Date Thesis Awarded

5-2019

Document Type

Honors Thesis

Degree Name

Bachelors of Science (BS)

Department

Physics

Advisor

Seth Aubin

Committee Members

Seth Aubin

Marc Sher

Christopher Bailey

Abstract

Supernova remnants (SNRs) play an important role in shaping the energy density, chemical enrichment, and interstellar medium (ISM) of galaxies, and in our understanding of stellar evolution. Due to the high plasma temperatures of SNRs, they primarily emit X-rays. Using data collected with the Chandra observatory, we study a novel statistical imaging analysis technique to probe the underlying structure and physical properties of DEM L71, a SNR in the Large Magellanic Cloud. We used the statistical properties of the photons within an image pixel, such as the median energy, to make images of the energetics across the SNR. We have applied this technique DEM L71 and found a previously unidentified structure. Based on the spatially-resolved statistical information we identified an unexpected feature. We present the analysis of the spectra, (column density NH, plasma temperature kT, and ionization timescale tau) of this feature and DEM L71 and surrounding regions. We conclude that this feature has a higher abundance of ejecta material than surrounding regions. Spectra fits give a ratio of the energy flux normalization values of the ejecta model to the ISM model as .32 for the region of interest (region 2). This value is twice as much as any of the regions of extracted spectra surrounding region 2. This study demonstrates the utility of the median energy imaging technique to identify new energy structures of SNRs.

Share

COinS