KDUST暗能量研究 詹虎 及张新民、范祖辉、赵公博等人 KDUST 宇宙学研讨会 国台，2009.12.16

Systematics of Dark Energy Probes Type Ia Supernova Luminosity evolution, Galactic & host-galaxy dust extinction, contamination. Weak lensing Shear calibration: Properties of additive & multiplicative shear errors? Photo-zs: What is the error distribution function? How and how well can we calibrate it? What is the impact of non-Gaussian photo-z errors on cosmological constraints? How about catastrophic redshift errors? Nonlinear evolution: Percent-level calibration of the nonlinear power spectrum at k < 1 h/Mpc? Baryonic influence on the dark matter distribution? Intrinsic alignment: Local & large-scale, intrinsic—intrinsic, gravitational—intrinsic alignments. How to remove/model the effects? Baryon Acoustic Oscillations Nonlinear evolution: Shift of the BAO scale? Higher-order statistics? Parameter estimation from non-Gaussian data? Galaxy bias: Scale dependence? luminosity dependence? Redshift distortion (spectroscopic BAO): Accurate calibration with N-body simulations? Cluster Counting Mass—observable relation: mean & variance? 12/16/2009 KDUST宇宙学

WL Shear Systematics Current best shear estimators can achieve multiplicative error (shear calibration error) of < 1% and residual shear of ~ 0.0001. Our forecasts for future surveys assume <m> ~ 0.5% and <c> ~ 10-5. 12/16/2009 KDUST宇宙学

WL Shear Systematics Parameter constraints Degradations due to shear errors are not bound (no self-calibration from WL itself). 12/16/2009 KDUST宇宙学

Uncertainty of Photo-z Error Distribution 12/16/2009 KDUST宇宙学

Uncertainty of Photo-z Error Distribution 12/16/2009 KDUST宇宙学

Dome A Advantages Good seeing: point sources, high-redshift objects, high-resolution imaging, source counts, shape measurement Infrared: high-redshift objects, photometric redshifts, low shape noise LONG night: time domain Dome A site is advantageous for controlling systematic errors of cosmological probes, which is critical to the success of future surveys. 12/16/2009 KDUST宇宙学

Dome A Advantages Slide from Jason Rhodes 12/16/2009 KDUST宇宙学

Simulation of Residual Shear 12/16/2009 KDUST宇宙学

Photo-z Sys Effects on DE Constraints Abdalla et al. (2008) Zhan et al. arXiv:0902.2599 A joint analysis of the shear and galaxy overdensities for the same set of galaxies involves galaxy—galaxy, galaxy—shear, and shear—shear correlations, which enable some calibration of systematics that would otherwise adversely impact each probe. While the WL constraints on the dark energy equation of state (EOS, w = p/r) parameters, w0 and wa, as dened by w = w0+wa(1-a), are sensitive to systematic uncertainties in the photo-z error distribution, the joint BAO and WL results remain fairly immune to these systematics. 12/16/2009 KDUST宇宙学

Impact of Systematics on DE Constraints Slide from Tony Tyson 12/16/2009 KDUST宇宙学 Zhan et al. arXiv:0902.2599

LSST w/ KDUST Calibration KDUST—LSST Synergy Dome A LSST LSST w/ KDUST Calibration Area/sq deg 5000—10000 20000 Gal dist n(z) z2exp(-z/0.6) z2exp(-z/0.5) Gal den/arcmin-2 70 40 Photo-z rms sz 0.03(1+z) 0.05(1+z) 0.04(1+z) Prior on photo-z bias sP(dz) 0.2sz 0.3sz Shear calibration error (×) ±0.002 ±0.005 ±0.003 Residual shear power (+) 4x10-10 10-9 6x10-10 SNeIa zmax >~ 2 0.8/1.2 -- 12/16/2009 KDUST宇宙学

KDUST Site Performance Without consideration for hardware or survey KDUST site assumptions: n(z) ~ z2exp(-z/0.6) (peaks at z=1.2) Photo-z rms: sz=0.03(1+z) (ugrizyJH) Photo-z bias prior: sP(dz)=0.2sz Shear calibration error: ±0.002 Residual shear power: 4×10-10 12/16/2009 KDUST宇宙学

