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arXiv:2108.03708 · IEEE International Symposium on High-Performance Computer Architecture (HPCA)

Detecting Qubit-coupling Faults in Ion-trap Quantum Computers

Andrii Maksymov, Jason Nguyen, Vandiver L. Chaplin, Yunseong Nam, Igor L. Markov

Published Apr 1, 2022• 7 citations
arXivHTMLPDF

Abstract

Ion-trap quantum computers offer a large number of possible qubit couplings, each of which requires individual calibration and can be misconfigured. To enhance the duty cycle of an ion trap, we develop a strategy that diagnoses individual miscalibrated couplings using only log-many tests. This strategy is validated on a commercial ion-trap quantum computer, where we illustrate the process of debugging faulty quantum gates. Our methodology provides a scalable pathway towards fault detections on a larger scale ion-trap quantum computers, confirmed by simulations up to 32 qubits.

DOI
10.1109/hpca53966.2022.00036

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Ion-trap quantum computers offer a large number of possible qubit couplings, each of which requires individual calibration and can be misconfigured. To enhance the duty cycle of an ion trap, we develop a strategy that diagnoses individual miscalibrated couplings using only log-many tests. This strategy is validated on a commercial ion-trap quantum computer, where we illustrate the process of debugging faulty quantum gates. Our methodology provides a scalable pathway towards fault detections on a larger scale ion-trap quantum computers, confirmed by simulations up to 32 qubits.
Ion trap is one of the leading physical platforms to implement quantum computation. Currently, high-fidelity elementary quantum operations above the fault-tolerant threshold, including state preparation, measurement and universal gates, have been demonstrated for tens of ionic qubits. One important future research direction is to further enlarge the qubit number to the scale required for solving practical problems while maintaining the high performance of individual qubits. This paper introduces the current mainstream schemes for scalable ion trap quantum computation like quantum charge-coupled device (QCCD) and ion-photon quantum network, and describes the main limiting factors in current research. Then we further explore new schemes to scale up the qubit number like two-dimensional ion crystals and dual-type qubit, and discuss the future research directions.
Quantum computers promise to solve certain problems more efficiently than their digital counterparts. A major challenge towards practically useful quantum computing is characterizing and reducing the various errors that accumulate during an algorithm running on large-scale processors. Current characterization techniques are unable to adequately account for the exponentially large set of potential errors, including cross-talk and other correlated noise sources. Here we develop cycle benchmarking, a rigorous and practically scalable protocol for characterizing local and global errors across multi-qubit quantum processors. We experimentally demonstrate its practicality by quantifying such errors in non-entangling and entangling operations on an ion-trap quantum computer with up to 10 qubits, and total process fidelities for multi-qubit entangling gates ranging from [Formula: see text] for 2 qubits to [Formula: see text] for 10 qubits. Furthermore, cycle benchmarking data validates that the error rate per single-qubit gate and per two-qubit coupling does not increase with increasing system size.
Abstract To harness the power of quantum computing, it is essential that a quantum computer provide maximal possible fidelity for a quantum circuit. To this end, much work has been done in the context of qubit routing or embedding, i.e., mapping circuit qubits to physical qubits based on gate performance metrics to optimize the fidelity of execution. Here, we take an alternative approach that leverages a unique capability of a trapped-ion quantum computer, i.e., the all-to-all qubit connectivity. We develop a method to determine a fixed number (budget) of quantum gates that, when calibrated, will maximize the fidelity of a batch of input quantum programs. This dynamic allocation of calibration resources on randomly accessible gates, determined using our heuristics, increases, for a wide range of calibration budget, the average fidelity from 70% or lower to 90% or higher for a typical batch of jobs on an 11-qubit device, in which the fidelity of calibrated and uncalibrated gates are taken to be 99% and 90%, respectively. Our heuristics are scalable, more than 2.5 orders of magnitude faster than a randomized method for synthetic benchmark circuits generated based on real-world use cases.
For the field of quantum computing and technology to continue its growth and begin to solve truly useful problems, it must overcome the limitations imposed by errors affecting quantum devices. Leading modern devices can be classed as “noisy intermediate-scale quantum” or NISQ devices. These are devices that have not realised fault-tolerance nor utilise error correction, but nonetheless could solve genuinely useful, classically intractable problems. However, the scalability and reliability of current NISQ devices is limited by the impact of errors. This thesis uses the principles of quantum control to work towards improving quantum technology reliability. By characterising the errors affecting a quantum device and tailoring robust, dynamic control solutions, I am able to achieve superior performance in a trapped-ion quantum device compared to its baseline or primitive operation. I begin by characterising our experimental system, a trapped 171Yb+ ion. Following on, I demonstrate three quantum control techniques. First, I work to improve the measurement fidelity of a trapped-ion hyperfine qubit using electron shelving to a metastable level. Second, this work develops and demonstrates an error characterisation tool to diagnose the correlation properties of errors affecting a quantum device. Building from this, I demonstrate the use of dynamically corrected gates to both improve single-qubit gate fidelities and reduce error correlations temporally between gates and spatially between qubits. Finally, I discuss and implement a more robust and flexible two-qubit entangling Mølmer-Sørensen gate using phase modulation of the interaction laser. All of this work adds to the “toolkit” of quantum control and can be used to improve both the reliability of modern device performance -- in particular by reducing susceptibility to noise -- and assist with building up to larger numbers of qubits and gates by tailoring more robust, scalable entangling gates between qubits.
High quality, fully programmable quantum processors are available with small numbers (<1000<1000<1000) of qubits, and the scientific potential of these near-term machines is not well understood. If the small number of physical qubits precludes practical quantum error correction, how can these error-susceptible processors be used to perform useful tasks? We present a strategy for developing quantum error detection for certain gate imperfections that utilizes additional internal states and does not require additional physical qubits. Examples for adding error detection are provided for a universal gate set in the trapped-ion platform. Error detection can be used to certify individual gate operations against certain errors, and the irreversible nature of the detection allows a result of a complex computation to be checked at the end for error flags.
Trapped-ion quantum computer hardware is scaling to larger qubit numbers, but the computational capabilities of these devices remain largely unknown. From an abstract computer-science perspective, we address this problem in a two-step approach: First, we categorize levels of qubit connectivity for a processor based on ion-shuttling and individual ion addressing. Second, we apply computer-science techniques to develop optimized compilers that map arbitrary algorithms to sequences of ion-register reconfiguration and gate operations. We present compilers for 1D and 2D architectures, optimizing cost functions such as the qubit reconfiguration effort.