Type ia supernovae as probes of dark energy
This presentation is the property of its rightful owner.
Sponsored Links
1 / 31

Type Ia Supernovae as Probes of Dark Energy PowerPoint PPT Presentation


  • 70 Views
  • Uploaded on
  • Presentation posted in: General

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

Download Presentation

Type Ia Supernovae as Probes of Dark Energy

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


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

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/


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

Measurement of flux gives distance

GR:

Measure apparent flux and redshift  can infer distance and cosmology

Standard candle:


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


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!

  • 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


“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 SNWhat we need to measure

Peak brightness

Colour (c)

Lightcurve width (stretch)


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)

~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)

4.5% statistical errors

WMAP-5

SNe

BAO

SNLS3 + BAO + WMAP5 “shifts” + Flat

Sullivan et al. 2009


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


Identified systematics in SNLS3 (preliminary)

Conley et al. 2009


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 (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


Identified systematics in SNLS3 (preliminary)

Most uncertainties arise from combining different SN samples

Conley et al. 2009


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


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)


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

  • 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

  • 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)


Observed: β ~ 2-3

Standard Dust: β ~ 4.1

“Bubble” significance versus “β”

Conley et al. (2007)


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

residual, no s correction

SN Stretch

Plot cosmological residual without(s-1) correction


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


Howell et al. (2008)

“Metallicity”

No trend between HD residual and inferred metallicity


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 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

Kasen et al. 2006

DES/VIDEO

Current

JDEM/Euclid?

Excludes effect of dust!


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


  • Login