John Peacock Tokyo HSC Workshop Nov 2006

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Systematic challenges in future dark energy
measurements

• John Peacock Tokyo HSC Workshop
  Nov 2006

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ESA-ESO Working Group on Fundamental Cosmology
John Peacock (Chair) Peter Schneider
(Co-Chair) George Efstathiou Jonathan R.
Ellis Bruno Leibundgut Simon Lilly
Yannick Mellier Major
contributors Pierre Astier, Anthony Banday,
Hans Boehringer, Anne Ealet, Martin Haehnelt,
Guenther Hasinger, Paolo Molaro, Jean-Loup Puget,
Bernard Schutz, Uros Seljak, Jean-Philippe Uzan
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Dark Energy Task Force
Report to NSF, DoE, NASA Rocky Kolb Andy Albrecht
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Cosmology Concordance Model

Heavy elements 0.03 Neutrinos 0.3 Stars
0.5 H He gas 4 Dark matter 20 Dark Energy
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• Outstanding questions
• initial conditions (inflation?)
• nature of the dark matter
• nature of the dark energy

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The cosmological parameters
Only 6 parameters needed (flat no gravity
waves)
Normalization Optical depth from
reionization Scalar spectral index Baryon
density (? ? h2) CDM density (? ? h2) H0 /
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WMAP3 2dFGRS
r (tensor fraction), curvature, m? , w P/?
(DE eqn of state) DE is entangled with other
parameters
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The nature of dark energy

• Zero-point energy?
• ) expect ?vac Emax4 (natural units ch1)
• But empirically Emax 2.4 meV - not a real
  cutoff
• (2) Dynamical Dark Energy
• Quintessence use inflationary technology of
  wlt0 from scalar fields
• Empirical w P/? c2 ( -1?) fit w(a) w0
  wa(1-a)

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Dark Energy sensitivity degeneracy
distance

• Vacuum affects H(z)
• H2(z) H20 ?M (1z) 3 ?R (1z) 4 ?V (1z)
  3 (1w)
• matter
  radiation vacuum
• Alters D(z) via r s c dz / H
• And growth via 2H d?/dt term in growth equation
• Both effects are
• Small (need D to 0.2 for w to 1)
• Degenerate with changes in ?m
• To measure w to a few , we need to have
• independent data on ?m and to be able to

Rule of 5
growth
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Dark energy current status
Combined
Need to aim for 1 precision in future work
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Ruling in L Bayesian view
Evidence ratio trade likelihood ratio against
how much of parameter space is ruled out Trotta
(2005) roughly 1 accuracy on w will prove its
L unless we measure a large likelihood against
that model
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Evolving Dark Energy pivot redshifts
Assume w w0 wa(1-a) If observe degeneracy
w0 A Bwa, ) w A (B1-a)wa ) zpivot
1/(1B) - 1 Method zpivot CMB 0.43 BAO
z1 0.54 BAO z1z3 0.85 Lensing 0.25
Difficult to get much baseline
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Not everything may fit new physics, or
systematics?- need for multiple independent
methods - harder in future
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The CMB common basis for all methods
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CMB degeneracies and w
Comoving distance-redshift relation (? ? h2)
CMB power spectrum depends only on ?m and ?b
(apart from large-scale ISW and
reionization) Thus degeneracy between curvature
and vacuum (vary both to keep D fixed) Flat case
vary ?v and w. Degeneracy broken by large-scale
effects. Thus limit on w from good CMB data alone
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Data requirements for DM/DE

• Nearly all of the methods need redshift
  information, up to and beyond z '1
• LSS/BAO need 3-D positions of 106 galaxies
  spread over 3000 deg2
• Clusters quasi all-sky distribution of 105
  clusters with eROSITA (104 SZ-clusters from
  Planck), cannot be individually followed-up by
  spectroscopy
• Weak lensing needs only approximate but unbiased
  redshifts of 109 galaxies over 20,000 deg2
• Supernovae have the same imaging needs, plus 8m
  spectroscopy
• Accurate photometric redshifts are essential,
  over wide regions of the sky.
• For BAO, direct spectroscopy is preferred
  (photo-zs gt10 X less effective)
• Near-IR is important for controlling catastrophic
  photo-z failures, and is potential bottleneck

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Lensing vs SNe vs BAO (Dune)
(SNAP) (WFMOS 5000)
And similar constraints from mass function of
100,000 clusters
DETF likes ? w0 ? wa but not so clear kill ?
first
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Probe 1 Supernovae
Ground vs HST
Standard candles distances to 5 Currently
samples of few hundred Space resolution essential
for high z
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Supernovae Future challenges

