Gamma Ray Burst Host Galaxy Statistical Analysis And Optical Afterglow Observation

Gammaray bursts(GRBs)are a kind of energetic explosions in the universe.Since Vela satellite observed GRBs and published the observed data,this phenomenon with high energy released in a short time scale and decaying rapidly raised a lot of attention from people.For many years,we have had complete observed data of GRBs,Which is due to more and more satellites launched for GRBs observation and telescopes on-ground.According to these observation data,the research of GRBs has obtained great achievement.But some intrinsic problems are still not resolved yet,this thesis can provide some help for this kind of problems.This thesisincludes the statistical research for the host galaxies of a special kind of GRBs and the optical afterglow observation of GRBs.This thesisintroduces the background of GRBs firstly,including the origin,prompt emission,afterglow and host galaxy observation with emphasis on observation,and then introduces some theoretical models and important statistical relationships of GRBs.This thesisintroduces the research for three kinds of samples.we collected the most complete host galaxies of GRB/SN events up to now(sample 1),broad-line type Ic supernova host galaxies(sample 2),and Super-luminous supernovae host galaxies(sample 3).According to the observation data,we calculated the stellar mass,star formation rate per mass and metallicity of the host galaxies using same method,and analyzed the distributions for different parameters,we found that the three samples are different on metallicity.We are not sure it is due to the sample selection effect or the intrinsic difference.In Chapter 3 and Chapter 4,this thesisintroduces the optical afterglowfollowingobservation of GRBs,including optical afterglowobservation and photometric reduction.Now,we have analyzed three GRBs' observation data and published on GCN.The three GRBs are GRB151210A?GRB161027A ? GRB160131 A.Finally,this thesis makes a summary for the main work,and some plans for increasingthe sample number and algorithm improvement.