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The SN Ia Rate In 0.5<z<0.9 Clusters

The SN Ia Rate In 0.5<z<0.9 Clusters. Keren Sharon Tel Aviv University. Avishay Gal-Yam, Dani Maoz, Alex Filippenko, Ryan Foley, Jeff Silverman, Harald Ebeling, C.J. Ma, Eran Ofek, Megan Donahue, Richard Ellis,Robert Kirshner, Thomas Matheson, John Mulchaey, Vicki Sarajedini, Mark Voit.

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The SN Ia Rate In 0.5<z<0.9 Clusters

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  1. The SN Ia Rate In0.5<z<0.9 Clusters Keren Sharon Tel Aviv University Avishay Gal-Yam, Dani Maoz, Alex Filippenko, Ryan Foley, Jeff Silverman, Harald Ebeling, C.J. Ma, Eran Ofek, Megan Donahue, Richard Ellis,Robert Kirshner, Thomas Matheson, John Mulchaey, Vicki Sarajedini, Mark Voit

  2. Gal-Yam et al. (2002) Sharon et al. (2007) Mannucci et al. (2007) Firenze, May 2008

  3. Overview • 15 Clusters at 0.5< z <0.9 • HST imaging (PI Gal-Yam) • Follow-up & luminosity from ground (@Keck, Palomar, Subaru) • Found ~10 cluster candidates Firenze, May 2008

  4. The Cluster Sample Figure: redshift distribution • 0.5>z>0.9 • x-ray luminous • Were previously observed by HST/ACS  1 epoch for free Lx distribution of MACS clusters, Ebeling et al. (2007) Firenze, May 2008

  5. The Cluster Sample Clusterz • MACS0911 0.504 • MACS2214 0.504 • MACS0257 0.506 • MACS0018 0.540 (aka CL0016) • MACS1149 0.544 • MACS1423 0.545 • MACS0717 0.548 • MACS0454 0.550 (aka MS0451) • MACS2129 0.570 • MACS0647 0.584 • SDSS1004 0.680 • MACS0744 0.686 • MS1054 0.830 • CL0152 0.831 • CL1226 0.888 Firenze, May 2008

  6. HST imaging • Epoch 1: Archival, ≥1 orbit in I814 or i775(and additional bands for some clusters) • Epoch 2: cycle 14, 1 orbit/cluster (4x~500s) • Epoch 3: cycle 15, 1 orbit/cluster (but 6 clusters not observed due to ACS’ untimely death) Firenze, May 2008

  7. Search • Promptly after observation • Image subtraction • All by human (i.e., me  ) • Total search area:340 arcmin2 37 candidates Firenze, May 2008

  8. Hosts Redshifts • Keck Sprctroscopy w/ LRIS or DEIMOS • 1’’ Longslit / multislit mask Firenze, May 2008

  9. Spectra examples Firenze, May 2008

  10. Hosts Redshifts • Keck Sprctroscopy w/ LRIS or DEIMOS • 1’’ Longslit / multislit mask  • 9* hosts @cluster z (*one via sdss photo-z) • 2 hostless • 8 BG • 8 FG • 3 AGN • 7 ??? 8-16 cluster events (?) Firenze, May 2008

  11. SN Candidates – examples1. cluster events 4.4’’ z=0.55 z=0.83 z=0.54 z=0.55 z=0.89 z=0.83 Firenze, May 2008

  12. SN Candidates – examples2. field events 4.4’’ z=0.87(bg) z=0.58(bg) z=0.49(fg) z=0.75(bg) z=0.23(fg) z=0.62(bg) Firenze, May 2008

  13. SN Candidates – examples3. hostless Cluster z=0.504 Cluster z=0.570 Firenze, May 2008

  14. Cluster stellar-luminosity enclosed in search area Sum over all images Control time Numbers to rates: * Firenze, May 2008

  15. Stellar Luminosity • Subaru photometry in BVRIz’ (Ebeling et al.) • 0.5x0.5 deg centered on cluster Firenze, May 2008

  16. Stellar Luminosity • Subaru photometry in BVRIz’ (Ebeling et al.) • 0.5x0.5 deg centered on cluster • Star / galaxy separation light profile / half-light radius scales with magnitude stars and other point sources populate a well-defined locus in this plot, and can be separated from galaxies. ● MU_MAX = peak surface brightness above the background level. (SExtractor) Firenze, May 2008

  17. Stellar Luminosity • Subaru photometry in BVRIz’ (Ebeling et al.) • 0.5x0.5 deg centered on cluster • Star / galaxy separation • Net flux inside search area = total flux in area – sky flux density x area •  ‘cluster SED’ Firenze, May 2008

  18. Stellar Luminosity (E Spec. Template: Kinney et al. 1996) Firenze, May 2008

  19. Stellar Luminosity (Spec. Template: Kinney et al. 1996) Firenze, May 2008

  20. Stellar Luminosity (Spec. Template: Kinney et al. 1996) Firenze, May 2008

  21. Stellar Luminosity (Spec. Template: Kinney et al. 1996) Firenze, May 2008

  22. Stellar Luminosity • Convert VRIz’ to restframe B / g • Correct for faint end of luminosity function, due to magnitude limit (usually m~25) • Results: enclosed B-band stellar luminosity, typically ~ 2-5 x1012 LB Firenze, May 2008

  23. Cluster stellar-luminosity enclosed in search area Sum over all images Control time Numbers to rates: * Firenze, May 2008

  24. Search Efficiency Simulations • >120 Fake SNe were blindly added to each image • Reduction and search as in real data • Recovery rate noted as function of magnitude Firenze, May 2008

  25. Search Efficiency Simulations Firenze, May 2008

  26. Search Efficiency Simulations Firenze, May 2008

  27. Uncertainties • Statistical: Poisson errors of order 30% • Systematic: rate estimated many times by Monte-Carlo simulation, drawing: • Stretch factor from Sullivan et al. (2006) • Luminosity, efficiency from their distributions(e.g., see Sharon et al. 2007) • Classification uncertainty (in progress) Firenze, May 2008

  28. Results Gal-Yam et al. (2002) PRELIMINARY SNuB ~ 0.5 SNe/(100yr 1010 LB) SNuM ~ 0.12 SNe/(100yr 1010 M) Sharon et al. (2007) Mannucci et al. (2008) Firenze, May 2008

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