Dark energy in the Dark energy in the Supernova Legacy Survey Supernova Legacy Survey Mark Sullivan (University of Toronto) Mark Sullivan (University of Toronto) http://legacy.astro.utoronto.ca/
Dec 15, 2015
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 + Justin Bronder, Richard McMahon, Nic Walton
Victoria Group
Chris Pritchet, Don Neill, Dave Balam
USA
LBL: Saul Perlmutter
CIT: Richard Ellis
Plus: Many students and associate members throughout the world
Durham, July 2006Durham, July 2006
SNLS: Vital StatisticsSNLS: Vital Statistics5 year (202n) rolling SN survey5 year (202n) rolling SN survey
Goal: 500 high-z SNe to measure “w”Goal: 500 high-z SNe to measure “w”
Uses “Megacam” imager on the Uses “Megacam” imager on the CFHT; griz every 4 nights in queue CFHT; griz every 4 nights in queue scheduled modescheduled mode
Survey running for 3 yearsSurvey running for 3 years
~~300 confirmed 300 confirmed zz>0.1 SNe Ia>0.1 SNe Ia
Largest single telescope sampleLargest single telescope sample
““On track” for 500 by survey endOn track” for 500 by survey end
Durham, July 2006Durham, July 2006
Supernova Legacy SurveySupernova Legacy Survey
Keck (8 nights/yr)
Gemini N & S (120 hr/yr)
VLT (120 hr/yr)
Magellan (15 nights/yr)
ImagingCFHT Legacy Survey
Deep program
Spectroscopy Types, redshifts from 8m-class
telescopes
DiscoveriesLightcurves
g’r’i’z’ every 4 days during dark
time
Durham, July 2006Durham, July 2006
Dark Energy in the SNLSDark Energy in the SNLS
Durham, July 2006Durham, July 2006
First-Year SNLS Hubble Diagram
First Year Results (Astier et al. 2006)First Year Results (Astier et al. 2006)Assuming flatness, w=-1: ΩM = 0.263 ± 0.042
15% of final sample
Durham, July 2006Durham, July 2006
Dark energy: SNLS + WMAPDark energy: SNLS + WMAP
066.0085.0984.0w
021.0029.0M 719.0
Spergel et al. (2006)
HST/GOODS+WMAP SNLS+WMAP
Durham, July 2006Durham, July 2006
The third year sampleThe third year sample
Third Year cosmological analysis:Third Year cosmological analysis: Data collection complete yesterday (end 06A)!Data collection complete yesterday (end 06A)! SN sample SN sample ~~4 times larger4 times larger Improved “z” data will make the z>0.8 SNe more Improved “z” data will make the z>0.8 SNe more
cosmologically powerful than in Year 1cosmologically powerful than in Year 1 Final results should be ready in the AutumnFinal results should be ready in the Autumn
Durham, July 2006Durham, July 2006
Preview of 3Preview of 3rdrd year Hubble Diagram ( year Hubble Diagram (preliminarypreliminary))
160 SNe Ia to z=0.8
~50 are still having data acquired or are still being reduced
~70 at z>0.8 await an improved k-correction template
Sullivan et al. in prep.
Durham, July 2006Durham, July 2006
UV and U-band k-correctionsUV and U-band k-corrections
At z<0.8, rest-frame B-V is used to colour-correct SNeAt z<0.8, rest-frame B-V is used to colour-correct SNe
At z>0.8:At z>0.8: i’ and z’ probe rest-frame U and B – i’ and z’ probe rest-frame U and B – no V datano V data Understanding of UV/U required for colour correction to be Understanding of UV/U required for colour correction to be
performedperformed Almost no data – error in existing templates essentially Almost no data – error in existing templates essentially
unknownunknown
Rest-frame UV study at Keck (PI: Richard Ellis)Rest-frame UV study at Keck (PI: Richard Ellis)
Durham, July 2006Durham, July 2006
SNe Ia show much diversity in the UV
Improving the k-correction spectral
template will decrease systematics from this
region at z>0.8
Ellis, Sullivan et al. in prep.
Durham, July 2006Durham, July 2006
Constraining population evolutionConstraining population evolution
Durham, July 2006Durham, July 2006
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; evolution in UV?U and near-UV uncertain; evolution in UV?
ExtinctionExtinction Grey dust; Effective RGrey dust; Effective RBB;; Dust evolutionDust evolution
Redshift evolution in the mix of SNeRedshift evolution in the mix of SNe ““Population drift” – environment?Population drift” – environment?
Evolution in SN propertiesEvolution in SN properties Light-curves/Colors/LuminositiesLight-curves/Colors/Luminosities
More “mundane”
More “scientifically interesting”
Durham, July 2006Durham, July 2006
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; evolution in UV?U and near-UV uncertain; evolution in UV?
ExtinctionExtinction Grey dust; Effective RGrey dust; Effective RBB;; Dust evolutionDust evolution
Redshift evolution in the mix of SNeRedshift evolution in the mix of SNe ““Population drift” – environment?Population drift” – environment?
