Searching for Supernovae in SDSS Galaxy Spectra

Rahman AmanullahRoger DeaneAriel GoobarMichelle KnightsAleksander KurekBob NicholHadi Rahmani

Cape Town Reloaded 2012

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)

Why Search for Supernovae in SDSS?

Perlmutter et al. (1998)

Type Ia supernova rates help constrain the time delay between progenitor formation and explosion. This improves cosmological constraints.

To do cosmology we need light curves not spectra, so why bother looking for supernovae in the SDSS database?

Supernova Rates

Ia Supernova rate as a function of redshift. Lines show models for different delay times of SNe progenitors.

Dahlen et al. (2004)

Supernova Rates

Dahlen et al. (2004)

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.

Dependence on Host Parameters

Sullivan et al. (2006)

Rates are seen to depend on star formation rate and stellar mass. We will look for relationships between galaxy properties and SN rates.

Searching for Supernovae

Example galaxy spectrum. Example galaxy spectrum with supernova.

Broad features

FFT Method to Reduce the Number of Candidates

FFT

Periodogram of spectrum

Supernovae Templates

SNIa Templates taken from Hsiao et al. (2007)

FFT Method to Reduce the Number of Candidates

FFT of SNIa Templates from Hsiao et al. (2007)

Epoch

FFT Method to Reduce the Number of Candidates

FFT of SNIa Templates from Hsiao et al. (2007)

These areas have increased power, relative to the rest of the periodogram.Epoch

Template Fitting

Spectrum smoothing using a Gaussian filter:

Template Fitting

We fit a polynomial to the residuals of the spectrum minus the template to correct for wavelength dependent effects.

Template Fitting

1) Smooth the spectrum to remove galaxy emission lines (Gaussian filter).

5) All spectra with epoch >-20 (at least some light comes from a supernova) are candidates.

4) The minimum χ2 indicates the best fit epoch.

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.

2) Step through all epochs, fitting the template to the spectrum.

Mock Catalogue

To test the efficiency of our methods, we use mock catalogues. These are generated using randomly chosen galaxy spectra from the SDSS dataset and inserting some SNIa templates into some of them.

Example spectrum from the mock catalogue with best fit template.

Summary

Finding supernovae in the SDSS spectral database can constrain supernova rates and give information about SN progenitors.

With a dataset of nearly one million objects, efficient techniques must be developed to perform this search in a computationally feasible way.

An FFT based method has been developed to cut down the number of candidates. Other methods, such as using supernovae identifier codes, are also being investigated.

As it is essential to know how efficient a method is before applying it to the SDSS data, a mock catalogue has been created.