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Calibration and Cross-Calibration of the SNLS and SDSS Supernova Surveys

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Calibration and Cross-Calibration of the SNLS and SDSS Supernova Surveys Introduction SNLS calibration Cross-calibration Conclusion Calibration and cross-calibration of the SNLS and SDSS supernova surveys Marc Betoule SNLS collaboration, JLA collaboration, CFHT LPNHE Fermilab, Apr. 2012 Betoule LPNHE Photometric calibration is the main source of uncertainty ∼ 1% reached in Regnault (2009) Need improvement for the final release Introduction SNLS calibration Cross-calibration Conclusion Context and motivations Cosmological constraint from type Ia SNe −0.5 BAO+WMAP7 Most stringent constraints to date on the dark energy equation −1.0 of state parameter 68.3% +0:078 95.4% w = −1:021−0:079. w 99.7% a ∼ 2 improvement wrt −1.5 CMB+BAO+H0 With all systematics SNLS3 −2.0 0.0 0.1 0.2 0.3 0.4 0.5 Ω m 68.3%, 95.4%, 99.7% confidence contours FwCDM (Sullivan, 2011) Betoule LPNHE Introduction SNLS calibration Cross-calibration Conclusion Context and motivations Cosmological constraint from type Ia SNe −0.5 BAO+WMAP7 Most stringent constraints to date on the dark energy equation −1.0 of state parameter 95.4% +0:078 99.7% w = −1:021−0:079. w a ∼ 2 improvement wrt −1.5 CMB+BAO+H0 Statistical only SNLS3 Photometric calibration −2.0 is the main source of 0.0 0.1 0.2 0.3 0.4 0.5 uncertainty Ωm 68.3%, 95.4%, 99.7% confidence contours FwCDM ∼ 1% reached in (Sullivan, 2011) Regnault (2009) Need improvement for the final release Betoule LPNHE Introduction SNLS calibration Cross-calibration Conclusion The type Ia SN Hubble diagram 26 24 HST C β 22 SDSS SNLS (s −20 1) − α + B 18 = m corr 16 Low−z m 14 Conley et al. (2011) 0.6 0.4 0.2 corr 0.0 m −0.2 −0.4 −0.6 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 z The luminosity of SNIae as a function of z: a precise photometry experiment (in average) Relative calibration between photometric bands and surveys 2 large similar surveys Betoule LPNHE Pushing this classic strategy Making the system redundant Shortening the calibration path Direct cross-calibration Cross-check of systematics Introduction SNLS calibration Cross-calibration Conclusion Overview Classic (star-based) calibration HST white dwarves as primary SNLS SDSS calibration source Megacam SDSS 2.5m Transfer to in-situ tertiary standards Landolt PT KPNO 1.3m PT 2.5m HST Betoule LPNHE Introduction SNLS calibration Cross-calibration Conclusion Overview Classic (star-based) calibration Megacam HST white dwarves as primary SNLS SDSS calibration source Megacam SDSS 2.5m Transfer to in-situ tertiary standards Landolt PT Pushing this classic strategy KPNO 1.3m PT 2.5m Making the system redundant HST Shortening the calibration path Direct cross-calibration Cross-check of systematics Betoule LPNHE Introduction SNLS calibration Cross-calibration Conclusion Outline 1 Introduction 2 SNLS calibration 3 Cross-calibration 4 Conclusion Betoule LPNHE Introduction SNLS calibration Cross-calibration Conclusion SNLS Photometric survey at CFHT 3.6 m telescope 40 nights/year over 5 years 4 deep fields of the CFHTLS Megaprime/MegaCam 1 deg2, 36 × 2k × 4:6k CCDs ! 