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SNLS : Spectroscopy of Supernovae with the VLT
(status)
Grégory Sainton LPNHE, CNRS/in2p3
University Paris VI & VII
Paris, France
On behalf of the SNLS collaboration
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Moriond 2004 : Exploring the UniverseG. Sainton : SNLS, SN identification with VLT
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Contents
Overview of the VLT observations
Spectroscopy analysis
First (preliminary) results
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Overview of the VLT observations
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SNLS observations with the VLT
• 240 hours for 2 years (VLT large programme) on FORS-1 (longslit spectrograph) to identify SNe of the CFHTLS SN programme.
• Target of opportunity mode :– No precise observation date provided in advance.– Observations are submitted, as soon as a
candidate is discovered at CFHT.– Our observations have first priority and are
conducted in Service Mode.
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Observing at VLT
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Data processing
• Data available in Garching about 12 hours after the observations.
• Preprocessing of the data done with the FORS pipeline, customized for the SNLS use.
• Extraction of the spectra performed with our own tools, based on a minimum variance estimation (Horne, 1986).
•It produces the spectrum and its associated error.
•The host spectrum is extracted when possible.
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Spectroscopy analysis
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Two goals for the spectroscopy :– Identify the SN
(Ia, or non Ia).
– Measure of the redshift.(host galaxy lines or from the SN
if no host galaxy)
– The age (with respect to the restframe B band maximum of the LC).
– The contamination of the SN spectrum by the host galaxy.
– The type of the host.
SN Identification
Enough to built the Hubble diagram
(dL,z)
To c
ross
-ch
eck
th
e
resu
lts
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SN Identification (cont.)
SNIa = no H + strong Si II
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• It’s based on the 2 fitting of our spectrum with a model (local SNe + local galaxy).
• All the local spectra are into a database.
• These local spectra are from different type and different age (in the restframe) :
• 87 spectra from 8 SNIa
• 56 spectra from 5 peculiar SNIa
• 9 spectra from 2 SNIc
• 11 spectra from 1 IIP
•The database also contains a sample of galaxy spectra in case the host galaxy spectrum is not available.
SN Identification (cont.)
The quality of the identification is limited by the diversity of the database
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Sobs(obs) – (Ssn(rest [1+z])+Sgal(rest [1+z]))
SN Identification (cont.)
obs)
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• Loop over all the selected combinations of galaxie/SNe.
•Robustified fit (outliers like bad sky lines are discarded).
• One can fit on a given region only (eg. reject telluric absorptions).
•Sort the result by ascending 2.
Model with a galaxy template
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First (preliminary) results
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A bit of statistics for SNIa
<S/N> is about 3 per bin of ~3 Angstroms.
Redshift distribution <S/N>~ 3A distribution27 SNIa
<z>=0.55
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Example (Typical SNIa)
Best fit with sn1994d @ -2 days
R10D1-04A @ z = 0.687Texp = 2150s ;
<S/N>=5.95
Fit with host galaxy
No LC yet to check verify the age fitted.
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Example (Another SNIa)
Best fit with sn1994d (Ia) @ +2 days
• To date, the farthest SN of the SNLS programme.
• Database very poor in SNe with UV coverage.
R6D4-9 @ z=0.95 ;
No host galaxy
Texp= 2150s with Grism 300V (optic)
Texp= 2150s with Grism 300I (near IR)
<S/N>2.66A=4.46
Preliminary
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Example (Peculiar SNIa)SN2003ha @ z=0.285 ; Texp= 2150s Best fit with sn1999aa @ -
7days
sn1999aa is a peculiar SNIa, overluminous.
Good agreement with the LC
Preliminary
36% of peculiar SNIa expected (Li et al, 2000).
One of the farthest SNIa peculiar never observed.
SNLS will estimate the SNIa peculiar rate at large redshift.
<S/N>2.66A=12.6
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Example (non Ia SN)
Best fit with sn1994i @ +2 days
sn1994i is a SNIc.
Max of the LC 2 magnitudes weaker than a normal SNIa.
• Ic identification is difficult, very few SNIc spectra available in the litterature.
• Only one Ic in the SNLS sample, so far.
sn2003hb @ z=0.167 ; Texp= 2150s
<S/N>2.66A=11.0
Preliminary
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Conclusion
• After 6 months, more than 50 candidates spectroed.
• Already about 30 SNIa found between z~0.17 and z~0.95 with VLT (38 with the other telescopes).
• Beyond ID and redshift, VLT observations will allow us to do systematic and quantitative comparison of low z and high SNIa (evolution, rate of peculiars Ia...).
• This software gives quantitative tools to identify spectra.
Thank you !
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Back up slides
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Details of this analysis1. To discriminate between the first best
solutions
2. To discriminate between different type of SN
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Texp calculation : How does it work ?
The request is to get a minimum signal to noise ratio of 5, for a 10A binning, in the region from the calcium H&K and the magnesium MgII.
Ca H&K
MgII
z Texp(s)
0.3 70
0.4 160
0.5 370
0.6 910
0.7 1380
0.8 3060
0.9 6420
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Constraining the parameters
GUI in Tcl/Tk