Estimating weak lensing convergence correlation of Type-Ia supernovae
  from 5-year SNLS data by internal error estimate technique
  We report non-zero weak lensing convergence correlation signal of Type-Ia
supernovae from 5-year Supernovae Legacy Survey data. For our analysis we
utilize 296 supernovae magnification data from 5-year SNLS in the weak lensing
limit. The data we use consists of measurements from four different patches,
each covering 1 square degree of the sky, merged together. We demonstrate that
it is possible to have a very good estimate of the two point correlation
function from this data using internal error estimate technique. In order to
have a good estimate of the corresponding covariance matrix we apply bootstrap
spatial re-sampling technique where we reshuffle the original data consisting
of 296 data points 100-10000 times and compare the results with that obtained
from original data points. We show that this technique helps us arrive at a
reliable conclusion on weak lensing convergence even though the original
dataset comprises of a small number of data points. This also allows us to
compute the corresponding covariance matrix with great accuracy.
