Master of Teaching | OISE @ UofT
Type 1a supernovae are the brilliant second deaths of stars comporable to our Sun. They are of particular use in astronomy since they occur under strict conditions and explode with a theoritically predictable luminosity. This makes them useful for measuring extragalatic distances by watching their brightness drop off. With over 300 time series data points in the form of CCD images, I created algorithms to sort and correct bad images, masked and extracted CCD data, and fit theoretical models to the time series in order to predict physical parameters such as when the supernova exploded (usually hidden by SNR).
Stars don't just radiate the visible light we use to see, they radiate over an entire spectrum of wavelengths. In fact, every object with thermal energy has a unique black body spectrum than can be captured with a spectrograph, allowing us to identify the object's properties like temperature and chemical make-up. I created a model, by callibrating a spectrograph with a neon lamp, in order to determine the temperature and recessional velocity of a distant iron gas cloud (not accounting for redshift).