We address the difference between integrable and chaotic motion in
quantum theory as manifested by the complexity of the corresponding
evolution operators. Complexity is understood here as the shortest
geodesic distance between the time-dependent evolution operator and the
origin within the group of unitaries. (An appropriate
'complexity metric' must be used that takes into account the relative difficulty of performing 'nonlocal’
operations that act on many degrees of freedom at once.) While simply
formulated and geometrically attractive, this notion of complexity is
numerically intractable save for toy models with Hilbert spaces of very
low dimensions. To bypass this difficulty, we trade the exact definition
in terms of geodesics for an upper bound on complexity, obtained by
minimizing the distance over an explicitly prescribed infinite set of
curves, rather than over all possible curves. Identifying this upper
bound turns out equivalent to the closest vector problem (CVP)
previously studied in integer optimization theory, in particular, in
relation to lattice-based cryptography. Effective approximate algorithms
are hence provided by the existing mathematical considerations, and they
can be utilized in our analysis of the upper bounds on quantum evolution
complexity. The resulting algorithmically implemented complexity bound
systematically assigns lower values to integrable than to chaotic
systems, as we demonstrate by explicit numerical work for Hilbert spaces
of dimensions up to \sim 10^4∼104.