  Flux tunability is an important engineering resource for superconducting
circuits. Large-scale quantum computers based on flux-tunable superconducting
circuits face the problem of flux crosstalk, which needs to be accurately
calibrated to realize high-fidelity quantum operations. Typical calibration
methods either assume that circuit elements can be effectively decoupled and
simple models can be applied, or require a large amount of data. Such methods
become ineffective as the system size increases and circuit interactions become
stronger. Here we propose a new method for calibrating flux crosstalk, which is
independent of the underlying circuit model. Using the fundamental property
that superconducting circuits respond periodically to external fluxes,
crosstalk calibration of N flux channels can be treated as N independent
optimization problems, with the objective functions being the periodicity of a
measured signal depending on the compensation parameters. We demonstrate this
method on a small-scale quantum annealing circuit based on superconducting flux
qubits, achieving comparable accuracy with previous methods. We also show that
the objective function usually has a nearly convex landscape, allowing
efficient optimization.
