Probing Dark Energy

Josh Frieman

PASCOS, Ohio State University, Sept. 10, 2006 PASCOS – Sept. 10, 2006 1

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/  <  1/3 and its relative contribution to the present density of the Universe: Special case: cosmological constant:

w

=  1  DE PASCOS – Sept. 10, 2006 2

What is the Nature of the Dark Energy?

Stress-Energy: Gravity: Inhomogeneity: G  = 8  G [T  (matter) + T  (dark energy)] G  + f(g  ) = 8  G T  (matter) (e.g., branes) Key Experimental Questions: 1. Is DE observationally distinguishable from a cosmological constant, for which T  (vacuum) =  g  /3, i.e.,

w

=—1 ? 2. Can we distinguish between gravity and stress-energy?

Combine geometric with structure-growth probes 3. Does dark energy evolve:

w

=

w

(

z

) ?

PASCOS – Sept. 10, 2006 3



Probing Dark Energy

• Probe dark energy through the history of the expansion rate: • • • • • •

H

2 (

z

)

H

0 2  

m

(1 

z

) 3  

DE

  

w

(

z

))

d

ln(1 

z

)    1  

m

 

DE

  1 

z

 2 and the growth of large-scale structure:

w

(

z

)     

w

0 

w a

(1 

a

)  ...

Geometric tests: Comoving distance Weak Lensing Standard Candles  Standard Rulers Baryon Oscillations Standard Population Clusters 

r

(

z

) 

d L

  

F

     1 

dz

    

z



r

(

z

)

d A

    1 

z

  1

r

(

z

)

dV dzd

 

r

2 (

z

)

H

(

z

) 4 PASCOS – Sept. 10, 2006 

Assuming flat Universe and

w a

=0

Constraints on

Constant

Dark Energy Equation of State

CFHT SNLS+ SDSS BAO Astier etal 05 Eisenstein etal 05 PASCOS – Sept. 10, 2006 5

Constraints on Time-varying Dark Energy 3-parameter Model Substantially weaker Jarvis etal 05 Assumes flat Universe PASCOS – Sept. 10, 2006 6

Scalar Field Dark Energy

 If Dark Energy is due to a scalar field, j , evolving in a potential, V( j ): j   3

H

j   

V

' V j  Density & pressure:  

P

 1 2 j  2 1 2 j  2 

V

( j ) 

V

( j ) j 7 PASCOS – Sept. 10, 2006

Scalar Field Dark Energy

aka quintessence General features: V j m eff < 3H 0 ~ 10 -33 eV (

w

< 0) (Potential < Kinetic Energy) (10 –3 eV) 4 V ~ m 2 j 2 ~  crit ~ 10 -10 eV 4 j ~ 10 28 eV ~ M Planck 10 28 eV Ultra-light particle: Dark Energy hardly clusters, nearly smooth Equation of state: usually,

w

Hierarchy problem: Why m/  Weak coupling: >  1 and evolves in time ~ 10  61 ?

Quartic self-coupling   < 10  122 j

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 Today  DE ~ a -3(1+

w

) a(t)

V

Scalar Field Models & Coincidence

`Dynamics’ models (Freezing models) `Mass scale’ models (Thawing models) V e.g., e –  or  –n M Pl Runaway potentials DE/matter ratio constant (Tracker Solution) j Ratra & Peebles; Caldwell, Steinhardt,etal; Albrecht etal,… j Pseudo-Nambu Goldstone Boson Low mass protected by symmetry (Cf. axion) JF, Hill, Stebbins, Waga V( j ) = M 4 [1+cos( j /f)] f ~ M Planck M ~ 0.001 eV ~ m 

Goal for ~2012: SPT+DES Caldwell & Linder Goal for ~2015+: JDEM, LSST

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 PASCOS – Sept. 10, 2006 12

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 PASCOS – Sept. 10, 2006 13

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) Time PASCOS – Sept. 10, 2006 14

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 PASCOS – Sept. 10, 2006

Published Light Curves for Nearby Supernovae More, Better needed 16

Supernovae Cf. Y.B.

On-going SN surveys (200) Future Surveys: PanSTARRS, DES, JDEM, LSST (2000) (3000) (10 5 ) high-z 17

Supernovae: the JDEM Future

• • Goal: Determine

w 0

to ~5% and

w a

• Statistical Requirement: ~1% to ~20% (combined with CMB)

relative

distance measurements (2% flux) in  z~0.1 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,… 18

Probing Dark Energy Evolution: 2% Mag Systematic Error Floors 3000 SNe JF, Huterer, Linder, Turner 03 19

Can we get there? Systematics Concerns

e.g., Luminosity Evolution: We believe SNe Ia at z~0.5 are not intrinsically ~25% fainter than nearby SNe (the basis for Dark Energy). Could SNe at z~1.5 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 Not (yet)

assuming

these exhaust the parameters that control L peak .

