The Dark Energy Survey in Context

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The Dark Energy Survey in Context

• Josh Frieman
• Fermilab and University of Chicago

White Papers submitted to Dark Energy Task
Force astro-ph/0510346 Theoretical
Computational Challenges astro-ph/0510194,5
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The Dark Energy Survey
Blanco 4-meter at CTIO

• 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

in systematics in cosmological parameter
degeneracies geometricstructure growth test
Dark Energy vs. Gravity
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Dark Energy Task Force Report

• Established by AAAC and HEPAP as joint
  subcommittee to advise the 3 agencies
• Strongly recommendan aggressive program to
  explore dark energy
• Considered 4 main techniques to study DE (those
  above)
• Defined stages of projects Stage Icompleted
  IIon-going IIInear-term, medium-cost,
  proposed IVLST, SKA, JDEM
• Recommend that theprogram have multiple
  techniques at every stage
• DETF Stage III 4-m telescope BAO photo-z,
  clusters w/ SZE, SNe , WL, i.e., DES and 8-m
  spectroscopic BAO (WFMOS)
• Recommend immediate start of Stage III
• Defined a Figure of Merit for comparing DE
  projects (see below)

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Photometric Redshifts
Elliptical galaxy spectrum
Measure relative flux in four filters
griz track the 4000 A break Estimate
individual galaxy redshifts with accuracy
?(z) lt 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 zgt1

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Galaxy Photo-z Simulations
VDES JK
DES griz filters
DES
DES VDES on ESO VISTA 4-m enhances science reach
10? Limiting Magnitudes g 24.6 r 24.1
i 24.0 z 23.9 2 photometric
calibration error added in quadrature Key
Photo-z systematic errors under control using
existing spectroscopic training sets to DES
photometric depth low-risk
Developed improved Photo-z Error Estimates and
robust methods of outlier rejection
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I. Clusters and Dark Energy
Number of clusters above observable mass
threshold

• Requirements
• Understand formation of dark matter halos
• Cleanly select massive dark matter halos (galaxy
  clusters) over a range of redshifts
• Redshift estimates for each cluster
• Observable proxy that can be used as cluster mass
  estimate
• O g(M)
• Primary systematic
• Uncertainty in bias scatter of mass-observable
  relation

Dark Energy equation of state

Mohr
Volume Growth
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Cluster Cosmology with DES

• 3 Techniques for Cluster Selection and Mass
  Estimation
• Optical galaxy concentration
• Weak Lensing
• Sunyaev-Zeldovich effect (SZE)
• Cross-compare these techniques to reduce
  systematic errors
• Additional cross-checks
• shape of mass function
• cluster correlations

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10-m South Pole Telescope (SPT)

• Sunyaev-Zeldovich effect
• Compton upscattering of CMB photons
• by hot gas in clusters
• - nearly independent of redshift
• - can probe to high redshift
• - need ancillary redshift measurement

SPT will carry out 4000 sq. deg. SZE Survey
PI J. Carlstrom (U. Chicago)
Dec 2005
NSF-OPP funded scheduled for Nov 2006
deployment DOE (LBNL) funding of readout
development
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SZE vs. Cluster Mass Progress in Realistic
Simulations
? Adiabatic ? CoolingStar Formation
SZE flux
small (10) scatter

• SPT Observable

Kravtsov
Nagai
Integrated SZE flux decrement depends only on
cluster mass insensitive to details of gas
dynamics/galaxy formation in the cluster core
robust scaling relations
Motl, etal
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Statistical Weak Lensing Calibrates Cluster Mass
vs. Observable Relation
Cluster Mass vs. Number of galaxies they
contain For DES, will use this to
independently calibrate SZE vs. Mass
SDSS Data Preliminary zlt0.3
Statistical Lensing eliminates projection
effects of individual cluster mass estimates Joh
nston, etal astro-ph/0507467
Johnston, Sheldon, etal, in preparation
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Background sources
Dark matter halos
Observer

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

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Weak Lensing Tomography

• Cosmic Shear Angular
• Power Spectrum in 4
• Photo-z Slices
• Shapes of 300 million
• galaxies, median redshift
• ?z? 0.7
• Primary Systematics
• photo-zs, PSF anisotropy,
• shear calibration

Statistical errors shown
Huterer
DES WL forecasts conservatively assume 0.9 PSF
median delivered to existing Blanco camera
DECam should do better be more stable
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Reducing WL Shear Systematics
Results from 75 sq. deg. WL Survey with Mosaic
II and BTC on the Blanco 4-m Bernstein,
etal DES comparable depth source galaxies
well resolved bright low-risk
(signal)
Cosmic Shear
(old systematic)
(improved systematic)
Red expected signal
DECamBlanco hardware improvements will further
reduce raw lensing systematics

Believe shear systematics under control at level
needed for DES
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III. Baryon Acoustic Oscillations (BAO) in the CMB

• Characteristic angular scale set by sound horizon
  at recombination standard ruler (geometric
  probe).

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Baryon Acoustic Oscillations CMB Galaxies
Acoustic series in P(k) becomes a single peak in
?(r)
CMB Angular Power Spectrum
SDSS galaxy correlation function
Bennett, etal
Eisenstein etal
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BAO in DES Galaxy Angular Power Spectrum
Wiggles due to BAO
Probe larger volume and redshift range than
SDSS Systematics photo-zs, photometric errors
Blake Bridle
Fosalba Gaztanaga
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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 lt z lt 0.75
• Larger sample, improved z-band response compared
  to ESSENCE, SNLS
• Improved photometric precision via in-situ
  photometric response measurements

SDSS
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DES Forecasts Power of Multiple Techniques
w(z) w0wa(1a) 68 CL

Assumptions Clusters ?80.75, zmax1.5, WL
mass calibration (no clustering) BAO
lmax300 WL lmax1000 (no bispectrum) Statistica
lphoto-z systematic errors only Spatial
curvature, galaxy bias marginalized Planck CMB
prior

DETF Figure of Merit inverse area of ellipse

• geometric
• growth

Clusters if ?80.9
geometric
Ma, Weller, Huterer, etal
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DES and the Dark Energy Program

• 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 factor 3-5
  improvement in DETF FOM
• Scientific and technical precursor to the more
  ambitious Stage IV Dark Energy projects to follow
  
• DES in unique international position to synergize
  with SPT (and VISTA) on the DETF Stage III
  timescale

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Extra Slides
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Bias
Variance and Bias of Photo-z Estimates
Variance
Cunha etal
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Clusters and Photo-z Systematics
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Weak Lensing Photo-z Systematics
?(w0)/?(w0pz fixed)
?(wa)/?(wapz fixed)
Ma
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BAO Photo-z Systematics
?(w0)/?(w0pz fixed)
?(wa)/?(wapz fixed)
Ma
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Supernovae and photo-z errors
Huterer
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Forecasts for Constant w Models
?(?DE) ?(w))
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Forecasts with WMAP Priors
?(w0) ?(wa)
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Survey Power (approximate)
Telescope Mirror Diameter (meters) Field of View (deg2) A??
SDSS 2.5 3.9 3
CFHT 3.6 1 4
PanSTARRS 1 PanSTARRS 4 1.8 4x1.8 7 4x7 15 60
DES 4 3 30
LSST 6.5 7 200
Partial Source Pan-STARRS Website