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Photometric Design Specifications

Photometric and Astrometric Calibration of LSST Data David L. Burke Kavli Institute for Particle Astrophysics and Cosmology Stanford Linear Accelerator Center NSF Conceptual Design Review Tucson September 18, 2007. Photometric Design Specifications.

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Photometric Design Specifications

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  1. Photometric and AstrometricCalibration of LSST Data David L. BurkeKavli Institute for Particle Astrophysics and CosmologyStanford Linear Accelerator Center NSF Conceptual Design ReviewTucsonSeptember 18, 2007

  2. Photometric Design Specifications Specifications for isolated bright stars (17 < r < 20). • Repeatability of measured flux over epochs of 0.005 mag (rms). • Internal zero-point uniformity for all stars across the sky 0.010 mag (rms) in g,r,i ; 0.020 in other bands. • Transformations between internal photometric bands known to 0.005 mag (rms) in g,r,i; 0.010 to other bands. • Transformation to a physical scale with accuracy of 0.020 mag.

  3. Further Calibration Specifications • Extrapolation to faint resolved sources is no more than factor two worse than performance on bright isolated stars. • Derived specifications on instrumental fidelity and pipeline algorithms. • Minimize impact on main telescope science survey. • Goal is, and present simulations assume, no observing by the main telescope dedicated to calibration of instrumental response or measurement of atmospheric extinction.

  4. Photometric Calibration Philosophy • Reduce accumulated all-sky multi-epoch survey to a single arbitrary scale for each filter band. • Reference stars:  108 main-sequence stars (105 per image). • Determine six filter-band zero-points. • Photometric standards:  2000 hydrogen white dwarf stars. • Physical scale • Conventional (Landolt, Stetson) standard stars. • HST 1% photometry – DA WDs. • NIST laboratory calibrated detectors?

  5. Science Targets Reference Stars ( 100 per chip per image) All Sky Reconstruction (~ Monthly; i.e. ~10 Epochs) Photometric Standards (~ 1 per image) Atmospheric Extinction Z(az,el,n,t) Instrumental Calibration I(x,y,n,t) Calibration Elements Accumulated LSST Multi-Epoch Survey Auxiliary Data

  6. Sloan SDSS “Über-cal” Southern Survey (Stripe 82) 300 deg2along celestial equator. Multiple (30-40) epochs. Main sequence stellar locus is quite narrow – easy to select large sample of well-understood stars. Averages of MS stars with r < 20 define photometric zero-points. Projections of main sequence locus in gri and riz.

  7. Flat-fielding error. gri Sloan SDSS “Über-Cal” Channel-by-channel averages of ~ 106 stars. Channel  Uniformity of internal zero points in photometric conditions: gri 5 milli-mags uz  10 milli-mags.  Meets LSST goals.

  8. Conclusions from SDSS Proof-of-principle under ideal conditions. Analysis indicates that variations in atmospheric conditions that are unobserved and un-modeled dominate residual calibration errors. We believe better control of these residual errors will be required to meet goals for performance over the course of the LSST survey.

  9. Aerosol Optical Depth AERONET (Mauna Loa) Cumulative Distributions (Mauna Loa) Year (from June 1994) Airborne

  10. Ozone and Water Vapor Ozone Content Above Hilo, HI (Total Ozone Monitoring Satellite – TOMS) Water Vapor Content at Mauna Loa (AERONET) Dobsons Column Height (cm) Days (from July 25, 1996) Year (from June 1994)

  11. Atmospheric Stability - Conclusions • Aerosols can change by a few percent in days. Ozone more slowly. • H2O can change by a few percent in hours. • Clouds (gray?) can change minute-to-minute with intricate spatial structure. • May not have uniformity of atmospheric throughput across LSST FOV.

  12. Extrapolation from SDSS to LSST • Cadence and Survey Operations • SDSS samples all five filters continuously – LSST will sample sky in two-three filters every four nights (40s visits). • LSST survey will be done almost exclusively at small airmasses (typically secz < 1.2). • Depth and statistics • LSST will see approximately an order magnitude more stars per epoch than SDSS. → 108 stars across surveyed sky.

  13. “Forward” Calibration • 1. Calibrate telescope and camera instrumentation. • I(x,y,n,t) • Reconstruction of photons in the telescope pupil. 2. Measure atmospheric extinction. Z(az,el,n,t) Photons at the top of the atmosphere to the telescope pupil.

