211 citations · 1.1k across the 14 of their papers we have counts for
14 papers
Characterizing non-Markovian Quantum Process by Fast Bayesian Tomography
R. Y. Su, J. Y. Huang, N. Dumoulin. Stuyck +15
To push gate performance to levels beyond the thresholds for quantum error correction, it is important to characterize the error sources occurring on quantum gates. However, the ch…
Learning correlated noise in a 39-qubit quantum processor
Robin Harper, Steven T. Flammia
Building error-corrected quantum computers relies crucially on measuring and modeling noise on candidate devices. In particular, optimal error correction requires knowing the noise…
Fast Bayesian tomography of a two-qubit gate set in silicon
T. J. Evans, W. Huang, J. Yoneda +9
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…
Fast Estimation of Sparse Quantum Noise
Robin Harper, Wenjun Yu, Steven T. Flammia
As quantum computers approach the fault tolerance threshold, diagnosing and characterizing the noise on large scale quantum devices is increasingly important. One of the most impor…
Scalable Bayesian Hamiltonian learning
Tim J. Evans, Robin Harper, Steven T. Flammia
As the size of quantum devices continues to grow, the development of scalable methods to characterise and diagnose noise is becoming an increasingly important problem. Recent metho…
Efficient learning of quantum noise
Robin Harper, Steven T. Flammia, Joel J. Wallman
Noise is the central obstacle to building large-scale quantum computers. Quantum systems with sufficiently uncorrelated and weak noise could be used to solve computational problems…