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arxiv: 2401.15829 · v6 · submitted 2024-01-29 · 🪐 quant-ph

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Efficient and high-performance routing of lattice-surgery paths on three-dimensional lattice

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classification 🪐 quant-ph
keywords lattice-surgeryschedulinglatticemethodquantumcomputingfault-toleranthigh-performance
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Encoding logical qubits with surface codes and performing multi-qubit logical operations with lattice surgery is one of the most promising approaches to demonstrate fault-tolerant quantum computing. Thus, a method to efficiently schedule a sequence of lattice-surgery operations is vital for high-performance fault-tolerant quantum computing. A possible strategy to improve the throughput of lattice-surgery operations is splitting a large instruction into several small instructions, such as Bell state preparation and measurements, and executing a part of them in advance. However, scheduling methods to fully utilize this idea have yet to be explored. In this paper, we propose a fast and high-performance scheduling algorithm for lattice-surgery instructions leveraging this strategy. We achieved this by converting the scheduling problem of lattice-surgery instructions to a graph problem of embedding 3D paths into a 3D lattice, which enables us to explore efficient scheduling by solving path search problems in the 3D lattice. Based on this reduction, we propose a method to solve the path-finding problems, the look-ahead Dijkstra projection. We numerically show that this method reduced the execution time of benchmark programs generated from quantum phase estimation algorithms by 3.8 times compared with a naive method based on greedy algorithms. Our study establishes the relation between the lattice-surgery scheduling and graph search problems, which leads to further theoretical analysis on compiler optimization of fault-tolerant quantum computing.

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Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Design automation and space-time reduction for surface-code logical operations using a SAT-based EDA kernel compatible with general encodings

    quant-ph 2026-04 unverdicted novelty 7.0

    KOVAL-Q uses SAT solving to optimize and verify surface-code logical operations with general encodings, finding d-cycle CNOTs and 2d-cycle rotations that reduce FTQC application runtime by about 10 percent.

  2. Triage: An Adaptive Parallel Window Decoding Scheduler for Real-time Fault-Tolerant Quantum Computation

    quant-ph 2026-05 unverdicted novelty 6.0

    Triage is an adaptive parallel window decoding scheduler that reduces average logical error rates by 52.6% compared to standard temporal parallelism while keeping stalls low under scarce classical resources.

  3. Toward designing workload-aware Surface Code Architectures

    quant-ph 2026-04 unverdicted novelty 6.0

    A workload-aware surface-code architecture with ancilla-centric patches and T-gate-based floorplanning reduces required data tiles by up to 21% while maintaining near-optimal cycles per instruction and reaching 90% ef...

  4. O3LS: Optimizing Lattice Surgery via Automatic Layout Searching and Loose Scheduling

    quant-ph 2026-04 unverdicted novelty 6.0

    O3LS reduces space overhead by up to 46.7% and time overhead by up to 36% in lattice surgery while suppressing logical error rates by up to an order of magnitude compared with prior layout and scheduling approaches.