Type ia supernovae as probes of dark energy
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Type Ia Supernovae as Probes of Dark Energy. Mark Sullivan University of Oxford. USA Andy Howell, Alex Conley, Saul Perlmutter , + …. Paris Reynald Pain, Pierre Astier , Julien Guy, Nicolas Regnault , Christophe Balland , Delphine Hardin ,+ …. Toronto

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Type Ia Supernovae as Probes of Dark Energy

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Type ia supernovae as probes of dark energy

Type Ia Supernovae as Probes of Dark Energy

Mark Sullivan

University of Oxford


Type ia supernovae as probes of dark energy

USA

Andy Howell, Alex Conley, Saul Perlmutter, + …

Paris

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

Toronto

Ray Carlberg, Kathy Perrett

Marseille

StephaneBasa, Dominique Fouchez

Victoria

Chris Pritchet

Oxford

Mark Sullivan, Isobel Hook, + …

The SNLS collaboration

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


Type ia supernovae as probes of dark energy

Nearly a century after Einstein, the “cosmological constant” is back in vogue

  • Deluge of astrophysical data show the expansion of the Universe is accelerating. What does this mean?

  • Gravity should act to slow the expansion

  • GR is “wrong” - modified gravity on large scales?

  • “Λ”, >70% of the Universe in an unknown form – “dark energy”

    • Characterised by an equation of state, w(z) or w(a)


The standard candle

The standard candle

Measurement of flux gives distance

GR:

Measure apparent flux and redshift  can infer distance and cosmology

Standard candle:


The modern day hubble diagram

The modern day Hubble Diagram

Fainter  Further 

Faster expansion 

More cosmological constant

Different cosmological parameters make different predictions in the distance-redshift relation

Fainter (Further)

Brighter  Nearer 

Slower expansion 

Higher mass density 

Less cosmological constant

“Nearby” standard candles

“Distance-redshift” relation

For a given redshift…

Universe was smaller


Type ia supernovae as probes of dark energy

White Dwarf

SNeIa: thermonuclear explosions of C-O white dwarf stars

“Standard” nuclear physics

Uniform triggering mass

Bright: 10 billion suns, peak in optical

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

Duration: a few weeks

Standardizable: 6% calibration

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


Sne are not good standard candles

SNe are not good standard candles!

  • Uncorrected dispersion is ~0.5mag – or 25% in distance

  • Empirical linear relations exist which reduce this scatter

    • Brighter SNe have wider light curves

    • Brighter SNe have a bluer optical colour


Cosmology with sne ia

“Measured” maximum light magnitude

Cosmology with SNe Ia

SNeIa are standardised, not standard, candles:

“c” –opticalcolour estimator corrects for extinction and/or intrinsic variation via β

s – “stretch” corrects for light-curve shape via α

“Standard” absolute magnitude

 and corrections reduce scatter from25%to6% in distance


A typical sn what we need to measure

A Typical SNWhat we need to measure

Peak brightness

Colour (c)

Lightcurve width (stretch)


Snls vital statistics

SNLS: Vital Statistics

>400 high-z confirmed SNeIa to measure “w”

2000 SN detections in total

  • 2003-2008 SN survey with “MegaCam” on CFHT

  • griz every 4 nights in queue mode, densely sampled SN light curves


Snls3 hubble diagram preliminary

SNLS3 Hubble Diagram (preliminary)

~250 distant SNLS SNeIa

128 local SNeIa

86 SDSS-SN Ia

17 from HST

476 SNetotal

SNLS+flatness+w=-1:

ΩM 0.271±0.017

Sullivan et al. 2009


Snls3 cosmological constraints preliminary

SNLS3 Cosmological Constraints (Preliminary)

4.5% statistical errors

WMAP-5

SNe

BAO

SNLS3 + BAO + WMAP5 “shifts” + Flat

Sullivan et al. 2009


Sne ia systematics and issues

SNeIa: Systematics and Issues

  • “Experimental Systematics”

    • Photometric calibration; contamination; Malmquist biases

  • Non-SN systematics

    • Peculiar velocities; Weak lensing

  • SN model and K-corrections

    • SED uncertainties; colour relations; light curve fitters

  • Extinction/Colour

    • Effective RV; Mix of intrinsic colour and dust

  • Redshift evolution in the mix of SNe

    • “Population drift” – environment?

