1. Supernova Legacy Survey Cosmology, Spectroscopy, and Progenitors T. Justin Bronder, DPhil Candidate Oxford University Isobel Hook, Supervisor

2. Overview Background on ‘Type Ia Cosmology’ Supernovae Legacy Survey Overview –Goals –Methods Photometry and Spectroscopy –Year 1 Cosmology Results Quantitative Spectroscopy of Hi-z SNe Ia –Goals / Methods / Results Brief intro to other SNLS Science –Ex) SNe Ia Hosts and Delay Times –Future work: Quantify evolution? Constrain progenitors?

3. Background Hydrogen? No H 2 present:H 2 present: General group? Type I supernovaeType II supernovae Other properties? SiHeneitherPhotometry/spectral properties Specific type? IaIbIcIIpIInII... - defining Type Ia Supernovae

4. Background Hydrogen? No H 2 present:H 2 present: General group? Type I supernovaeType II supernovae Other properties? SiHeneitherPhotometry/spectral properties Specific type? IaIbIcIIpIInII... - defining Type Ia Supernovae

5. Background (cont) Cosmological utility as ‘standardizeable candle’ –Variance in B’ peak magnitude –Peak mag. correlates w/ decline rate of light curve – empirical correction reduces peak magnitude deviations enough for cosmological use –Chart SNe Ia with z to determine matter / dark matter content in the Universe ‘s’ parameter – Goldhaber et al 2001

6. Cosmological constraints come from many sources Combine with Type Ia supernova surveys = ‘Cosmological Concordance Model’

7. Results inconsistent with  M =1 spatially flat cosmology (SNe too faint) SN data favor  >0 What is dark energy? Differentiate via the equation of state <w = p 

8. Background (cont) Issues / Concerns / Criticisms –Understanding of SNe Ia physics Extensive agreement (theory / observation / models) on basic model: –C/O White Dwarf exceeds M Ch –Thermonuclear runaway disrupts WD, late time – radioactive decay of unstable nuclear burning products Many questions follow: –Progenitor scenario – Single or Double Degenerate –Burning front – Detonation / Deflagration / Both –‘homogeneity’? Case of 1991T, 1991bg –Host dependence? Early galaxies host dimmer SNe Ia –Type Ia Cosmology Statistics and Systematics Luminosity calibration Evolution Extinction

9. SNLS collaboration http://cfht.hawaii.edu/SNLS/ Chris Pritchet: U. Victoria Ray Carlberg: U. Toronto Andy Howell: U. Toronto Mark Sullivan: U. Toronto Arif Babul: U. Victoria David Balam: U. Victoria Sara Ellison: U. Victoria F.D.A. Hartwick: U. Victoria Henk Hoekstra: CITA Don Neill: U. Toronto Julio Navarro: U. Victoria Kathy Perrett: U. Toronto David Schade: HIA Pierre Astier : CNRS-IN2P3, Paris Eric Aubourg Christophe Balland Luc Simard: HIA Peter Stetson: HIA Sidney van den Bergh: HIA Jon Willis: U. Victoria Isobel Hook: U. Oxford Justin Bronder: U. Oxford Richard McMahon: U. Cambridge Reynald Pain: CNRS-IN2P3, Paris Saul Perlmutter:LBNL Robert Knop: U. Vanderbilt James Rich: CEA-Saclay Nic Walton: U. Cambridge Eric Smith: Vanderbilt University Greg Aldering: LBNL Lifan Wang: LBNL Rachel Gibbons: LBNL Vitaly Fadayev: LBNL Stephane Basa Sylvain Baumont Sebastien Fabbro Melanie Filliol Ariel Goobar: Stockholm Delphine Guide Julien Guy Delphine Hardin Nicolas Regnault Tony Spadafora: LBNL Max Scherzer: LBNL Harish Agarwal: LBNL Herve Lafoux Vincent Lebrun Martine Mouchet Ana Mourao Nathalie Palanques Gregory Sainton Canada, France, UK, US, Sweden, Portugal

