The Properties Of High Velocity Supernovae La And The Stripped-Envelope Supernovae

Supernova (SN) is one of the grandest explosions in the universe. As the final phase of the setellar evolution, it play an important role in the mass recycle. Type Ia SN is a powerful tool to probe the expansion history of the universe, due to the homogeneity in their peak brightness. According to the ejecta velocity, SNe Ia can be further classified as normal and high velocity (HV) subclass. The normal and HV SNe show differences in the intrinsic brightness and the light curve shapes. We examine the fraction of HV SNe in the Nearby Supernova Factory (SNFactory) data set and get a low value compared to the previous studies. In this thesis, we search for the potential bias in the SNFactory, and estimate the influence of the HV SNe on the cosmology.In the universe the Stripped-envelope SNe (SESNe) are as common as SNe Ia. Since the large differences between individual SESN, there are a few studies on the characteris-tics of the SESNe sample. Using the Lick Observatory Supernova Search (LOSS) unfil-tered photometry data, we search for the relationship betwen the light curve parameters and the host environment of SESNe, and try to constrain the progenitor of SESNe using the optical data.THU-NAOC Transient Survey is a time domain survey aiming to detect the SNe at early phases. Being one of the largest survey in China, since 2012 TNTS has detected a large number of transients. In this thesis, we give an introduction on the imaging system and describe the setting of the data reduction pipeline in detail.In this thesis, we make some innovations,· We examine potential system bias in SNFactory data sample, including the light curve fitting, screening bias and survey detection efficiency. Using the Sloan digital sky survey data, we study the host galaxy properties of the HV SNe. Using the Si II λA4128 line as velocity indicator, we estimate the HV SNe fraction for the Supernova Legacy Survey sample and to check the velocity evolution at higher redshift.· We estimate the SESNe unfiltered light curve parameters using a template stretch fitting. With the Galaxy Evolution Explorer UV data, we find two subclasses of SESNe according the local environment and light curve decay rates. We put a constraint on the progenitor of SN 2007gr with the optical data obtained by ground-based telescopes and Hubble space telescope.· We write the data reduction pipeline used by TNTS. Tuning the input parameters for the image analysis software and the object selection code, we get a high detection efficiency on TNTS.