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arXiv:2510.17689 · Physical Review A

Synthesizing an optimal spin-qubit shuttling-bus architecture for the surface code

Pau Escofet, Eduard Alarcón, Sergi Abadal, Andrii Semenov, Niall Murphy, Elena Blokhina, Carmen G. Almudéver

Published Feb 4, 2026• 0 citations
arXivHTMLPDF

Abstract

As quantum computers scale toward millions of physical qubits, it becomes essential to robustly encode individual logical qubits to ensure fault tolerance under realistic noise. A high-quality foundational encoding allows future compilation techniques and heuristics to build on optimal or near-optimal layouts, improving scalability and error resilience. In this work, we synthesize a one-dimensional shuttling bus architecture for the rotated surface code, leveraging coherent spin-qubit shuttling, following a novel methodology we name Quantum Reverse Mapping. We formulate a mixed-integer optimization model that yields optimal solutions with relatively low execution time for small code distances, and propose a scalable heuristic that matches optimal results while maintaining linear computational complexity. We evaluate the synthesized architecture using architectural metrics, such as shuttling distance and cycle time, and full quantum simulations under realistic noise models, showing that the proposed design can sustain logical error rates as low as $2\times 10^{-10}$ per round at code distance 21, showcasing its feasibility for scalable quantum error correction in spin-based quantum processors.

