Probing Dark Energy

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Probing Dark Energy

• Josh Frieman

PASCOS, Ohio State University, Sept. 10, 2006
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Dark Energy and the Accelerating Universe
Brightness of distant Type Ia supernovae, along
with CMB and galaxy clustering data,
indicates the expansion of the Universe is
accelerating, not decelerating. This requires
either a new form of stress-energy with negative
effective pressure or a breakdown of General
Relativity at large distances
DARK ENERGY Characterize by its
effective equation of state w p/?lt?1/3 and
its relative contribution to the present
density of the Universe
?DE Special case cosmological
constant w ?1
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What is the Nature of the Dark Energy?

• Stress-Energy G?? 8?G T??(matter)
  T??(dark energy)
• Gravity G?? f(g??) 8?G
  T??(matter) (e.g., branes)
• Inhomogeneity
• Key Experimental Questions
• Is DE observationally distinguishable from a
  cosmological
• constant, for which T?? (vacuum)
  ?g??/3, i.e., w 1?
• Can we distinguish between gravity and
  stress-energy?
• Combine geometric with structure-growth
  probes
• Does dark energy evolve ww(z)?

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Probing Dark Energy

• Probe dark energy through the history of the
  expansion rate
• and the growth of large-scale structure
• Parametrize DE Evolution
  
• Geometric tests
• Comoving distance Weak Lensing
  
• Standard Candles Supernovae
  
• Standard Rulers Baryon Oscillations
• Standard Population Clusters

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Assuming flat Universe and wa0
Constraints on Constant Dark Energy Equation of
State CFHT SNLS SDSS BAO Astier etal
05 Eisenstein etal 05
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Constraints on Time-varying Dark
Energy 3-parameter Model Substantially
weaker Jarvis etal 05
Assumes flat Universe
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Scalar Field Dark Energy

• If Dark Energy is due to a scalar field, j,
  evolving in a potential, V(j)
• Density pressure

V(j)
j
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Scalar Field Dark Energy
aka quintessence
General features meff lt 3H0 10-33 eV (w lt
0) (Potential lt Kinetic Energy) V m2?2
?crit 10-10 eV4 ? 1028 eV MPlanck
V(j)
(103 eV)4
j
1028 eV
Ultra-light particle Dark Energy hardly
clusters, nearly smooth Equation of state
usually, w gt ?1 and evolves in time Hierarchy
problem Why m/? 10?61? Weak coupling
Quartic self-coupling ?? lt 10?122
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The Coincidence Problem
Why do we live at the special epoch when the
dark energy density is comparable to the matter
energy density?
?matter a-3
?DE a-3(1w)
a(t)
Today
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Scalar Field Models Coincidence
Dynamics models (Freezing models)
Mass scale models (Thawing models)
V
V
e.g., e? or ?n
?
?
MPl
Runaway potentials DE/matter ratio
constant (Tracker Solution)
Pseudo-Nambu Goldstone Boson Low mass protected
by symmetry (Cf. axion) JF, Hill, Stebbins,
Waga V(?) M41cos(?/f) f MPlanck M
0.001 eV m?
Ratra Peebles Caldwell, Steinhardt,etal
Albrecht etal,
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Goal for 2012 SPTDES
Goal for 2015 JDEM, LSST
Caldwell Linder
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Probing Dark Energy

• Primary Techniques identified by the
• Dark Energy Task Force report
• Supernovae
• Galaxy Clusters
• Weak Lensing
  
• Baryon Acoustic Oscillations
• Multiple Techniques needed complementary in
  systematics
• and in science reach

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Probing Dark Energy

• Primary Techniques identified by the
• Dark Energy Task Force report
• Supernovae
• Galaxy Clusters
• Weak Lensing
  
• Baryon Acoustic Oscillations
• Multiple Techniques needed complementary in
  systematics
• and in science reach

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• Type Ia SN
• Peak Brightness
• as a calibrated
• Standard Candle
• Peak brightness
• correlates with
• decline rate
• Phillips 1993
• After correction,
• ? 0.15 mag
• (7 distance error)

Luminosity
Time
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Supernova Hubble Diagram CFHT Supernova Legacy
Survey Astier etal 05 Needed more, better
data at low and Intermediate redshift
KAIT, SNF, CSP, CfA
SDSS
ESSENCE, SNLS
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Published Light Curves for Nearby Supernovae
More, Better needed
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Supernovae
Cf. Y.B.
On-going SN surveys
(200)
Future Surveys PanSTARRS, DES, JDEM, LSST

