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Constraining Dark Energy with the Supernova Legacy Survey. Mark Sullivan University of Toronto http://legacy.astro.utoronto.ca/ http://cfht.hawaii.edu/SNLS/. Paris Group Reynald Pain, Pierre Astier, Julien Guy, Nicolas Regnault, Christophe Balland, Delphine Hardin, Jim Rich, + ….

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Constraining Dark Energy with the Supernova Legacy Survey

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Constraining Dark Energy with the Supernova Legacy Survey

Mark Sullivan

University of Toronto

http://legacy.astro.utoronto.ca/

http://cfht.hawaii.edu/SNLS/


Paris Group

Reynald Pain, Pierre Astier, Julien Guy, Nicolas Regnault, Christophe Balland, Delphine Hardin, Jim Rich, + …

Toronto Group

Ray Carlberg, Alex Conley, Andy Howell, Kathy Perrett, Mark Sullivan

Victoria Group

Chris Pritchet, Dave Balam, + …

Marseille Group

Stephane Basa, Dominique Fouchez, + …

UK

Gemini PI: Isobel Hook, Richard McMahon, + …

USA

LBL: Saul Perlmutter, + …

CIT: Don Neill

The SNLS collaboration

Full list of collaborators at: http://cfht.hawaii.edu/SNLS/


White Dwarf

SNe Ia are thermonuclear explosions of C-O white dwarf stars

“Standard” nuclear physics

Bright: 10 billion suns

Standardizable: 7% calibration

Brightness and homogeneity make them the best measure of distance, and hence dark energy, in the Universe


Supernova Legacy Survey (2003-2008)

  • 5 year survey, goal: 500 distant SNe Ia to measure “w”

  • Uses CFHT/“Megacam”

  • 36 CCDs, good blue response

  • 4 filters for good k-corrections and color measurement

Megaprime


CFHT-LS Organisation

  • SNLScollaboration

  • Data-processing

  • Major Spectroscopic Program

    • Gemini (Canada/UK/USA)

      • 120 hrs/yr (60:40:20)

    • VLT (France/Other Euros)

      • 120 hrs/yr

    • Keck (through LBL)

      • 40 hrs/yr

  • Cosmological analyses

  • Magellan near-IR study (Freedman et al.)

  • Rest-frame I-band Hubble diagram

  • Keck SN Ia UV study (Ellis/Sullivan et al.)

  • LRIS high-S/N - metallicity through UV lines

  • Testing accuracy of k-corrections in the UV

  • SN IIP study (Nugent/Sullivan/Ellis et al.)

  • Using SNe IIP as standard candles

  • Independent Hubble diagram to z=0.5


Supernova Legacy Survey

Imaging

Distances from

light-curves

Spectroscopy

Redshifts  Distances from cosmological model

Discoveries

Lightcurves

Gemini N & S (120 hr/yr)

VLT (120 hr/yr)

g’r’i’z’ every 4 days during dark time

Magellan (15 nights/yr)

Keck (8 nights/yr)


k-corrections in SNLS


k-corrections in SNLS


Making a standard candle

1. “Phillipsrelation”: A correction to SN Ia light-curves based on light-curve shape drastically improves the quality of the standard candle.

Brightness 

56Ni  56Co  56Fe powers the SN Ia light-curve

  • Conventional Wisdom:

  • SNe are a one-parameter family defined by amount of 56Ni synthesized in the explosion.

  • More 56Ni  greater luminosity  higher Temperatures  higher opacity  broader LC

Time 

Brightness 

Time 


Making a standard candle

1. “Phillipsrelation”: A correction to SN Ia light-curves based on light-curve shape drastically improves the quality of the standard candle.

2. SN colour: A correction to the SN luminosity based on the SN colour

Fainter 

Blue

Red

Colour at peak


Making a standard candle

1. “Phillipsrelation”: A correction to SN Ia light-curves based on light-curve shape drastically improves the quality of the standard candle.

20%

Brightness 

2. SN colour: A correction to the SN luminosity based on the SN colour

  • Many methods:

  • Stretch – Perlmutter 97, 99

  • (M)LCS(2k2) – Riess, 95,96, Jha 07

  • SALT(2) – Guy 05, 07

  • SiFTO – Sullivan 07

  • CMAGIC – Wang et al.; Conley 06

  • Δm15 – Phillips 93; Hamuy 95; Prieto 06

Brightness 

7%!