  14. Auxiliary Telescope Auxiliary Telescope Measure (changes in) atmospheric transmission with sufficient resolution in wavelength to accurately compute spectral extinction across all wavelengths, e.g. with MODTRAN4. • Spectroscopy (R = l/dl 100) or photometry with  10-12 appropriately chosen bands; B, A, and F stars < 15 magnitude. Spectrographic and photometric standards. →Extract Z(az,el,n,t) relative to standard atmosphere.

  15. Atmospheric Models and Simulations MODTRAN4 (USAF) U.S. Standard Atmosphere (1976)

  16. Observing Tests at CTIO (Tololo) Observing with 1.5m and RCSpec 6 nights in 2007A – completed. 6 nights approved for 2007B. Fit with Kurucz model SED and templates from MODTRAN4. TO BE UPDATED WITH LATEST RESULTS FOR PRESENTATION IN SEPTEMBER.

  17. IR Cloud Monitor Downward Radiance from Atmospheric Constituents South Pole W/m2/cm-1/sr Mean Latitude Co-Bore Sighted with LSST

  18. Instrumental Optical Calibration Dome Screen Every point on the screen must provide uniform (Lambertian) illumination of the angular FOV – fill LSST étendue. Tunable Laser Calibrated Photodiode Calibrate at NIST across wavelength (griz) to part in ~ 10-3. LSST – PanSTARRS Collaboration

  19. Back-Lit Diffuse Dome Screen Concept Sketch and Prototype Side-Emitting Optical Fiber Somta Corp of Riga, Latvia Mirror Diffuser Collimator

  20. Performance and Issues • Illumination uniformity. • Stray and scattered light. • Mechanical construction. Test on CTIO Blanco. Comparison of Blanco r-filter facility reference bandpass and dome illumination measurements.

  21. AstrometrySpecification and Approach • Relative astrometry – stacking images raft-by-raft to  10 milliarcsec, and across the 3 FOV to  15 mas. • Consistent multi-color observations; refraction. • Zero proper motion for galaxies and QSOs; parallax of stars. • Absolute astrometry – transformation to external system to  50 mas. • Reference catalogs and QSO solutions. • Radio sources? • Image-by-image, chip-by-chip: (x,y) (RA,DEC). • Best fit (6 parameter/chip) to accumulated multi-epoch survey. • Stability of relative and absolute solutions.

  22. Stromlo Southern Sky Survey Complete southern sky: 20,000 square degrees – first light 2007. 1.3 meter telescope 8 square degree FOV S/N = 5 in 110 sec exposures. Developing collaboration with SkyMapper team.

  23. Calibration Data Science Images Nightly Weekly Nightly Monthly Pre-Survey Operation Calibration QA Calibration Products Pipeline Pixel Level Correction Pixel Level Correction Identify Photometric Standards Coarse Calibration Register & Stack Photometry & Spectroscopy of Primary Photometric Standards Source Detection & Measurement Source Detection & Measurement Instrumental Calibration Data Auxiliary Atmospheric Data Co-Measurement Object Catalog Deep Detection Pipeline Monthly Photometric and Astrometric Standards Catalogs Catalog-Level Photometric and Astrometric Calibration Calibration Pipeline Schematic (c.f. Previous “Calibration Elements” Slide) LSST DM (Axelrod, et al.)

  24. Calibration Simulation

  25. Simulation Work Packages

  26. Status, Risks, and Mitigation • Proof of “ubercal” principle from analysis of SDSS data. • Risks in extrapolation to LSST identified and mitigation in progress. • Photometry: Spatial, temporal, and spectral variations in atmospheric extinction . • Collation of existing data, models, and simulations done. • Observing tests underway with telescopes and instruments similar to those proposed for LSST. • Plan to fully “mock-up” LSST and auxiliary equipment with telescopes on Tololo.

  27. Status, Risks, and Mitigation • Photometry: Instrumental calibration. • “Prototype” dome screen will be in early use with PanStarrs-1. • Photometry: Complexity of reconstruction. • Full simulation of data and pipeline. • Mock data challenges. • Astrometry: Standards and algorithms. • Early development of algorithms and codes with data from SkyMapper. • Astrometry: Instrumental accuracy. • Flow-down of specifications to telescope and camera.

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