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Supernova Cosmology today & yesterday. Marek Kowalski Physikalisches Institut Universität Bonn 5 .10.2010, Heidelberg. Congratulations !. A bit brighter M. fainter then expected . normalization. SNe Ia Hubble Diagram . M 1 0 0.72 0.28 0 1.
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Supernova Cosmologytoday & yesterday Marek KowalskiPhysikalischesInstitutUniversität Bonn 5.10.2010, Heidelberg
A bit brighter M fainterthen expected normalization SNeIa Hubble Diagram • M • 1 0 0.72 0.28 0 1 Supernova Cosmology Project (SCP)Kowalski et al. (2008) fainter
SNeIa Hubble Diagram • M • 1 0 0.72 0.28 0 1 Supernova Cosmology Project (SCP)Kowalski et al. (2008) HST SNLS Essence fainter SDSS PanStarrs PTF SNF CfA
SNeIa as “standard” Candles MB, α, β fittedalongwithcosmologicalparameters • Redder Supernovae are dimmer Intrinsically SNe have wider lightcurves. Astier et al., SNLS, 2005
Simulation of thewidth-brightnessrelation Simulation of brighter-wider relation Kasen, Roepke, Woosley, Nature 2009 Kasen, Roepke, Woosley, Nature 2009
Dust Extinction Excesscolor (B-V) • (possible) sources of reddening • Host galaxy dust • Dust shell around SN • intrinsic reddening Extinction coefficient Result of several studies β≈2-3 ≠ RB =4.1 (i.e. MW dust) Guy et al, 3-year SNLS, 2010
Thereddeninglaw of SNe Ia(broad band) SALT2 reddeninglaw Milky-Waylike dustextinction Guy et al., SNLS, A&A , 2010
Supernova Factory Supernova Factory Collaboration: Lawrence Berkeley National Lab Laboratorie de Physique Nucleaire et de Haute Energies de Paris Institut de Physique Nucleaire de Lyon Centre de Recherche Astronomy de Lyon Yale University Bonn University Tsinguha University, Bejing MPA, Garchingen seeposterby C. Buton
SNfactory: producing unique nearby SNe data 1. Discover 2. Observe 3. Analyses SNIFS: Custom spectrograph for nearby SN observations
SuperNova Integral Field Spectrograph (SNIFS) Microlens array to two channel spectrograph 15x15 = 225 spectra Photometric Channel Galaxy + Sky Acquisition, Guiding Extinction monitoring, calibration SN + Galaxy + Sky Sky Pick-off Prism at SN loc 6” x 6” FOV; 0.4”/spaxel 9.4’ x 9.4’ FOV; 0.14”/pix SN
Spectroscopicfeatures Spectralindicator, e.g. equilvilantwidth (EW) traceintrinsicvariability
Correcting SNeIawith spectroscopicindicators Spectralindicator, e.g. equilvilantwidth (EW) traceintrinsicvariability
Correcting SNeIawith spectroscopicindicators Spectralindicator, e.g. equilvilantwidth (EW) traceintrinsicvariability
The power of spectrophotometry CorrectingwithSi-equivilantwidth (EWSi) : βλ/βV Feature responsible for SALT2 colorlaw Chotard et. al., SNfactory A&A, 2011
The power of spectrophotometry CorrectingforintrinsicvariabilitywithEWSi + EWCa: βλ/βV Consistentwithregulardust extinctionlaw! (RV=2.8 withcolordispersionadded to fit) Chotard et. al., SNfactory A&A, 2011
SNe at large Redshifts (z>1) Observations from Space with the Hubble Space Telescopes: + NIR sensitivity
HST Survey of Clusters with z ≥ 1 Survey of z>0.9 galaxyclusters ⇒ SNefromcluster & field ⇒ about 2 x moreefficient ⇒ enhencement of earlyhosts ⇒ 20 new HST SNe ⇒ 10 high quality z>1 SNe! • Cycle 14, 219 orbits (PI S. Perlmutter) 24 clusters fromRCS,RDCS,IRAC, XMM Supernova Cosmology Project Suzuki et al., 2011
HST Survey of Clusters with z ≥ 1 Factor 3-5 moreearly hosted Supernovae! Supernova Cosmology Project Suzuki et al., 2011
HST Survey of Clusters with z ≥ 1 Union 2.1 - 580 SNe
Dark Energy Supernova Cosmology Project Suzuki et al., 2011 Equation of state: p=wρ Constant w: w=-0.951±0.078 cosmological constant SNe (Union 2.1, Suzuki et. al, 2011) BAO (Percival et. al, 2010) CMB (WMAP-7 year data, 2010)
Dark Energy Supernova Cosmology Project Suzuki et al., 2011 Equation of state: p=wρ Constant w: w=-0.951±0.078 Redshiftdependent w: w(a)=w0+(1-a)xwa Wa = 0.14±0.68 Λ cosmological constant No deviationfrom w=-1 (i.e. Λ)
A floating non-SNe bin to decouple low from high-redshift constraints Redshiftdependent EOS Assuming step-wise constant w: ~20% improved constraints