  • Evolution in SN properties

    • Light-curves/Colours/Luminosities

Tractable, can be modelled


Type ia supernovae as probes of dark energy

Identified systematics in SNLS3 (preliminary)

Conley et al. 2009


Snls3 cosmological constraints preliminary1

SNLS3 Cosmological Constraints (Preliminary)

4.5% statistical errors

WMAP-5

SNe

~5% systematic errors

~7% stat + sys errors

No evidence for departures from w=-1

BAO

SNLS3 + BAO + WMAP5 “shifts” + Flat

Sullivan et al. 2009


Snls3 cosmological constraints preliminary2

SNLS3 Cosmological Constraints (Preliminary)

4.5% statistical errors

WMAP-5

SNe

~5% systematic errors

~7% stat + sys errors

No evidence for departures from w=-1

BAO

SNLS3 + BAO + WMAP5 “shifts” + Flat

Sullivan et al. 2009


Type ia supernovae as probes of dark energy

Identified systematics in SNLS3 (preliminary)

Most uncertainties arise from combining different SN samples

Conley et al. 2009


Calibration

Calibration

  • The single greatest challenge in SNLS3

    (and probably every current SN Iasurvey…)

  • All SNe must be placed on the same photometric system

  • Different SN samples are calibrated to different systems:

    • Historical low-redshift samples: Observed in U,B,V,R (Landolt)

    • High-z: Observed in g,r,i,z- calibrate to SDSS or Landolt?

  • Challenges:

    • Zeropoints (colour terms)

    • Filter (system) throughput

  • Goal: Replace low-z sample & remove dependence on Landolt system


Type ia supernovae as probes of dark energy

Identified systematics in SNLS3 (preliminary)

When low-redshift sample is replaced, systematics should drop below 4%

Need for a “rolling” low-z survey (e.g. PTF, Skymapper)


Sne ia systematics and issues1

SNeIa: Systematics and Issues

  • “Experimental Systematics”

    • Photometric calibration; contamination; Malmquist biases

  • Non-SN systematics

    • Peculiar velocities; Weak lensing

  • SN model and K-corrections

    • SED uncertainties; colour relations; light curve fitters

  • Extinction/Colour

    • Effective RV; Mix of intrinsic colour and dust

  • Redshift evolution in the mix of SNe

    • “Population drift” – environment?

  • Evolution in SN properties

    • Light-curves/Colours/Luminosities

Tractable, can be modelled

“Extinction”

Increasing knowledge of SN physics

“Population Evolution”


Astrophysics i colour correction

Astrophysics – I: Colour correction

  • Dust would give a linear relation in log/log space

  • But, slope, β, << 4.1 (MW dust)

  • Mixture of external extinction and intrinsic relation?

  • Properties of the dust near SNe?

  • Dust in MW is different to other galaxies?

Before correction

β≈2.9

After correction

SN Colour


Hubble bubble

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)


Bubble significance versus

Observed: β ~ 2-3

Standard Dust: β ~ 4.1

“Bubble” significance versus “β”

Conley et al. (2007)


Astrohysics ii sn properties and environment

Astrohysics– II: SN properties and environment

Young

Old

SN light-curve shape strongly depends on host galaxy properties

Strong correlation with inferred age(or morphological type)


Demographic shifts and cosmology

Demographic shifts and cosmology

residual, no s correction

SN Stretch

Plot cosmological residual without(s-1) correction


Type ia supernovae as probes of dark energy

Metallicity

See Timmes, Brown & Truran (2003) for full story, including role of 56Fe

  • CNO catalysts pile up into 14N when H-burning is completed.

  • During He-burning, 14N is converted into 22Ne, neutron-rich

  • Higher metallicity means neutron-rich SN Ia

  • More neutrons during SN, means stable 58Ni and less 56Ni

  • Fainter SN

CNO cycle

Slowest

step


Metallicity

Howell et al. (2008)

“Metallicity”

No trend between HD residual and inferred metallicity


The next surveys

The next surveys

  • Low-z: New surveys needed to replace existing samples

    • Palomar Transient Factory (PTF)

    • 5 years, the first local rolling search (“SNLS @ low-z”)

    • First compete census of SNeIa in the local universe


The next surveys1

The next surveys

  • Higher-z:

    • Dark Energy Survey (DES)

    • Starts 201X, “super-charged”-SNLS

    • Intriguing synergy with VISTA/VIDEO near-IR survey

  • Ultimately, JDEM or similar mission


Near ir models predict smaller dispersion

Near-IR: Models predict smaller dispersion

Kasen et al. 2006

DES/VIDEO

Current

JDEM/Euclid?

Excludes effect of dust!


Summary

Summary

  • “SNLS3” constraints on <w>: <w>-1 to <4.5% (stat)

    (inc. flat Universe, BAO+WMAP-5)

  • Cosmological constant is completely consistent with data

  • Systematics ~5%; total error ~6%; dominated by z<0.1 sample

  • “SNLS5” statistical uncertainty will be <4%:

    • 400 SNLS + 200? SDSS + larger z<0.1 samples, BAO, WL

      Current issues:

  • Photometric calibration limiting factor; will improve dramatically

  • Mean SN Iaproperties evolve with redshift – no bias in cosmology detected

  • No evidence for metallicity effects

  • Colourcorrections poorly understood

  • Need for z<0.1 samples with wide wavelength coverage

    • Replace existing sample & disentangle SN Iacolours and progenitors

    • PTF underway since March 2009


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