Baryonic and Dark Matter Next Generation Surveys Scientific
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 9/10/2020 & Taylor et al 2005 Io. P-RAS Meeting 1
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Outline • • 9/10/2020 Scientific aims of future surveys Overview of future surveys Challenges for future surveys Summary Io. P-RAS Meeting 3
Outline • • 9/10/2020 Scientific aims of future surveys Overview of future surveys Challenges for future surveys Summary Io. P-RAS Meeting 4
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 (Eo. S, evolution) Initial conditions (s 8, ns, dns/dlnk) Testing Einstein Gravity 9/10/2020 Io. P-RAS Meeting 5
Properties of Dark Matter 1. Cold Dark Matter: • • Mass – break in matter power spectrum Thermal properties – resolve smallest halos with shear and flexion. 2. Neutrinos • 9/10/2020 Mass – another scale length in matter power spectrum from free-streaming. Io. P-RAS Meeting 6
Baryonic & Dark Matter in COSMOS Residual systematics. Blue: (“B stellar mass galaxy number modes”) Yellow: Red: hot gas B-mode map 9/10/2020 Io. P-RAS Meeting Massey, et al, Nature, 2007 7
COSMOS 3 -D Dark Matter Maps Photon equation of motion: Righ 0. 0 Redshift 0. 4 0. 2 t Asc 0. 6 0. 8 ensio n Declination 9/10/2020 Io. P-RAS Meeting Massey, et al, Nature (2007) 8
Observable Effects of Dark Energy n Geometry: DE changes the photon distance-redshift relation: r(z) w = -1 w=0 Angular diameter distance DA Luminosity Distance DL z n Dynamics: Alters the growth of density perturbations, d(t). d r 9/10/2020 Io. P-RAS Meeting 9
Constraining w from the CMB + Supernova Energy-density scales with expansion as Close to a Cosmological Constant. (assumes flat Universe) 9/10/2020 Spergel et al Ap. J 2006 Io. P-RAS Meeting 10
Constraining w from the CMB + Supernova Energy-density scales with expansion as + Lensing from CFHT Close to a Cosmological Constant. (assumes flat Universe) 9/10/2020 Spergel et al Ap. J 2006, Tereno. Io. P-RAS et al. Meeting 2006 11
Initial Conditions - Inflation 9/10/2020 Spergel et al. Ap. J, 2006 Io. P-RAS Meeting 12
Testing Einstein Gravity • Three tests of gravity: 1. Model testing. Eg, DGP, Te. Ve. S, braneworld. 2. Generalized Einstein metric 3. Consistency Relations: Geometric w. G versus Dynamic w. D. 9/10/2020 Io. P-RAS Meeting 13
Outline • • 9/10/2020 Scientific aims of future surveys Overview of future surveys Challenges for future surveys Summary Io. P-RAS Meeting 14
Timeline Lensing (+z) 2004 2005 CFHTLS 2006 2007 Pan-STARRS-1 2008 VST-KIDS 2009 Pan-STARRS-4 2010 DES 2011 HSC/Subaru 2012 2013 2014 LSST 2015 2016 2017 DUNE 2018 2019 2020 SKA (Radio) 9/10/2020 2025 ELT Spec SDSS/AAOmega DEEP 2 LAMOST WFMOS VIRUS IR Space UKIDSS VIKING/VHS Planck JWST SNAP/JEDI/ADEPT/Destiny? DUNE SKA Io. P-RAS (Radio) Meeting DUNE 15
2003 -2008: CFHTLS • Canada-France-Hawaii 3. 6 m Telescope • Mauna Kea • 40 CCD, 340 Mpixels • 1 sq deg Mega. Cam • Surveys: • Wide: 170 sq deg u*g’r’i’z’, i’=24. 5 • Deep: 4 sq deg, r’=28 9/10/2020 Io. P-RAS Meeting 16
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. 4 Gpixel camera. 7 sq deg fov. • Medium Deep Survey • 3 p Survey • g, r, i, z, y (r=24. 5) 9/10/2020 • PS 4 – 4 x. PS 1 (2009). Io. P-RAS Meeting 17
