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Future observational prospects for dark energy

Future observational prospects for dark energy. Roberto Trotta Oxford Astrophysics & Royal Astronomical Society. TODAY. w eff ~ -1 § 0.2 for z < 1. Investigating dark energy. The equation of state parameter w(z) = p/  w = -1 w = const  -1 w(z)

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Future observational prospects for dark energy

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  1. Future observational prospectsfor dark energy Roberto Trotta Oxford Astrophysics & Royal Astronomical Society

  2. TODAY weff ~ -1 § 0.2 for z < 1 Investigating dark energy • The equation of state parameter w(z) = p/ • w = -1 • w = const  -1 • w(z) • or perhaps another theory of gravity • Theoretical explanations must be guided by observational constraints: Seljak et al 2005 Jarvis et a 2005

  3. Number of assumptions Observational techniques • Weak gravitational lensing • Baryonic acoustic oscillations • Integrated Sachs-Wolfe effect • SNe luminosity distance (fluctuations?) • Cluster abundance Challenging control of systematics Less accurate, but systematics free Limited by cosmic variance SNe variability, evolution Do we understand clusters? Calibration

  4. Weak gravitational lensing • Based on well-understood physics • Independent of mass-to-light relation • Probes geometry & growth of structures • Potential to achieve percent accuracy on w • Limited to z < 1 • Systematic errors control • Image quality (0.1 to 1% distortions) • Gravitational-intrinsic correlations • Photo-z accuracy (tomography) • Non-linear effects • Strategies • Large (104-105) spectroscopic training sets • B-modes quantify the success of the correction • Use of radial information, cross-correlations between redshift bins • Combination of tomography/reconstruction with geometric test, checks for consistency

  5. Baryonic acoustic oscillations transverse ! DA(z) • A clean probe of geometry • Measures the angular diameter distance (transverse) and expansion rate (radial) • No known systematic effect can erase/mimick it • Based on well-known physical processes • Extends our window to z ~ 3 • In-built consistency check • Independent probe, curvature test, distinguish modifications of GR radial ) H(z) • Requirements • Large and deep spectroscopic survey (GWFMOS) • Photo-z’s are insufficient • Disadvantage • Lower statistical accuracy than weak lensing

  6. Growth of structures Standard rulers Acoustic oscillations SNe type Ia Clusters Weak lensing 3D reconstruction + SZ + WL calibration transverse (2D) geometric test transverse + radial (3D) + Planck CMB + Planck CMB Tomography + Planck CMB + SDSS 20% 20% Photometry z = 1 10% 10% + Planck CMB + Planck CMB + SNe Accuracy on w 5% 5% + Planck CMB + Planck CMB Spectroscopy z=1 and z = 3 1-2% 1-2% 2009 2015 Dark energy discovery space systematics impact Observational techniques 2015

  7. Proposals • Dark Energy Survey, darkCAM • visible survey cameras, 4-5 bands • 5,000 – 10,000 sq deg to z » 1 • Pan-STARRS • US Air Force, 4 telescopes planned • 3,000 sq deg in 5 bands • Spectrographs • VIRUS, 200 sq deg, z » 3 • AAOmega, 500 to 1,000 sq deg • GWFMOS (HyperSuprime), z ~ 1 and z ~ 3 • (Almost) everything you can think of • LSST, SKA (> 2015) darkCAM DES GWFMOS > 1 billion USD worth of proposals until 2015

  8. CFHT-LS 700 SNe DES 5’000 deg2, 4% on w Pan-STARRS, full system deployed in 2009? DES 5’000 deg2, 1-2% on w CFHT-LS 170 deg2 darkCAM, 1-2% on w VST – KIDS 1700 deg2 Pan-STARRS, full system deployed in 2009? DES 5’000 deg2, 5-20% on w SPT darkCAM, 5-20% on w Pan-STARRS, full system deployed in 2009? Present and upcoming surveys SNe LSST ? 20’000 deg2 out to z » 3 Imaging surveys WL BAO SZ 2006 2009 2013 2014 2015 GWFMOS 2’000 deg2 @ z » 1 300 deg2 @ z » 3 AAOmega 1’000 & 500 deg2 ? Spectroscopy BAO VIRUS ? 200 deg2 @ z » 3

  9. Present Future “Trust me, I’m a Bayesian!” Bayes factor B01 Mismatch with prediction w w0 Evidence in favour of w=-1 compared to -1/3 < w < -1 = 0.1 not worth mentioning = 0.01 moderate = 0.002 strong RT (2005)

  10. Closing remarks • Preparing for the unexpected • What will be the most interesting questions in 2010? • Dark energy could surprise us again: maximise the discovery potential • Developping know-how • Indispensable tools on the road to even larger surveys • Making the most of the data • Statistical tools for optimal parameter inference • Model selection approach, surveys optimization • Plenty of other science! • Next generation of surveys will provide extremely high quality data for numerous astronomical and astrophysical studies

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