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Testing Dark Energy with Supernova (and other cosmological probes). Marek Kowalski Physikalisches Institut Universität Bonn 16.9.2009, Szczecin. Content. Introduction to supernova cosmology SNe observations & cosmological parameters Constraints on selected models. . M. - PowerPoint PPT Presentation
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16.9.2009 Marek Kowalski Grasscosmofun
Testing Dark Energy with Supernova(and other cosmological probes)
Marek Kowalski
Physikalisches Institut Universität Bonn16.9.2009, Szczecin
16.9.2009 Marek Kowalski Grasscosmofun
Content
Introduction to supernova cosmology
SNe observations & cosmological parameters
Constraints on selected models
16.9.2009 Marek Kowalski Grasscosmofun
1998: Discovery of dark energy
M
16.9.2009 Marek Kowalski Grasscosmofun M
Weak lensing mass census Large scale structure Baryon Accoustic OscillationsM= 0.3
Flat universe
+ M = 1.01+/-0.02
1998: Discovery of dark energy
16.9.2009 Marek Kowalski Grasscosmofun
WMAP 2006
16.9.2009 Marek Kowalski Grasscosmofun
SDSS, Eisenstein et al. (2005)
Baryon Acoustic Oscillation (BAO)
16.9.2009 Marek Kowalski Grasscosmofun
16.9.2009 Marek Kowalski Grasscosmofun 1
Supernova Type Ia
•Type Ia supernovae (SNe Ia) provide bright “standard candle” that can be used to construct a Hubble diagram.
• Accretion sends mass of white dwarf star to Chandrasekhar limit leading to gravitational collapse and a thermo-nuclear explosion of its outer layers.
• Each one is a strikingly similar explosion event with nearly the same peak intensity.
16.9.2009 Marek Kowalski Grasscosmofun
Astronomers think in…
Magnitudes: m = -2.5 log(Flux) + constant
Filter: B,V,R,I,Z (400-900 nm)
16.9.2009 Marek Kowalski Grasscosmofun
“Standard” Candles
• Nearby supernovae used to study SNe light curve (z<0.1)• Brightness not quite standard
Stretching the timescale:
€
t'= s× t
M '= M+α (s−1)
Correcting the Brightness:
Intrinsically brighter SNe have wider
lightcurves.
16.9.2009 Marek Kowalski Grasscosmofun
Spectra used for Identification & Redshift determination
16.9.2009 Marek Kowalski Grasscosmofun
Searching for Supernovae
Reference new picture difference
SN-Candidate
One example - the SNLS: • Canadian-French-Hawaii Telescope: 3.6 m
• MegaCam Camera: 3.6 108 pixels
• 5-year program finding about 500 SNe Ia
16.9.2009 Marek Kowalski Grasscosmofun
SNLS-Lightcurves
16.9.2009 Marek Kowalski Grasscosmofun
Sloan Digitial Sky Survey (SDSS)
First year papers: arXiv:0908.4274, arXiv:0908.4276
16.9.2009 Marek Kowalski Grasscosmofun Sloan Digital Sky Survey
16.9.2009 Marek Kowalski Grasscosmofun
SNe at large Redshifts (z>1)Observations from Space with the Hubble Space Telescopes:
15
16.9.2009 Marek Kowalski Grasscosmofun
SNe Type Ia & Acceleration of the Universe
Normalization
fainter then expected
M
1 00.73 0.270 1
slightly brighter M
fain
ter
Supernova Cosmology Project Kowalski et al., Ap.J. (2008)
16.9.2009 Marek Kowalski Grasscosmofun
Analysis aspects
Consistent Lightcurve FitsSALT fitter used for all SNe using mostly original band-passes (Guy et al 2005/2007).
Blind analysisThe analysis (i.g. cuts) were developed on a blinded data set, all luminosities were offsetby a hidden redshift-dependent amount.
Robust analysisInitial cosmological fit using median statistics.3-sigma outliers removed. Assignment of sample dependent dispersion.
Stretch and color corrected luminosity:
Large sample of SNe allows new studies of systematic errors
16.9.2009 Marek Kowalski Grasscosmofun
A heterogenous data sample
16.9.2009 Marek Kowalski Grasscosmofun
Study of - mean deviation- residual slope
A heterogenous data sample
16.9.2009 Marek Kowalski Grasscosmofun
Test for Tension
high-zlow
-z
mean deviation: OK
16.9.2009 Marek Kowalski Grasscosmofun
Test for Tension
high-zlow
-z
residual slope: (OK)
16.9.2009 Marek Kowalski Grasscosmofun
Testing SN evolution by subdividing the sample
Evolution test:Redshift
No significant evidence for evolution!
