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Baryonic and Dark Matter

Baryonic and Dark Matter. Next Generation Surveys: Scientific, Observational and Instrumental Challenges. Andy Taylor Institute for Astronomy, School of Physics University of Edinburgh, UK. Gray & Taylor et al 2005. Outline. Scientific aims of future surveys Overview of future surveys

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Baryonic and Dark Matter

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  1. Baryonic and Dark Matter Next Generation Surveys: Scientific, Observational and Instrumental Challenges Andy Taylor Institute for Astronomy, School of Physics University of Edinburgh, UK Gray & Taylor et al 2005 IoP-RAS Meeting

  2. IoP-RAS Meeting

  3. Outline • Scientific aims of future surveys • Overview of future surveys • Challenges for future surveys • Summary IoP-RAS Meeting

  4. Outline • Scientific aims of future surveys • Overview of future surveys • Challenges for future surveys • Summary IoP-RAS Meeting

  5. Aims of Lensing Surveys • What are the scientific challenges for lensing? • Astrophysical: • Galaxy halo properties (galaxy-galaxy, galaxy-quasar) • Clusters & filaments (mass mapping vs Xray & starlight) • High-redshift Universe (gravitational telescopes) • Fundamental: • Dark Matter properties ( DM mass & interactions, neutrino mass) • Dark Energy properties (EoS, evolution) • Initial conditions (s8, ns, dns/dlnk) • Testing Einstein Gravity IoP-RAS Meeting

  6. Properties of Dark Matter • Cold Dark Matter: • Mass – break in matter power spectrum • Thermal properties – resolve smallest halos with shear and flexion. • Neutrinos • Mass – another scale length in matter power spectrum from free-streaming. IoP-RAS Meeting

  7. Baryonic & Dark Matter in COSMOS Residual systematics (“B modes”) Blue: stellar mass Yellow: galaxy number Red: hot gas B-mode map IoP-RAS Meeting Massey, et al, Nature, 2007

  8. COSMOS 3-D Dark Matter Maps Photon equation of motion: Right Ascension Redshift 0.0 0.2 0.4 0.6 0.8 Declination IoP-RAS Meeting Massey, et al, Nature (2007)

  9. w = -1 r(z) w = 0 z Observable Effects of Dark Energy • Geometry: DE changes the photon distance-redshift relation: r(z) • Angular diameter • distance DA • Luminosity • Distance DL • Dynamics: Alters the growth of density perturbations, d(t). d r IoP-RAS Meeting

  10. Constraining w from the CMB + Supernova Energy-density scales with expansion as Close to a Cosmological Constant. (assumes flat Universe) Spergel et al ApJ 2006 IoP-RAS Meeting

  11. Constraining w from the CMB + Supernova + Lensing from CFHT Energy-density scales with expansion as Close to a Cosmological Constant. (assumes flat Universe) Spergel et al ApJ 2006, Tereno et al 2006 IoP-RAS Meeting

  12. Initial Conditions - Inflation Spergel et al. ApJ, 2006 IoP-RAS Meeting

  13. Testing Einstein Gravity • Three tests of gravity: • Model testing. Eg, DGP, TeVeS, braneworld. • Generalized Einstein metric • Consistency Relations: Geometric wG versus Dynamic wD. IoP-RAS Meeting

  14. Outline • Scientific aims of future surveys • Overview of future surveys • Challenges for future surveys • Summary IoP-RAS Meeting

  15. Timeline Lensing (+z) Spec IR Space 2004 SDSS/AAOmega • CFHTLS DEEP2 2006 LAMOST • Pan-STARRS-1UKIDSS • VST-KIDSVIKING/VHS Planck 2009 Pan-STARRS-4 • DES WFMOS JWST JWST 2011 HSC/Subaru VIRUS 2012 2013 SNAP/JEDI/ADEPT/Destiny? 2014 LSST 2015 2016 • DUNEDUNE DUNE 2018 2019 • SKA (Radio) SKA (Radio) 2025 ELT IoP-RAS Meeting

  16. 2003-2008: CFHTLS • Canada-France-Hawaii 3.6m Telescope • Mauna Kea • 40 CCD, 340 Mpixels • 1 sq deg MegaCam • Surveys: • Wide: 170 sq deg • u*g’r’i’z’, i’=24.5 • Deep: 4 sq deg, r’=28 IoP-RAS Meeting

