SN Ia Rates in the SNLS: SN Ia Rates in the SNLS: Progress Report Progress Report
Mark Sullivan Mark Sullivan University of OxfordUniversity of Oxford
http://legacy.astro.utoronto.ca/http://legacy.astro.utoronto.ca/http://cfht.hawaii.edu/SNLS/http://cfht.hawaii.edu/SNLS/
Paris
Reynald Pain, Pierre Astier, Julien Guy, Nicolas
Regnault, Christophe Balland, Delphine Hardin,
Jim Rich, + …
Oxford
Mark Sullivan, Isobel Hook, + …
Full list of collaborators at: http://cfht.hawaii.edu/SNLS/
Victoria
Chris Pritchet, Dave Balam
Toronto
Ray Carlberg, Alex Conley, Andy Howell, Kathy
Perrett
The SNLS The SNLS collaborationcollaboration
Marseille
Stephane Basa, Dominique Fouchez
LBL
Saul Perlmutter, + …
Paris
Reynald Pain, Pierre Astier, Julien Guy, Nicolas
Regnault, Christophe Balland, Delphine Hardin,
Jim Rich, + …
Oxford
Mark Sullivan, Isobel Hook, + …
Full list of collaborators at: http://cfht.hawaii.edu/SNLS/
Victoria
Chris Pritchet, Dave Balam
Toronto
Ray Carlberg, Alex Conley, Andy Howell, Kathy
Perrett
The SNLS The SNLS collaborationcollaboration
Marseille
Stephane Basa, Dominique Fouchez
LBL
Saul Perlmutter, + …
SNLS: Vital StatisticsSNLS: Vital Statistics
5 year “rolling” SN survey5 year “rolling” SN survey
Goal: >400 high-z SNe to measure “w”Goal: >400 high-z SNe to measure “w”
Uses “Megacam” imager on the CFHT; griz Uses “Megacam” imager on the CFHT; griz every 4 nights in queue scheduled modeevery 4 nights in queue scheduled mode
Survey nearly completeSurvey nearly complete
>>350 confirmed 350 confirmed zz>0.1 SNe Ia>0.1 SNe Ia
~~2000 SN detections in total2000 SN detections in total
Previous results: volumetric ratesPrevious results: volumetric rates
Neill et al. (2006)
Extend to test SN Ia rate evolution
Passive Passive hostshosts
Star-forming Star-forming hostshosts
Previous results: Connection to host galaxiesPrevious results: Connection to host galaxies
170 SNLS SNe Ia170 SNLS SNe Ia
SN rate versus host SFR
SN stretch distributions split by galaxy star-
formation rate
SN Ia
rate
per
uni
t mas
s
SFR per unit mass
SN stretch (s)
Evidence for two/multiple SN Ia channels, or just a wide-range of delay-
times with one channel?
Sullivan et al. (2006)
Extend to measure SNIa DTD
Extend to measure stretch-age relations
What’s new?What’s new?
Improved efficienciesImproved efficiencies Detailed simulations of entire surveyDetailed simulations of entire survey
Improved photometric typingImproved photometric typing Better templates, understanding of SNeBetter templates, understanding of SNe
More spectroscopic redshifts (VVDS, DEEP)More spectroscopic redshifts (VVDS, DEEP)
Improved host galaxy analysisImproved host galaxy analysis Deeper data, better calibrationDeeper data, better calibration Star-formation “bursts” now includedStar-formation “bursts” now included
More SNe!More SNe! Evolution in rates, DTDs, ...Evolution in rates, DTDs, ...
All SNLS SN Candidates
“Real” SN Ia Sample “Fake” Sample
Final SN Ia Sample
Masking (star halos, etc.)
