Benchmarking and characterizing 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 characterizing a two-qubit gate set on a silicon-based spin qubit device. FBT is built on an adaptive self-consistent linearization 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 randomized benchmarking (or other characterization measurements), and can be performed in real time, providing continuously updated estimates of full process matrices while data are acquired.
The 2023 Boyer Lecture series is called 'The Atomic Revolution' and is presented by Professor Michelle Simmons AO, a pioneer in atomic electronics and global leader in quantum computing.READ
CQC2T Director Professor Michelle Simmons AO and Chief Investigator Professor Yuerui (Larry) Lui were recognised in the prestigious 2023 Prime Minister’s award ceremony held at Parliament House last nREAD
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Fault-tolerant, error-corrected quantum computation is commonly acknowledged to be crucial to the realisation of large-scale quantum algorithms that could lead to extremely impactful scientific or comREAD
Engineers show that a jellybean-shaped quantum dot creates more breathing space in a microchip packed with qubits.READ