Quo Vadis, Supernova Cosmology? w = 0.951 ± 0.053 (stat) ± 0.057 (stat) Union 2.1, Suzuki et al. 2011
Control of systematicerrorscrucial! Examplefrom Union2 compilation (Amanullah et al, 2010) see also, N. Renault, et al., SNLS, A&A, 2009
1% perturbation of primaryreferencespectrum U. Feindt, K. Paech, MK, seeposter
Control of systematicerrorscrucial... ...but SN statisticshelps, too! Self-calibrating Hubble diagram: Calibrationoffsets determinedwith SN dataitself No inconsistencyseen so far: σ(flux)≈1% Methodoutperforms conventionalonefor >3000 SNe (e.g. DES) U. Feindt, K. Paech, MK, seeposter
Conclusion • Progress in our understanding of SNe • Data still consistent cosmological constant • Sys. uncertainties are of similar size as statistical • Next generation surveys are designed to control systematic errors • ~100 times larger statistics expected from future surveys will also help reduce systematic error
Parameters of ΛCDM SNe (Union 2.1, Suzuki et. al, 2011) BAO (Percival et. al, 2010) CMB (WMAP-7 year data, 2010) Supernova Cosmology Project Suzuki et al., 2011 ΩΛ=0.729 ± 0.014 and allowing for curvature: Ωk=0.002 ± 0.005
Supernova Type Ia • White dwarf in binarysystem • Masstransfer up to „critical“ Chandrasekharmass of 1.4 M • Thermonuclearexplosion • Explosion of similarenergies • Visiblein cosmicdistances
Light-curvefitterdifference Kessler et al. (SDSS), 2009 • MLCS2K2: w = -0.76 ± 0.07 (stat) • Trained on low-zdata • Prior on extinction • SALT2: w = -0.96 ± 0.06 (stat) • Trained on low-z + SNLS data • Empiraclemodelforextinction
Light-curvefitterdifference Origins of the “discrepancy” now well identified • Model rest-frame UV calibration → disappearswithimprovedphotometriccalibration • Treatment of thecolorvariability of SNeIa → disappearswhenassumptions (i.e. priors) are dropped (Guy, 2011) Differencebetweenfitsshouldn‘tbetaken as measure of systematicuncertainty
Correcting SNeIawith spectroscopicindicators
Host galaxydependence Evidence (4 sigma) forhost stellar massdependence of SN brightnessafterstretch & colorcorrection (Sullivan et al. 2010)
Puttingit all together - the Union2 • 557 SNefrom 17 datasets • Consistent lightcurve fits • (SALT2), including sample • dependent pass-band function • Error propagationleads to • covariancetermsbetweenSNe
CosmologicalParameters Supernova Cosmology Project Amanullah et al. 2010 Combination of SNe with: BAO (Percival et. al., 2010) CMB (WMAP-7 year data, 2010) For a flat Universe: Ωm= 0.279±0.014(stat) ±0.009(sys) … and with curvature: Ωm= 0.281±0.014(stat) ±0.010(sys) Ωk= -0.004±0.006(stat) ±0.001(sys) M
Equation of state: w=p/ w = -0.997±0.052 (stat) ±0.061 (sys) – flat universe w = -1.035±0.057 (stat) ±0.076 (sys) – curved universe
SNeIa as “standard” Candles MB, α, β fittedalongwithcosmologicalparameters Intrinsically SNe have wider lightcurves. Test: Redshiftdependence of α Guy et al, 3-year SNLS, 2010
(Selected)Future Projects Project z-range # SNe Pan-STARRS 0.1-0.5 ~104 DES (2012) 0.1-0.9 ~10 LSST (2018) 0.1-0.9 ~106 JDEM/Euclid (2018?) 0.2-3.0 >3000
The Large SynopticSurveyTelescope 8.4 m diameter 9.6 sq.deg FOV 3.2x109pixels 15 s exposures
LSST: > 105 SNe Ia per year http://www.lsst.org/lsst/scibook
SN Iaphotometricredshifts(fromsimulations) σz=0.007 σμ=0.16 http://www.lsst.org/lsst/scibook
SN cosmology: BAO & DlExample: equation of state w(z)=w0+waxz(1+z)-1 http://www.lsst.org/lsst/scibook
Euclid & Supernovae Astier, Guy & Pain, A&A, accepted (2010) Addingfilter-wheelforopticalchannelwouldallowforextraordinary SN survey 18 monthsurvey (10 & 50 sqdeg) wouldprovidecompetetiveconstraints on darkenergy
Conclusion • Data consistent with cosmological constant • Systematic uncertainties are of similar size as statistical • No show stoppers identified (but lots of work) • Next generation surveys are designed to control systematic errors and can significantly improve on current constraints
Currentsurveys HST SNLS Essence SDSS PanStarrs PTF SNF CfA redshift