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A Taxonomy of Small Markovian Errors

PRX Quantum

Blume-Kohout, Robin J.; da Silva, Marcus P.; Nielsen, Erik N.; Proctor, Timothy J.; Rudinger, Kenneth M.; Sarovar, Mohan S.; Young, Kevin C.

Errors in quantum logic gates are usually modeled by quantum process matrices (CPTP maps). But process matrices can be opaque and unwieldy. We show how to transform the process matrix of a gate into an error generator that represents the same information more usefully. We construct a basis of simple and physically intuitive elementary error generators, classify them, and show how to represent the error generator of any gate as a mixture of elementary error generators with various rates. Finally, we show how to build a large variety of reduced models for gate errors by combining elementary error generators and/or entire subsectors of generator space. We conclude with a few examples of reduced models, including one with just 9N2 parameters that describes almost all commonly predicted errors on an N-qubit processor.

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TYPE Journal Article YEAR 2022
OSTIDOI

Characterizing Midcircuit Measurements on a Superconducting Qubit Using Gate Set Tomography

Physical Review Applied

Rudinger, Kenneth M.; Ribeill, Guilhem J.; Govia, Luke C.G.; Ware, Matthew; Nielsen, Erik N.; Young, Kevin; Ohki, Thomas A.; Blume-Kohout, Robin J.; Proctor, Timothy J.

Measurements that occur within the internal layers of a quantum circuit—midcircuit measurements—are a useful quantum-computing primitive, most notably for quantum error correction. Midcircuit measurements have both classical and quantum outputs, so they can be subject to error modes that do not exist for measurements that terminate quantum circuits. Here we show how to characterize midcircuit measurements, modeled by quantum instruments, using a technique that we call quantum instrument linear gate set tomography (QILGST). We then apply this technique to characterize a dispersive measurement on a superconducting transmon qubit within a multiqubit system. By varying the delay time between the measurement pulse and subsequent gates, we explore the impact of residual cavity photon population on measurement error. QILGST can resolve different error modes and quantify the total error from a measurement; in our experiment, for delay times above 1000ns we measure a total error rate (i.e., half diamond distance) of ϵ⋄=8.1±1.4%, a readout fidelity of 97.0±0.3%, and output quantum-state fidelities of 96.7±0.6% and 93.7±0.7% when measuring 0 and 1, respectively.

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TYPE Journal Article YEAR 2022
ScopusOSTIDOI

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

Nature Communications

Blume-Kohout, Robin J.; Gamble, John K.; Nielsen, Erik N.; Rudinger, Kenneth M.; Mizrahi, Jonathan; Fortier, Kevin M.; Maunz, Peter

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).

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TYPE Journal Article YEAR 2017
ScopusOSTIDOI

Detecting and tracking drift in quantum information processors

Nature Communications

Proctor, Timothy J.; Revelle, Melissa R.; Nielsen, Erik N.; Rudinger, Kenneth M.; Lobser, Daniel L.; Maunz, Peter; Blume-Kohout, Robin J.; Young, Kevin

If quantum information processors are to fulfill their potential, the diverse errors that affect them must be understood and suppressed. But errors typically fluctuate over time, and the most widely used tools for characterizing them assume static error modes and rates. This mismatch can cause unheralded failures, misidentified error modes, and wasted experimental effort. Here, we demonstrate a spectral analysis technique for resolving time dependence in quantum processors. Our method is fast, simple, and statistically sound. It can be applied to time-series data from any quantum processor experiment. We use data from simulations and trapped-ion qubit experiments to show how our method can resolve time dependence when applied to popular characterization protocols, including randomized benchmarking, gate set tomography, and Ramsey spectroscopy. In the experiments, we detect instability and localize its source, implement drift control techniques to compensate for this instability, and then demonstrate that the instability has been suppressed.

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TYPE Journal Article YEAR 2020
ScopusOSTIDOI
Results 1–25 of 124
Results 1–25 of 124