the dark energy survey
DESCRIPTION
The Dark Energy Survey. White Papers submitted to Dark Energy Task Force: astro-ph/0510346 Theoretical & Computational Challenges: astro-ph/0510194,5. Josh Frieman. The Dark Energy Survey. Blanco 4-meter at CTIO. Study Dark Energy using 4 complementary* techniques: - PowerPoint PPT PresentationTRANSCRIPT
1P5 – April 20, 2006
The Dark Energy Survey
Josh Frieman
White Papers submitted to Dark Energy Task Force:
astro-ph/0510346
Theoretical & Computational Challenges:astro-ph/0510194,5
2P5 – April 20, 2006
The Dark Energy Survey• Study Dark Energy using 4 complementary* techniques: I. Cluster Counts II. Weak Lensing III. Baryon Acoustic
Oscillations IV. Supernovae
• Two multiband surveys: 5000 deg2 g, r, i, z 40 deg2 repeat (SNe)
• Build new 3 deg2 camera and Data management sytem Survey 2009-2015 (525 nights) Response to NOAO AO
Blanco 4-meter at CTIO
*in systematics & in cosmological parameter degeneracies*geometric+structure growth: test Dark Energy vs. Gravity
3P5 - April 20, 2006
The DES CollaborationFermilab: J. Annis, H. T. Diehl, S. Dodelson, J. Estrada, B. Flaugher, J. Frieman, S. Kent, H. Lin, P. Limon, K. W. Merritt, J. Peoples, V. Scarpine, A. Stebbins, C. Stoughton, D. Tucker, W. WesterUniversity of Illinois at Urbana-Champaign: C. Beldica, R. Brunner, I. Karliner, J. Mohr, R. Plante, P. Ricker, M. Selen, J. ThalerUniversity of Chicago: J. Carlstrom, S. Dodelson, J. Frieman, M. Gladders, W. Hu, S. Kent, R. Kessler, E. Sheldon, R. WechslerLawrence Berkeley National Lab: N. Roe, C. Bebek, M. Levi, S. PerlmutterUniversity of Michigan: R. Bernstein, B. Bigelow, M. Campbell, D. Gerdes, A. Evrard, W. Lorenzon, T. McKay, M. Schubnell, G. Tarle, M. TecchioNOAO/CTIO: T. Abbott, C. Miller, C. Smith, N. Suntzeff, A. WalkerCSIC/Institut d'Estudis Espacials de Catalunya (Barcelona): F. Castander, P. Fosalba, E. Gaztañaga, J. Miralda-EscudeInstitut de Fisica d'Altes Energies (Barcelona): E. Fernández, M. MartínezCIEMAT (Madrid): C. Mana, M. Molla, E. Sanchez, J. Garcia-BellidoUniversity College London: O. Lahav, D. Brooks, P. Doel, M. Barlow, S. Bridle, S. Viti, J. Weller University of Cambridge: G. Efstathiou, R. McMahon, W. Sutherland University of Edinburgh: J. Peacock University of Portsmouth: R. Crittenden, R. Nichol, W. PercivalUniversity of Sussex: A. Liddle, K. Romer
plus students
4P5 – April 20, 2006
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
P5 – April 20, 2006
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
Galaxy Photo-z Simulations
+VDES JK
Improved Photo-z & Error Estimates and robust methods of outlier rejection
DES
Cunha, etal
DES + VDES on
ESO VISTA 4-m
enhances science reach
6P5 – April 20, 2006
I. Clusters and Dark Energy
MohrVolume Growth(geometry)
Number of clusters above observable mass threshold
Dark Energy equation of state
dN(z)
dzd
dV
dz dn z
•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: O =g(M)
Primary systematic: Uncertainty in bias & scatter of mass-observable relation
7P5 – April 20, 2006
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
8P5 – April 20, 2006
10-m South Pole Telescope (SPT)
SPT will carry out 4000 sq. deg. SZE Survey
PI: J. Carlstrom (U. Chicago)
NSF-OPP funded & scheduled for Nov 2006 deploymentDOE (LBNL) funding of readout development
Sunyaev-Zel’dovich effect- Compton upscattering of CMB photons by hot gas in clusters- nearly independent of redshift: - can probe to high redshift - need ancillary redshift measurement
Dec 2005
9P5 – April 20, 2006
SZE vs. Cluster Mass: Progress in Realistic
Simulations
Motl, etalIntegrated 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
flu
x
Adiabatic∆ Cooling+Star Formation
SPT
Obs
erva
ble
Kravtsov
Future:SCIDACproposal
small (~10%) scatter
10P5 – April 20, 2006
Statistical Weak Lensing CalibratesCluster Mass vs. Observable Relation
Cluster Massvs. Number of galaxies they contain
For DES, will use this to independently calibrate SZE vs. Mass
Johnston, Sheldon, etal, in preparation
Statistical Lensing eliminates projection effectsof individual cluster massestimates
Johnston, etalastro-ph/0507467
SDSS DataPreliminaryz<0.3
11P5 – April 20, 2006
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
12P5 – April 20, 2006
•Cosmic Shear Angular Power Spectrum in 4 Photo-z Slices
•Shapes of ~300 million galaxies median redshift z = 0.7
•Primary Systematics: photo-z’s, PSF anisotropy, shear calibration
Weak Lensing Tomography
DES WL forecasts conservatively assume 0.9” PSF = median delivered to existing Blanco camera: DES should do better & be more stable (see Brenna’s talk)
Huterer
Statistical errorsshown
13P5 - April 20, 2006
Reducing WL Shear Systematics
See Brenna’s talk for DECam+Blancohardwareimprovements that will reduce raw lensing 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 under control at level needed for DES
(old systematic)
Cosmic Shear
14P5 - April 20, 2006
III. Baryon Acoustic Oscillations (BAO) in the CMB
Characteristic angular scale set by sound horizon at recombination: standard ruler (geometric probe).
