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QSCOUT Progress Report, June 2022 [Quantum Scientific Computing Open User Testbed]

Clark, Susan M.; Norris, Haley R.; Landahl, Andrew J.; Yale, Christopher G.; Lobser, Daniel L.; Van Der Wall, Jay W.; Revelle, Melissa R.

Quantum information processing has reached an inflection point, transitioning from proof-of-principle scientific experiments to small, noisy quantum processors. To accelerate this process and eventually move to fault-tolerant quantum computing, it is necessary to provide the scientific community with access to whitebox testbed systems. The Quantum Scientific Computing Open User Testbed (QSCOUT) provides scientists unique access to an innovative system to help advance quantum computing science.

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Three-Photon Optical Pumping for Trapped Ion Quantum Computing

Hogle, Craig W.; Ivory, Megan K.; Lobser, Daniel L.; Ruzic, Brandon R.; DeRose, Christopher T.

In this report we describe the testing of a novel scheme for state preparation of trapped ions in a quantum computing setup. This technique optimally would allow for similar precision and speed of state preparation while allowing for individual addressability of single ions in a chain using technology already available in a trapped ion experiment. As quantum computing experiments become more complicated, mid-experiment measurements will become necessary to achieve algorithms such as quantum error correction. Any mid-experiment measurement then requires the measured qubit to be re-prepared to a known quantum state. Currently this involves the protected qubits to be moved a sizeable distance away from the qubit being re-prepared which can be costly in terms of experiment length as well as introducing errors. Theoretical calculations predict that a three-photon process would allow for state preparation without qubit movement with similar efficiencies to current state preparation methods.

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Engineering the Quantum Scientific Computing Open User Testbed

IEEE Transactions on Quantum Engineering

Clark, Susan M.; Lobser, Daniel L.; Revelle, Melissa R.; Yale, Christopher G.; Bossert, David B.; Burch, Ashlyn D.; Chow, Matthew N.; Hogle, Craig W.; Ivory, Megan K.; Pehr, Jessica; Salzbrenner, Bradley S.; Stick, Daniel L.; Sweatt, W.C.; Wilson, Joshua M.; Winrow, Edward G.; Maunz, Peter

The Quantum Scientific Computing Open User Testbed (QSCOUT) at Sandia National Laboratories is a trapped-ion qubit system designed to evaluate the potential of near-term quantum hardware in scientific computing applications for the U.S. Department of Energy and its Advanced Scientific Computing Research program. Similar to commercially available platforms, it offers quantum hardware that researchers can use to perform quantum algorithms, investigate noise properties unique to quantum systems, and test novel ideas that will be useful for larger and more powerful systems in the future. However, unlike most other quantum computing testbeds, the QSCOUT allows both quantum circuit and low-level pulse control access to study new modes of programming and optimization. The purpose of this article is to provide users and the general community with details of the QSCOUT hardware and its interface, enabling them to take maximum advantage of its capabilities.

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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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Results 1–25 of 56
Results 1–25 of 56