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Quantifying Dark Energy using Cosmic Shear
Thank introducer. Thank everyone for coming. Sarah Bridle University of Manchester
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Quantifying Dark Energy Using Cosmic Shear
Introduction to Cosmic Shear Potential limitations Shear measurement Intrinsic alignments Dark Energy Survey LSST
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Quantifying Dark Energy Using Cosmic Shear
Introduction to Cosmic Shear Potential limitations Shear measurement Intrinsic alignments Dark Energy Survey LSST
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Concordance Model 75% Dark Energy 5% Baryonic Matter
20% Cold Dark Matter
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Why is the Universe Accelerating?
Einstein’s cosmological constant A new fluid called Dark Energy Equation of state w = p/ General Relativity is wrong Answers: 50% Lambda; ~3 people DE; ~ no people MG
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The Future HSC AFTA JDEM
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Comparison of different methods
Galaxy clustering Supernovae Gravitational shear Quality of dark energy constraint Example for optical ground-based surveys Dark Energy Task Force report astro-ph/
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Seeing the Invisible: Is there something in between us and the wall and tree?
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Simulated Dark Matter Map
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Shear Map
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Results from the HST COSMOS Survey
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Credit: NASA, ESA and R. Massey (California Institute of Technology)
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The Visible The Invisible
Credit: NASA, ESA and R. Massey (California Institute of Technology) Credit: NASA, ESA and R. Massey (California Institute of Technology)
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In 3 Dimensions Pictures + videos from
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Quantifying Dark Energy Using Cosmic Shear
Introduction to Cosmic Shear Potential limitations Shear measurement Intrinsic alignments Dark Energy Survey LSST
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Comparison of different methods
Galaxy clustering Supernovae Gravitational shear Quality of dark energy constraint Example for optical ground-based surveys Dark Energy Task Force report astro-ph/
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Cosmic Shear: Potential systematics
Shear measurement Photometric redshifts Intrinsic alignments Accuracy of predictions
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Quantifying Dark Energy Using Cosmic Shear
Introduction to Cosmic Shear Potential limitations Shear measurement Intrinsic alignments Dark Energy Survey
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Cosmic Shear gi~0.2 Real data: gi~0.03
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Atmosphere and Telescope
Convolution with kernel Real data: Kernel size ~ Galaxy size
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Pixelisation Sum light in each square
Real data: Pixel size ~ Kernel size /2
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Noise Mostly Poisson. Some Gaussian and bad pixels.
Uncertainty on total light ~ 5 per cent
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Bridle et al 2010
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A typical galaxy image for cosmic shear
Intrinsic galaxy shape b/a ~ 0.5 Uncertainty due to noise σb/a ~ 0.5 Modification due to lensing Δb/a ~ 0.05 Effect of changing w by 1% δb/a ~
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GREAT08 Results in Detail
Bridle et al 2010 See also GREAT10 Kitching et al, and GREAT3 Rowe, Mandelbaum et al
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m3shape Shear Measurement Code
Tomek Kacprzak Barney Rowe Michael Hirsch Sarah Bridle Lisa Voigt Joe Zuntz Forward model and fit Default: Galaxy is sum of two co-elliptical Sersics; PSF is Moffat Default: Maximum Likelihood. Takes about 1 second per galaxy Zuntz, …, SB et al 2013
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What causes the bias? For model fitting methods
Noise bias Refregier, SB et al; Kacprzak, SB et al 2012 Maximum likelihood methods are biased Calibration works well enough Model bias Voigt & Bridle 2009 e.g use wrong profile in fit e.g. use elliptical isophote model in fit
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Noise Bias Many identical images with different noise
Kacprzak, Zuntz, Rowe, Bridle et al 2012
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Bias disappears at high S/N Above requirements at low S/N
Refregier, Kacprzak, Amara, Bridle, Rowe 2012 Kacprzak, Zuntz, Rowe, Bridle et al 2012
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What causes the bias? For model fitting methods
Noise bias Refregier, SB et al; Kacprzak, SB et al 2012 Maximum likelihood methods are biased Calibration works well enough Model bias Voigt & Bridle 2009 e.g use wrong profile in fit e.g. use elliptical isophote model in fit
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But galaxies aren’t simple…
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The effect of realistic galaxy shapes
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Impact on dark energy constraints
Kacprzak, SB, et al 2013
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The GREAT3 Challenge From the GREAT3 Challenge Handbook (Mandelbaum, Rowe, et al 2013)
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The GREAT3 Challenge From the GREAT3 Challenge Handbook (Mandelbaum, Rowe, et al 2013)
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Typical data – multiple exposures
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How to deal with overlaps?
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Quantifying Dark Energy Using Cosmic Shear
Introduction to Cosmic Shear Potential limitations Shear measurement Intrinsic alignments Dark Energy Survey LSST
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The Future HSC AFTA JDEM
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The Dark Energy Survey Blanco 4-meter at CTIO
Survey project using 4 complementary techniques: I. Cluster Counts II. Weak Lensing III. Large-scale Structure IV. Supernovae • Two multiband surveys: 5000 deg2 grizY to 24th mag 30 deg2 repeat (SNe) • Build new 3 deg2 FOV camera and Data management system Survey (525 nights) Facility instrument for Blanco
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DES Collaboration The DES is an international project to “nail down” the dark energy equation of state. Funding from DOE, NSF and collaborating institutions and countries Fermilab, UIUC/NCSA, University of Chicago, LBNL, NOAO, University of Michigan, University of Pennsylvania, Argonne National Laboratory, Ohio State University, Santa-Cruz/SLAC Consortium, Texas A&M UK Consortium: UCL, Cambridge, Edinburgh, Portsmouth, Sussex, Nottingham ET Zurich LMU Ludwig-Maximilians Universität Spain Consortium: CIEMAT, IEEC, IFAE Brazil Consortium: Observatorio Nacional, CBPF,Universidade Federal do Rio de Janeiro, Universidade Federal do Rio Grande do Sul 120+ scientists 12+ institutions CTIO
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DES First Light 12 Sep 2012
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First Confirmed SNe from DES
Nov Dec. 15 SN Ia at z=0.2 confirmed at AAO
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DECam image of deep SN field will be visited many times during survey, resulting in very deep co-add
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grizY co-add image of SPT
DECam 1x1deg grizY co-add image of SPT cluster z=0.32 ~50,000 galaxies in this image
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High Redshift Cluster Discovered by DES
from DES Science Verification data in November
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DES Cluster Weak Lensing
Stacked (statistical) Weak Lensing cluster shear profiles will calibrate cluster mass-observable relations Preliminary cluster mass map from DES Science Verification data Melchior et al in prep
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Quantifying Dark Energy Using Cosmic Shear
Introduction to Cosmic Shear Potential limitations Shear measurement Intrinsic alignments Dark Energy Survey LSST
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Sign up to get involved https://docs. google. com/spreadsheet/ccc
Current status: 2 page SoI went to Science Board on Friday! Hopefully invited to submit full proposal for ~April
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Summary Cosmic shear the greatest potential of all for DE
Intrinsic alignments can be marginalised away We plan to calibrate shear measurement biases Dark Energy Survey early data now in Survey started September for 5 years Get involved in the Large Synoptic Survey Telescope (LSST)
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