Dark Energy in the Supernova Legacy Survey

Dark Energy in the Supernova Dark Energy in the Supernova Legacy SurveyLegacy Survey

Mark Sullivan (University of Toronto)Mark Sullivan (University of Toronto)

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

Toronto Group

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

Alex Conley

French Group

Reynald Pain (PI), Pierre Astier, Julien Guy, Nicolas Regnault,

Jim Rich, Stephane Basa, Dominique Fouchez

UK

Gemini PI: Isobel Hook

Victoria Group

Chris Pritchet, Don Neill, Dave Balam

USA

LBL: Saul Perlmutter

CIT: Richard Ellis

Plus: Many students and associate members throughout the world

AAS Calgary June 2006AAS Calgary June 2006

SNLS: Vital StatisticsSNLS: Vital Statistics202n/5 year rolling SN survey202n/5 year rolling SN survey

Uses “Megacam” 36CCD 1 sq. deg. Uses “Megacam” 36CCD 1 sq. deg. imager on the CFHTimager on the CFHT

Observe in griz every 4Observe in griz every 4thth night in night in Grey/Dark timeGrey/Dark time

Typical seeing: 0.5-0.6 arcsecTypical seeing: 0.5-0.6 arcsec

Depth i’>24.5 (S/N=8) in 1 hrDepth i’>24.5 (S/N=8) in 1 hr

4 survey fields; 2 always available:4 survey fields; 2 always available:

Queue scheduling – and the highest queue priority – offers Queue scheduling – and the highest queue priority – offers protection from weatherprotection from weather

D1 (02:26,-04)D1 (02:26,-04) VIMOS, SWIRE, GALEX, XMM DeepVIMOS, SWIRE, GALEX, XMM Deep

D2 (10:00,+02)D2 (10:00,+02) COSMOS: ACS, Spitzer, GALEX, XMM etc.COSMOS: ACS, Spitzer, GALEX, XMM etc.

D3 (14:19,+53)D3 (14:19,+53) Groth Strip: – ACS, DEEP-II, GALEX etc.Groth Strip: – ACS, DEEP-II, GALEX etc.

D4 (22:15,-18)D4 (22:15,-18) GALEX, XMM DeepGALEX, XMM Deep


OrganisationOrganisationCFHT-LS CFHT-LS (imaging) – 2003-2008(imaging) – 2003-2008

DEEPDEEP WIDEWIDE

Galaxy studiesGalaxy studies

Time sequenced dataset Time sequenced dataset (202n over 5 years)(202n over 5 years)

Cosmic shearCosmic shear

ClustersClustersSNLSSNLS collaborationcollaboration

Data-processingData-processing

Major Spectroscopic ProgramMajor Spectroscopic Program

Gemini (Canada/UK/USA)Gemini (Canada/UK/USA)

120 hrs/yr (60:40:20)120 hrs/yr (60:40:20)

VLT (France/Other Euros)VLT (France/Other Euros)

120 hrs/yr120 hrs/yr

Keck (through LBL)Keck (through LBL)

40 hrs/yr40 hrs/yr

Cosmological analysesCosmological analyses

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

Rest-frame I-band Hubble diagramRest-frame I-band Hubble diagramKeck SN Ia UV study (Ellis/Sullivan et Keck SN Ia UV study (Ellis/Sullivan et

al.)al.)

LRIS high-S/N - metallicity through UV LRIS high-S/N - metallicity through UV lineslines

Testing accuracy of k-corrections in Testing accuracy of k-corrections in the UVthe UV

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

Using SNe IIP as standard candlesUsing SNe IIP as standard candles

Independent Hubble diagram to z=0.5Independent Hubble diagram to z=0.5


Current StatusCurrent Status

Survey has now been running for 3 yearsSurvey has now been running for 3 years

Nearly 300 spectroscopically confirmed SNe IaNearly 300 spectroscopically confirmed SNe Ia ““On track” for 500 by survey endOn track” for 500 by survey end


Rolling Light-curvesRolling Light-curves


Redshift distributionRedshift distribution

Redshift range: 0.08<z<1.06

SNLS-03D4agSNLS-03D4ag


Typical light-curvesTypical light-curves

z = 0.91

z = 0.36

Rolling search: Lightcurves are

equally well-sampled at all phases


Cosmological ConstraintsCosmological Constraints


First-Year SNLS Hubble Diagram

First Year Results (Astier et al. 2006)First Year Results (Astier et al. 2006)

Intrinsic disp.: 0.13 ± 0.02

Low-z: 0.15 ±0.02

SNLS: 0.12 ± 0.02

Assuming flatness, w=-1: ΩM = 0.263 ± 0.042


Dark energy: SNLS + BAODark energy: SNLS + BAO

Assuming flatness:

ΩM = 0.271 ± 0.021

w=-1.023 ± 0.087


Dark energy: SNLS + WMAPDark energy: SNLS + WMAP

066.0085.0984.0w

021.0029.0M 719.0

Spergel et al. (2006)


Coming soon…Coming soon…

The first year SNLS dataset provides the best SN The first year SNLS dataset provides the best SN sample for measuring “w”sample for measuring “w”

This sample is only 10-15% of the final sampleThis sample is only 10-15% of the final sample

Third Year cosmological analysis:Third Year cosmological analysis: Data collection complete in 2 monthsData collection complete in 2 months SN sample 4-5 times largerSN sample 4-5 times larger Improved “z” data will make the higher-redshift SNe Improved “z” data will make the higher-redshift SNe

more cosmologically powerful than in Year 1more cosmologically powerful than in Year 1 Results should be ready in the FallResults should be ready in the Fall


Where Next?Where Next?


