Fast Bayesian tomography of a two-qubit gate set in silicon

Abstract

Benchmarking and characterising quantum states and logic gates is essential in the development of devices for quantum computing. We introduce a Bayesian approach to self-consistent process tomography, called fast Bayesian tomography (FBT), and experimentally demonstrate its performance in characterising a two-qubit gate set on a silicon-based spin qubit device. FBT is built on an adaptive self-consistent linearisation that is robust to model approximation errors. Our method offers several advantages over other self-consistent tomographic methods. Most notably, FBT can leverage prior information from randomised benchmarking (or other characterisation measurements), and can be performed in real time, providing continuously updated estimates of full process matrices while data is acquired.

10 pages + 6 page appendix, 6 figures, comments welcome

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Cited by in corpus (5)

• The randomized measurement toolbox
• Review of performance metrics of spin qubits in gated semiconducting nanostructures
• High-fidelity operation and algorithmic initialisation of spin qubits above one kelvin
• Compressive gate set tomography
• Exploring ab initio machine synthesis of quantum circuits