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RushHour introduces a hardware-compiler co-design for dynamic lattice surgery, enabling efficient reconfiguration of ancilla space and just-in-time resource allocation on quantum chips. This approach allows algorithms to run entirely on smaller, early-stage fault-tolerant devices that previously required significantly larger footprints or suffered from high time overheads due to rigid scheduling. By spanning the full spectrum of area-speed trade-offs in a unified framework, RushHour represents a significant step toward practical deployment of large-scale quantum applications under strict resource constraints.
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RushHour: A Dynamically Reconfigurable Lattice-Surgery Architecture

arXiv3 min read

arXiv:2608.18985v1 Announce Type: new Abstract: Practical fault-tolerant quantum computing (FTQC) requires efficient lattice surgery (LS), so that large algorithms fit on resource-constrained quantum chips. Existing approaches, however, are rigid: qubits, routing space, and resource states are allocated ahead of execution, which prevents running on small chips, leaves statically scheduled executions with large time overheads, and fixes each design at a single area of the space-time trade-off. We present dynamic LS, which enables efficient reconfiguration of the ancilla space, just-in-time allocation of resource states, and dynamic rotations of logical qubits, thereby spanning the entire space-time trade-off with a single, unified approach. We realize dynamic LS with RushHour through a hardware-compiler co-design: the RushHour ISA formalizes and programs our dynamic lattice model, the Lattice Management Unit abstracts dynamic lattice management and performs efficient lattice reconfiguration, and the RushHour Compiler compiles logical circuits for physical chips into optimized ISA programs while pipelining instructions. We evaluate RushHour against six state-of-the-art compilers and two resource models. On the smallest chips, 86% of benchmarks run only with RushHour, while existing approaches require 1.2-3.5$\times$ larger chips. On space-constrained early-FTQC chips, RushHour runs a median 2.0-7.2$\times$ faster than the best feasible alternative, while achieving results comparable to the state of the art on very large chips. RushHour's constructive results run 4.8$\times$ from an idealized-machine resource limit.

Abstract:Practical fault-tolerant quantum computing (FTQC) requires efficient lattice surgery (LS), so that large algorithms fit on resource-constrained quantum chips. Existing approaches, however, are rigid: qubits, routing space, and resource states are allocated ahead of execution, which prevents running on small chips, leaves statically scheduled executions with large time overheads, and fixes each design at a single area of the space-time trade-off. We present dynamic LS, which enables efficient reconfiguration of the ancilla space, just-in-time allocation of resource states, and dynamic rotations of logical qubits, thereby spanning the entire space-time trade-off with a single, unified approach. We realize dynamic LS with RushHour through a hardware-compiler co-design: the RushHour ISA formalizes and programs our dynamic lattice model, the Lattice Management Unit abstracts dynamic lattice management and performs efficient lattice reconfiguration, and the RushHour Compiler compiles logical circuits for physical chips into optimized ISA programs while pipelining instructions. We evaluate RushHour against six state-of-the-art compilers and two resource models. On the smallest chips, 86% of benchmarks run only with RushHour, while existing approaches require 1.2-3.5$\times$ larger chips. On space-constrained early-FTQC chips, RushHour runs a median 2.0-7.2$\times$ faster than the best feasible alternative, while achieving results comparable to the state of the art on very large chips. RushHour's constructive results run 4.8$\times$ from an idealized-machine resource limit.

arXiv:2608.18985 [quant-ph]

(or arXiv:2608.18985v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2608.18985 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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Full text under the publisher's open licence · 304 words

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