage IV Dark Energy projects to follow: LSST and JDEM

• DES in unique international position to synergize with SPT and VISTA on the DETF Stage III timescale

DES and the Dark Energy Program

des collaboration meeting – dec. 11, 2006 1 dark energy survey science proposal josh frieman

Documents