(2000) (3000) (105) high-z
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Supernovae the JDEM Future

• Goal Determine w0 to 5 and wa to 20
  (combined with CMB)
• Statistical Requirement 1 relative distance
  measurements
• (2 flux) in ?z0.1 redshift bins
• Assume systematic error can be reduced to this
  level
• Kim, etal 04, Kim Miquel 05
  
• Require 3000 SNe spread over z 0.3-1.7 and a
• well-observed sample at low z to
  anchor the Hubble
• diagram. Consequent requirements
  for NIR imaging and
• photometric stability lead to a
  space-based mission.
• Proposals SNAP, DESTINY, JEDI,

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Probing Dark Energy Evolution 2 Mag Systematic
Error Floors
3000 SNe
JF, Huterer, Linder, Turner 03
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Can we get there? Systematics Concerns
e.g., Luminosity Evolution We believe
SNe Ia at z0.5 are not intrinsically 25
fainter than nearby SNe (the basis for
Dark Energy). Could SNe at z1.5 be 2
fainter/brighter than those nearby, in a way that
leaves all other observables fixed?
Key Many observables per SN which needed?
Expectation drift in progenitor population mix
(progenitor mass, age, metallicity, C/O,
accretion rates, etc). Control the variety of
host environments at low redshift spans a
larger range of metallicity, environment, than
the median differences between low- and
high-z environments, so we can compare
high-z apples with low-z apples, using host
info., LC shape, colors, spectral
features spectral evolution, and
assuming these exhaust the parameters that
control Lpeak.
Not (yet) guaranteed by SN theory
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SDSS II Supernova SurveySept-Nov. 2005-7

• Obtain 200 high-quality SNe Ia light curves in
  the redshift desert z0.05-0.35 continuous
  Hubble diagram
• Probe Dark Energy in z regime less sensitive to
  evolution than, and complementary to, deeper
  surveys
• Study SN Ia systematics with high photometric
  accuracy

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SDSS 2.5 meter Telescope
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SN 2005 gb
Composite gri images
Before
After
z 0.086, confirmed at ARC 3.5m
Preliminary gri light curve and fit from low-z
templates
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SDSS II 130 spectroscopically confirmed Type
Ia Supernovae from the Fall 2005 Season First
Results aiming for Jan. 07 AAS
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Unusual SN 2005gj

• Followed this object all semester with MDM
• 12 observations
• Type Ia strongly interacting with CSM
• Only 1 other object like this
• 2002ic
• Prieto et al. 2006 (in preparation)
• Spitzer observations

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Probing Dark Energy

• Primary Techniques identified by the
• Dark Energy Task Force report
• Supernovae
• Galaxy Clusters
• Weak Lensing
  
• Baryon Acoustic Oscillations
• Multiple Techniques needed complementary in
  systematics
• and in science reach

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Evolution of Structure Robustness of the
paradigm recommends its use as a Dark Energy
probe Price additional cosmological and
structure formation parameters Bonus additional
structure formation Parameters Methods WL,
Clusters
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w 1
Growth of Density Perturbations
Volume Element
Flat, matter-dominated

• w -0.7

Raising w at fixed WDE decreases growth rate of
density perturbations and decreases volume
surveyed
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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 (geometry)
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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 (geometry)
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Clusters form hierarchically
z 7
z 5
z 3
dark matter
time
z 0.5
z 0
z 1
Kravtsov
5 Mpc
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Theoretical Abundance of Dark Matter Halos
Warren etal
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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 (geometry)
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Cluster Selection

• 4 Techniques for Cluster Selection
• Optical galaxy concentration
• Weak Lensing
• Sunyaev-Zeldovich effect (SZE)
• X-ray

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Holder
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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 (geometry)
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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.

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Galaxy Photo-z Simulations
DES griz filters
VDES JK
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
Cunha, etal
Improved Photo-z Error Estimates and robust
methods of outlier rejection
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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 (geometry)
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Precision Cosmology with Clusters?

