  We explore the ability of weak lensing surveys to locate massive clusters. We
use both analytic models of dark matter halos and mock weak lensing surveys
generated from a large cosmological N-body simulation. The analytic models
describe average properties of weak lensing halos and predict the number
counts, enabling us to compute an effective survey selection function. We test
the model prediction for the peak number counts in weak lensing mass maps
against the mock numerical data, and find that the noise due to intrinsic
galaxy ellipticities causes a systematic effect which increases the peak
counts. We develop a correction scheme for the systematic effect in an
empirical manner, and show that, after the correction, the model prediction
agrees well with the mock data. The mock data is also used to examine the
completeness and efficiency of the weak lensing halo search with fully taking
into account the noise and the projection effect by large-scale structures. We
show that the detection threshold of S/N=4-5 gives an optimal balance between
completeness and efficiency. Our results suggest that, for a weak lensing
survey with a galaxy number density of ng=30/arcmin^2 with a mean redshift z=1,
the mean number of peaks in the 10sq deg area is N_peak=62 for a detection
threshold S/N=4. The contamination rate is 42%, and thus, on average, 36 out of
62 peaks (at least) are signals from real halos. Weak lensing surveys thus
provide a reasonably efficient way to searching for massive clusters.