• Now 500 SNe (SNLS). 2010 5,000 (Pan-STARRS)
• Could yield w to 2, but
• Photometric accuracy to lt 1 needed
• Malmquist worries at higher z
• Contamination by non-Ia
• Non-MW extinction
• Evolution of these factors, even ignoring
  intrinsic evolution

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Probe 2 Gravitational lensing
Image distortion depends on - D(z) via baseline -
growth of structure
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Shear Data Ground vs Space
Typical cosmic shear is 1, and must be
measured with high accuracy Even so, 1
precision on w needs gt 10,000 deg2 surveys
Space small and stable PSF ? larger number of
resolved galaxies ? reduced systematics
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Photometric redshifts
Broad-band data can give ?z/(1z) ' 0.04 But
expect catastrophic failures for zgt1 with optical
only Sufficiently deep near-IR (K ' 22) needs
space
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Lensing future challenges

• PSF correction STEP testing shows that even
  measuring shear with 1 precision is hard.
• Photo-z precision need to know ltzgt in a few
  tomographic z bands to 0.1 fractional accuracy
• needs gt105 zs to calibrate
• Nonlinear corrections most observations to date
  probe only shear correlations lt 10 arcmin
• need more accurate models for nonlinear P(k)
• effect of baryons?
• Intrinsic effects
• alignment of close pairs
• foreground-background alignments

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Probe 3 Clusters of galaxies
Evolving mass function sensitive to g(z) Apparent
baryon fraction depends on D(z)
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Clusters future challenges

• Projection effects Need X-ray survey (eROSITA?)
• Mass estimates
• Accuracy of mass estimation from X-ray/SZ (8
  rms)
• Self-calibration to avoid bias in masses
• Redshift accuracy
• need ? z/(1z) ' 0.02
• Maybe OK via averaging photo-zs
• but needs 105 zs for calibration in any case

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Probe 4 P(k) and Baryon oscillations

• Matter-radiation horizon
• 123 (?m h2 / 0.13)-1 Mpc
• (2) Acoustic horizon at last scattering
• 147 (?m h2 / 0.13)-0.25 (?b h2 / 0.024)-0.08 Mpc
• Standard rulers to probe distance-z relation

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BAO Precision on D(z) and volume
Takada
error in D (V / 5 h-3 Gpc3)-1/2 (kmax / 0.2
h Mpc-1)-1/2

• 0.7 lt z lt 1.3 1 (h-1Gpc)3 540 deg2
• 2.5 lt z lt 3.5 1 (h-1Gpc)3 254 deg2
• Thus 1 distance accuracy (5 on w) needs 2000
  (z1) or 1000 (z3) deg2
• Really prefer gt 5000 deg2 at z 1 (gt5 million
  zs) z 3 selection problematic

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BAO with Photo-zs
Schuecker
Much less efficient e.g. ESO VST/KIDS, 60
million photo-z over 1500 deg2 gives 14
predicted error on w 100 times bigger sample
needed for same accuracy as WFMOS Possibly
interesting with all-sky data, but demanding on
photometric uniformity
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Systematics

• Need to show that acoustic scale is at linear
  prediction to few parts in 1000
• Why might it not be?
• Mass nonlinearities
• Scale-dependent bias
• Mask convolution
• Missing close pairs
• Needs many semi-realistic mock surveys

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Semianalytic galaxies in MS 1014M halo
Dark matter
Galaxies
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Galaxy power bigger nonlinear effects at z3
than at z1
z3
z7
DM
gals
Power spectrum from MS divided by a baryon-free
LCDM spectrum
z0
z1
Springel et al. 2005
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Larger volumes mock galaxy P(k) data
Semianalytic data from Durham 1 Gpc/h cube
(ICC1000) Systematic shift in oscillation scale
relative to linear theory of 1 Can plausibly
calibrate this down to 0.1 shift
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Pan-STARRS 1

• 1.8m telescope on Haleakala, Maui
• 7 deg2 OT CCD camera
• Survey operations from mid-2007
• Initial programme runs to end 2010
• 20,000 deg2 grizy to i23.8
• 84 deg2 grizy to i27.0
• Most powerful imaging cosmology data prior to
  DES, HSC
• Should get w to 2-3 from each of lensing, SNe,
  photo-z BAOs
• Science consortium Hawaii, MPG Germany, CfA,
  JHU, UK (Belfast, Durham, Edinburgh)

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