  17. 2007-2010: Pan-STARRS-1 • Panoramic Survey Telescope and Rapid • Response System (Pan-STARRS). • Hawaii, MPIA, Taiwan, • Harvard, Johns Hopkins, • UK (Edinburgh, Belfast, Durham), • 1.8 meter primary • 1.4Gpixel camera. • 7 sq deg fov. • Medium Deep Survey • 3p Survey • g, r, i, z, y (r=24.5) • PS4 – 4xPS1 (2009). IoP-RAS Meeting

  18. 2008-2013: VST-KIDS & VIKING • ESO’s Kilo-Degree Survey • 2m primary • 184Mpixels 1sqdeg fov OmegaCAM • 1,500 sq deg • u’g’r’i’z’ • VIKING • (VISTA Kilo-degree INfrared Galaxy survey) • 1500 sq deg in parallel on VISTA • Z,Y,J,H,Ks IoP-RAS Meeting

  19. 2010-2015: DES • The Dark Energy Survey. • 4-metre Blanco at CTIO (South) • 500 Megapixel, 3 sqdeg fov camera • 5 yr survey (30% of time). • g,r,i,z over 5000 sq deg • r = 24.1 (10sig) • 4 dark energy probes: • WL, BAOs, SN & Clusters IoP-RAS Meeting

  20. 2011-2016: Subaru-HyperSuprimeCam • 8.3m Primary • 3.14 sq deg fov • 1.4 Gpixel camera • HyperSuprimeCam • 3500 sq deg/year • ~17,500 sq deg (5 yrs) • ugriz? ? IoP-RAS Meeting

  21. 2014-2024: LSST • Large Synoptic Survey Telescope (LSST) • 8.4m (effectively 6.5m) Primary • 3.2 Gpixel, 9.6 sq deg fov camera • ugrizY • Cerro Pachon, Chile • 30Tbyte per night IoP-RAS Meeting

  22. 2017-2021: DUNE – Dark UNiverse Explorer • Proposal to ESA Cosmic Visions programme. • 1.2m satellite telescope • r-i-z + Y,J,H • 0.5 sq deg fov • 3-year weak lensing survey: • 20,000 sq deg • AB=24.5 (10sig), zm=0.9 • n0=35/sq arcmin • Ground-based optical complement • needed for photo-z’s. IoP-RAS Meeting

  23. 2020-2025: SKA • Square Kilometre Array (SKA) Radio interferometer. Frequency range 100 MHz - 25 GHz 1 sq deg fov (1.4GHz) - 200 sq deg (0.7GHz) 20,000 sqdeg zm~1.0 sz=0 (spec) n0=10/sqarcmin (useable HI sources) IoP-RAS Meeting

  24. Grasp vs. Start Date SKA~108 103 102 10 1 LSST HSC PS4 DES Grasp (D2*fov) Dark Energy Survey Pan-STARRS-1 PS1 Grasp for optical surveys doubles every ~2.5 yrs CFHT VST-KIDS 170 sq deg DUNE 1700 sq deg 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 IoP-RAS Meeting Start Date

  25. Survey Area vs. End Date 104 103 102 PS1 PS4 DUNE LSST SKA HSC DES Area [sqdeg] Dark Energy Survey Pan-STARRS-1 VST-KIDS 170 sq deg CFHT-W 1700 sq deg 2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 End Date IoP-RAS Meeting

  26. Survey Depth vs. Area 104 103 102 PS1 DUNE PS4/ SKA LSST HSC DES Area [sqdeg] VST-KIDS Constant Time CFHT-W 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 Depth (Median Redshift) IoP-RAS Meeting

  27. Dark Energy Figure of Merit (FoM) • Dark Energy Task Force Figure of Merit: • Define pivot redshift, zp: wa w(z) wp Dw0 w = -1 zp z IoP-RAS Meeting 0

  28. Dark matter halos Observer 3-D Shear Power (e.g. Heavens 2003, Kitching, Heavens & Taylor 2005) Background sources IoP-RAS Meeting

  29. 3-D Shear Ratios Background sources Dark matter halos (Jain & Taylor 2003, Taylor, Kitching, Bacon, Heavens 2005) Observer • Signal depends on (Wm, Wv, w0, wa) and is insensitive to clustering. IoP-RAS Meeting

  30. FoM for Dark Energy from Lensing 3-D shear power and shear-ratios combined with Planck Explorer CMB survey (2008) Current limit 1/FoM CFHT KIDS PS1 SKA DES HSC PS4 FoM doubles every 2.5 yrs DUNE LSST Saturation IoP-RAS Meeting 2023 (with Tom Kitching) End Date

  31. Outline • Scientific aims of future surveys • Overview of future surveys • Challenges for future surveys • Summary IoP-RAS Meeting