• Effect of
• Uncertainty in
• mass-observable
• relation

Mass threshold
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Cluster Mass Estimates

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

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SZE vs. Cluster Mass Progress toward Realistic
Simulations
? Adiabatic ? CoolingStar Formation
SZE flux
small (10) scatter

• SZE 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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Gravitational Lensing by Clusters
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Weak Lensing of Faint Galaxies distortion of
shapes
Background Source shape
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Weak Lensing of Faint Galaxies distortion of
shapes
Foreground Cluster
Background Source shape
Note the effect has been greatly exaggerated here
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Lensing of real (elliptically shaped) galaxies
Foreground Cluster
Background Source shape
Co-add signal around a number of Clusters
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Statistical Weak Lensing by Galaxy Clusters
Mean Tangential Shear Profile in
Optical Richness (Ngal) Bins to 30
h-1Mpc Sheldon, Johnston, etal SDSS
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Statistical Weak Lensing Calibrates Cluster Mass
vs. Observable Relation
Cluster Mass vs. Number of galaxies they
contain Future use this to independently
calibrate, e.g., 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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Dark Energy Survey South Pole Telescope
See also APEX, ACT,
Dec 2005
10-m South Pole Telescope 4000 sq. deg. SZE
Survey
Blanco 4-m Optical Telescope at CTIO 5000 sq.
deg. Dark Energy Survey
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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 geometricstructure growth test
Dark Energy vs. Gravity
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The DES Instrument DECam
F8 Mirror
Filters Shutter
3556 mm
CCD Read out
Hexapod
Optical Lenses
1575 mm
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Probing Dark Energy

• Primary Techniques identified by the
• Dark Energy Task Force report
• Supernovae
• Galaxy Clusters
• Weak Lensing
  
• Baryon Acoustic Oscillations
• Multiple Techniques needed complementary in
  systematics
• and in science reach

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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 shear and mass
Jain
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Weak Lensing Tomography

• Cosmic Shear
• Angular Power
• Spectrum in 4
• Photo-z Slices
• Future Shapes of 108-109 galaxies
• Primary Systematics
• photo-zs, PSF anisotropy,
• shear calibration

Statistical errors shown
Huterer
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Weak Lensing Systematics Anisotropic PSF
Focus too low
Focus (roughly) correct
Focus too high

• 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 --gt
• can use stars in all the images much better
  PSF interpolation

Jarvis and Jain
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PCA Analysis Improved Systematics Reduction
Focus (roughly) correct
Focus too high
Focus too low

• 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!

Jarvis and Jain
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Reducing WL Shear Systematics
Cosmic Shear
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)
(old systematic)
(improved systematic)
Red expected signal
DECamBlanco hardware improvements that will
reduce raw lensing systematics

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The Large Synoptic Survey Telescope (LSST)

• Time-Domain Astronomy
• survey visible sky every few
• nights
• Weak Lensing
• Cluster Counts
• Galaxy Clustering
• .

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Probing Dark Energy

• Primary Techniques identified by the
• Dark Energy Task Force report
• Supernovae
• Galaxy Clusters
• Weak Lensing
  
• Baryon Acoustic Oscillations
• Multiple Techniques needed complementary in
  systematics
• and in science reach

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Baryon Acoustic Oscillations (BAO) in the CMB

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

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Sound Waves in the Early Universe

• Before recombination
• Universe is ionized.
• Photons provide enormous pressure and restoring
  force.
• Perturbations oscillate as acoustic waves.

• After recombination
• Universe is neutral.
• Photons can travel freely past the baryons.
• Phase of oscillation at trec affects late-time
  amplitude.

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Sound Waves

• Each initial overdensity (in dark matter gas)
  is an overpressure that launches a spherical
  sound wave.
• This wave travels outwards at 57 of the speed
  of light.
• Pressure-providing photons decouple at
  recombination. CMB travels to us from these
  spheres.
• Sound speed plummets. Wave stalls at a radius of
  150 Mpc.
• Overdensity in shell (gas) and in the original
  center (DM) both seed the formation of galaxies.
  Preferred separation of 150 Mpc.

Eisenstein
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A Statistical Signal

• The Universe is a super-position of these shells.
• The shell is weaker than displayed.
• Hence, you do not expect to see bullseyes in the
  galaxy distribution.
• Instead, we get a 1 bump in the correlation
  function.

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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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Baryon Oscillations In the Matter
Power Spectrum Future HETDEX WFMOS SDSS
III Seo Eisenstein Hu Haiman
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Conclusions

• Excellent prospects for increasing the precision
  on Dark Energy parameters from a sequence of
  increasingly complex and ambitious experiments
  over the next 5-15 years DESSPT, PANSTARRS,,
  followed by LSST and JDEM
• Exploiting complementarity of multiple probes
  will be key we dont know what the ultimate
  systematic error floors for each method will be.
  Combine geometric with structure-growth probes to
  help distinguish modified gravity from dark
  energy.
• What parameter precision is needed to stimulate
  theoretical progress? It depends in large part on
  what the answer is.