2008 -2013: VST-KIDS & VIKING • ESO’s Kilo-Degree Survey • 2 m primary • 184 Mpixels 1 sqdeg fov Omega. CAM • 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 9/10/2020 Io. P-RAS Meeting 18
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 (10 sig) • 4 dark energy probes: WL, BAOs, SN & Clusters 9/10/2020 Io. P-RAS Meeting 19
2011 -2016: Subaru-Hyper. Suprime. Cam • 8. 3 m Primary • 3. 14 sq deg fov • 1. 4 Gpixel camera Hyper. Suprime. Cam • 3500 sq deg/year ~17, 500 sq deg (5 yrs) • ugriz? 9/10/2020 ? Io. P-RAS Meeting 20
2014 -2024: LSST • Large Synoptic Survey Telescope (LSST) • • • 8. 4 m (effectively 6. 5 m) Primary 3. 2 Gpixel, 9. 6 sq deg fov camera ugriz. Y Cerro Pachon, Chile 30 Tbyte per night 9/10/2020 Io. P-RAS Meeting 21
2017 -2021: DUNE – Dark UNiverse Explorer • Proposal to ESA Cosmic Visions programme. • 1. 2 m 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 (10 sig), zm=0. 9 • n 0=35/sq arcmin • Ground-based optical complement needed for photo-z’s. 9/10/2020 Io. P-RAS Meeting 22
2020 -2025: SKA • Square Kilometre Array (SKA) Radio interferometer. Frequency range 100 MHz - 25 GHz 1 sq deg fov (1. 4 GHz) - 200 sq deg (0. 7 GHz) 20, 000 sqdeg zm~1. 0 sz=0 (spec) n 0=10/sqarcmin (useable HI sources) 9/10/2020 Io. P-RAS Meeting 23
Grasp vs. Start Date SKA~108 103 LSST HSC PS 4 DES 102 Grasp (D 2*fov) 10 Dark Energy Survey Pan-STARRS-1 PS 1 Grasp for optical surveys doubles every ~2. 5 yrs CFHT VST-KIDS 170 sq deg 1 1700 sq deg 2002 9/10/2020 2004 2006 2008 2010 2012 Io. P-RAS Meeting Start Date 2014 DUNE 2016 2018 2020 24
Survey Area vs. End Date PS 1 PS 4 HSC 104 DUNE LSST SKA DES Area [sqdeg] Dark Energy Survey Pan-STARRS-1 VST-KIDS 103 170 sq deg 102 CFHT-W 9/10/2020 2008 2010 1700 sq deg 2012 2014 2016 End Date Io. P-RAS Meeting 2018 2020 2022 2024 2026 25
Survey Depth vs. Area PS 1 DUNE PS 4/ SKA LSST HSC 104 DES Area [sqdeg] VST-KIDS 103 nt Tim e CFHT-W 102 0. 6 9/10/2020 Const a 0. 7 0. 8 0. 9 1. 0 1. 1 Depth (Median Redshift) Io. P-RAS Meeting 1. 2 1. 3 26
Dark Energy Figure of Merit (Fo. M) • Dark Energy Task Force Figure of Merit: • Define pivot redshift, zp: wa w(z) wp Dw 0 w = -1 zp 9/10/2020 0 Io. P-RAS Meeting z 27
3 -D Shear Power (e. g. Heavens 2003, Kitching, Heavens & Taylor 2005) Dark matter halos Background sources Observer 9/10/2020 Io. P-RAS Meeting 28
3 -D Shear Ratios (Jain & Taylor 2003, Taylor, Kitching, Bacon, Heavens 2005) Dark matter halos Background sources Observer • Signal depends on (Wm, Wv, w 0, wa) and is 9/10/2020 insensitive to clustering. Io. P-RAS Meeting 29
Fo. M for Dark Energy from Lensing 3 -D shear power and shear-ratios combined with Planck Explorer CMB survey (2008) 1/Fo. M Current limit CFHT KIDS PS 1 SKA DES PS 4 HSC Fo. M doubles every 2. 5 yrs DUNE LSST Saturation 9/10/2020 (with Tom Kitching) Io. P-RAS Meeting End Date 30 2023
Outline • • 9/10/2020 Scientific aims of future surveys Overview of future surveys Challenges for future surveys Summary Io. P-RAS Meeting 31
Effect of Systematics n What is the effect of systematics in results? n Can estimate effect using Fisher Matrix formalism: n Eg for a straight line zero-point fit: y b db 9/10/2020 Io. P-RAS Meeting (Taylor, Kitching & Heavens, 2006) 32 x