10. I – SNLS Overview Populate Hubble Diagram with over ~700 Type Ia SNe (.2 <z< 1.0) to estimate w to + 0.1 CFHT ‘Megacam’ used to acquire multiple (~5 epochs monthly) points in g’r’i’z’ for 1- potential candidate ID and 2-luminosity calibration (‘stretch factor’) Candidates verified w/ 8m-class telescopes – Gemini, VLT, and Keck Publications: –astro-ph/0509195 - Gemini spectroscopy, Howell et al –astro-ph/0510447 - Measurements for Cosmology, Astier et al –‘Photometric Selection of high-z Type Ia Candidates’ – Sullivan et al –VLT Spectroscopy summary – in prep –Much more on Hi-z SNe science in the works

11. -Possible Type Ia candidates followed up with 8m spectroscopy  main purpose is candidate ID and redshift confirmation -GMOS: 0.75’’ slit range = 465-930 nm 1.34 A/binned pixel disp. 45-90 min exposure time -FORS1: 0.7’’-1.3’’ slit range = 445-1100 nm 2.69 A/binned pixel disp. 25-62.5 min exposure time

12. Example Gemini/GMOS Nod & Shuffle spectrum 2 hr exposure SN i=24.0 Wavelength

13. Host Galaxy spectrum

14. Smoothed spectrum allowing for: template host galaxy subtraction Reddening Extracted spectrum SiII

15. - latest LSS / CMB / Baryon Acoustic Peak Oscillations results added to concordance model (Allen, Schmidt, & Fabian 2002 / Spergel et al 2003 / Eisenstein et al 2005)

16. - SNLS Hubble diagram – Astier et al (accepted by A&A) -  M =.263 +.042 (stat) +.032 (sys) (flat  CDM model) - w = -1.023 +.090 (stat) +.054 (sys)

17. I – SNLS Overview Spectroscopy implications –Only 1 epoch Velocity gradients, etc. not viable –SNR to maximize number of candidates observed + identified No synthetic spectra/detailed line analysis SNR-driven error bars on any results Well suited for SNLS purposes –Candidate ID via template-matching ‘Superfit’ (Howell et al. 2002, Lidman et al. 2005) Results in Gemini/VLT data papers 72 observations - 47 confirmed Ia (Gemini, 12 months) 108 observations – 67 confirmed Ia (VLT, 18 months

18. II – SNLS Spectroscopic Science Main purpose of spectra is ID/z –More thorough analysis a necessity for Object clarification / independent identification Physical insight –Evolution / systematic checks / progenitors –Needs + survey constraints imply data set is best suited for: Quantify the distribution of spectral properties (check for evolution w/ z, environment) –Specific comparison to low-z Ia SNe population –Type Ia sub-types ? Object clarification independent of  2 fits Another parameter space to explore the systematics of this large sample for cosmology

19. II – Science w/ SNLS spectroscopy - background - expansion velocity of CaII H&K feature -May also probe for Z effects (Hoflich et al 1998, Lentz et al 2000) if measured on a high-z population

20. II – Science w/ SNLS spectroscopy - background -R{CaII} and R{SiII} – spectral feature ratios from Nugent et al.1995 -Utilized in other empirical treatments of Type Ia spectra

21. II – Science w/ SNLS spectroscopy - background - Velocity gradients / spectral feature ratios explored empirically in Benetti et al 2004 - continuum of Type Ia properties? Two different populations?

22. II – Science with SNLS spectroscopy -Equivalent Widths (EW) -Shape independent method of spectral feature strength -Folatelli 2004 – EW measurements for Type Ia – specific features -Folatelli found this measurement useful for quantifying SNe Ia spectral - homogeneity – subtype ID, correlations w/ lightcurve-shape params

23. II- EW Results – Low z Distribution of spectral properties »EW {CaII} - Check of overluminous SNe Ia

24. II- EW Results – Low z Distribution of spectral properties »EW {SiII} - smaller epoch evolution than other features - correlates to Lightcurve parameters

25. II- EW Results – Low z Distribution of spectral properties »EW {SiII} - smaller epoch evolution than other features - correlates to Lightcurve parameters

26. II- EW Results – Low z Distribution of spectral properties »EW {MgII} - clear check of underluminous objects - additional correlation to luminosity params

27. II – Methods – EW (cont)

30. III – Equivalent Width results Quantitative analysis –Extensive low-z data employed to generate a mean trend for branch normal SNe Ia –Comparison ‘model’ for high-z objects Ejection velocities of CaII H&K feature also measured –Gaussian fit to feature – minima of fit = blueshift  velocity –Low redshift branch normal ‘model’ computed for quantitative comparison