KDUST Site Performance Without consideration for hardware or survey KDUST site assumptions: n(z) ~ z2exp(-z/0.6) (peaks at z=1.2) Photo-z rms: sz=0.03(1+z) (ugrizyJH) Photo-z bias prior: sP(dz)=0.2sz Shear calibration error: ±0.002 Residual shear power: 4×10-10 LSST site assumptions: n(z) ~ z2exp(-z/0.5) (peaks at z=1) Photo-z rms: sz=0.05(1+z) Photo-z bias prior: sP(dz)=0.3sz Shear calibration error: ±0.005 Residual shear power: 10-9 12/16/2009 KDUST宇宙学

KDUST—LSST Synergy n(z) ~ z2exp(-z/0.5) Photo-z rms: sz=0.05(1+z) LSST 20,000 sq. deg. ugrizy n(z) ~ z2exp(-z/0.5) Photo-z rms: sz=0.05(1+z) Photo-z bias prior: sP(dz)=0.3sz Shear calibration error: ±0.005 Residual shear power: 10-9 12/16/2009 KDUST宇宙学

KDUST—LSST Synergy 5000 sq. deg.: n(z) ~ z2exp(-z/0.6) KDUST JH + LSST ugrizy 5000 sq. deg.: n(z) ~ z2exp(-z/0.6) Photo-z rms: sz=0.03(1+z) Photo-z bias prior: sP(dz)=0.2sz Shear calibration error: ±0.002 Residual shear power: 4×10-10 15000 sq. deg.: n(z) ~ z2exp(-z/0.5) Photo-z rms: sz=0.04(1+z) Photo-z bias prior: sP(dz)=0.2sz Shear calibration error: ±0.003 Residual shear power: 6×10-10 12/16/2009 KDUST宇宙学

KDUST—LSST Synergy 10000 sq. deg.: n(z) ~ z2exp(-z/0.6) KDUST JH + LSST ugrizy 10000 sq. deg.: n(z) ~ z2exp(-z/0.6) Photo-z rms: sz=0.03(1+z) Photo-z bias prior: sP(dz)=0.2sz Shear calibration error: ±0.002 Residual shear power: 4×10-10 10000 sq. deg.: n(z) ~ z2exp(-z/0.5) Photo-z rms: sz=0.04(1+z) Photo-z bias prior: sP(dz)=0.2sz Shear calibration error: ±0.003 Residual shear power: 6×10-10 12/16/2009 KDUST宇宙学

Most importantly, KDUST helps control the systematics! KDUST—LSST Synergy KDUST JH + LSST ugrizy 5000 sq. deg.: n(z) ~ z2exp(-z/0.6) Photo-z rms: sz=0.03(1+z) Photo-z bias prior: sP(dz)=0.2sz Shear calibration error: ±0.002 Residual shear power: 4×10-10 15000 sq. deg.: n(z) ~ z2exp(-z/0.5) Photo-z rms: sz=0.04(1+z) Photo-z bias prior: sP(dz)=0.2sz Shear calibration error: ±0.003 Residual shear power: 6×10-10 Most importantly, KDUST helps control the systematics! SNe: SNAP like (z < 1.7) 12/16/2009 KDUST宇宙学

Comparable constraints to LSST can be obtained Zhao et al. 12/16/2009 KDUST宇宙学

New Results from Current Data Data: WMAP5 + small-scale CMB + SDSS LRG + ”constitution” sample (SN: CFA+UNION) New Results from Current Data Zhao & Zhang, arXiv: 0908.1568 12/16/2009 KDUST宇宙学 20

Dark Energy EOS Eigenmodes Dark energy EOS is interpolated from 30 parameters evenly spaced between a=0 and 1. KDUST modes probe slightly higher redshift than LSST ones. 12/16/2009 KDUST宇宙学

Summary Dome A has a great potential for dark energy studies. One scenario for KDUST would be focusing on NIR (JHK) bands and obtaining ugrizy data from LSST through collaboration. We need to explore other probes (such as strong lensing) that can take advantage of the Dome A site. To enable the sciences that KDUST is supposed to deliver, we must study the science cases in detail now and take the data challenge very seriously. 12/16/2009 KDUST宇宙学

Potential Collaborations Common aspects R&D tools Data pipelines Data management LAMOST TMT China Transient alerts Target selection Precise astrometry Precise photometry Spectroscopic follow-up Deep NIR imaging High-res imaging Redshift calibration Survey coverage Continuous observing 12/16/2009 KDUST宇宙学