Observational culls (data quality)
PhotoID: LC Fitting, Cull non-Ias
All unmasked SNLS imaging data
Detection efficiencies (z,s,c) Visibility (field,season)
Add random fake SNe Ia
Recover using RTA search software
Apply same data quality culls
€
rV =1V
1ε i zi,si,c i( )ΔTi
resti
N
∑
Constructing the rate
Efficiencies from Efficiencies from Monte Carlo simsMonte Carlo sims
Result is a grid of Result is a grid of efficiencies in efficiencies in
redshift,stretch,colourredshift,stretch,colour
Perrett et al. (2008)
Mag
z
s
c
Drifts in colour and stretch in SNLSDrifts in colour and stretch in SNLS
Example: Spectrscopic Example: Spectrscopic samplesample
Brighter/broader/bluer SNe Brighter/broader/bluer SNe easier to find and observe easier to find and observe spectroscopicallyspectroscopically
Observed stretch and colour Observed stretch and colour should change with zshould change with zStretch
Colour
Detection bias onlyDetection and spectroscopy
Perrett et al. (2008)
Malmquist effects: Compare to dataMalmquist effects: Compare to data
SN redshift estimationSN redshift estimationImproved version of Improved version of Sullivan et al. 2006Sullivan et al. 2006
LM method followed LM method followed by grid searchby grid search
z,s,c,dm,Tmaxz,s,c,dm,Tmax
Optional priorsOptional priors
Full PDF output for Full PDF output for each parametereach parameter
SN Ia
SN redshift estimationSN redshift estimation
SN IaCC SNe
Improved version of Improved version of Sullivan et al. 2006Sullivan et al. 2006
LM method followed LM method followed by grid searchby grid search
z,s,c,dm,Tmaxz,s,c,dm,Tmax
Optional priorsOptional priors
Full PDF output for Full PDF output for each parametereach parameter
SN redshift estimationSN redshift estimation
SN IaCC SNeUnknown
Improved version of Improved version of Sullivan et al. 2006Sullivan et al. 2006
LM method followed LM method followed by grid searchby grid search
z,s,c,dm,Tmaxz,s,c,dm,Tmax
Optional priorsOptional priors
Full PDF output for Full PDF output for each parametereach parameter
Volumetric rate evolutionVolumetric rate evolution
Perrett et al. (2008)
Preliminary
Pass
ive
Pass
ive
Star
-form
ing
Star
-form
ing
Star
burs
ting
Star
burs
ting
Little morphological information Little morphological information availableavailable
CFHT u*g’r’i’z’ imaging via the CFHT u*g’r’i’z’ imaging via the Legacy program.Legacy program.
PEGASE2 used to fit SED PEGASE2 used to fit SED templates to optical data templates to optical data measured from custom stacksmeasured from custom stacks
Star-formation rate, total stellar Star-formation rate, total stellar mass, mean age are estimated. mass, mean age are estimated.
Hosts classified by physical Hosts classified by physical parametersparameters
Physical Parameters of SNLS SN Ia hostsPhysical Parameters of SNLS SN Ia hosts
Sullivan et al. (2006)Sullivan et al. (2006)
u g
r iz
““Age” versus stretchAge” versus stretch0.2<z<0.8
Indicative of Delay-time Distribution (e.g. Totani et al.)?
DTDs from SN Ia host agesDTDs from SN Ia host ages
Caveats:Caveats:These are based on average galaxy agesThese are based on average galaxy ages ““mass-weighted”, “luminosity-weighted”, ... ?mass-weighted”, “luminosity-weighted”, ... ?
Sensitive to IMF/SFH choices, age/metallicity isSensitive to IMF/SFH choices, age/metallicity isssues ues Corrections:Corrections: Efficiencies, volume, visibility,“age of Universe”, SFR(z)Efficiencies, volume, visibility,“age of Universe”, SFR(z)
No resolution below ~0.5Gyr, no information at t>~10GyrNo resolution below ~0.5Gyr, no information at t>~10GyrSNe with very faint/no hosts not included (<10)SNe with very faint/no hosts not included (<10)
Nonetheless, SNLS is:Nonetheless, SNLS is: A well understood survey, large number of SNeA well understood survey, large number of SNe Has a high spectroscopic completeness, external redshiftsHas a high spectroscopic completeness, external redshifts
DTDDTD0.2<z<0.8
Preliminary
Monte Carlo error analysis yet to be performed
DTDDTD0.2<z<0.8
Preliminary“A+B”
DTDDTD0.2<z<0.8
PreliminaryGaussian
DTDDTD0.2<z<0.8
PreliminaryPower law
DTDDTD0.2<z<0.8
PreliminaryExponential
SummarySummarySNLS is a large homogeneous SN Ia sample, ideal for SNLS is a large homogeneous SN Ia sample, ideal for rates studiesrates studiesLarge amount of host galaxy dataLarge amount of host galaxy data
SN Ia rates:SN Ia rates: Measurement of volumetric rate extended to look for Measurement of volumetric rate extended to look for
evolutionevolution Measurement of galaxy rate extended to “DTD”Measurement of galaxy rate extended to “DTD”
Galaxy age distribution will place constraints on DTDGalaxy age distribution will place constraints on DTDLarge number of other transients not yet exploitedLarge number of other transients not yet exploited
Papers coming soon...Papers coming soon...