Demonstration of qubit operations below a rigorous fault tolerance threshold with gate set tomography

By Robin Blume-Kohout, J. Gamble, Erik Nielsen, Kenneth M. Rudinger, J. Mizrahi, K. Fortier, Peter Maunz. Nature Communications, 2016

311 citations recorded by the source corpus.

Quantum information processors promise fast algorithms for problems inaccessible to classical computers. But since qubits are noisy and error-prone, they will depend on fault-tolerant quantum error correction (FTQEC) to compute reliably. Quantum error correction can protect against general noise if—and only if—the error in each physical qubit operation is smaller than a certain threshold. The threshold for general errors is quantified by their diamond norm. Until now, qubits have been assessed primarily by randomized benchmarking, which reports a different error rate that is not sensitive to all errors, and cannot be compared directly to diamond norm thresholds. Here we use gate set tomography to completely characterize operations on a trapped-Yb+-ion qubit and demonstrate with greater than 95% confidence that they satisfy a rigorous threshold for FTQEC (diamond norm ≤6.7 × 10−4). Quantum computation will depend on fault-tolerant error correction, which requires the chance for errors to occur to be below a certain threshold. Here the authors use gate set tomography as a means to rigorously characterize error rates of single-qubit operations of a qubit encoded in a trapped ion.

Subfields: Artificial Intelligence, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/8d66ec384a71ae64a01ef0d85e6fb317e7e5a1a5

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Citations in the corpus

Noise-induced barren plateaus in variational quantum algorithms (2020, methodology): “The noise model employed in our numerical simulations was obtained by performing one-and two-qubit gate-set tomography [103, 104] on the five-qubit IBM Q Ourense superconducting qubit device.”
Observation of separated dynamics of charge and spin in the Fermi-Hubbard model (2020, background): “However, common calibration tools, such as randomized benchmarking [59, 60], compressed sensing [61, 62], gate set tomography [63, 64], and cross-entropy benchmarking [65] are often too slow to capture drifts and fluctuations in the hardware.”
The randomized measurement toolbox (2022, background): “On the theory side, compressive GST 108 is a formulation of GST as a tensor completion problem in an effort to bring down the (substantial) computational complexity of the method and provide rigorous convergence guarantees.”
Detecting crosstalk errors in quantum information processors (2019, background): “Finally, note that the CPTP maps describing experimental operations are only unique up to a gauge freedom [7, 47, 37].”
Review of performance metrics of spin qubits in gated semiconducting nanostructures (2021, background): “[16] Robin Blume-Kohout, John King Gamble, Erik Nielsen, Kenneth Rudinger, Jonathan Mizrahi, Kevin Fortier, and Peter Maunz.”