  32. db Effect of Systematics • What is the effect of systematics in results? • Can estimate effect using Fisher Matrix formalism: • Eg for a straight line zero-point fit: y b IoP-RAS Meeting x (Taylor, Kitching & Heavens, 2006)

  33. Image Distortions • Image distortions: (Kitching, Taylor & Heavens 2007) calibration rotation bias. IoP-RAS Meeting

  34. Image Distortions • Image distortions: calibration, rotation, bias. • Effect of these on constant w: • Shear Power: no 1st order effect from gbias: • Shear-ratios: No bias to 1st order. • Require: IoP-RAS Meeting

  35. Observational Challenges • Photometric redshifts: calibration, bias, outliers zphot zspec Abdalla et al (2007) (Abdalla et al, 2007; Kitching, Taylor & Heavens 2007) IoP-RAS Meeting

  36. Observational Challenges • Photometric redshifts: calibration, bias, outliers • Can estimate bias effect from Fisher analysis: • Shear Power: • Shear-ratios: Shear-ratio: IoP-RAS Meeting

  37. Photometric Redshift Challenges • 5-optical + 3-IR? VST-KIDS/VIKING. • Do we need U-band? VST-KIDS • Calibration with spectroscopic surveys • How many? 105? VLT, WFMOS, ELTs? • Need synergy with IR & spectroscopic surveys. Abdalla et al (2007) IoP-RAS Meeting

  38. Intrinsic Alignment Challenges • Two alignment effects: • Intrinsic-Intrinsic alignments • Galaxy-Intrinsic alignment IoP-RAS Meeting (Bridle & King, 2007; Kitching, Taylor & Heavens 2007)

  39. Intrinsic Alignment Challenges • Model using Heymans et al (2006). • Find no effect on shear-ratio signal (averaged out), but enters noise. • Minimal effect on shear-power (but see Bridle & King 2007). • Using signal where alignment contribution is small. IoP-RAS Meeting

  40. Marginalize over Nuisance Parameters • Use data to estimate these parameters (self-calibration). • Marginalisation over uncertainties will increase error: w Dwmarg Dwcond gbias IoP-RAS Meeting

  41. Marginalize over Nuisance Parameters • Effect of marginalisation over image distortion uncertainties, for Shear + Ratios + Planck: • For a DUNE mission FoM (Dwp): • Shear Power Shear-Ratio Combined • Baseline 500 (0.015) 150 (0.024) 915 (0.012) • Pz+IA+g 116 (0.03) 70 (0.03) 670 (0.014) • 0.1% prior 440 (0.02) 100 (0.028) 900 (0.012) Mostly photo-z’s Mostly Image Distortions (Kitching, Taylor & Heavens 2007) IoP-RAS Meeting

  42. Nonlinear Matter Distribution • Non-linear matter power spectrum. • Fitting functions not accurate • Need MC N-body sims • Baryons? • Non-Gaussian corrections to the shear field. • Covariance of power (4pt-fn) • Higher-order correlations • Non-Gaussian likelihoods log Clgg log l P(k) k IoP-RAS Meeting

  43. Data Analysis Challenges • Tera/Pico-Bytes of data to push through pipeline. (eg. LSST raw=1500GB & Cats=400GB) • 4 layers: • Data acquisition, book keeping • Raw Data Reduction (registration) • Shape analysis (KSB++, shapelets, K2K, automated) • Science analysis (map making, power spectra, etc) • How do we simulate large dynamic range? • And Monte-Carlo surveys ~1000 times? • c.f. CMB temperature & polarisation experiments (see A. Challinor’s Talk). IoP-RAS Meeting

  44. Organizational Challenges • How to coordinate the effort? • EU Research-Training Network. • DUEL (Dark Universe with Extragalactic Lensing) • Exploit Cosmological Lensing from CFHTLS, Pan-STARRS, VST-KIDS • Plan for future surveys (DUNE…) • 8 Network Partners: • Edinburgh, Paris, Bonn, Heidelberg, Munich, Leiden, Naples, British Columbia • 7 Postdocs & 7 PhD students across network. • Training & exchange of methods & data. IoP-RAS Meeting

  45. Conclusions • Map dark matter in 3-D over all sky to z=1. • Expect DE FoM to double every 2.5 years. • Dark Energy probes saturate beyond z=1. • Bias in nuisance parameters biases w. • Self-calibration leads to doubling of errors. • Can add extra priors, or combine WL methods. • Optical/IR, Photo-z/Spec-z, Ground-Space synergies • Major challenges in data analysis lie ahead! IoP-RAS Meeting

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