Current status – Current status – and where nextand where next??First year:First year: NN~~70; w=-1.0270; w=-1.02 w: ±0.09 (stat) (RED)w: ±0.09 (stat) (RED) w: ±0.055 (sys) (BLUE)w: ±0.055 (sys) (BLUE)

Third Year:Third Year: N~250-300N~250-300

End-of-survey:End-of-survey: N~500-600N~500-600 ±~0.05 (stat)±~0.05 (stat) ±??? (sys)±??? (sys)

Substantial effort needs to be invested not only in “N”, but in reducing systematics


Potential Systematics in measuring wPotential Systematics in measuring wPhotometric zeropointsPhotometric zeropoints

Mismatches to local SNe observationsMismatches to local SNe observations

Contamination by non-SNe IaContamination by non-SNe Ia Spectroscopy is criticalSpectroscopy is critical

K-correctionsK-corrections U and near-UV uncertain - U and near-UV uncertain - see poster 13.04 by Eric Hsiaosee poster 13.04 by Eric Hsiao

ExtinctionExtinction Effective REffective RBB;; Dust evolution; Grey dustDust evolution; Grey dust

Redshift evolution in the mix of SNeRedshift evolution in the mix of SNe ““Population drift”Population drift”

Evolution in SN propertiesEvolution in SN properties Light-curves/Colors/LuminositiesLight-curves/Colors/Luminosities

More “mundane”

More “scientifically interesting”

?White Dwarf

Many competing models for:Many competing models for:• Nature of progenitor system – the Nature of progenitor system – the

“second star”“second star”• Single versus double degenerateSingle versus double degenerate• Young versus old progenitorYoung versus old progenitor• Explosion mechanism?Explosion mechanism?• Mass transfer mechanism?Mass transfer mechanism?


SNLS work on understanding SNe IaSNLS work on understanding SNe Ia

Relationship with environment (Sullivan et al. 2006)Relationship with environment (Sullivan et al. 2006) SN explode in galaxies with different ages/metallicitiesSN explode in galaxies with different ages/metallicities Population “drift”? – galaxy mix evolves with redshiftPopulation “drift”? – galaxy mix evolves with redshift

Evolution in SN propertiesEvolution in SN properties Rise-time analysis (Conley et al. 2006)Rise-time analysis (Conley et al. 2006)

High signal/noise UV spectroscopy (Ellis/Sullivan et al.)High signal/noise UV spectroscopy (Ellis/Sullivan et al.) Progenitor metallicity mostly affects the UV – Evolution?Progenitor metallicity mostly affects the UV – Evolution? Improved U-band k-correctionsImproved U-band k-corrections

Relationship with environment (Sullivan et al. 2006)Relationship with environment (Sullivan et al. 2006) SN explode in galaxies with different ages/metallicitiesSN explode in galaxies with different ages/metallicities Population “drift”? – galaxy mix evolves with redshiftPopulation “drift”? – galaxy mix evolves with redshift

Evolution in SN propertiesEvolution in SN properties Rise-time analysis (Conley et al. 2006)Rise-time analysis (Conley et al. 2006)

High signal/noise UV spectroscopy (Ellis/Sullivan et al.)High signal/noise UV spectroscopy (Ellis/Sullivan et al.) Progenitor metallicity mostly affects the UV – Evolution?Progenitor metallicity mostly affects the UV – Evolution? Improved U-band k-correctionsImproved U-band k-corrections


Evolution in Ia properties with z?Evolution in Ia properties with z?

Riess et al. 1999 rise time of low-z and high-z SNe different by 5.8.

Limitations:

•Inhomogeneous data

•No early-time data

Conley et al. find low-z and high-z SNLS risetimes consistent at 1

Conley et al. 2006, AJ, submitted

tr: rise time


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CFHT u*g’r’i’z’ imaging via the CFHT u*g’r’i’z’ imaging via the Legacy program. (UofT seeing Legacy program. (UofT seeing limit stacks)limit stacks)

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

Recent star-formation rate, Recent star-formation rate, and total stellar mass are and total stellar mass are estimated. estimated.

Sources classified based on Sources classified based on their specific star-formation their specific star-formation rate.rate.

CFHT u*g’r’i’z’ imaging via the CFHT u*g’r’i’z’ imaging via the Legacy program. (UofT seeing Legacy program. (UofT seeing limit stacks)limit stacks)

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

Recent star-formation rate, Recent star-formation rate, and total stellar mass are and total stellar mass are estimated. estimated.

Sources classified based on Sources classified based on their specific star-formation their specific star-formation rate.rate.

