Transcript SNe Ia and the effect of environment

Supernova Legacy Survey
Mark Sullivan
University of Oxford
http://legacy.astro.utoronto.ca/
http://cfht.hawaii.edu/SNLS/
Paris Group
Toronto Group
Victoria Group
Chris Pritchet, Dave
Balam, + …
USA
LBL: Saul Perlmutter,
+…
Ray Carlberg, Alex Conley,
Andy Howell, Kathy Perrett
Reynald Pain, Pierre
Astier, Julien Guy, Nicolas
Regnault, Christophe
Balland, Delphine Hardin,
Jim Rich, + …
Marseille Group
Stephane Basa,
Dominique Fouchez
Oxford
Isobel Hook (Gemini PI),
Mark Sullivan, Emma
Walker
The SNLS
collaboration
Full list of collaborators at: http://cfht.hawaii.edu/SNLS/
SNLS: Vital Statistics
5 year “rolling” SN survey
Goal: 500 high-z SNe to measure “w”
Uses “Megacam” imager on the
CFHT; griz every 4 nights in queue
scheduled mode
Survey running for 4 years
~350 confirmed z>0.1 SNe Ia
>1500 SN detections in total


Largest single telescope
sample
450-500 by survey end
Cosmology with SNe Ia
Distance estimator constructed in rest-frame B-band:
B  mB  M B   ( s  1)    c
“Measured”
maximum light
magnitude
Standard absolute Bband magnitude
s – “stretch” corrects
for light-curve shape
via α
“c” – B-V colour
estimator corrects for
extinction and/or intrinsic
variation via β
Note: 2 DOF for the cosmological fits is >>1 unless an “intrinsic dispersion” term is added –
this parameterises our lack of knowledge about SNe
SNLS 1st year – 71 high-z SNe Ia
Astier et al. 2006
First-Year SNLS Hubble Diagram
470 citations
(297 in refereed
journals)
ΩM = 0.263 ± 0.042 (stat) ± 0.032 (sys)
<w>=-1.02 ± 0.09 (stat) ± 0.054 (sys) (with BAO + Flat Universe)
SNLS 3rd year versus 1st year
Increase in SN numbers: 71 to ~250

Ability to test SN sub-samples (+ “astrophysical systematics”)
Optimised survey design and calibration


Deeper/more frequent z’ exposures increases utility of z>0.7 SNe
3-year monitoring of fields; better understanding of Megacam array
Improved understanding of SN Ia properties


New “k-correction” template (Hsiao et al. 2007) incorporates Ellis et
al. UV spectra: reduction in potential source of systematics
New light curve fitting techniques exploit better understanding of SN
light curves at λ<4000A (rms: 0.19 -> 0.16mag)
Hubble
Diagram
~240 distant SNe Ia
(error was 0.042 in A06)
B  mB  M B   ( s  1)    c
Sullivan et al. in prep
Cosmological Constraints (Preliminary)
SNe
WMAP-3
6-7% measure
of <w>
BAO
SNLS+BAO (No flatness)
BAO
SNe
SNLS + BAO + simple WMAP + Flat
(relaxing flatness: error in <w>
goes from ~0.065 to ~0.115)
Potential SN Systematics in measuring w(a)
“Experimental Systematics”

Calibration, photometry, Malmquist-type effects
Contamination by other SNe or peculiar SNe Ia

Minimized by spectroscopic confirmation
Non-SNe systematics

Peculiar velocities; Hubble Bubble; Weak lensing
K-corrections and SN spectra

UV uncertain; “golden” redshifts; spectral evolution?
Extinction/Colour

“Extinction”
Effective RV; Intrinsic colour versus dust
Redshift evolution in the mix of SNe

“Population drift” – environment?
Evolution in SN properties

Light-curves/Colors/Luminosities
Increasing
knowledge of SN
“Population
physics
Evolution”
Residual without c-correction
β=4.1
Colour
correction
Colour—luminosity
relationship
inconsistent with
MW-type dust
Best-fit: β~3
SN Colour (c)
MW-dust: β≡RB=4.1
B  mB  M B   ( s  1)    c
SN colour-colour space
SN B-V
In colour colour
space, MW-type
extinction laws
also don’t work
SN U-B
Combination of dust+intrinsic?
SN B-V
In colour colour
space, MW-type
extinction laws
also don’t work
SN U-B
Residuals by host type
SNe in passive galaxies show a smaller scatter
“Intrinsic dispersion” consistent with zero
(Does intrinsic dispersion in SNe arise from dust?)
Cleaner sample: But SNe in passive galaxies are at high-z
(~20%: two component model) + very few locally
Passive hosts
Star-forming
hosts
Residual without c-correction
Residual without c-correction
Colour correction
required in all host
types – with a similar
β
180 high-z SNe
Star-forming
hosts
40 high-z SNe
Passive hosts
SN Colour (c)
Either:
a) Passive hosts have dust
b) An intrinsic relation
dominates over dust
Large “local” SN surveys
covering a wide wavelength
range (inc. near-IR) urgently
needed to disentangle this
Not clear what more of the
same will tell us…
SN Ia SFR dependencies – potential evolution?
SN Ia rate per unit mass
SN rate versus
host SFR
SN stretch distributions
split by galaxy starformation rate
Star-forming
hosts
SFR per unit mass
SNRIa t   A M stellar B  SFR
Passive
hosts
170 SNLS SNe Ia
(Update from Sullivan et al. 2006; better
zeropoints, host photometry, more SNe)
SN stretch (s)
SN mix predicted to evolve with redshift
SNRIa t   A M stellar B  SFR
Predicted mix
of two
components
evolves
strongly with
redshift
Redshift drift in stretch?
Nearby
z<0.75
Average stretch, and thus
average intrinsic brightness of
SNe Ia evolves with redshift
if stretch correction works
perfectly, this will not affect
cosmology
z>0.75
Full 1st year sample: solid
s<1 at z<0.4 and s>1 at z>0.4:
dashed
Howell et al. 2007
Future SN Ia Prospects
Short-term:
Current constraints on <w>: <w>=-1 to ~6-7% (stat)
(inc. flat Universe, BAO+WMAP-3)
At SNLS survey end statistical uncertainty will be 4-5%:


500 SNLS + 200 SDSS + larger local samples
Improved external constraints (BAO, WL)
Longer term:
No evolutionary bias in cosmology detected (tests continue!)
SNe in passive galaxies: seem more powerful probes, but
substantially rarer (esp. at high-z)
Colour corrections are the dominant uncertainty

Urgent need for z<0.1 samples with wide wavelength coverage

Not clear what the “next step” at high-z should be
Paris Group
Toronto Group
Victoria Group
Chris Pritchet, Dave
Balam, + …
USA
LBL: Saul Perlmutter,
+…
Ray Carlberg, Alex Conley,
Andy Howell, Kathy Perrett
Reynald Pain, Pierre
Astier, Julien Guy, Nicolas
Regnault, Christophe
Balland, Delphine Hardin,
Jim Rich, + …
Marseille Group
Stephane Basa,
Dominique Fouchez
Oxford
Isobel Hook (Gemini PI),
Mark Sullivan, Emma
Walker
The SNLS
collaboration
Full list of collaborators at: http://cfht.hawaii.edu/SNLS/