SearcharxivSearch

arXiv · 2508.03914

Moveless: Minimizing Overhead on QCCDs via Versatile Execution and Low Excess Shuttling

Abstract

One of the most promising paths towards large scale fault tolerant quantum computation is the use of quantum error correcting stabilizer codes. Just like every other quantum circuit, these codes must be compiled to hardware in a way to minimize the total physical error introduced into the system, for example either due to high latency execution or excessive gates to meet connectivity limitations of the target hardware. However, unlike arbitrary quantum circuits, all syndrome extraction circuits have several common properties, for example they have a bipartite connectivity graph, consist only of commuting subcircuits, among other properties. For the most part, compilation methods have aimed at being generic, able to map any input circuit into executables on the hardware, and therefore cannot appropriately exploit these properties and result in executables which have higher physical error. In the case of modular trapped ion systems, specifically QCCDs, this corresponds to the insertion of excessive shuttling operations necessary to realize arbitrary qubit interactions. We propose a compilation scheme explicitly tailored for the structural regularity of QEC circuits based on several key observations: 1. only ancilla or data (but not both) should be shuttled, 2. stabilizers can be executed in any order meaning we can dynamically modify circuit execution on a per-cycle basis 3. ancilla are indistinguishable meaning any can be selected to begin a stabilizer measurement and retain a fixed-point mapping between cycles, and 4. QCCD hardware limits the number of parallel operations equal to the number traps in the system, meaning fewer ancilla are necessary and can be reused. Our resulting compiler, leads to QEC circuits which are on average 3.38x faster to execute, and lead to up to two orders of magnitude of improvement in logical error rates with realistic physical error rates.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sahil Khan, Suhas Vittal, Kenneth Brown, Jonathan Baker. 2025-08-05. Moveless: Minimizing Overhead on QCCDs via Versatile Execution and Low Excess Shuttling. https://arxiv.org/abs/2508.03914

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Probing the Error-Mitigation Threshold with Matrix Product States

Quantum error mitigation relies on accurate noise characterization, but mismatches between the actual and characterized noise can be amplified and drive a sharp threshold between successful and failed mitigation. In random circuits, this threshold maps onto a random-field Ising transition, but previous exact numerics were limited to small one-dimensional and all-to-all systems, leaving explicit two-dimensional architectures unresolved. We develop a fixed-bond-dimension matrix-product-state method for the replicated transfer dynamics that extends threshold calculations beyond exact propagation while retaining the finite-size signatures of the transition. At system sizes beyond previous exact studies, we recover the predicted absence of a threshold for quenched disorder in 1D, obtain a sharper annealed all-to-all critical point, and resolve architecture-dependent finite-depth thresholds in 2D square and heavy-hex circuits. These results establish replicated tensor-network dynamics as a practical tool for probing error-mitigation thresholds in large and higher-dimensional noisy circuits.

quant-ph

Low-cost algorithm-to-execution framework for surface-code quantum computing

The execution of useful quantum algorithms on fault-tolerant processors requires more than a mapping from logical gates to encoded operations: the spatial organization, non-Clifford resource supply, and execution schedule must also be determined while keeping physical overhead within practical limits. Although the theoretical hierarchy from logical circuits to fault-tolerant operations is well established, these implementation choices are often specified and optimized separately. Here we develop a low-cost algorithm-to-execution framework for surface-code quantum computing. From hierarchical algorithm descriptions, it constructs dependency-preserving logical schedules and an executable workload capturing logical interactions, operation parallelism, and time-resolved non-Clifford demand, thereby linking logical computation to surface-code organization, resource-state preparation, and fault-tolerant execution in a traceable workflow. We apply the framework to twenty benchmark circuits across seven algorithm families and a hierarchically composed application-scale elliptic-curve discrete-logarithm workload. Physical costs vary substantially even for circuits with similar logical resource counts. Under our direct-rotation calibration, non-Clifford implementation selection reduces space-time volume by up to 241.5 times versus an all-synthesis baseline for the QAOA amplitude-amplification workload. Circuit-specific surface-code layouts reduce routed-latency estimates for all twenty benchmarks; thirteen also reduce space-time volume because communication savings outweigh added spatial overhead. These results show that low-cost fault-tolerant execution depends on computation scheduling and organization, not aggregate logical resource counts alone.

quant-ph

Sample-optimal learning of stabilizer states

It is well-known that learning a pure $n$-qubit stabilizer state $|\psi\rangle$ both requires, and can be accomplished with, access to a number of copies of $|\psi\rangle$ linear in $n$. However, the precise constant coefficient of this scaling does not appear to have been determined. Here we prove that $L_\delta(n)$, the smallest number of copies from which a quantum procedure can identify any stabilizer state with failure probability at most $0<\delta<1/8$, satisfies $n+\lceil\log_2(1/\delta)\rceil-3\leq L_\delta(n)\leq n+\left\lceil\log_2(1/\delta)\right\rceil+4$. We present a polynomial-time quantum learning algorithm that saturates this bound, achieving a constant factor improvement in sample-complexity over previously known approaches. As an immediate corollary, we obtain via the Choi-Jamiolkowski isomorphism an algorithm for learning an unknown $n$-qubit Clifford unitary from $2n+\left\lceil\log_2(1/\delta)\right\rceil+4$ queries, the $n$-dependence of which we show to be optimal. Our proof technique, which involves Fourier analysis on the abelian group $\mathbb{Z}_4^n \times \mathbb{F}_2^{n(n-1)/2}$, seems to be qualitatively different to previous approaches to stabilizer state learning, and may be of some independent interest; in particular, it admits natural generalisations to further problems in quantum learning theory.

quant-ph