Characterizing Continuously Parameterized Gates with Gate Set Tomography

Gate set tomography (GST) is a widely used technique for characterizing a set of noisy quantum gates. GST is formulated for a discrete gate set, but quantum processors often use gates with continuous-valued parameters (such as rotation angles), and the error on these gates may depend on the values of their parameters. Here, we present a method for GST of gate sets containing continuously parameterized gates. We introduce a class of parameter-dependent models for error on continuously parameterized single-qubit gates, using the error generator formalism, and we show how to use GST to fit these models to data. The result is an estimated error map, for each gate, that is a function of the gate's parameters. We demonstrate our method with single-qubit GST experiments, and we explore how well our error models capture real device noise.