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Batching Circuits to Reduce Compilation in Quantum Control Hardware

Proceedings - 2022 IEEE International Conference on Quantum Computing and Engineering, QCE 2022

Grinevich, Ashlyn D.; Lobser, Daniel L.; Yale, Christopher G.; Van Der Wall, Jay W.; Maupin, Oliver G.; Goldberg, Joshua D.; Chow, Matthew N.; Revelle, Melissa R.; Clark, Susan M.

At Sandia National Laboratories, QSCOUT (the Quantum Scientific Computing Open User Testbed) is an ion-trap based quantum computer built for the purpose of allowing users low-level access to quantum hardware. Commands are executed on the hardware using Jaqal (Just Another Quantum Assembly Language), a programming language designed in-house to support the unique capabilities of QSCOUT. In this work, we describe a batching implementation of our custom software that speeds the experimental run-time through the reduction of communication and upload times. Reducing the code upload time during experimental runs improves system performance by mitigating the effects of drift. We demonstrate this implementation through a set of quantum chemistry experiments using a variational quantum eigensolver (VQE). While developed specifically for this testbed, this idea finds application across many similar experimental platforms that seek greater hardware control or reduced overhead.

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Hybrid MEMS-CMOS ion traps for NISQ computing

Quantum Science and Technology

Blain, Matthew G.; Haltli, Raymond A.; Maunz, P.; Nordquist, Christopher N.; Revelle, Melissa R.; Stick, Daniel L.

Surging interest in engineering quantum computers has stimulated significant and focused research on technologies needed to make them manufacturable and scalable. In the ion trap realm this has led to a transition from bulk three-dimensional macro-scale traps to chip-based ion traps and included important demonstrations of passive and active electronics, waveguides, detectors, and other integrated components. At the same time as these technologies are being developed the system sizes are demanding more ions to run noisy intermediate scale quantum (NISQ) algorithms, growing from around ten ions today to potentially a hundred or more in the near future. To realize the size and features needed for this growth, the geometric and material design space of microfabricated ion traps must expand. In this paper we describe present limitations and the approaches needed to overcome them, including how geometric complexity drives the number of metal levels, why routing congestion affects the size and location of shunting capacitors, and how RF power dissipation can limit the size of the trap array. We also give recommendations for future research needed to accommodate the demands of NISQ scale ion traps that are integrated with additional technologies.

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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.; Grinevich, 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 C.

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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Diagnosing and Destroying Non-Markovian Noise

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

Nearly every protocol used to analyze the performance of quantum information processors is based on an assumption that the errors experienced by the device during logical operations are constant in time and are insensitive to external contexts. This assumption is pervasive, rarely stated, and almost always wrong. Quantum devices that do behave this way are termed "Markovian:' but nearly every system we have ever probed has displayed drift or crosstalk or memory effects they are all non-Markovian. Strong non-Markovianity introduces spurious effects in characterization protocols and violates assumptions of the fault-tolerance threshold theorems. This SAND report details a three year laboratory-directed research and development (LDRD) project entitled, "Diagnosing and Destroying non-Markovian Noise in Quantum Information Processors." This program was initiated to build tools to study non-Markovian dynamics and quantum systems and develop robust methodologies for eliminating it. The program achieved a number of notable successes, including the first statistically rigorous protocol for identifying and characterizing drift in quantum systems, a formalism for modeling memory effects in quantum devices, and the successful suppression of drift in a Sandia trapped-ion quantum processor.

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Results 26–50 of 67
Results 26–50 of 67