System wide optimization for dark energy science: DESC-LSST collaborations Tony Tyson LSST Dark...
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System wide optimization for dark energy science: DESC-LSST collaborations
Tony Tyson
LSST Dark Energy Science Collaboration meetingJune 12-13, 2012
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Multiple LSST probes of dark energy
• Use the same LSST survey data products
• Analyzed for different signals
• Multiple cross checks
• Combination is far more powerful than root mean square
• Maximally sensitive to new physics
Primary LSST probesWeak Lens shear cross correlation tomography Weak Lens magnification cross correlation tomography 2-D Baryon Acoustic Oscillations Supernovae Shear peak statistics Galaxy cluster counts
Secondary LSST probesTime domain tomography of QSOs and AGNs
Anisotropy of WL+BAO and SN signals
New Energy or New Gravity?
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DE Probes and DESC Tasks
• Measure geometry with Baryon Acoustic Oscillations– Photo-z effects, Non-linear corrections
• Measure mass and geometry with Weak Lensing Tomography– Measure and control systematics
• Combine multiple LSST probes – Break degeneracies– Minimize sensitivity to systematics
• Even better precision: DESC R&D– Photo-z and shear estimation algorithms, and their validation
• System-wide systematics relevant to DE– Optics, Detectors, Wavefront sensor, Guider, Calibration, …
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DETF – Science Book – Astro 2010 – CD-1
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DESC
WHY NOW?
Getting started:https://www.lsstcorp.org/sciencewiki/index.php?title=Getting_Started
Register for the All Hands Meeting (Aug 13-17):https://www.lsstcorp.org/ahm2012/
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Optimize LSST Survey for Dark Energy
LSST PROJECT
LSST DARK ENERGY SCIENCE
COLLABORATION
Get close to the experiment: System-wide involvementValidate algorithms, develop new algorithms
Ensure Simulator fidelity Test the Simulator and System ComponentsExplore cadence scenarios and systematics
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Modes of Interaction
LSST PROJECTLSST DARK ENERGY
SCIENCECOLLABORATION
STUDENTS
DESC students work with existing LSST R&D groups Help validate algorithms, develop new algorithms
Help ensure Simulator fidelity Help test the Simulator and System Components
Explore cadence scenarios and systematics
LSST PROJECT
LSST PROJECT
LSST PROJECT
STUDENTS
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Tasks
WEAK LENS SHEAR• PSF Systematics• PSF Control• Wavefront sensing• Stack-Fit and Multi-Fit• Galaxy shear• End-to-end simulations
PHOTOMETRIC REDSHIFT• Algorithms,• Photometry, Calibration• Required precision• Systematics, Simulations
BARYON ACOUSTIC OSCILLATIONS• Simulations
WIDE AREA ISSUES• Dither, Patch effects
SUPERNOVAE• Third parameter
EXTRACTING DE SCEINCE• Joint WL+BAO • Cross-calibration• All probes
MAPPING ONTO THEORY• Experiment constraints• Statistical inference
DATA MANAGEMENT• Automated DQA: document LSE-63• Computation
LSST Hardware systematics• CCDs, Optics
CALIBRATION• Spec/Phot
PRECURSOR AND TEST DATA• Subaru• f/1.2 LSST Camera Beam tests
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Example near-term focus areas
WAVEFRONT SENSING
DESC students work with existing LSST R&D groups Help validate algorithms, develop new algorithms
Help ensure Simulator fidelity Help test the Simulator and System Components
Explore cadence scenarios and systematics
PHOTOMETRIC CALIBRATION
IMSIM: LSS WL
STACKFIT DEVELOPMENT AND TESTS
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F. Roddier, Applied Optics, 27, 1223, 1998
More intense Less intense
Wavefront curvature sensing
ScienceFocal Plane
I I
I I
2 r
R
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Ghost rays (about 3% of direct intensity)Direct rays
Photometric calibration: flat field
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DM Pipelines
Solar System Cosmology
Defects
MilkywayExtended Sources
Transients
Base Catalog
All Sky Database
Instance CatalogGeneration
Generate the seed catalog as required for simulation. Includes:
Metadata Size Position
Operation Simulation
Type Variability
Source Image Generation
Color Brightness Proper motion
Introduce shear parameter from cosmology metadata
DM Data base load simulation
Generate per FOV
Photon Propagation
Operation Simulation
Atmosphere
Telescope
Camera
Defects Formatting Generate per Sensor
Calibration Simulation
LSST Sample Images and Catalogs
IMAGE SIMULATIONS
DESC
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Shape measurements on galaxy and star images
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Measuring faint galaxy shear: Stack-Fit
• Measure the shape of galaxies whose apparent shape is distorted by the point-spread function (PSF)
• PSF varies within CCDs and between CCDs and between exposures due to optics and atmosphere variations
• The Stack-Fit Algorithm: 1. Measure PSF within each CCD for each exposure 2. Separately make weighted co-add of all dithered images of the
field 3. Co-add with same weights the CCD PSF eigenfunctions 4. Use this PSF co-add map to interpolate the PSF at each galaxy’s
position 5. Convolve this PSF with a galaxy model, and fit.
• Test performance on end-to-end LSST image simulations• Test via comparing HST and Subaru WL mass reconstruction
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Subaru-HST shear component comparison @ 40 source galaxies/arcmin2
e1 Subaru-e1 HST e2 Subaru-e2 HST
Binned by magnitude
Systematic offset test: post Stack-Fit galaxy-by-galaxy distribution of Subaru-HST shear components
Will Dawson, UCD
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Test Stack-Fit using full LSST image simulations
LSST cosmic shear residual systematic errors
Jee & Tyson 2011
Initial tests on LSST image simulations, including atmosphere and focal plane errors, suggest that residual systematic shear correlations may be reduced below the shot noise in ~100 images of a field.
R&D on this and similar algorithms is planned, using the end-to-end LSST survey image simulations -- including realistic lensing power spectra and observational systematics.
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Testing CCD systematics: f/1.2 beam
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DETF FoM(t) during ten year survey
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Testing general models of dark energy
Science Book Ch. 15.1