Optical Typing of SNe Ia hostsOptical Typing of SNe Ia hosts


SNLS: SN rate as a function of sSFRSNLS: SN rate as a function of sSFRUse specific star-

formation rate (SFR per unit

mass) to classify the SNLS SNIa

hosts

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

SNLS “passive” galaxies

125 Host Galaxies at

z<0.75

Low-redshift data from Mannucci et al. 2005


““A+B” ModelA+B” Model

SFRBMAt stellarIaSNR

Scannapieco & Bildsten (2005) and Mannucci et al. Scannapieco & Bildsten (2005) and Mannucci et al. (2005): Two component model(2005): Two component model

PromptPrompt: P=B @ t=0 and P=0 at all other times: P=B @ t=0 and P=0 at all other times

DelayedDelayed: P=A constant with time: P=A constant with time


Mannucci et al. 2006 – P(t)Mannucci et al. 2006 – P(t)

“Delayed”

“Prompt”

““A+B” essentially A+B” essentially approximates the details of approximates the details of

the SNIa delay-time the SNIa delay-time probability distributionprobability distribution


Mix will evolve with redshift…Mix will evolve with redshift…

Relative mix Relative mix evolves evolves stronglystrongly

with redshiftwith redshift

“B” component

“A” component

“A+B” total

Neill et al. (2006) SNLS

SNIa rate

SFRBMAt stellarIaSNR


Light-curve width / host-typeLight-curve width / host-type

Light-curveLight-curve widthwidth is a key is a key parameter for standardizing parameter for standardizing SNe Ia as calibrateable SNe Ia as calibrateable candlescandles

We use the “stretch” We use the “stretch” technique (e.g. Perlmutter et technique (e.g. Perlmutter et al. 1997)al. 1997)

Stretch is known to depend Stretch is known to depend on environment locally:on environment locally:

e.g. Riess et al. (1999), e.g. Riess et al. (1999), Hamuy et al. (1995;2000)Hamuy et al. (1995;2000)


Stretch/EnvironmentStretch/Environment

Stretch

Fainter SNe Brighter SNe


Further evidence for A+B?Further evidence for A+B?

All star-forming galaxies

Star-forming galaxies plus “mass-scaled”

passive

All star-forming galaxies MINUS

passive


Other environmental differences?Other environmental differences?

(Conley et al. 2006, AJ submitted)(Conley et al. 2006, AJ submitted)

No evidence for gross differences

between light-curves in passive

and active galaxies


Cosmological effects?Cosmological effects?

“First-year” SNLS dataset plus low-z

classified by morphology

More to come in the third year

analyses…

Black – passive

Red – active


Spectral UV evolution studiesSpectral UV evolution studies

Possible metallicity clues in the far-UV spectrumPossible metallicity clues in the far-UV spectrum Address concerns over systematics?Address concerns over systematics?

Little is known in the UV at z=0Little is known in the UV at z=0 Atmosphere precludes observationsAtmosphere precludes observations Space-based time is hard to come bySpace-based time is hard to come by

Try at intermediate redshift – where a guaranteed supply Try at intermediate redshift – where a guaranteed supply of SNe (SNLS) removes scheduling problemsof SNe (SNLS) removes scheduling problems

Keck-I/LRIS campaign (PI: Ellis) using LRIS-BKeck-I/LRIS campaign (PI: Ellis) using LRIS-B

~25 high-quality (S/N) spectra down to rest-frame 2800A~25 high-quality (S/N) spectra down to rest-frame 2800A

Lentz et al. (2000)

Varying metallicity changes line

blanketing in the UV


Mean z=0.5 UV spectrumMean z=0.5 UV spectrum

Ellis, Sullivan et al.

Preliminary


SummarySummary

SNLS is a mature survey – 8-10 new SNe Ia confirmed SNLS is a mature survey – 8-10 new SNe Ia confirmed every monthevery month

With nearly 300 SNe Ia in hand, the survey will have With nearly 300 SNe Ia in hand, the survey will have around 500 by the scheduled finish in 2008around 500 by the scheduled finish in 2008

11stst year SNLS dataset is the most uniform, well year SNLS dataset is the most uniform, well understood, and statistically powerful SN Ia data setunderstood, and statistically powerful SN Ia data set

SNLS data is currently the best SN Ia dataset to SNLS data is currently the best SN Ia dataset to combine with either BAO or WMAP data to measure combine with either BAO or WMAP data to measure dark energy.dark energy.


SummarySummary

The challenge now is the control of systematics:The challenge now is the control of systematics: SNe Ia know and “care” about their environmentSNe Ia know and “care” about their environment Light-curve width depends on age of the progenitor Light-curve width depends on age of the progenitor

populationpopulation Evidence for wide-range of delay-times, or two progenitors Evidence for wide-range of delay-times, or two progenitors

– relative mix evolves with redshift?– relative mix evolves with redshift?

The final SNLS data set will be essential for constraining The final SNLS data set will be essential for constraining systematics for next generation projects like the LSST or systematics for next generation projects like the LSST or NASA’s JDEM.NASA’s JDEM.

Dark Energy in the Supernova Legacy Survey

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