probing dark energy

1PASCOS – Sept. 10, 2006

Probing Dark Energy

Josh Frieman

PASCOS, Ohio State University, Sept. 10, 2006

PASCOS – Sept. 10, 2006 2

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/<1/3and its relative contribution to the present density of the Universe: DE

Special case: cosmological constant: w = 1

Dark Energy and the Accelerating Universe

3PASCOS – Sept. 10, 2006

What is the Nature of the Dark Energy?

Stress-Energy: G = 8G [T(matter) + T(dark energy)]

Gravity: G + f(g) = 8G 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: w=w(z)?

4PASCOS – Sept. 10, 2006

• 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

Probing Dark Energy

€

H 2(z)

H02

= Ωm (1+ z)3 + ΩDE exp 3 (1+ w(z))d ln(1+ z)∫[ ] + 1− Ωm − ΩDE( ) 1+ z( )2

€

δ a( )ρ

€

w(z) = w0 + wa (1− a) + ...

€

r(z) = Fdz

H z( )∫ ⎡

⎣ ⎢

⎤

⎦ ⎥

dL z( ) = 1+ z( )r(z)

dA z( ) = 1+ z( )−1

r(z)

dV

dzdΩ=

r2(z)

H(z)

5PASCOS – Sept. 10, 2006

Constraints

on Constant

Dark Energy

Equation of State

CFHT SNLS+

SDSS BAO

Astier etal 05

Eisenstein etal 05

Assuming flat Universe and wa=0

6PASCOS – Sept. 10, 2006

Constraints

on

Time-varying

Dark Energy

3-parameter

Model

Substantially

weaker

Jarvis etal 05

Assumes flat

Universe

7PASCOS – Sept. 10, 2006

Scalar Field Dark Energy

If Dark Energy is due to a scalar field, , evolving in a potential, V():

Density & pressure:

)(

)(2

21

221

ϕϕ

ϕϕ

VP

V

−=

+=

&

&

'3 VH −=+ ϕϕ &&&

V

Scalar Field Dark Energy

Ultra-light particle: Dark Energy hardly clusters, nearly smoothEquation of state: usually, w > 1 and evolves in timeHierarchy problem: Why m/ϕ ~ 1061?Weak coupling: Quartic self-coupling ϕ < 10122

General features:

meff < 3H0 ~ 10-33 eV (w < 0)(Potential < Kinetic Energy)

V ~ m22 ~ crit ~ 10-10 eV4

~ 1028 eV ~ MPlanck

aka quintessence

V

1028 eV

(10–3 eV)4

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(1+w)

a(t)Today

Scalar Field Models & Coincidence

VV

Runaway potentialsDE/matter ratio constant(Tracker Solution)

Pseudo-Nambu Goldstone BosonLow mass protected by symmetry

(Cf. axion) JF, Hill, Stebbins, Waga V() = M4[1+cos(/f)]

f ~ MPlanck M ~ 0.001 eV ~ m

e.g., e–ϕ or ϕ–n

MPl

Ratra & Peebles; Caldwell, Steinhardt,etal; Albrecht etal,…

`Dynamics’ models

(Freezing models)

`Mass scale’ models

(Thawing models)

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

Goal for ~2012: SPT+DES

12PASCOS – Sept. 10, 2006

Probing Dark EnergyPrimary 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

13PASCOS – Sept. 10, 2006

Probing Dark EnergyPrimary 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

14PASCOS – Sept. 10, 2006

Type Ia SNPeak Brightnessas a calibrated`Standard’ Candle

Peak brightnesscorrelates with decline rate

Phillips 1993

After correction,~ 0.15 mag(~7% distance error)

Luminosity

Time

PASCOS – Sept. 10, 2006

Supernova

Hubble

Diagram

CFHT Supernova

Legacy Survey

Astier etal 05

Needed: more, better

data at low and

Intermediate redshift

KAIT, SNF, CSP, CfA

SDSSESSENCE, SNLS

16

Published Light Curves for Nearby Supernovae

More,

Better

needed

17

On-going SN surveys

Future Surveys:

PanSTARRS, DES, JDEM, LSST

(200)

(2000) (3000) (105)

high-z

Supernovae

Cf. Y.B.

18

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 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,…

19

Probing Dark Energy Evolution: 2% Mag Systematic Error Floors

JF, Huterer, Linder, Turner 03

3000 SNe

PASCOS – Sept. 10, 2006

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

assuming these exhaust the parameters that control Lpeak.

Can we get there? Systematics Concerns

Not (yet)guaranteedby SN theory

21PASCOS – Sept. 10, 2006

22

SDSS II Supernova SurveySept-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

SDSS 2.5 meter Telescope

24

25

SN 2005 gb

z = 0.086, confirmed at ARC 3.5mPreliminary gri light curve and fit from low-z templates

Before After

Composite gri

images

26

SDSS II:~130

spectroscopically

confirmed

Type Ia

Supernovae

from the

Fall 2005

Season

First Results

aiming for

Jan. 07 AAS

27

28PASCOS – Sept. 10, 2006

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 aTIFF (LZW) decompressor

are needed to see this picture.

