Characterization of Pauli Error Models

While stochastic Pauli errors play an important role in modeling fault-tolerant architectures, such error models are usually dismissed as not being representative of errors found in physical systems. A recent experimental implementation of Pauli frame randomization, a technique to shape general error models into Pauli error models, demonstrates that these simple and highly structured error models are indeed experimentally relevant. In this talk I will describe a proposal to exploit the structure of Pauli error models on Clifford group operations to obtain simple and highly accurate reconstructions of noise models in randomized experiments.