Searching for Supernovae

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Searching for Supernovae

  1. 1. Cape Town Reloaded 2012 Searching for Supernovae in SDSS Galaxy Spectra Rahman Amanullah Roger Deane Ariel Goobar Michelle Knights Aleksander Kurek Bob Nichol Hadi Rahmani
  2. 2. Why Search for Supernovae in SDSS? To do cosmology we need light curves not spectra, so why bother looking for supernovae in the SDSS database? Perlmutter et al. (1998)
  3. 3. Why Search for Supernovae in SDSS? To do cosmology we need light curves not spectra, so why bother looking for supernovae in the SDSS database? Type Ia supernova rates help constrain the time delay between progenitor formation and explosion. This improves cosmological constraints. Perlmutter et al. (1998)
  4. 4. Supernova Rates Ia Supernova rate as a function of redshift. Lines show models for different delay times of SNe progenitors.Dahlen et al. (2004)
  5. 5. Supernova Rates A photometrically selected sample could yield different SN rates to a spectroscopic one. There could be other surprises once broken up as a function of host type, inclination etc.Dahlen et al. (2004)
  6. 6. Dependence on Host Parameters Rates are seen to depend on star formation rate and stellar mass. We will look for relationships between galaxy properties and SN rates.Sullivan et al. (2006)
  7. 7. Searching for Supernovae Broad features Example galaxy spectrum. Example galaxy spectrum with supernova.
  8. 8. FFT Method to Reduce the Number of Candidates Periodogram of spectrum FF T
  9. 9. Supernovae Templates SNIa Templates taken from Hsiao et al. (2007)
  10. 10. FFT Method to Reduce the Number of Candidates Epoch FFT of SNIa Templates from Hsiao et al. (2007)
  11. 11. FFT Method to Reduce the Number of Candidates These areas have increased power, relative to the rest of the Epoch periodogram. FFT of SNIa Templates from Hsiao et al. (2007)
  12. 12. Template FittingSpectrum smoothing using a Gaussian filter:
  13. 13. Template Fitting We fit a polynomial to the residuals of the spectrum minus the template to correct for wavelength dependent effects.
  14. 14. Template Fitting1) Smooth the spectrum to remove galaxy emission lines (Gaussian filter).2) Step through all epochs, fitting the template to the spectrum.3) For each epoch: * Scale the template appropriately. * Subtract the template from the spectrum. * Fit a second order polynomial to the residuals, to remove wavelength- dependent effects. * Calculate the χ2 using the template + polynomial as the model.4) The minimum χ2 indicates the best fit epoch.5) All spectra with epoch >-20 (at least some light comes from asupernova) are candidates.
  15. 15. Mock CatalogueTo test the efficiency of our methods, we use mock catalogues. These aregenerated using randomly chosen galaxy spectra from the SDSS datasetand inserting some SNIa templates into some of them. Example spectrum from the mock catalogue with best fit template.
  16. 16. SummaryFinding supernovae in the SDSS spectral database can constrainsupernova rates and give information about SN progenitors.With a dataset of nearly one million objects, efficient techniquesmust be developed to perform this search in a computationallyfeasible way.An FFT based method has been developed to cut down thenumber of candidates. Other methods, such as usingsupernovae identifier codes, are also being investigated.As it is essential to know how efficient a method is beforeapplying it to the SDSS data, a mock catalogue has beencreated.

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