Evolution in SN propertiesEvolution in SN properties Light-curves/Colors/LuminositiesLight-curves/Colors/Luminosities
“Population Evolution”
?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?
Durham, July 2006Durham, July 2006
SNLS: SN rate as a function of sSFRSNLS: SN rate as a function of sSFR
Per unit stellar mass, SNe are at least an order of magnitude more common in star-forming galaxies
SN rate in SNLS “passive” galaxies 125 Host
Galaxies at z<0.75
Sullivan et al. (2006)
Durham, July 2006Durham, July 2006
““A+B” Model for SN Ia rateA+B” Model for SN Ia rate
SFRBMAt stellarIaSNR
Scannapieco & Bildsten (2005) and Mannucci et al. Scannapieco & Bildsten (2005) and Mannucci et al. (2005) proposed a two-component model:(2005) proposed a two-component model:
Confirmed by SNLS results:Confirmed by SNLS results: SNR is linearly proportional to galaxy mass and SFRSNR is linearly proportional to galaxy mass and SFR SNe Ia will originate from a wide range in progenitor ageSNe Ia will originate from a wide range in progenitor age Two components? Or one with a wide range in delay-time?Two components? Or one with a wide range in delay-time? Either way – the mix of the two components will evolve Either way – the mix of the two components will evolve
with redshift…with redshift…
Durham, July 2006Durham, July 2006
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
SFRBMAt stellarIaSNR
Durham, July 2006Durham, July 2006
Population evolution: stretch and colourPopulation evolution: stretch and colour
Distance estimator used:Distance estimator used:
(how) Do these vary across environment?(how) Do these vary across environment?
By understanding and calibrating any relationships, we can By understanding and calibrating any relationships, we can improve the quality of our standard candleimprove the quality of our standard candle
csmBB )1(
s – “stretch” corrects s – “stretch” corrects for light-curve shape for light-curve shape
via via αα““c” – B-V colour corrects c” – B-V colour corrects
for extinction (and for extinction (and intrinsic variation) via intrinsic variation) via ββ
Durham, July 2006Durham, July 2006
““Stretch” and EnvironmentStretch” and Environment
Stretch
Fainter/faster SNe Brighter/slower SNe
Sullivan et al. (2006)
Star-forming galaxies
Passive galaxies
Similar trend observed at low-redshift
Simplest inference:
Older progenitors produce smaller stretch, fainter SNe
Younger progenitors produce larger stretch, brighter SNe
Durham, July 2006Durham, July 2006
Yet – so far – the stretch correction seems to work Yet – so far – the stretch correction seems to work equally well in all environmentsequally well in all environments
(Conley et al. 2006, AJ in press)(Conley et al. 2006, AJ in press)
No evidence for gross differences
between light-curves in passive
and active galaxies
Durham, July 2006Durham, July 2006
Colour relationshipsColour relationships
First year sample: β=1.6
(Milky Way dust predicts β=4.1)
But – stretch correlates with environment; so perhaps the colour correction (β) should
correlate with stretch
Fainter
Brighter SN Colour
Combination of:
Intrinsic “brighter-bluer” relationship
Extinction
Durham, July 2006Durham, July 2006
Colour relationships – low stretchColour relationships – low stretch
Preferentially located in passive galaxies
Less dust
Intrinsic SN relationship only?
Durham, July 2006Durham, July 2006
Colour relationships – high stretchColour relationships – high stretch
Effective β differs according to environment
Preferentially located in star-forming galaxies
Extinction much greater
Intrinsic SN relationship PLUS dust?
Or just different intrinsic SN relationship?
Durham, July 2006Durham, July 2006
Low-stretch SNe show a far smaller scatter on the Hubble Diagram – but, they are rarer (A+B!)
Low-stretch
rms: 0.14
High-stretch
rms: 0.20
Durham, July 2006Durham, July 2006
SummarySummary
33rdrd year analysis: challenge is controlling year analysis: challenge is controlling systematics such as population drift:systematics such as population drift: SNe Ia know and “care” about their environmentSNe Ia know and “care” about their environment Stretch depends on age of the progenitor populationStretch depends on age of the progenitor population SNe with narrow light-curves – preferentially hosted in SNe with narrow light-curves – preferentially hosted in
passive galaxies – show less scatter passive galaxies – show less scatter Cosmology with sub-samples of SNe improves the Cosmology with sub-samples of SNe improves the
power of the standard candlepower of the standard candle
Durham, July 2006Durham, July 2006
SummarySummary
The SNLS dataset is the most uniform, well understood, The SNLS dataset is the most uniform, well understood, and statistically powerful SN Ia data set – currently the and statistically powerful SN Ia data set – currently the best SN dataset to combine with BAO or WMAP data to best SN dataset to combine with BAO or WMAP data to measure w.measure w.
33rdrd year analysis will be completed in the Autumn – year analysis will be completed in the Autumn – watch this spacewatch this space
The final SNLS data set will be essential for constraining The final SNLS data set will be essential for constraining systematics and when planning next generation projects systematics and when planning next generation projects like the LSST or NASA’s JDEM.like the LSST or NASA’s JDEM.