Riken Institute’s work scales up silicon-based quantum processors

Researchers from the RIKEN Center for Emergent Matter Science and collaborators have achieved high-fidelity control of a five-qubit silicon array using a single shared microwave line, a technique that addresses a key obstacle to building larger quantum processors. Silicon spin qubits, promising for their compatibility with existing chip manufacturing, previously suffered accuracy loss during parallel operation; the team identified the AC Stark shift as the primary source of this error and developed a phase calibration protocol to mitigate its effects.

“This shows that high-fidelity control can be maintained even when several qubits are operated at the same time and represents an important step toward scaling up silicon-based quantum processors,” says Leon Camenzind, a research scientist at RIKEN. The study, published in Nature Physics, reports fidelities above 99.99% when up to three qubits were operated simultaneously.

AC Stark Shift Impacts on Silicon Spin Qubit Control

Exceeding 99% single-qubit gate fidelities were achieved by the team, reaching 99.999% on individual qubits. The AC Stark shift alters a qubit’s effective energy levels, introducing unwanted phase shifts that degrade control accuracy; the researchers discovered this effect interfered with intended qubit control when multiple qubits were driven at once.

Yi-Hsien Wu, the first author who conducted the experiments as part of doctoral research, explained that their method circumvents the need for individual calibration procedures for every qubit combination. “Rather than requiring an entirely separate calibration procedure for every possible combination of qubits, our method uses calibrations between pairs of qubits to compensate for the unwanted phase shifts,” Wu stated, detailing a scalable approach to error mitigation.

This pairwise calibration technique allowed the team to maintain high fidelity even while controlling up to three qubits simultaneously, achieving fidelities above 99.99%. The researchers employed an optimized device design and carefully calibrated microwave control pulses to minimize the impact of the AC Stark shift, demonstrating a pathway toward more efficient control systems. While the calibration protocol successfully mitigated phase shifts, the team identified drive-induced decoherence as a remaining source of error when all five qubits in the array operated concurrently.

Decoherence, a loss of quantum coherence, occurred due to the increased microwave power required for simultaneous operation, reducing fidelities to approximately 99.9%, a level close to the practical requirements of fault-tolerant quantum computing. “This is a limitation, but further improvements to device design could help mitigate this source of error,” Camenzind said, suggesting that refinements to the physical qubit structure could further enhance performance.

Traditionally, each qubit requires its own dedicated control line, increasing system complexity and cost. This work supports the viability of a shared-line approach, simplifying control infrastructure and potentially enabling larger-scale quantum processors.

According to Camenzind, “our study supports the use of shared control lines as a practical approach to scaling up quantum processors.” Combined with silicon’s compatibility with established semiconductor manufacturing, this advance could help enable larger quantum processors capable of performing increasingly complex computations. Unlike other qubit technologies requiring specialized fabrication techniques, silicon qubits can use established infrastructure, potentially accelerating the development and deployment of quantum computers.

Seigo Tarucha, project manager of a silicon quantum computing project, emphasized the importance of this work within the broader context of fault-tolerant quantum computing. “Our long-term goal is to build a fault-tolerant quantum computer based on silicon spin qubits, and reliable parallel control is an essential step toward that goal,” Tarucha stated.

This shows that high-fidelity control can be maintained even when several qubits are operated at the same time and represents a step toward scaling up silicon-based quantum processors.

Leon Camenzind, a research scientist at RIKEN and co-first author who supervised the experiments
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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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