15P5 - April 20, 2006
Baryon Acoustic Oscillations: CMB & Galaxies
CMBAngularPowerSpectrum
SDSS galaxycorrelation function
Acoustic series in P(k) becomes a single peak in (r)
Bennett, etal
Eisenstein etal
16P5 – April 20, 2006
BAO in DES: Galaxy Angular Power Spectrum
Probe substantially larger volume and redshift range than SDSS
Wiggles due to BAO
Blake & BridleFosalba & Gaztanaga
17P5 – April 20, 2006
IV. Supernovae• Geometric Probe of Dark Energy
• Repeat observations of 40 deg2 , using 10% of survey time
• ~1900 well-measured SN Ia lightcurves, 0.25 < z <
0.75
• Larger sample, improved z-band response compared to ESSENCE, SNLS; address issues they raise
• Improved photometric precision via in-situ photometric response measurements SDSS
18P5 – April 20, 2006
DES Forecasts: Power of Multiple Techniques
Ma, Weller, Huterer, etal
Assumptions:Clusters: 8=0.75, zmax=1.5,WL mass calibration(no clustering)
BAO: lmax=300WL: lmax=1000(no bispectrum)
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
19P5 – April 20, 2006
• 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 (PanSTARRS is in the Northern hemisphere; cannot be done with existing facilities in the South)
DES and a Dark Energy Program
20P5 – April 20, 2006
Extra Slides
P5 – April 20, 2006
Spectroscopic Redshift Training Sets for DES
Redshift SurveyNumber 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)
P5 – April 20, 2006
DES Cluster Photometric Redshift Simulations
DES:for clusters,(z) < 0.02 for z <1.3
DES+VDESgriz+JK on VISTA:extend photo-z’s toz~2(enhances, but not critical to, science goals)
P5 – April 20, 2006
Variance and Bias of Photo-z Estimates
Cunha etal
Variance Bias
P5 – April 20, 2006
Photo-z Error Distributions & Error Estimates
P5 – April 20, 2006
Robustly Reducing Catastrophic Errors
Remove 10% of objects via color cuts 30% improvement
Original 10% Cut
P5 – April 20, 2006
Clusters and Photo-z Systematics
27P5 – April 20, 2006
Weak Lensing & Photo-z Systematics
Ma
(w0)/(w0|pz fixed) (wa)/(wa|pz fixed)
28P5 – April 20, 2006
BAO & Photo-z Systematics
Ma
(w0)/(w0|pz fixed)
(wa)/(wa|pz fixed)
29P5 – April 20, 2006
Supernovae and photo-z errors
Huterer
30P5 - April 20, 2006
Improving Corrections for Anisotropic PSF
Whisker plots for three BTC camera exposures; ~10% ellipticity Left and right are most extreme variations, middle is more typical. Correlated variation in the different exposures: PCA analysis -->
can use stars in all the images: much better PSF interpolation
Focus too lowFocus (roughly) correctFocus too high
Jarvis and Jain
31P5 - April 20, 2006
PCA Analysis
Remaining ellipticities are essentially uncorrelated. Measurement error is the cause of the residual shapes. 1st improvement: higher order polynomial means PSF accurate to smaller scales 2nd: Much lower correlated residuals on all scales
Focus too lowFocus (roughly) correctFocus too high
32P5 – April 20, 2006
Image
Lensing ClusterSource
Tangential shear
33P5 – April 20, 2006
Statistical Weak Lensing by Galaxy Clusters
Mean
Tangential
Shear
Profile
in Optical
Richness
(Ngal) Bins
to 30 h-1Mpc
Sheldon,
Johnston, etal
SDSS preliminary
34P5 – April 20, 2006
Johnston, Sheldon, etalSDSS preliminary
Invert Mean Shear Profile to obtain Mean Mass Profile
Virial Mass
Vir
ial r
adiu
s
35P5 – April 20, 2006
Precision Cosmology with Clusters
• 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: O =g(M)
Primary systematic: Uncertainty in bias & scatter of mass-
observable relation
Sensitivity to Mass Threshold
dN(z)
dzd c
H z dA2 1 z 2 dM
dn M,z dM
f M 0
Massthreshold
36P5 – April 20, 2006
Forecasts for Constant w Models(DE) (w)
37P5 – April 20, 2006
Forecasts with WMAP Priors(w0) (wa)