Mitigating Shear-dependent Object Detection Biases with Metacalibration
  Metacalibration is a new technique for measuring weak gravitational lensing
shear that is unbiased for isolated galaxy images. In this work we test
metacalibration with overlapping, or ``blended'' galaxy images. Using standard
metacalibration, we find a few percent shear measurement bias for galaxy
densities relevant for current surveys, and that this bias increases with
increasing galaxy number density. We show that this bias is not due to blending
itself, but rather to shear-dependent object detection. If object detection is
shear independent, no deblending of images is needed, in principle. We
demonstrate that detection biases are accurately removed when including object
detection in the metacalibration process, a technique we call metadetection.
This process involves applying an artificial shear to images of small regions
of sky and performing detection on the sheared images, as well as measurements
that are used to calculate a shear response. We demonstrate that the method can
accurately recover weak shear signals even in highly blended scenes. In the
metacalibration process, the space between objects is sheared coherently, which
does not perfectly match the real universe in which some, but not all, galaxy
images are sheared coherently. We find that even for the worst case scenario,
in which the space between objects is completely unsheared, the resulting shear
bias is at most a few tenths of a percent for future surveys. We discuss
additional technical challenges that must be met in order to implement
metadetection for real surveys.
