Type of Submission
Poster
Keywords
Supernovae, cosmology, wavelets
Abstract
As cosmological probes, Type Ia Supernovae are some of the most useful. These exploding stars are used to measure cosmic distances and are useful to test and refine cosmological models. While SNe Ia are extremely uniform, the need for more precise measurements of the peak magnitude has led to the development of methods to correct current measurements for statistical errors. The work presented here has developed a new method for measuring the strength of spectral lines with a goal of using them as a basis for correcting the measured peak magnitudes. Wavelets were used to decompose the spectra so that the noise and large scale structure of the spectra were removed. From the resulting spectra it is straight forward to establish a new method of measuring the strength of the spectral features. The subgroups which have been proposed are reproduced by this method, also Principle Components Analysis was applied to the data set and the Philips relation between peak magnitude and the rate of change of the magnitude was confirmed. Future work involves development of a correction term to the Hubble Diagram and an algorithm for producing synthetic spectra.
Campus Venue
Stevens Student Center
Location
Cedarville, OH
Start Date
4-16-2014 11:00 AM
End Date
4-16-2014 2:00 PM
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Supernovae Wavelet Spectral Index Method: A Step Toward Precision Cosmology
Cedarville, OH
As cosmological probes, Type Ia Supernovae are some of the most useful. These exploding stars are used to measure cosmic distances and are useful to test and refine cosmological models. While SNe Ia are extremely uniform, the need for more precise measurements of the peak magnitude has led to the development of methods to correct current measurements for statistical errors. The work presented here has developed a new method for measuring the strength of spectral lines with a goal of using them as a basis for correcting the measured peak magnitudes. Wavelets were used to decompose the spectra so that the noise and large scale structure of the spectra were removed. From the resulting spectra it is straight forward to establish a new method of measuring the strength of the spectral features. The subgroups which have been proposed are reproduced by this method, also Principle Components Analysis was applied to the data set and the Philips relation between peak magnitude and the rate of change of the magnitude was confirmed. Future work involves development of a correction term to the Hubble Diagram and an algorithm for producing synthetic spectra.
