  Performance of cryptanalytic quantum search algorithms is mainly inferred
from query complexity which hides overhead induced by an implementation. To
shed light on quantitative complexity analysis removing hidden factors, we
provide a framework for estimating time-space complexity, with carefully
accounting for characteristics of target cryptographic functions. Processor and
circuit parallelization methods are taken into account, resulting in the
time-space trade-offs curves in terms of depth and qubit. The method guides how
to rank different circuit designs in order of their efficiency. The framework
is applied to representative cryptosystems NIST referred to as a guideline for
security parameters, reassessing the security strengths of AES and SHA-2.
