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Cosmology with Supernovae

Cosmology with Supernovae. Bruno Leibundgut European Southern Observatory. Outline. Systematics of Type Ia Supernovae The Hubble diagram of Type Ia Supernovae From distances to acceleration The equation of state parameter. evolution (primary and secondary)

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Cosmology with Supernovae

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  1. Cosmology with Supernovae Bruno Leibundgut European Southern Observatory

  2. Outline • Systematics of Type Ia Supernovae • The Hubble diagram of Type Ia Supernovae • From distances to acceleration • The equation of state parameter

  3. evolution (primary and secondary) • interstellar and intergalactic dust • gravitational lensing The principle • Establish a cosmological distance indicator in the local universe (z<0.05) • custom yardstick (e.g. Cepheids, SNe II, Tully-Fisher relation, fundamental plane relation, surface brightness fluctuations) • standard candles (e.g. SN Ia) • Measure objects at cosmological distances • establish identity of distance indicator • control measurement errors

  4. evolution  light curve shapes, colours, spectroscopy • dust  colours, spectroscopy • gravitational lensing  difficult, need mapping of light beam The experiment • Establish a cosmological distance indicator in the local universe (z<0.05) • Type Ia Supernovae can be normalised through their light curves (102 objects) • excellent distance indicators (Phillips 1993, Hamuy et al. 1996, Riess et al. 1996, 1998, 1999, Perlmutter et al. 1997, Phillips et al. 1999, Suntzeff et al. 1999, Jha et al. 1999, 2003) • Measure objects at cosmological distances • 77 distant SNe Ia (0.3<z<1.0) published (Garnavich et al. 1998, Riess et al. 1998, Perlmutter et al. 1997, 1999, Tonry et al. 2003, Suntzeff et al. 2003, Jha et al. 2003, Leibundgut et al. 2003)

  5. Steps in the analysis •  photometric system •  spectroscopy •  photometry, epoch, K-corrections •  light curves, colours •  local calibration •  luminosity distances •  cosmological models • Accurate photometry • Secure classification • Light curve • Normalisation • Distances • Cosmological parameters • Cosmological implications

  6. The nearby SN Ia sample Evidence for good distances

  7. SN 1994D

  8. Leibundgut and Sollerman 2001 Tonry et al. 2003 Coil et al. 2000 Classification • Establish an object as a Type Ia Supernova • spectral evolution of supernovae

  9. H Ca II K  (Ångstrom) Classification • Establish an object as a Type Ia Supernova • spectral evolution of supernovae • Determine the supernova redshift • often done from galaxy lines (emission and absorption)

  10. Light Curves • Determine the maximum for the distance determination • K-corrections • based on spectral series from nearby supernovae • light curve fitting • light curve shape – luminosity correlation

  11. Light Curves • Determine the maximum for the distance determination • K-corrections • based on spectral series from nearby supernovae • light curve fitting • light curve shape – luminosity correlation

  12. Light curve shape – luminosity • m15relation Phillips (1993), Hamuy et al. (1996), Phillips et al. (1999) • MLCS Riess et al. (1996, 1998), Jha et al. (2003) • stretch Perlmutter et al. (1997, 1999), Goldhaber et al. (2001) • MAGIC Wang et al. (2003)

  13. Altavilla, Thesis

  14. The magic of the light curve shapes Goldhaber et al. 2001

  15. B V I The SN Ia luminosity can be normalised Bright = slow Dim = fast Riess et al. 1996

  16. SN Ia Correlations • Luminosity vs. decline rate • Phillips 1993, Hamuy et al. 1996, Riess et al. 1996, 1998, Perlmutter et al. 1997, Goldhaber et al. 2001 • Luminosity vs. rise time • Riess et al. 1999 • Luminosity vs. color at maximum • Riess et al. 1996, Tripp 1998, Phillips et al. 1999 • Luminosity vs. line strengths and line widths • Nugent et al. 1995, Riess et al. 1998, Mazzali et al. 1998 • Luminosity vs. host galaxy morphology • Filippenko 1989, Hamuy et al. 1995, 1996, Schmidt et al. 1998, Branch et al. 1996

  17. Riess et al. 1998 Phillips et al. 1999 Perlmutter et al. 1997 SN Ia Correlations Drell et al. 2000

  18. SN Ia Correlations Leibundgut 2000

  19. Testing the SNe Ia as distance indicators • Hubble diagram of SNe Ia in the local, linear expansion, Hubble flow • Calibration through “primary” distance indicators • Theoretical models

