Experimental Comparison of Two Quantum Computing Architectures (1702.01852v1)

Abstract: We run a selection of algorithms on two state-of-the-art 5-qubit quantum computers that are based on different technology platforms. One is a publicly accessible superconducting transmon device with limited connectivity, and the other is a fully connected trapped-ion system. Even though the two systems have different native quantum interactions, both can be programmed in a way that is blind to the underlying hardware, thus allowing the first comparison of identical quantum algorithms between different physical systems. We show that quantum algorithms and circuits that employ more connectivity clearly benefit from a better connected system of qubits. While the quantum systems here are not yet large enough to eclipse classical computers, this experiment exposes critical factors of scaling quantum computers, such as qubit connectivity and gate expressivity. In addition, the results suggest that co-designing particular quantum applications with the hardware itself will be paramount in successfully using quantum computers in the future.

• The paper experimentally compares two 5-qubit quantum architectures, superconducting and trapped-ion, using specific algorithms to evaluate performance differences driven by qubit connectivity.
• Connectivity significantly impacts performance, with the fully connected trapped-ion platform showing higher fidelity for algorithms requiring many qubit interactions compared to the limited connectivity superconducting device.
• The study highlights trade-offs between gate speed and coherence/fidelity, and suggests that systematic errors, rather than random ones, are crucial factors limiting performance in current systems.

Comparative Evaluation of Superconducting and Trapped-Ion Quantum Computing Architectures

The research paper "Experimental Comparison of Two Quantum Computing Architectures" by Linke et al. presents a meticulous experimental evaluation of two distinct 5-qubit quantum computing platforms: a superconducting transmon device and a trapped-ion system. These platforms represent diverging technological paths towards the realization of scalable quantum computers, distinguished primarily by their native qubit connectivity and interaction mechanisms.

Technical Summary

The core aim of this paper was to execute and compare identical quantum algorithms on the two platforms. The superconducting transmon device features limited connectivity (star-shaped), whereas the trapped-ion system leverages full connectivity among qubits. The algorithms tested include the Margolus and Toffoli gates, as well as the Bernstein-Vazirani and Hidden Shift algorithms. These algorithms were selected due to their varying connectivity requirements and gate complexity, allowing for a comprehensive assessment of each architecture's strengths and limitations.

Key Findings

1. Algorithm Performance: The paper found that algorithms demanding higher connectivity, such as the Hidden Shift algorithm, were more efficiently executed on the fully connected trapped-ion platform. For instance, the fidelity of the Hidden Shift algorithm was significantly higher (77.1% for ions compared to 35.1% for superconductors), emphasizing the potential advantage of all-to-all connectivity in certain quantum computational tasks.
2. Gate and Connectivity Metrics: The superconducting system, constrained by its star-shaped connectivity, showed reduced performance for tasks requiring connections not inherently supported by its architecture. This resulted in additional overhead from SWAP operations, impacting the fidelity of complex circuits like the full Toffoli gate.
3. Error Propagation: The researchers utilized models to categorize errors as either random or systematic, with the latter more accurately predicting the outcomes observed, particularly for the superconducting device. This suggests that systematic coherence errors, possibly arising from calibration inaccuracies or environmental disturbances, play a significant role in these systems.
4. Execution Time and Fidelity: While the superconducting device offered faster gate operations, the trapped-ion system provided superior coherence times and gate fidelities. These contrasting attributes highlight the trade-offs between computational speed and stability in these quantum architectures.

Implications and Future Directions

The comparative insights from this paper affirm that the scalability and practical efficiency of quantum computers hinge significantly on architectural decisions, such as qubit connectivity and gate design. As the quantum computing field progresses, these findings underscore the necessity of tailoring algorithms to the intrinsic characteristics of specific platforms to maximize efficiency and reliability.

From a theoretical standpoint, this work suggests that future advancements may involve hybrid methodologies, potentially combining the high connectivity of ion traps with the rapid gate speeds of superconductors. Moreover, the research advocates for the co-design of quantum algorithms and hardware, a strategy that could be pivotal in surpassing current technological barriers and in optimizing quantum computational capabilities.

In conclusion, while neither system currently surpasses classical computation for the demonstrated tasks, this paper provides valuable insight into design considerations and error analysis that will inform the development of more advanced quantum computing systems. The interplay between connectivity, gate expressivity, and error management will undoubtedly shape the future landscape of quantum computation.