Image Distortions • Image distortions: (Kitching, Taylor & Heavens 2007) calibration rotation 9/10/2020 Io. P-RAS Meeting bias. 33
Image Distortions • Image distortions: calibration, rotation, bias. • Effect of these on constant w: – Shear Power: no 1 st order effect from gbias: – Shear-ratios: No bias to 1 st order. • Require: 9/10/2020 Io. P-RAS Meeting 34
Observational Challenges • Photometric redshifts: calibration, bias, outliers zphot zspec 9/10/2020 (Abdalla Io. P-RAS Meeting et al, 2007; Kitching, Taylor & Heavens 2007) Abdalla et al (2007) 35
Observational Challenges • Photometric redshifts: calibration, bias, outliers Shear-ratio: • Can estimate bias effect from Fisher analysis: – Shear Power: – Shear-ratios: 9/10/2020 Io. P-RAS Meeting 36
Photometric Redshift Challenges • • • 5 -optical + 3 -IR? VST-KIDS/VIKING. Abdalla et al (2007) Do we need U-band? VST-KIDS Calibration with spectroscopic surveys – How many? 105? VLT, WFMOS, ELTs? • 9/10/2020 Need synergy with IR & spectroscopic surveys. Io. P-RAS Meeting 37
Intrinsic Alignment Challenges • Two alignment effects: - Intrinsic-Intrinsic alignments Galaxy-Intrinsic alignment 9/10/2020 Io. P-RAS Meeting (Bridle & King, 2007; Kitching, Taylor & Heavens 2007) 38
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. 9/10/2020 Io. P-RAS Meeting 39
Marginalize over Nuisance Parameters • Use data to estimate these parameters (self-calibration). • Marginalisation over uncertainties will increase error: w Dwmarg Dwcond gbias 9/10/2020 Io. P-RAS Meeting 40
Marginalize over Nuisance Parameters • Effect of marginalisation over image distortion uncertainties, for Shear + Ratios + Planck: • For a DUNE mission Fo. M (Dwp): Baseline Pz+IA+g 0. 1% prior Mostly photo-z’s Shear Power 500 (0. 015) 116 (0. 03) 440 (0. 02) Shear-Ratio Combined 150 (0. 024) 915 (0. 012) 70 (0. 03) 670 (0. 014) 100 (0. 028) 900 (0. 012) Mostly Image Distortions 9/10/2020 Meeting (Kitching, Taylor & Heavens. Io. P-RAS 2007) 41
Nonlinear Matter Distribution • Non-linear matter power spectrum. – Fitting functions not accurate log Clgg – Need MC N-body sims – Baryons? • log l Non-Gaussian corrections to the shear field. – Covariance of power (4 pt-fn) – Higher-order correlations – Non-Gaussian likelihoods 9/10/2020 Io. P-RAS Meeting P(k) 42 k
Data Analysis Challenges • Tera/Pico-Bytes of data to push through pipeline. (eg. LSST raw=1500 GB & Cats=400 GB) • 4 layers: – – • Data acquisition, book keeping Raw Data Reduction (registration) Shape analysis (KSB++, shapelets, K 2 K, automated) Science analysis (map making, power spectra, etc) How do we simulate large dynamic range? – – 9/10/2020 And Monte-Carlo surveys ~1000 times? c. f. CMB temperature & polarisation experiments (see A. Challinor’s Talk). Io. P-RAS Meeting 43
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: • – – 9/10/2020 Edinburgh, Paris, Bonn, Heidelberg, Munich, Leiden, Naples, British Columbia 7 Postdocs & 7 Ph. D students across network. Training & exchange of methods & data. Io. P-RAS Meeting 44
Conclusions • • • Map dark matter in 3 -D over all sky to z=1. Expect DE Fo. M 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! 9/10/2020 Io. P-RAS Meeting 45
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