guaranteed PASCOS – Sept. 10, 2006 by SN theory

PASCOS – Sept. 10, 2006 21

SDSS II Supernova Survey Sept-Nov. 2005-7

• Obtain ~200

high-quality

SNe Ia light curves in the `redshift desert’ z~0.05-0.35: 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 22

SDSS 2.5 meter Telescope

24

Composite gri images Before

SN 2005 gb

After z = 0.086, confirmed at ARC 3.5m

Preliminary gri light curve and fit from low-z templates 25

SDSS II:

~130 spectroscopically confirmed Type Ia Supernovae from the Fall 2005 Season First Results aiming for Jan. 07 AAS 26

27

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 QuickTime™ and a TIFF (LZW) decompressor are needed to see this picture.

PASCOS – Sept. 10, 2006 28

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 PASCOS – Sept. 10, 2006 29

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 PASCOS – Sept. 10, 2006 30

Growth of Density Perturbations Flat, matter-dominated w = –1 w = -0.7

Volume Element Raising

w

at fixed 

DE

: decreases growth rate of density perturbations and decreases volume surveyed PASCOS – Sept. 10, 2006 31

Clusters and Dark Energy

•Requirements 1.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)

Number of clusters above observable mass threshold Dark Energy equation of state

dN

(

z

)

dzd

 

dV dz d

   Primary systematic: Uncertainty in bias & scatter of mass-observable relation  Volume Growth (geometry) PASCOS – Sept. 10, 2006 32 Mohr

Clusters and Dark Energy

•Requirements 1.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)

Number of clusters above observable mass threshold Dark Energy equation of state

dN

(

z

)

dzd

 

dV dz d

   Primary systematic: Uncertainty in bias & scatter of mass-observable relation  Volume Growth (geometry) PASCOS – Sept. 10, 2006 33 Mohr

Clusters form hierarchically

z = 7

dark matter

z = 5 z = 3

z = 0.5

time

z = 0 z = 1 Kravtsov PASCOS – Sept. 10, 2006 5 Mpc 34

Theoretical Abundance of Dark Matter Halos Warren et al ‘05 

n

(

z

)   

M

min (

dn

/

d

ln

M

)

d

ln

M

PASCOS – Sept. 10, 2006 Warren etal 35

Clusters and Dark Energy

•Requirements 1.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)

Number of clusters above observable mass threshold Dark Energy equation of state

dN

(

z

)

dzd

 

dV dz d

   Primary systematic: Uncertainty in bias & scatter of mass-observable relation  Volume Growth (geometry) PASCOS – Sept. 10, 2006 36 Mohr

Cluster Selection

• • • • • 4 Techniques for Cluster Selection: Optical galaxy concentration Weak Lensing Sunyaev-Zel’dovich effect (SZE) X-ray PASCOS – Sept. 10, 2006 37

PASCOS – Sept. 10, 2006 Holder 38

Clusters and Dark Energy

•Requirements 1.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)

Number of clusters above observable mass threshold Dark Energy equation of state

dN

(

z

)

dzd

 

dV dz d

   Primary systematic: Uncertainty in bias & scatter of mass-observable relation  Volume Growth (geometry) PASCOS – Sept. 10, 2006 39 Mohr

Photometric Redshifts

Elliptical galaxy spectrum • 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.

PASCOS – Sept. 10, 2006 40

Galaxy Photo-z Simulations

DES +VDES JK griz filters 10  Limiting Magnitudes i r g z 24.6

24.1

24.0

23.9

ESO VISTA 4-m enhances science reach +2% photometric calibration error added in quadrature Key: Photo-z systematic errors under control using

existing

spectroscopic training sets to DES photometric depth Improved Photo-z & Error Estimates and robust methods of outlier rejection PASCOS – Sept. 10, 2006 Cunha, etal 41

Clusters and Dark Energy

•Requirements 1.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)

Number of clusters above observable mass threshold Dark Energy equation of state

dN

(

z

)

dzd

 

dV dz d

   Primary systematic: Uncertainty in bias & scatter of mass-observable relation  Volume Growth (geometry) PASCOS – Sept. 10, 2006 42 Mohr



Precision Cosmology with Clusters?

