  To obtain an accurate cosmological inference from upcoming weak lensing
surveys such as the one conducted by Euclid, the shear measurement requires
calibration using galaxy image simulations. We study the efficiency of
different noise cancellation methods that aim at reducing the simulation volume
required to reach a given precision in the shear measurement. Explicitly, we
compared fit methods with different noise cancellations and a method based on
responses. We used GalSim to simulate galaxies both on a grid and at random
positions in larger scenes. Placing the galaxies at random positions requires
their detection, which we performed with SExtractor. On the grid, we neglected
the detection step and, therefore, the potential detection bias arising from
it. The shear of the simulated images was measured with the fast moment-based
method KSB, for which we note deviations from purely linear shear measurement
biases. For the estimation of uncertainties, we used bootstrapping as an
empirical method. We find that each method we studied on top of shape noise
cancellation can further increase the efficiency of calibration simulations.
The improvement depends on the considered shear amplitude range and the type of
simulations (grid-based or random positions). The response method on a grid for
small shears provides the biggest improvement. In the more realistic case of
randomly positioned galaxies, we still find an improvement factor of 70 for
small shears using the response method. Alternatively, the runtime can be
lowered by a factor of 7 already using pixel noise cancellation on top of shape
noise cancellation. Furthermore, we demonstrate that the efficiency of shape
noise cancellation can be enhanced in the presence of blending if entire scenes
are rotated instead of individual galaxies.
