  Efforts to scale-up quantum computation have reached a point where the
principal limiting factor is not the number of qubits, but the entangling gate
infidelity. However, the highly detailed system characterization required to
understand the underlying error sources is an arduous process and impractical
with increasing chip size. Open-loop optimal control techniques allow for the
improvement of gates but are limited by the models they are based on. To
rectify the situation, we provide an integrated open-source tool-set for
Control, Calibration and Characterization, capable of open-loop pulse
optimization, model-free calibration, model fitting and refinement. We present
a methodology to combine these tools to find a quantitatively accurate system
model, high-fidelity gates and an approximate error budget, all based on a
high-performance, feature-rich simulator. We illustrate our methods using
simulated fixed-frequency superconducting qubits for which we learn model
parameters with less than 1% error and derive a coherence limited
cross-resonance (CR) gate that achieves 99.6% fidelity without need for
calibration.
