1. Constraining Dark Energy with the Large Synoptic Survey Telescope
Hu Zhan UC Davis

2. Outline Dark energy probes The Large Synoptic Survey Telescope
Supernovae, cluster counting, baryon acoustic oscillations (BAO), weak lensing (WL), cosmic microwave background (CMB), gamma-ray bursts, SMBBH in-spirals…
The Large Synoptic Survey Telescope
Dark energy, dark matter, Solar system, optical transients (SN, GRB, NEO), galactic map
LSST BAO and WL
Photo-zs, systematic noises, joint analysis of BAO and WL
Summary
6/21/2006
LANL

3. Evidence for Dark Energy
Spergel et al. (2006)
6/21/2006
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4. Dark Energy Probes Probe Measurements Remarks Supernovae DL(z)
Presently most powerful
Clusters
DA(z), H(z), & G(z)
Large systematic errors, need to understand nonlinear astrophysics (e.g., mass—observable relation, mass function, both mean & scatter, …)
BAO
DA(z) & H(z)
Emerging, less affected by astrophysical uncertainties, less powerful WL
DA(z) & G(z)
Emerging, potentially powerful, limited by systematic errors
CMB
DLSS & Late ISW
Relatively weak constraints
Dark Energy Task Force report
6/21/2006
LANL

5. Supernova Distances Low-z SNe are needed.
SN constraints on dark energy equation of state parameters are sensitive to the mean curvature.
Subject to evolutional uncertainties
6/21/2006
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6. Cluster Counting LCDM:
Wm=0.27 (dotted line), Wm=0.3 (solid line), Wm=0.33 (shot-dashed line)
OCDM: long-dashed lines
Wm=0.27, 0.3, 0.33 (top to bottom)
Haiman, Mohr, & Holder (2001)
6/21/2006
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7. Large Synoptic Survey Telescope The
8.4-meter primary
10 deg2 FOV
3 billion pixels
µm (ugrizy)
15-s exposures
15 TB/night
200 PB total
Key Missions:
Dark energy
Solar system
Optical transients
Galactic map
20,000 deg2 survey area
r = 26.5 mag
~109 galaxies
~106 SNe
~104 clusters
First light ~ 2012
National Optical Astronomy Observatory
Research Corporation
The University of Arizona
University of Washington
Brookhaven National Laboratory
Harvard-Smithsonian Center for Astrophysics
Johns Hopkins University
Las Cumbres Observatory, Inc.
Lawrence Livermore National Laboratory
Stanford Linear Accelerator Center
Stanford University
The Pennsylvania State University
University of California, Davis
University of Illinois at Urbana-Champaign

8. LSST Supernovae
z = 0.8
z = 0
SN spectrum has many features that are useful for determining its redshift photometrically. The maximum error in the mean redshift is 0.01 near z = 0.7. Typical errors are 5 to 10 times smaller. This is better than galaxy photo-zs.
Pinto, Smith, & Garnavich (205th AAS)
Wang, Pinto, & Zhan (207th AAS)
6/21/2006
LANL

9. LSST Clusters
Shear-selected clusters: false detections, completeness, uncertainties of the mass function…
6/21/2006
Wang et al. (2004)

10. (Angular & radial scales)
BAO as a Standard Ruler
+ RS~150 Mpc
Angular diameter distance & Hubble parameter
(Sound horizon at recombination)
RS = c Dz/H = Dq D
(Angular & radial scales)
6/21/2006
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11. Cosmic Shear
The cosmic shear is a tiny gravitational distortion to the shapes of galaxies.
The shear power spectrum measures the potential fluctuations of the intervening cosmic field.
The lensing kernel is geometric.
Wittman et al. (2000)
6/21/2006
LANL

12. Formalism
potential PS
(BAO)
(WL)
I choose to normalize the galaxy/shear power spectrum to the dimensionless potential power spectrum, because potential perturbations are more fundamental than density perturbations. WL shear and CMB temperature fluctuations are driven directly by the fluctuations in the gravitational potential.
6/21/2006
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13. Angular Power Spectra Galaxy PS Shear PS Song & Knox (2004)
Zhan (astro-ph/ )
6/21/2006
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14. Photo-z
u band helps reduce the confusion between the Lyman break and Balmer break
LSST photo-z calibration plan
6/21/2006
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15. Number of Bins wa w0 4000 sq deg WL alone
Photo-z error distribution uncertain w0
Ma, Hu, & Huterer (2006)
Zhan, astro-ph/
6/21/2006
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16. Photo-z Degradation to WL Constraints
Huterer et al. (2006)
6/21/2006
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17. Photo-z Degradation to WL Constraints
Degradation without bound!
Ma, Hu, & Huterer (2006)
6/21/2006
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18. Angular Galaxy Power Spectra
Sensitivity to photo-z bias
6/21/2006
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19. Tomographic Binning Gaussian P(zph | z), sz = sz0(1 + z)
Ma, Hu, & Huterer (2006)
Gaussian P(zph | z), sz = sz0(1 + z)
n(z) can be quite complex.
6/21/2006
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20. Systematics LSST BAO LSST WL sz = 0.05(1+z), 50 galaxies/arcmin-2,
EP = s(wp)×s(wa), Nsys – additive systematic noise
6/21/2006
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21. Multiplicative Systematics
Huterer et al. (2006)
6/21/2006
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22. Additive Systematics
Huterer et al. (2006)
6/21/2006
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23. Complementarity
Galaxy clustering bias
Photo-z bias
Photo-z rms
Spectroscopic calibrations must be carried out to map the photo-z error distribution!
6/21/2006
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24. Constraints on Galaxy Bias and Photo-zs
Schneider et al., astro-ph/
6/21/2006
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25. Constraints on Galaxy Bias and Photo-zs
Schneider et al., astro-ph/
6/21/2006
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26. LSST BO + WL
sP(sz) = sz/20 , Nsys = 10-8
6/21/2006
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27. Curvature? BO & WL not affected by WK
no systematic noise
1000 sq deg spectroscopic survey: w0—wa degrades quite a bit if no high-z data; even worse if WK is unknown.
BO & WL not affected by WK
Knox, Song, & Zhan (astro-ph/ )
6/21/2006
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28. Dark Energy Models w0 & wa effects on qs cancel each other.
SUGRA?
w0 & wa effects on qs cancel each other.
Same qs, wm, wb, …
6/21/2006
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29. Summary
BAO and WL are highly complementary to each other. One should use multiple techniques jointly to constrain dark energy, whenever possible.
Photo-z calibration with spectroscopy is crucial to achieve BAO self-calibration of the photo-z error distribution.
Systematic errors must be well controlled especially for the WL technique.
The impact of non-Gaussian photo-z error distribution on dark energy constraints needs to be quantified.
There are many other challenges. For instance, we do not know the nonlinear matter power spectrum to 1% even without baryons.
6/21/2006
LANL