Evolution test:Population
16.9.2009 Marek Kowalski Grasscosmofun
Systematic errors
Nuisance parameters for systematic errors: μ =mmax −M +α (s −1) − βc + ΔM + ΔM i
common for all z>0.2 SNe sample dependent
16.9.2009 Marek Kowalski Grasscosmofun
Perlmutter et al., 1999
Results: Cosmological fit parameters
M
M
m = 0.274 ± 0.016(stat) ± 0.012(sys)
Ωm = 0.285 ± 0.020(stat) ± 0.010(sys)
Ωk = −0.010 ± 0.010(stat) ± 0.005(sys)
Combination of SNe with: BAO (Eisenstein et. al., 2005)CMB (WMAP-5 year data, 2008)
For a flat Universe:
… and with curvature:
16.9.2009 Marek Kowalski Grasscosmofun
Equation of state: w =p/
w =−0.969 ±0.061(stat) ±0.065(sys)SNe + BAO + CMB
... and allowing for curvature: w =−1.001±0.071(stat) ±0.081(sys)
With systematics
16.9.2009 Marek Kowalski Grasscosmofun
Redshift dependent w
w=w0 + (1-a) wa
w0+ w
a= 0
16.9.2009 Marek Kowalski Grasscosmofun
Redshift dependent w
Assuming step-wise constant w:
A floating non-SNe bin to decouple low from high-redshift constraints
16.9.2009 Marek Kowalski Grasscosmofun
Constraining Dark Energy models
16.9.2009 Marek Kowalski Grasscosmofun
- ln(1+z)
m
Constraining Models (I):Growing Neutrinos
w0 =−1+m,0
12 eV C. Wetterich (2007), L. Amendola et al. (2007),
Scalar-field couples to massive neutrinos.
Once neutrinos become sub-relativistic, one obtains -like behavior.
Today: massive neutrinos and small offset of w from -1:
Early dark energy (e) is second parameter and LSS and WMAP constrain e to be less then a few % (Doran et al. 2007). We assume a 10% linear growth prior.
D.Rubin, E. Linder, MK et al., ApJ (2009)
16.9.2009 Marek Kowalski Grasscosmofun
Constraining Models (I):Growing Neutrinos
Ear
ly d
ark
ener
gy
e
m<1.2 (h/0.7)2 eV @ 95 CL stat error onlym<2.1 (h/0.7)2 eV @ 95 CL with sys error
with sys error
3
2
1
Lab constraints:m2 eVKatrin sensitivity:m 0.2 eVoszillations:m0.05 eV
16.9.2009 Marek Kowalski Grasscosmofun
Constraining Models (II):Braneworld Gravity
Gravity leaking into extra dimensions on the scales of the Hubble radius can mimic cosmic acceleration.Dvali, Gabadadze, Porrati (2000) - DGP
We chose dark matter and curvature as DGP parameters to obtain an effective Dark Energy equation of state:
w(z) =−1−k(z)
1+m(z)−k(z)
16.9.2009 Marek Kowalski Grasscosmofun
DGP-Model versus CDM: 2
stat = 15.0 (stat error only) 2
sys = 2.7 (with sys. error)
Constraining Models (II):Braneworld Gravity
D.Rubin, E. Linder, MK et al., ApJ (2009)
16.9.2009 Marek Kowalski Grasscosmofun
Constraining Models (III):Backreaction
€ €
H(z) = H0 ×
Ωm (1+ z)3 + (1− Ωm )(1+ z)−n
From a solution to the Buchert Eq:
Perturbation expansion
(if appliciable): n= -1
n =1.6±0.9 @ 68% stat error onlyΩm=0.42±0.04 @ 68% stat error only
Boljakov et al. 2008Larena et al. 2008
16.9.2009 Marek Kowalski Grasscosmofun
Future projectsfor Dark Energy
Project z-range # SNe
Pan-STARRS 0.1-0.5 ~104
LSST (2015) 0.1-0.9 ~106
SNAP (2018) 0.2-3.0 >3000
(JDEM/Euclid)SNAP
Other important future methods:Weak lensing Cluster rates Baryon acoustic osciallation
16.9.2009 Marek Kowalski Grasscosmofun
Summary
SNe as standard candles provide a direct measurement of the Acceleration history
Combining SNe, BAO, and CMB we (slowly) become able to test individual models for dark energy
Today, systematic uncertainties are of similar size as statistical uncertainties (some even say they are larger). Next generation surveys offer the chance to improve on both.
16.9.2009 Marek Kowalski Grasscosmofun
Union
Union
Union
Riess GoldDavis 2007
Union w/oNew SCP SNe
without the 8new nearby SNe
184 SNe 192 SNe
Comparison with previous compilations