Time 


“Local” SN Ia Hubble Diagrams

Most light-curve fitting techniques fare equally well

Prieto et al. 2006

Jha et al. 2007


Light-curve fit parameters from different fitters are tightly correlated


A Typical SNWhat we need to measure

Peak brightness

Colour (c)

Lightcurve width (stretch)


SNLS: Current status

  • Survey running for 3.5 years

  • ~310 confirmed distant SNe Ia (+ 40-50 not yet processed)

    • ~ Largest single telescope sample of SNe

    • “On track” for 500 spectroscopically confirmed SNe Ia by survey end (>1000/>2000 total SNIa/All SN light-curves)


“Rolling” light-curves


First-Year SNLS Hubble Diagram

SNLS 1st year

Astier et al. 2006

349 citations

(187 in refereed journals)

ΩM = 0.263 ± 0.042 (stat) ± 0.032 (sys)

<w>=-1.02 ± 0.09 (stat) ± 0.054 (sys)


“Third year” SNLS Hubble Diagram (preliminary)

3/5 years of SNLS

~240 distant SNe Ia

  • Independent analysis to 1st year:

    • Different calibration route

    • Different photometric methods

    • Different SN light-curve analysis tools

Preliminary

Sullivan et al. 2007


“Third year” SNLS Hubble Diagram (preliminary)

Best-fit for SNLS+flatness

Preliminary

(error was 0.042 in A06)

ΩM=0.3, Ωλ=0

ΩM=1.0, Ωλ=0

Sullivan et al. 2007


Cosmological Constraints (Preliminary)

SNe

WMAP-3

6-7% measure of <w>

SNe

BAO

BAO

SNLS+BAO (No flatness)

SNLS + BAO + simple WMAP + Flat

Sullivan et al. 2007


Future Prospects with SNLS

  • Current constraints on <w>: <w>=-1 to ~6-7% (stat)

  • <w> >-0.8 excluded at 3-sigma level

  • At survey end a 4-5% statistical measure will be achieved:

    • 500 SNLS + 200(?) SDSS + new local samples

    • Improved external constraints (BAO, WMAP, WL)

  • Systematic errors becoming ever more important


Potential SN Systematics in measuring w(a)

More “mundane”

  • “Experimental Systematics”

    • Calibration, photometry, Malmquist-type effects

  • Contamination by non-SNe Ia

    • Minimized by spectroscopic confirmation

  • K-corrections

    • UV uncertain; “golden” redshifts; spectral evolution?

  • Non-SNe systematics

    • Peculiar velocities; Hubble Bubble; Weak lensing

  • Extinction

    • Effective RB;Dust evolution

  • Redshift evolution in the mix of SNe

    • “Population drift” – environment?

  • Evolution in SN properties

    • Light-curves/Colors/Luminosities

More “scientifically interesting”


Hubble Bubble

  • Latest MLCS2k2 paper (Jha 2007)

    • MLCS2k2 attempts to separate intrinsic colour-luminosity and reddening

  • 3σ decrease in Hubble constant at ≈7400 km/sec – local value of H0 high; distant SNe too faint

  • Local void in mass density?

  • Could have significant effects on w measurement

SALT

MLCS2k2

No Bubble with other light-curve fitters!

Conley et al. (2007)


Light-curve fit parameters from different fitters are tightly correlated


Handling colour in SN Ia

  • Colour is the most important correction to SN Ia luminosities

  • Underlying physics: Redder SNe Ia are fainter due to

    • Extinction along the line of sight

    • Intrinsic luminosity/colour relationship of the SN population

  • Two basic approaches:

    • Attempt to identify intrinsic relationship and assume standard dust dominates the rest (Jha et al.)

    • Fit a luminosity/colour relationship empirically on the SN data

β=4.1


Observed: β ~ 2

Standard Dust: β ~ 4.1

“Bubble” significance versus “β”

Conley et al. (2007)


All fitters agree: β<4.1

Conley et al. (2007)


What does β=2 (RV=1) mean?

  • Very strange dust? But RV=1 is not seen anywhere in the Milky Way

  • Dust around SNe is changed by the explosion?

  • Most likely: SNe have an (as yet) uncorrected-for intrinsic colour-luminosity relationship

  • While fitting empirically for β may be empirical, currently it’s the best way


Potential SN Systematics in measuring w(a)

More “mundane”

  • “Experimental Systematics”

    • Calibration, photometry, Malmquist-type effects

  • Contamination by non-SNe Ia

    • Minimized by spectroscopic confirmation

  • K-corrections

    • UV uncertain; “golden” redshifts; spectral evolution?

  • Non-SNe systematics

    • Peculiar velocities; Hubble Bubble; Weak lensing

  • Extinction

    • Effective RB;Dust evolution

  • Redshift evolution in the mix of SNe

    • “Population drift” – environment?

  • Evolution in SN properties

    • Light-curves/Colors/Luminosities

More “scientifically interesting”


More “mundane”

More “scientifically interesting”

Potential SN Systematics in measuring w(a)

  • “Experimental Systematics”

    • Calibration, photometry, Malmquist-type effects

  • Contamination by non-SNe Ia

    • Minimized by spectroscopic confirmation

  • K-corrections

    • UV uncertain; “golden” redshifts; spectral evolution?

  • Non-SNe systematics

    • Peculiar velocities; Hubble Bubble; Weak lensing

  • Extinction

    • Effective RB;Dust evolution

  • Redshift evolution in the mix of SNe

    • “Population drift” – environment?

