  The theory of quantum algorithms promises unprecedented benefits of
harnessing the laws of quantum mechanics for solving certain computational
problems. A persistent obstacle to using such algorithms for solving a wide
range of real-world problems is the cost of loading classical data to a quantum
state. Several quantum circuit-based methods have been proposed for encoding
classical data as probability amplitudes of a quantum state. However, they
require either quantum circuit depth or width to grow linearly with the data
size, even though the other dimension of the quantum circuit grows
logarithmically. In this paper, we present a configurable bidirectional
procedure that addresses this problem by tailoring the resource trade-off
between quantum circuit width and depth. In particular, we show a configuration
that encodes an $N$-dimensional state by a quantum circuit with $O(\sqrt{N})$
width and depth and entangled information in ancillary qubits. We show a
proof-of-principle on five quantum computers and compare the results.