DOI
10.1103/4p4q-fm3y

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As quantum computers scale toward millions of physical qubits, it becomes essential to robustly encode individual logical qubits to ensure fault tolerance under realistic noise. A high-quality foundational encoding allows future compilation techniques and heuristics to build on optimal or near-optimal layouts, improving scalability and error resilience. In this work, we synthesize a one-dimensional shuttling bus architecture for the rotated surface code, leveraging coherent spin-qubit shuttling, following a novel methodology we name Quantum Reverse Mapping. We formulate a mixed-integer optimization model that yields optimal solutions with relatively low execution time for small code distances, and propose a scalable heuristic that matches optimal results while maintaining linear computational complexity. We evaluate the synthesized architecture using architectural metrics, such as shuttling distance and cycle time, and full quantum simulations under realistic noise models, showing that the proposed design can sustain logical error rates as low as 2×10−102\times 10^{-10}2×10−10 per round at code distance 21, showcasing its feasibility for scalable quantum error correction in spin-based quantum processors.
Fault-tolerant quantum computing requires not only reliable logical qubit storage, but also the ability to perform high-fidelity logical operations between error-corrected qubits at scale. While much of the existing literature focuses on optimizing syndrome extraction for a single logical qubit, the co-design of physical architectures that support both robust error correction and efficient logical computation remains an open challenge. In this work, we propose a multi-qubit spin-qubit shuttling bus architecture that addresses both requirements simultaneously. The architecture optimizes the physical qubit layout for syndrome extraction and supports transversal two-qubit logical gates between an arbitrary number of logical qubits, achieving all-to-all logical connectivity through coherent spin shuttling. We further propose an ancilla-sharing scheme that encodes multiple logical qubits within a single logical element, compressing the physical footprint of the processor and improving long-range gate fidelity. Extending the architecture from a one-dimensional bus to a two-dimensional grid of shuttling tracks reduces the inter-qubit distance, yielding consistent improvements in logical error. Finally, we apply the Quantum Reverse Mapping methodology at the logical level to optimize the layout of a \textit{15-to-1} magic state distillation circuit, demonstrating how the transversal capabilities of the proposed architecture can be leveraged for universal fault-tolerant computation. Taken together, these results establish a principled co-design framework that bridges the physical, error-correction, and logical computation layers of the quantum stack, and demonstrate that spin-qubit shuttling architectures are a viable and flexible substrate for scalable fault-tolerant quantum computation.
Spin qubits in silicon quantum dot arrays are a promising quantum computation platform for long-term scalability due to their small qubit footprint and compatibility with advanced semiconductor manufacturing. However, spin qubit devices face a key architectural bottleneck: the large physical footprint of readout components relative to qubits prevents a dense layout where all qubits can be measured simultaneously, complicating the implementation of quantum error correction. This challenge is offset by the platform's unique rapid shuttling capability, which can be used to transport qubits to distant readout ports. In this work, we explore the design constraints and capabilities of spin qubits in silicon and propose the SNAQ (Shuttling-capable Narrow Array of spin Qubits) surface code architecture, which relaxes the 1:1 readout-to-qubit assumption by leveraging spin shuttling to time-multiplex ancilla qubit initialization and readout. Our analysis shows that, given sufficiently high (experimentally demonstrated) qubit coherence times, SNAQ delivers an orders-of-magnitude reduction in chip area per logical qubit. Additionally, by using a denser grid of physical qubits, SNAQ enables fast transversal logic for short-distance logical operations, achieving over 10x improvement in local logical clock speed while still supporting global operations via lattice surgery. This translates to a 3.2-5.7x improvement in key Adder and Lookup fault-tolerant subroutines. Our work pinpoints critical hardware metrics and provides a compelling path toward high-performance fault-tolerant computation on near-term-manufacturable spin qubit arrays.
Qubit shuttling promises to advance some quantum computing platforms to the qubit register sizes needed for effective quantum error correction (QEC), but also introduces additional errors whose impact must be evaluated. The established method to investigate the performance of QEC codes in a realistic scenario is to employ a standard noise model known as circuit-level noise, where all quantum operations are modeled as noisy. In the present work, we take this noise model and single out the effect of shuttling errors by introducing them as an additional so-called error location. This hardware abstraction is motivated by the SpinBus architecture and allows a systematic numerical investigation to map out the resulting two-dimensional parameter space. To this end, we take the Surface code and perform large scale simulations, most notably extracting the threshold across said two-dimensional parameter space. We study two scenarios for shuttling errors, depolarization on the one hand and dephasing on the other hand. For a purely dephasing shuttling error, we find a threshold of several percent, provided that all other operations have a high fidelity. The qubit overhead needed to reach a logical error rate of 10 − 12 (known as the "teraquop" regime \cite{Gidney2021Jul} increases only moderately for shuttling error rates up to about 1 % per shuttling operation. The error rates at which practically useful, i.e. well below threshold error correction is predicted to be possible are comfortably higher than what is expected to be achievable for spin qubits. Our results thus show that it is reasonable to expect shuttling operations to fall below threshold already at surprisingly large error rates. With realistic efforts in the near term, this offers positive prospects for spin qubit based quantum processors as a viable avenue for scalable fault-tolerant error-corrected quantum computing.
Efficient quantum error correction and fault-tolerant quantum computing require scalable, high-fidelity long-range connectivity. In neutral-atom quantum computers, this is commonly achieved through atom transport, but shuttling introduces latency and motional heating that worsen with system size. Here, we introduce a neutral-atom architecture based on static atomic buses, in which auxiliary mediator atoms enable long-range entangling operations without qubit transport. The architecture naturally supports long-range stabilizer measurements in high-rate LDPC codes and transversal logical gates between neighboring surface-code patches, enabling a modular framework for efficient logical memories, Clifford computation, and magic-state distillation. To realize these capabilities, we co-design optimal-control protocols for bus-mediated controlled-Z gates that incorporate both microscopic neutral-atom dynamics and architectural constraints. We obtain smooth bus-mediated gates with fidelities approaching 99.9% and durations of a few hundred nanoseconds by combining time-optimal control with interaction-flatness and robustness constraints. Large-scale simulations of quantum error correction and logical entangling operations between neighboring surface-code patches predict more than an order-of-magnitude improvement in logical error rates compared with atom-shuttling architectures under realistic noise. The architecture achieves logical gate times of approximately 100 us and quantum-error-correction cycle times of about 1 ms for code distances d<12. These results establish static atomic buses as a practical alternative to atom shuttling for scalable fault-tolerant neutral-atom quantum computing.
We present a fault-tolerant mapping of rotated surface codes onto a 2×N2\times N2×N silicon spin-qubit railway architecture, utilizing electron shuttling to resolve the wiring fan-out bottleneck. Employing circuit-level noise modeling, we evaluate threshold performances across various noise biases. We demonstrate that shuttling check qubits instead of data qubits fundamentally improves system thresholds. Crucially, under a noise model biased towards dephasing for spin-qubit shuttling, the non-CSS XZZX surface code outperforms standard CSS variants. By tailoring the topological code to this specific inherent bias, we show that the Megaquop footprint is achievable with a distance 7 code requiring a p=10−3p = 10^{-3}p=10−3 physical error rate, highlighting a pathway for substantial hardware reductions in early fault-tolerant quantum processors.
Quantum computation holds the promise of solving certain complex problems exponentially faster than classical computers. However, the high prevalent noise in current quantum devices impedes the accurate execution of even basic algorithms. This can be remedied by protecting quantum information with a quantum error-correcting code, where the logical information of an algorithmic qubit is spread across multiple physical qubits. Individual quantum errors are then located and corrected by the fault-tolerant measurement of multi-qubit stabilizer operators (parity checks). Unfortunately, error correction and fault tolerance both impose large demands on the qubit overhead: hundreds to thousands of physical qubits per logical qubit. We reduce the spacetime cost of fault tolerance by redesigning key building blocks of an error-corrected quantum computer. First, we develop a combinatorial proof with flag fault tolerance that exponentially reduces the extra qubits needed to measure a stabilizer of any size, while tolerating one fault. We leverage these proofs to then design state preparation circuits for the Steane and Golay codes with 100% yield. Next, we improve error correction on a planar layout by showing that a distance-four code encoding six logical qubits protects information as well as the distance-five surface code, using one-tenth as many physical qubits. Finally, we optimize the time overhead of logical gates in surface code quantum computers by protecting measurement results with a classical code, cutting computation time by a factor of two to six. Our hardware-agnostic optimizations of fault tolerance overheads thus suggest new routes to advance the timeline of error-free quantum computing.