The discovery and classification of 16 supernovae at high redshifts in
  ELAIS-S1 - the Stockholm VIMOS Supernova Survey II
  Supernova surveys can be used to study a variety of subjects such as: (i)
cosmology through type Ia supernovae (SNe), (ii) star-formation rates through
core-collapse SNe, and (iii) supernova properties and their connection to host
galaxy characteristics. The Stockholm VIMOS Supernova Survey (SVISS) is a
multi-band imaging survey aiming to detect supernovae at redshift ~0.5 and
derive thermonuclear and core-collapse supernova rates at high redshift. In
this paper we present the supernovae discovered in the survey along with light
curves and a photometric classification into thermonuclear and core-collapse
types. To detect the supernovae in the VLT/VIMOS multi-epoch images, we used
difference imaging and a combination of automatic and manual source detection
to minimise the number of spurious detections. Photometry for the found
variable sources was obtained and careful simulations were made to estimate
correct errors. The light curves were typed using a Bayesian probability method
and Monte Carlo simulations were used to study misclassification. We detected
16 supernovae, nine of which had a core-collapse origin and seven had a
thermonuclear origin. The estimated misclassification errors are quite small,
in the order of 5%, but vary with both redshift and type. The mean redshift of
the supernovae is 0.58. Additionally, we found a variable source with a very
extended light curve that could possibly be a pair instability supernova.
