Statistical learning to estimate noise in quantum systems - Yuval Sanders

Quantum computers are only valuable insofar as they can be trusted to perform properly. Yet the field of research responsible for providing techniques for establishing this trust—the field of quantum characterization, verification and validation (QCVV)—remains in its infancy. In this talk, I shall describe the potential impact of statistical learning methods on noise characterization for quantum systems. I shall present the recently released QInfer codebase and how it can be applied to at least one practical problem facing quantum computing: the characterization of unwanted resonances between a qubit and its environment.