SNIa photometric studies in SNLS -...

SNIa photometric studies in SNLS

Nathalie Palanque-Delabrouille Moriond, March 2010 1

Nathalie Palanque-Delabrouille, CEA-Saclay

Spectroscopy already

limiting factor

Identification of SNIa without spectroscopy

Determine redshift of SNIa

Restrain to photometry

LSST 1 million SNIa

DES > 1.000 SNIa

Pan-STARRS > 100.000 SNIa

The Dark Energy Survey


Photometric study with SNLS

⇒ record of all transient events

SNIa

not SN

i r z g

i r z g

Rolling search mode (2003-2008) 1 observation / 4 nights 4 bands g r i z


Photometric study with SNLS

⇒ record of all transient events Rolling search mode (2003-2008) 1 observation / 4 nights 4 bands griz

G. Bazin et al., A&A,499 (2009) 653

Photometric selection of 117 SNCC

Core-collapse rate

Nathalie Palanque-Delabrouille 4 Moriond, March 2010

1- SNIa photometric identification 3-year SNLS data (2003 – 2006)

2- SNIa photometric redshift - incomplete zgal catalogs - wrong host galaxy - do better than zgal ?


SNIa photometric identification

AGN? Detections in i band (0.1 < z < 1.1)

300 000

Rejection of noise, stars, AGNs 1500

Identifiable host with photometric redshift O. Ilbert et al., A&A 457 (2006) 841I

1200 events with zgal


SNIa photometric identification Fit for SNIa (SALT2*) at zgal → color, shape (x1), normalization, tMAX

*SALT2: J. Guy et al., A&A 466 (2007) 11

Rejection of - core-collapse SN - bad zgal

Cuts on shape (duration) color color-magnitude



z gal -

zsp

e

-1 0 1

-0.4

0

0.4

Iaspec Iaphot CCspec MC .

50% of extreme colors ⇔ bad zgal

color





Iaspec Iaphot CCspec MC .

g

g-i

SN CC

SN Ia



511 SN Ia


Sample comparison Iaspec Iaphot

i

<z>phot = 0.9

<z>spec = 0.6


Samples comparison

color shape x1

mB - [MB - α(s-1)] – 5log(dL) vs. color mB - [MB - βc] – 5log(dL) vs. shape x1

-0.3 0 0.3

1

0

-1

-3 0 3

1

0

-1

brighter-bluer, brighter-slower relations : excellent agreement (over common magnitude range)

181 Iaspec 330 Iaphot

511 events

redshift

0 0.2 0.4 0.6 0.8 1 1.2

c!

-

1 x

" -

M +

B

m

34

36

38

40

42

44

46


Photometric Hubble diagram Iaspec Iaphot

(ΩM, ΩΛ) = (.23, .77) (ΩM, ΩΛ) = (1, 0)

181 Iaspec 330 Iaphot

Increased statistics by > x2 Subsample studies (split by color, shape or redshift)

Estimated contamination 0 SN IIp 3% other CC (Ib/Ic)

511 SNIa

Nathalie Palanque-Delabrouille 12 Moriond, March 2010

1- SNIa photometric identification 3-year SNLS data (2003 – 2006)

2- SNIa photometric redshift - incomplete zgal catalogs - wrong host galaxy - do better than zgal ?


SNIa photometric redshift Color-based

SNIa z = 0.45

400 600 800 λ (nm)

Wang et al. (2007)

Color-redshift degeneracies g r i z

Drawbacks

redshift

r -

i

At tMAX only

Adequate fit initialization

- χ2 vs. z map for c=shape=0 → z ini - fit with prior on c → z, shape - fit with prior on z, shape → z, shape, c

Break (some) color-redshift degeneracies

Use of full light curve


SNIa photometric redshift Light curve fit

SNIa z = 0.45

Palanque-Delabrouille et al. (2010) — SNLS Kessler et al. (2010) — SDSS

Advantages

875 900 925 time (day)

Drawbacks

Fit redshift, t0, color, shape, normalization

SNIa photometric redshift


SN photometric redshift

Palanque-Delabrouille et al., arXiv:0911.1629

outlier rate* 0.7%

resolution*

0.015

0.024 resolution:

rms of (zpho-zspe)/(1+zspe)

outlier rate: resolution > 0.015

Ia MC .



host galaxy photometric redshift

outlier rate 5.5%

resolution 0.037

SN photometric redshift

outlier rate 0.7%

resolution

0.015

0.024

Conclusions


SNIa identification in SNLS based on host galaxy redshift (zgal)

- stats x2 (→ subsample studies) - 3% contamination from core-collapse SN


- precision σΔz/(1+z) ~ 0.02 for z up to 1, better than zgal - 0.7% catastrophic redshifts (non SNIa contamination?) - negligible bias : < Δz > = 0.008 up to z=1.1

Combined analysis (identification + SN redshift) to be done Application to future surveys (LSST …)

SNIa photometric studies in SNLS -...

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