31. III - Results Distribution of spectral properties : »EW {CaII} - SNLS 1 st Year - reduced chi squared:.511

32. III - Results Distribution of spectral properties : »EW {CaII} - epoch and sampling ‘free’ comparison via residuals – compare SNe populations w/ K-S Test – no significant difference

33. III - Results Distribution of spectral properties : »EW {SiII} - SNLS 1st Year - reduced chi squared:.471

34. III - Results Distribution of spectral properties : »EW {SiII} - KS test results show a difference (not significant) – identifies outliers independently of photometry / typing

35. III - Results Distribution of spectral properties : »EW {SiII} - recall light curve – spectra correlation

36. III - Results Distribution of spectral properties : »EW {SiII} - most objects follow Low-z trend… shift in distribution? Significant outliers?

37. III - Results Distribution of spectral properties : »EW {MgII} - SNLS 1st Year - reduced chi squared:.421

38. III - Results Distribution of spectral properties : »EW {MgII} - K-S test results similar to EW{CaII} – note possible overluminous outliers

39. III - Results Distribution of spectral properties : »V ej {CaII} - SNLS 1 st Year - reduced chi squared:.372

40. III - Results Distribution of spectral properties : »V ej {CaII} - Residuals – outliers noted – trend or small numbers? Possible metallicity indication – epoch not quite early enough to match predictions

41. III - Results Quantitative look at distribution of these spectral properties shows ‘no significant difference’ at high-z –Caveat – large error bars  test for broad consistency –K-S tests on residuals support  2 results –no major / systematic shift in Ia properties at high-z –Definite differences Are these expected? Implications for SNe Ia cosmology? Object sub-typing / systematic checks / PG’s –Spectroscopic outliers noted for i) follow up investigation ii) ‘spectroscopic’ SNLS Hubble diagram to check cosmology systematics –Host Galaxy – Luminosity/sub-type correlation at low z Quantitative spectroscopy + high-z host/environment data will enable exploration of this observation  test age/metallicity and progenitor dependencies

42. IV – SNLS science [brief intro] - Sullivan et al (2003) – ‘morphological’ SNe Ia Hubble diagram - Residuals for objects in E/S0 hosts were smaller than other host types - results w/in each type still supported dark matter model - extrapolate to higher redshift – unveil population / age / evolutionary differences  clues to progenitors? … delay times?

43. IV – SNLS science [brief intro] - delay times useful in constraining PG scenarios (SD v DD) - Previous work (Madau et al 1998, Dahlen & Fransson 1999, Gal-Yam & Maoz 2004, Strolger et al 2004) gave delay times from ~ 1.0 to 4.0 Gyr - heavily dependent on SFR assumptions - no results quite explained Fe / O (Ia / CC SNe) ratio in galaxy clusters Scannapieco & Bildsten 2005 – 2-component Type Ia formation - Scannapieco & Bildsten 2005 – 2-component Type Ia formation i) ‘prompt’ – proportional to SFR ii) extended – proportional to mass - quantifies simple observation that SNe Ia are seen in all galaxy types - SNLS data: Host spectra can be used to quantify local SFR and mass = specific star-formation rate  test this model - initial results ‘agree’ – two Type Ia channels or one channel with a large range in PG system age

44. IV – SNLS science [brief intro] - other evidence for two- channel/extended PG time Ia channels? - distribution of light-curve properties (here presented by star-formation rate rather than morphology courtesy of M. Sullivan) corroborates previous observations - evidence for two PG channels or populations?

45. IV – SNLS science [brief intro] - evidence for two PG channels or populations? - additional physical insight with spectroscopy?

46. IV – SNLS science [brief intro] - evidence for two PG channels or populations? - additional physical insight with spectroscopy?

47. Conclusion Brief summary of ‘Type Ia Cosmology’ –Earlier results (Riess et al 1998, Perlmutter et al 1999) supported by SNLS –Will also constrain w for additional cosmological insight SNLS Science and Spectroscopy –Successful at main goal – object ID / redshift –Quantified analysis can also i – check for broad consistency to low-z population ii – id sub-types and outliers  exert an additional systematic control on large SNLS data set iii – combine with other SNLS science to provide insight into Type Ia physics / pg’s