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The Super/Nova Acceleration Probe (SNAP)

The Super/Nova Acceleration Probe (SNAP). Natalia Kuznetsova Lawrence Berkeley National Lab. Cosmo06 September 24 - 29, 2006 Tahoe City, CA. SNAP 101. Space-based 2-m class telescope dedicated to performing precision measurements of the dark energy equation of state parameter w through:

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The Super/Nova Acceleration Probe (SNAP)

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  1. The Super/Nova Acceleration Probe (SNAP) Natalia Kuznetsova Lawrence Berkeley National Lab Cosmo06 September 24 - 29, 2006 Tahoe City, CA

  2. SNAP 101 • Space-based 2-m class telescope dedicated to performing precision measurements of the dark energy equation of state parameter w through: • A wide field lensing survey • Discovery and follow-up of ~2,000 type Ia supernovae SNAP will be very data-rich, producing data useful not only for precision cosmology studies, but for many other applications 2

  3. Focal plane Integral Field Spectrograph (3”x3”) Fixed filters atop the sensors Visible NIR Spectrograph port 3

  4. HDF GOODS COSMOS Physics with SNAP: Deep & Large Space Surveys SNAP Deep Survey Area • The SNAP surveys will have an unprecedented combination of depth, solid-angle, angular resolution, temporal sampling, and wavelengthcoverage • Hubble Deep Fields illustrate the impact of a deep space survey. • SNAP SN survey 5,000 x HDF. • SNAP mAB = 27.7 per filter (30.4 co-added) every 4 days • SNAP lensing survey ~106 x HDF, 500 x COSMOS! • mAB = 28.1 co-added SNAP Lensing Survey Area 4

  5. Physics With SNAP: Supernovae SNAP ‘s homogeneous SN dataset over the redshift range up to z = 1.7 will have carefully controlled systematics • The quality, not the quantity, of SN observations is the primary factor for dark energy accuracy • SNAP will have photometric measurements of ~2,000 type Ia SN in 9 broadband filters, as well as their spectra at maximum light ~2000 SNe Ia DE discovery redshift z 5

  6. ground (0.7” seeing) space (0.12”) Physics with SNAP: Weak Lensing • Weak lensing (WL) provides an independent and complementary measurement of cosmological parameters • Space-based WL measurements are particularly helpful at small scales, where the shot noise is small due to the large surface density of resolved galaxies Courtesy Jason Rhodes 6

  7. Ancillary Science From SNAP • Galaxy structure formation • Galaxy clusters • Gamma-ray burst afterglows • Reionization history • Transients/variables • Stars • Solar system objects • Strong gravitational lensing • …. 7

  8. Simulating a Dark Energy Mission • We have created a sophisticated simulation that allows one to simulate a dark energy mission (space- or ground- based) • It is a collaborative project written in object-oriented Java • Basis for future data processing pipeline 8

  9. Studies with SNAPsim • SNAPsim is easily configurable for studying various choices of mission parameters • Examples of studies done using SNAPsim include: • SNAP exposure time - cadence trade study • SNAP detector-noise requirements • Calibration error propagation • Spectroscopic measurement requirements • Alternative instrumentation suites • SNAP primary aperture trade study • Ground-based missions • SNAP telescope blur requirements • Weak gravitational lensing mission simulation 9

  10. Simulated and fitted lightcurves for a type Ia SN at z = 1.7 SNAPsim Physics • Type Ia, II supernova spectra, varying stretch • Zodiacal background • Cardelli-Clayton-Mathis model dust • Atmosphere effects for ground-based missions • Sophisticated fitting algorithms for lightcurve and cosmology fitting filter 7 filter 8 filter 9 10

  11. Lightcurve Redshift Series Z = 0.8 Z = 1.2 Z = 1.6 Optical Bands Rest frame B NIR Bands Rest frame V 11

  12. Extracting Cosmology • The final step of the simulation is extracting the cosmological parameters • The plot is an example of the cosmology to be obtained from SNAP results only (no CMB priors) courtesy Eric Linder 12

  13. NIR Detector R&D • SNAPsim is used extensively for SNAP’s instrumentation and R&D work • For example, a recent study has investigated the effect of varying NIR detector parameters on the output physics • The idea is to find out what combination of detector specs (dark current, read noise, quantum efficiency) produces optimal science at the lowest cost Infrared Sensors m Error Contours Total Noise (e) QE courtesy Matt Brown 13

  14. IR Detector Trade-Off Study (2) m error vs. redshift for visible only and visible + NIR detectors Matt Brown et al. , proc. of 2006 SPIE symposium on Astronomical Telescopes and Instrumentation 14

  15. Simulating a Ground-Based Observatory Atmosphere transmission • SNAPsim is also capable of simulating a ground-based observatory • As an example, we simulate a somewhat idealized 8-m class telescope in the Southern hemisphere, with NIR detectors • We then look at the lightcurves for z = 1.2 and z = 1.4 supernovae for a GOODS South target and an equatorial pole one Atmosphere emission Natalia Kuznetsova, Larry Gladney, Alex Kim 15

  16. Simulating a Ground-Based Observatory (2) • Examples: a (somewhat) idealized 8-m ground telescope (with IR), observing a target in the GOODS South field and an equatorial one • Equatorial pole target gets a worse S/N, but there are no “holes” in the lightcurve GOODS South target Equatorial pole target 16

  17. Point source y  Spectrograph Simulation • Pixel-level simulation using shapelets to create fake spectra of both point and extended objects courtesy Richard Massey 17

  18. Spectrograph Simulation (2) Same magnitude SN and galaxy; no noise SN spectrum Reconstructed SN spectrum (z = 1.7)  y Host galaxy spectrum (a few slices from slicer mirror) courtesy Alain Bonissent 18

  19. Pixel Scale for Weak Lensing Contribution of intrinsic shear variance to the weak lensing power spectrum error • Also using shapelets to simulate space-based, pixel-level images • Initial result: SNAP nominal pixel scale of 0.10 arcsec/pixel is in the optimal well • This pixel scale is optimal for both supernova and weak lensing studies SNAP nominal courtesy Will High 19

  20. Self Calibration in Supernova Surveys • Filter zeropoint uncertainties affect precision of cosmological parameters. • Fitting for all SN distance moduli  simultaneously allows for a degree of self calibration which yields a noticeable improvement in the final precision (Kim & Miquel, Astropart. Phys. 24 (2006), 451). • We show this effect by simulating an SNLS-like survey and comparing the results against the usual SN by SN fit; we fit for s(WM) with w=-1. courtesy Lorenzo Faccioli; also see poster in hallway 20

  21. Conclusions • SNAP is specifically targeted at controlling systematic uncertainties • Our sophisticated mission simulation, SNAPsim, enables us to pursue such a tight control of errors • Numerous R & D, trade-off, and physics studies in progress, not only those presented in this talk • For more info, please go to http://snap.lbl.gov 21

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