300Mpixels 4 photometric bands gM rM iM zM Betoule LPNHE Introduction SNLS calibration Cross-calibration Conclusion Step I: Mapping the instrument response Twilight observations give wrong answers Mostly reflections in the optical path (ghosts) Any optical effect affecting differently parallel and isotrope illumination (Small angle scattering, optical distortions ...) Varying filters Number of Landolt star observations (i) 3 3 Critical in the transfer of average 2 2 calibration to SN CCD 1 Landolts and other standards observed at 1 specific positions 0 0 1 2 3 4 5 6 7 8 SN uniformly dispatched 0 CCD Betoule LPNHE Introduction SNLS calibration Cross-calibration Conclusion Mapping the response: the grid observations Dithered observations of dense stellar fields 13 exposures Logarithmically increasing steps from 1.5' to 1/2 deg 4-10 independent grid datasets /band ! measure a correction δzp to the twilight flat-field 2003 35 -0.12 30 -0.12 Observation model 25 -0.03 20 -0.09 mADU(x; star) = m(x0; star) + δzp(x) 15 -0.06 m(x0) ∼ 100000 nuisance parameters δzp ∼ 100 parameters 10 -0.12 5 -0.12 0 Betoule 0 5 10 15 20 25 30 35LPNHE Introduction SNLS calibration Cross-calibration Conclusion Mapping the response: the grid observations Dithered observations of dense stellar fields 13 exposures Logarithmically increasing steps from 1.5' to 1/2 deg 4-10 independent grid datasets /band ! measure a correction δzp to the twilight flat-field 2004 35 -0.15 -0.15 30 Observation model 25 -0.12 -0.03 mADU(x; star) = 20 m(x0; star) + δzp(x) + δk(x)(g − i) 15 -0.06 m(x0) ∼ 100000 nuisance parameters 10 -0.09 δzp ∼ 100 parameters 5 -0.12 0 Betoule 0 5 10 15 20 25 30 35LPNHE Introduction SNLS calibration Cross-calibration Conclusion Mapping the response: the grid observations Dithered observations of dense stellar fields 13 exposures Logarithmically increasing steps from 1.5' to 1/2 deg 4-10 independent grid datasets /band ! measure a correction δzp to the twilight flat-field 2005 35 -0.12 -0.15 30 -0.15 -0.09 Observation model 25 mADU(x; star) = 20 m(x0; star) + δzp(x) + δk(x)(g − i) 15 -0.03 -0.06 m(x0) ∼ 100000 nuisance parameters 10 -0.15 δzp ∼ 100 parameters 5 -0.12 0 Betoule 0 5 10 15 20 25 30 35LPNHE Introduction SNLS calibration Cross-calibration Conclusion Mapping the response: the grid observations Dithered observations of dense stellar fields 13 exposures Logarithmically increasing steps from 1.5' to 1/2 deg 4-10 independent grid datasets /band ! measure a correction δzp to the twilight flat-field 2006 35 -0.15 30 -0.15 -0.09 Observation model 25 mADU(x; star) = 20 -0.03 m(x0; star) + δzp(x) + δk(x)(g − i) 15 -0.06 -0.12 m(x0) ∼ 100000 nuisance parameters 10 -0.15 δzp ∼ 100 parameters 5 0 -0.12 Betoule 0 5 10 15 20 25 30 35LPNHE Introduction SNLS calibration Cross-calibration Conclusion Mapping the response: the grid observations Dithered observations of dense stellar fields 13 exposures Logarithmically increasing steps from 1.5' to 1/2 deg 4-10 independent grid datasets /band ! measure a correction δzp to the twilight flat-field 2007 35 -0.12 -0.15 30 -0.15 Observation model 25 -0.06 mADU(x; star) = 20 m(x0; star) + δzp(x) + δk(x)(g − i) 15 -0.03 m(x0) ∼ 100000 nuisance parameters 10 -0.09 δzp ∼ 100 parameters 5 -0.15 0 Betoule 0 5 10 15 20 25 30 35LPNHE Introduction SNLS calibration Cross-calibration Conclusion Mapping the response: the