  • Evolution in SN properties

    • Light-curves/Colors/Luminosities

“Population Evolution”


White Dwarf

  • Many uncertainties:

  • Nature of progenitor system – the “second star”

  • Single versus double degenerate?

  • Young versus old progenitor?

  • Explosion mechanism?

  • Effect of progenitor metallicity on luminosity?

?


Host galaxies impact SN properties

SN Ia Light-curve shape depends on morphology

e.g. Hamuy et al. (2000)

High stretch

Low stretch

Some evidence that SNe Ia in ellipticals show smaller scatter

Sullivan et al. (2003)


r

i

z

g

u

Typing of SNLS SN Ia hosts

  • Little morphological information available

  • CFHT u*g’r’i’z’ imaging via the Legacy program.

  • PEGASE2 is used to fit SED templates to the optical data.

  • Recent star-formation rate, total stellar mass, mean age are estimated.

  • Hosts classified according to physical parameters instead of “what they look like”.

Passive

Star-forming

Starbursting

Sullivan et al. (2006)


SNLS: SN rate as a function of sSFR

SN Ia hosts classified by star-formation activity

Per unit stellar mass, SNe are at least an order of magnitude more common in more vigorously star-forming galaxies

SNLS “passive” galaxies


SNLS selection of hosts

D2 ACS imaging

Plenty of irregular/late-type systems

Few genuine ellipiticals


SN Ia Stretch dependencies

Stretch by galaxy star-formation activity

Stretch versus mean age

Star-forming

Passive

The majority of SN Ia come from young stellar populations

170 SNe Ia

(Update from Sullivan et al. 2006; better zeropoints, host photometry, more SNe)


Recent SNLS evidence for two components for SNe Ia

Older progenitor SNe

Empirically, SN Rate is proportional to galaxy mass

Preferentially found in old stellar environments

Typically fainter with faster light-curves (low stretch)

Younger progenitor SNe

Empirically, SN rate is proportional to galaxy star formation rate

Exclusively found in later type star-forming galaxies

Typically brighter with slower light-curves (high stretch)

(Extreme example: SNLS-03D3bb?)


Recent SNLS evidence for two components for SNe Ia

Older progenitor SNe

Empirically, SN Rate is proportional to galaxy mass

Preferentially found in old stellar environments

Typically fainter with faster light-curves (low stretch)

Younger progenitor SNe

Empirically, SN rate is proportional to galaxy star formation rate

Exclusively found in later type star-forming galaxies

Typically brighter with slower light-curves (high stretch)

(Extreme example: SNLS-03D3bb?)

Could evolution between the two components with redshift distort the dark energy signal?


SN population drift?

Relative mix of evolves with redshift

A+B predictions, but similar for any two component model

Sullivan et al. 2006


Stretch versus redshift (3rd year)

?


Evolution in Stretch?

Gaussians – predicted evolution from A+B model

Average stretch, and thus average intrinsic brightness of SNe Ia evolves with redshift

but

if stretch correction works perfectly, this should not affect cosmology

Nearby

z<0.75

z>1

Howell et al. 2007


Effect on cosmology

Extreme case using SNLS 1st year

Use only s<1 SNe Ia at z<0.4, only s>1 SNe at z>0.4

Effects of evolution smaller than error budget for determination of <w>, must be studied closely to determine the effect on measuring w(a)

SNLS yr 1 N: 115

 = 1.6  = 1.8

w = -1.05  0.09

M = 0.27  0.02

Yr 1 s split N: 56

 = 1.4  = 1.8

w = -0.92  0.15

M = 0.28  0.03


Split by s (preliminary)


Stretch correction across environments

Rest-frame B composite light-curve

Conley et al. 2006

No evidence for gross differences between light-curves in passive and active galaxies


“Morphological” Hubble diagram


SN Subsets

Split by host galaxy

Passive

α=1.34 ± 0.25

β=2.52 ± 0.2

σ~0.10 mag

<w>=-0.88±0.11

Star-forming

α=1.19 ± 0.15

β=2.71 ± 0.2

σ~0.140 mag <w>=-1.04±0.08

Preliminary

Problems: Low-redshift sample very small, Malmquist correction likely to be different


Varying metallicity changes line blanketing in the UV

Do SNe Ia Evolve? UV Spectrum Probes Metallicity

Lentz et al. (2000)


High S/N spectra of SNLS SNe

Ellis, Sullivan et al. 2007


Light-curve width dependence

Implications for JDEM: k-corrections must improve in accuracy


Summary

  • SNLS is a well-controlled, calibrated and understood experiment

  • Current SN Ia measurement determine <w> to ~ 6-7%

    • SNLS is the best cosmological SN Ia dataset available

  • In 2-3 years, 4-5% will be achieved

  • Colour is the critical correction to SN Ia distances; currently can only be handled empirically

  • SNe Ia have a range of progenitor ages

    • Impacts on light-curve shape: faster/older & slower/younger

  • SNe in passive galaxies are better standard candles?

    • More homogeneous stellar population? Less dust?


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