29PASCOS – Sept. 10, 2006

Probing Dark EnergyPrimary 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

30PASCOS – Sept. 10, 2006

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 formationParameters

Methods: WL, Clusters

31PASCOS – Sept. 10, 2006

Growth of Density Perturbations Volume Element

Flat, matter-dominated

w = -0.7w = –1

Raising w at fixed DE: decreases growth rate of

density perturbations and decreases volume surveyed

32PASCOS – Sept. 10, 2006

Clusters and Dark Energy

MohrVolume Growth(geometry)

Number of clusters above observable mass threshold

Dark Energy equation of state

€

dN(z)

dzdΩ=

dV

dz dΩn 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

33PASCOS – Sept. 10, 2006

Clusters and Dark Energy

MohrVolume Growth(geometry)

Number of clusters above observable mass threshold

Dark Energy equation of state

€

dN(z)

dzdΩ=

dV

dz dΩn 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

34PASCOS – Sept. 10, 2006

Clusters form hierarchically

z = 7 z = 5 z = 3

z = 1 z = 0.5 z = 0

5 Mpc

dark matterdark matter

timetime

Kravtsov

35PASCOS – Sept. 10, 2006

Theoretical Abundance of Dark Matter Halos

Warren et al ‘05

Warren etal

€

n(z) = (dn /d ln M)d ln MM min

∞

∫

36PASCOS – Sept. 10, 2006

Clusters and Dark Energy

MohrVolume Growth(geometry)

Number of clusters above observable mass threshold

Dark Energy equation of state

€

dN(z)

dzdΩ=

dV

dz dΩn 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

37PASCOS – Sept. 10, 2006

Cluster Selection

• 4 Techniques for Cluster Selection:

• Optical galaxy concentration

• Weak Lensing

• Sunyaev-Zel’dovich effect (SZE)

• X-ray

38PASCOS – Sept. 10, 2006Holder

39PASCOS – Sept. 10, 2006

Clusters and Dark Energy

MohrVolume Growth(geometry)

Number of clusters above observable mass threshold

Dark Energy equation of state

€

dN(z)

dzdΩ=

dV

dz dΩn 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

40PASCOS – Sept. 10, 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.

Elliptical galaxy spectrum

41PASCOS – Sept. 10, 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

42PASCOS – Sept. 10, 2006

Clusters and Dark Energy

MohrVolume Growth(geometry)

Number of clusters above observable mass threshold

Dark Energy equation of state

€

dN(z)

dzdΩ=

dV

dz dΩn 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

43PASCOS – Sept. 10, 2006

Precision Cosmology with Clusters?

Effect of Uncertainty inmass-observable relation

Sensitivity to Mass Threshold

€

dN(z)dzdΩ

= cH z( )

dA2 1+z( )2 dM

dnM,z( )

dMf M( )

0

∞∫ Mass

threshold

44PASCOS – Sept. 10, 2006

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

45PASCOS – Sept. 10, 2006

SZE vs. Cluster Mass: Progress toward 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

SZE

Obs

erva

ble

Kravtsov

small (~10%) scatter

46PASCOS – Sept. 10, 2006

Gravitational Lensing by Clusters

Weak Lensing of Faint Galaxies: distortion of shapes

BackgroundSourceshape

ForegroundCluster

Weak Lensing of Faint Galaxies: distortion of shapes

BackgroundSourceshape

Note: the effect has been greatly exaggerated here

ForegroundCluster

Lensing of real (elliptically shaped) galaxies

Co-add signal around a number of Clusters

BackgroundSourceshape

50PASCOS – Sept. 10, 2006

Statistical Weak Lensing by Galaxy Clusters

Mean

Tangential

Shear

Profile

in Optical

Richness

(Ngal) Bins

to 30 h-1Mpc

Sheldon,

Johnston, etal

SDSS

51PASCOS – Sept. 10, 2006

Statistical Weak Lensing CalibratesCluster Mass vs. Observable Relation

Cluster Massvs. Number of galaxies they contain

Future:use this to independently calibrate, e.g., SZE vs. Mass

Johnston, Sheldon, etal, in preparation

Statistical Lensing eliminates projection effectsof individual cluster massestimates

Johnston, etalastro-ph/0507467

SDSS DataPreliminaryz<0.3

52PASCOS – Sept. 10, 2006

Dark Energy Survey + South Pole Telescope

10-m South Pole Telescope: 4000 sq. deg. SZE Survey

Dec 2005

Blanco 4-m Optical Telescope at CTIO: 5000 sq. deg. Dark Energy Survey

See also: APEX, ACT,…

53PASCOS – Sept. 10, 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

PASCOS – Sept. 10, 2006

The DES Instrument: DECam

3556 mm

1575 mm

Hexapod

Optical Lenses

F8 Mirror

CCDRead out

Filters Shutter

55PASCOS – Sept. 10, 2006

Probing Dark EnergyPrimary 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

56PASCOS – Sept. 10, 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

Weak Lensing: Cosmic Shear

57PASCOS – Sept. 10, 2006

Weak lensing: shear and mass

Jain

58PASCOS – Sept. 10, 2006

•Cosmic Shear Angular Power Spectrum in 4 Photo-z Slices

•Future: Shapes of 108-109 galaxies

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

Weak Lensing Tomography

Huterer

Statistical errorsshown

PASCOS – Sept. 10, 2006

Weak Lensing Systematics:

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

PASCOS – Sept. 10, 2006

PCA Analysis: Improved Systematics Reduction

• 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

Jarvis and Jain

61PASCOS - Sept. 10, 2006

Reducing WL Shear Systematics

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)

(old systematic)

Cosmic Shear

62

The Large Synoptic Survey Telescope

(LSST)

Time-Domain Astronomy

survey visible sky every few

nights

Weak Lensing

Cluster Counts

Galaxy Clustering

….

63PASCOS – Sept. 10, 2006

Probing Dark EnergyPrimary 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

64PASCOS - Sept. 10, 2006

Baryon Acoustic Oscillations (BAO) in the CMB

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

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.

Big

Bang T

oday

Recombinationz ~ 1000

~400,000 yearsIonized Neutral

Time

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.

68PASCOS - Sept. 10, 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

BaryonOscillationsIn theMatter PowerSpectrum

Future:HETDEXWFMOS`SDSS III’

Seo &Eisenstein

Hu &Haiman

70PASCOS – Sept. 10, 2006

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.