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Supernova Cosmology today & yesterday

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 Cosmology today & yesterday

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  1. Supernova Cosmologytoday & yesterday Marek KowalskiPhysikalischesInstitutUniversität Bonn 5.10.2010, Heidelberg

  2. Congratulations!

  3. 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

  4. 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

  5. SNeIa as “standard” Candles MB, α, β fittedalongwithcosmologicalparameters • Redder Supernovae are dimmer Intrinsically SNe have wider lightcurves. Astier et al., SNLS, 2005

  6. Simulation of thewidth-brightnessrelation Simulation of brighter-wider relation Kasen, Roepke, Woosley, Nature 2009 Kasen, Roepke, Woosley, Nature 2009

  7. 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

  8. Thereddeninglaw of SNe Ia(broad band) SALT2 reddeninglaw Milky-Waylike dustextinction Guy et al., SNLS, A&A , 2010

  9. 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

  10. SNfactory: producing unique nearby SNe data 1. Discover 2. Observe 3. Analyses SNIFS: Custom spectrograph for nearby SN observations

  11. 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

  12. 178 SN spectral time series in the Hubble flow (0.03<z<0.1)

  13. Spectroscopicfeatures Spectralindicator, e.g. equilvilantwidth (EW) traceintrinsicvariability

  14. Correcting SNeIawith spectroscopicindicators Spectralindicator, e.g. equilvilantwidth (EW) traceintrinsicvariability

  15. Correcting SNeIawith spectroscopicindicators Spectralindicator, e.g. equilvilantwidth (EW) traceintrinsicvariability

  16. The power of spectrophotometry CorrectingwithSi-equivilantwidth (EWSi) : βλ/βV Feature responsible for SALT2 colorlaw Chotard et. al., SNfactory A&A, 2011

  17. The power of spectrophotometry CorrectingforintrinsicvariabilitywithEWSi + EWCa: βλ/βV Consistentwithregulardust extinctionlaw! (RV=2.8 withcolordispersionadded to fit) Chotard et. al., SNfactory A&A, 2011

  18. SNe at large Redshifts (z>1) Observations from Space with the Hubble Space Telescopes: + NIR sensitivity

  19. 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

  20. HST Survey of Clusters with z ≥ 1 Factor 3-5 moreearly hosted Supernovae! Supernova Cosmology Project Suzuki et al., 2011

  21. HST Survey of Clusters with z ≥ 1 Union 2.1 - 580 SNe

  22. 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)

  23. 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)

  24. A floating non-SNe bin to decouple low from high-redshift constraints Redshiftdependent EOS Assuming step-wise constant w: ~20% improved constraints

  25. Quo Vadis, Supernova Cosmology? w = 0.951 ± 0.053 (stat) ± 0.057 (stat) Union 2.1, Suzuki et al. 2011

  26. Control of systematicerrorscrucial! Examplefrom Union2 compilation (Amanullah et al, 2010) see also, N. Renault, et al., SNLS, A&A, 2009

  27. 1% perturbation of primaryreferencespectrum U. Feindt, K. Paech, MK, seeposter

  28. 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

  29. 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

  30. Primaryreferencespectrum(e.g. BD17°4708)

  31. 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

  32. Supernova Type Ia • White dwarf in binarysystem • Masstransfer up to „critical“ Chandrasekharmass of 1.4 M • Thermonuclearexplosion • Explosion of similarenergies • Visiblein cosmicdistances

  33. 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

  34. 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

  35. Correcting SNeIawith spectroscopicindicators

  36. Host galaxydependence Evidence (4 sigma) forhost stellar massdependence of SN brightnessafterstretch & colorcorrection (Sullivan et al. 2010)

  37. Puttingit all together - the Union2 • 557 SNefrom 17 datasets • Consistent lightcurve fits • (SALT2), including sample • dependent pass-band function • Error propagationleads to • covariancetermsbetweenSNe

  38. 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

  39. 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

  40. Constraints as a function of redshift

  41. SNeIa as “standard” Candles MB, α, β fittedalongwithcosmologicalparameters Intrinsically SNe have wider lightcurves. Test: Redshiftdependence of α Guy et al, 3-year SNLS, 2010

  42. (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

  43. The Large SynopticSurveyTelescope 8.4 m diameter 9.6 sq.deg FOV 3.2x109pixels 15 s exposures

  44. LSST: > 105 SNe Ia per year http://www.lsst.org/lsst/scibook

  45. SN Iaphotometricredshifts(fromsimulations) σz=0.007 σμ=0.16 http://www.lsst.org/lsst/scibook

  46. SN cosmology: BAO & DlExample: equation of state w(z)=w0+waxz(1+z)-1 http://www.lsst.org/lsst/scibook

  47. Euclid & Supernovae Astier, Guy & Pain, A&A, accepted (2010) Addingfilter-wheelforopticalchannelwouldallowforextraordinary SN survey 18 monthsurvey (10 & 50 sqdeg) wouldprovidecompetetiveconstraints on darkenergy

  48. 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

  49. Currentsurveys HST SNLS Essence SDSS PanStarrs PTF SNF CfA redshift

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