grid observations Dithered observations of dense stellar fields 13 exposures Logarithmically increasing steps from 1.5' to 1/2 deg 4-10 independent grid datasets /band ! measure a correction δzp to the twilight flat-field 2007 35 -0.12 -0.15 30 -0.15 Observation model 25 mADU(x; star) = 20 m(x0; star) + δzp(x) + δk(x)(g − i) 15 -0.03 -0.06 m(x0) ∼ 100000 nuisance parameters 10 -0.09 δzp ∼ 100 parameters 5 -0.15 0 -0.15 Betoule 0 5 10 15 20 25 30 35LPNHE Introduction SNLS calibration Cross-calibration Conclusion Mapping the response: the grid observations Dithered observations of dense stellar fields 13 exposures Logarithmically increasing steps from 1.5' to 1/2 deg 4-10 independent grid datasets /band ! measure a correction δzp to the twilight flat-field 2008 35 -0.12 -0.15 30 Observation model 25 -0.03 mADU(x; star) = 20 m(x0; star) + δzp(x) + δk(x)(g − i) 15 m(x0) ∼ 100000 nuisance parameters 10 -0.06 -0.09 δzp ∼ 100 parameters 5 -0.15 -0.15 0 Betoule 0 5 10 15 20 25 30 35LPNHE Introduction SNLS calibration Cross-calibration Conclusion Mapping the response: the grid observations Dithered observations of dense stellar fields 13 exposures Logarithmically increasing steps from 1.5' to 1/2 deg 4-10 independent grid datasets /band ! measure a correction δzp to the twilight flat-field 2009 35 -0.15 -0.15 30 -0.12 Observation model 25 -0.03 mADU(x; star) = 20 m(x0; star) + δzp(x) + δk(x)(g − i) 15 -0.06 m(x0) ∼ 100000 nuisance parameters 10 -0.12 δzp ∼ 100 parameters 5 -0.09 -0.12 0 -0.15 Betoule 0 5 10 15 20 25 30 35LPNHE Introduction SNLS calibration Cross-calibration Conclusion Intrinsic limitations Expensive Finite number of stars External observations Limited resolution ∼ 1=2 night for all bands Limited precision Photometric time u g r 35 35 35 0.005 0.005 30 0.005 30 30 0.010 0.005 0.010 25 25 25 0.010 20 20 20 0.010 0.005 0.005 Solving for the zero point 0.010 15 15 15 10 10 10 0.015 0.005 0.005 and response map at same 0.005 0.010 5 5 5 0.005 0.005 0.010 0 0 0 time is poorly conditionned 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 i i2 z 35 35 350.015 0.010 0.010 30 30 30 Perfect photometric 0.005 0.005 0.010 25 25 25 0.005 0.010 conditions required 20 20 20 15 0.005 15 15 Radial gradient ∼ 1% 10 10 10 0.010 0.005 0.010 0.015 5 0.010 5 5 0 0 0 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 Betoule LPNHE Introduction SNLS calibration Cross-calibration Conclusion Results Evaluating the impact of flat-fielding errors on the calibration Independent observations ! errors average out After selection ∼ 6 useable independent photometric corrections per band All epochs agree with rms < :3% in all bands g r 0:010 0:010 0:005 0:005 0:000 0:000 0:005 0:005 − − 0:010 0:010 − − 2003-102004-032004-122005-102006-092007-032007-11 2003-10 2004-12 2005-10 2006-09 2007-03 2007-11 i z 0:010 0:010 0:005 0:005 0:000 0:000 0:005 0:005 − − 0:010 0:010 − − 2003-10 2004-12 2005-10 2006-09 2007-03 2003-10 2004-12 2005-10 2007-03 2007-12 Betoule LPNHE Introduction SNLS calibration Cross-calibration Conclusion Step II: Anchoring to HST SNLS HST Doubling the original path MegaCam Uncertainty on the landolt to MegaCam transformation MegaCam KPNO 1.3m Direct observations of the Landolt CALSPEC Solar Analogs with MegaCam.
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