  20. The nearby SN Ia sample z<0.1 102 SNe Ia Tonry et al. 2003

  21. Absolute Magnitudes of SNe Ia Saha et al. 1999

  22. Almost there … Assume you have done: • sufficient photometry • several filters • accurate galaxy subtraction (templates) • (positive) classification • redshift determination • K-corrections • light curve fitting/normalisation It’s now time to plot the distances vs. the redshifts for the distant SNe Ia as well

  23. Supernova cosmology Tonry et al. 2003

  24. Starting from Einstein’s Field equation

  25. Friedmann cosmology Assumption: homogeneous and isotropic universe Null geodesic in a Friedmann-Robertson-Walker metric:

  26. Cosmology in the Hubble diagram

  27. 209 SN Ia and medians Tonry et al. 2003

  28. Distant objects appear fainter than their nearby counterparts This is a 2.5 result (High-z SN Team and Supernova Cosmology Project) evolution dust cosmology Checks: Dust observations over many filters Evolution spectroscopy Cosmology more distant SNe Ia Distant SNe Ia

  29. 79 SNe Ia 155 SNe Ia Tonry et al. 2003 H0=63 km s-1 Mpc-1 Cosmology Leibundgut 2001

  30. 2dF: M=0.2±0.03 SN Ia and 2dF constraints KP: h = 0.72 ± 0.08 Tonry et al. 2003

  31. Is evolution a problem? Falco et al. 1999 Leibundgut 2001 Is dust a problem?

  32. Absorption distributions

  33. SNe Ia in elliptical galaxies • Determination of host galaxy morphologies • 38 SNe Ia from the SCP sample Sullivan et al. 2003

  34. M=0.28; =0.72 Modified Hubble diagram • Supernova Cosmology Project Sample Sullivan et al. 2003 Sullivan et al. (2003)

  35. SN Ia Systematics? • Explosions not fully understood • many possible models • Chandrasekhar-mass models • deflagrations vs. detonations • Progenitor systems not known • white dwarfs yes, but … • double degenerate vs. single degenerate binaries • Evolution very difficult to control

  36. (age of the universe) (CMB and cluster masses) (inflation) evolution dust gravitational lensing selection biases inhomogoneities changing constants (G, , c) particle physics Is  real? NO YES

  37. Nature of the Dark Energy? • Currently four proposals: • cosmological constant

  38. Nature of the Dark Energy? • Currently four proposals: • cosmological constant • quintessence • decaying particle field • signature: • equation of state parameter with • leaking of gravity into a higher dimension • phantom energy  leads to the Big Rip

  39. On to new physics? • All proposed solutions would require additions beyond the current standard model of physics. • Type Ia Supernovae can distinguish between those possibilities • required is a large homogeneous set (about 200) of distant (0.2 < z< 0.8) supernovae

  40. The equation of state parameter  • General luminosity distance • with and M= 0 (matter) R= (radiation) = -1 (cosmological constant)

  41. Garnavich et al. 1998 w

  42. Cosmic strings Quintessence Cosmological constant SN Ia and 2dF constraints 2dF:  M h = 0.2 ± 0.03 KP: h = 0.72 ± 0.08 Tonry et al. 2003

  43. Summary • Supernovae measure distances over a large cosmological range • They are complementary to the CMB measurements in that they can measure the dynamics of the cosmic expansion • map the cosmological expansion • SNe Ia indicate accelerated expansion for the last 6 Gyr • There are indications that the accelerations turns into a deceleration at z>1 (>8 Gyr) • dynamic age of the universe H0t0=0.95±0.04 (13 Gyr for H0=72 km s-1Mpc-1; 15 Gyr for H0=64 km s-1Mpc-1)

  44. Summary (Problems) • Supernova systematics • unknown explosion mechanism • unknown progenitor systems • light curve shape correction methods for the luminosity normalisation (SCP vs. HZT) • signatures of evolution in the colours? • spectroscopy?

  45. The Future • Future experiments will distinguish between a cosmological constant or quintessence • ESSENCE, CFHT Legacy Survey, VST, VISTA, NGST, LSST, SNAP • Systematic uncertainties depend on our understanding of the supernovae • nearby samples, explosion models, radiation hydrodynamics

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