Sensitivity to Mass Threshold Effect of Uncertainty in mass-observable relation

dN

(

z

)

dzd

 

c

 

d

2

A

 1 

z

 2  

dM

0 PASCOS – Sept. 10, 2006  ,

z



dM

Mass threshold 43

Cluster Mass Estimates

• • 4 Techniques for Cluster Mass Estimation: • Optical galaxy concentration • • Weak Lensing Sunyaev-Zel’dovich effect (SZE) • X-ray Cross-compare these techniques to reduce systematic errors Additional cross-checks: shape of mass function; cluster correlations PASCOS – Sept. 10, 2006 44

SZE vs. Cluster Mass: Progress toward Realistic Simulations



∆ Adiabatic Cooling+Star Formation

small (~10%) scatter Kravtsov Integrated SZE flux decrement depends only on cluster mass: insensitive to details of gas dynamics/galaxy formation in the cluster core robust scaling relations PASCOS – Sept. 10, 2006 Nagai Motl, etal 45

Gravitational Lensing by Clusters

PASCOS – Sept. 10, 2006 46

Weak Lensing of Faint Galaxies: distortion of shapes Background Source shape

Weak Lensing of Faint Galaxies: distortion of shapes Foreground Cluster Note: the effect has been greatly exaggerated here Background Source shape

Lensing of real (elliptically shaped) galaxies Foreground Cluster Co-add signal around a number of Clusters Background Source shape

Mean Tangential Shear Profile in Optical Richness (N gal ) Bins to 30 h -1 Mpc Sheldon, Johnston, etal SDSS Statistical Weak Lensing by Galaxy Clusters PASCOS – Sept. 10, 2006 50

Statistical Weak Lensing Calibrates Cluster Mass vs. Observable Relation Cluster Mass vs. Number of galaxies they contain SDSS Data Preliminary z<0.3

Future: use this to independently calibrate, e.g., SZE vs. Mass Johnston, Sheldon, etal, in preparation PASCOS – Sept. 10, 2006 Statistical Lensing eliminates projection effects of individual cluster mass estimates Johnston, etal astro-ph/0507467 51

Dark Energy Survey + South Pole Telescope

See also: APEX, ACT,… Blanco 4-m Optical Telescope at CTIO: 5000 sq. deg. Dark Energy Survey PASCOS – Sept. 10, 2006 Dec 2005 10-m South Pole Telescope: 4000 sq. deg. SZE Survey 52

The Dark Energy Survey

• Study Dark Energy using 4 complementary* techniques: I. Cluster Counts II. Weak Lensing III. Baryon Acoustic Oscillations IV. Supernovae Blanco 4-meter at CTIO • Two multiband surveys: 5000 deg 2 40 deg 2

g, r, i, z

repeat (SNe) • Build new 3 deg 2 camera and Data management sytem Survey 2009-2015 (525 nights) Response to NOAO AO *in systematics & in cosmological parameter degeneracies *geometric+structure growth: test Dark Energy vs. Gravity PASCOS – Sept. 10, 2006 53

F8 Mirror

The DES Instrument: DECam

Filters Shutter 3556 mm CCD Read out Hexapod Optical Lenses 1575 mm PASCOS – Sept. 10, 2006

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 PASCOS – Sept. 10, 2006 55

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 PASCOS – Sept. 10, 2006 56

Weak lensing: shear and mass PASCOS – Sept. 10, 2006 Jain 57

Weak Lensing Tomography

•Cosmic Shear Angular Power Spectrum in 4 Photo-z Slices • Future: Shapes of 10 8 10 9 galaxies Statistical errors shown •Primary Systematics: photo-z’s, PSF anisotropy, shear calibration Huterer 58 PASCOS – Sept. 10, 2006

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 --> can use stars in all the images: much better PSF interpolation Jarvis and Jain PASCOS – Sept. 10, 2006

PCA Analysis: Improved Systematics Reduction Focus too low Focus (roughly) correct Focus too high • 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 PASCOS – Sept. 10, 2006

Cosmic Shear Reducing WL Shear Systematics (signal) (old systematic) (improved systematic) Red: expected signal Results from 75 sq. deg. WL Survey with Mosaic II and BTC on the Blanco 4-m Bernstein, etal DECam+Blanco hardware improvements that will reduce raw lensing systematics DES: comparable depth: source galaxies well resolved & bright: low-risk PASCOS - Sept. 10, 2006 61

The Large Synoptic Survey Telescope (LSST) Time-Domain Astronomy survey visible sky every few nights Weak Lensing Cluster Counts Galaxy Clustering ….

62

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 PASCOS – Sept. 10, 2006 63

Baryon Acoustic Oscillations (BAO) in the CMB  Characteristic angular scale set by sound horizon at recombination: standard ruler (geometric probe).

64 PASCOS - Sept. 10, 2006

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 t rec late-time amplitude.

affects Ionized Recombination z ~ 1000 ~400,000 years Time Neutral

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

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.

Baryon Acoustic Oscillations: CMB & Galaxies CMB Angular Power Spectrum Acoustic series in

P

(

k

) becomes a single peak in  (

r

) SDSS galaxy correlation function Bennett, etal PASCOS - Sept. 10, 2006 Eisenstein etal 68

Baryon Oscillations In the Matter Power Spectrum Future: HETDEX WFMOS `SDSS III’ Seo & Eisenstein Hu & Haiman

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: DES+SPT, PANSTARRS,…, followed by LSST and JDEM • Exploiting complementarity of multiple probes will be key: we don’t 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.

PASCOS – Sept. 10, 2006 70