49 citations · 66 across the 2 of their papers we have counts for
5 papers · 1 filter
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…
Statistical analysis of randomized benchmarking
Robin Harper, Ian Hincks, Chris Ferrie +2
Randomized benchmarking and variants thereof, which we collectively call RB+, are widely used to characterize the performance of quantum computers because they are simple, scalable…
Fault-Tolerant Logical Gates in the IBM Quantum Experience
Robin Harper, Steven T. Flammia
Quantum computers will require encoding of quantum information to protect them from noise. Fault-tolerant quantum computing architectures illustrate how this might be done but have…