Quantum computing architectures based on neutral atoms offer large scales and high-fidelity operations. They can be heterogeneous, with different zones for storage, entangling operations, and readout. Zoned architectures improve computation fidelity by shielding idling qubits in storage from side-effect noise, unlike monolithic architectures where all operations occur in a single zone. However, supporting these flexible architectures with efficient compilation remains challenging. In this paper, we propose ZAC, a scalable compiler for zoned architectures. ZAC minimizes data movement overhead between zones with qubit reuse, i.e., keeping them in the entanglement zone if an immediate entangling operation is pending. Other innovations include novel data placement and instruction scheduling strategies in ZAC, a flexible specification of zoned architectures, and an intermediate representation for zoned architectures, ZAIR. Our evaluation shows that zoned architectures equipped with ZAC achieve a 22x improvement in fidelity compared to monolithic architectures. Moreover, ZAC is shown to have a 10% fidelity gap on average compared to the ideal solution. This significant performance enhancement enables more efficient and reliable quantum circuit execution, enabling advancements in quantum algorithms and applications. ZAC is open source at https://github.com/UCLAVAST/ZAC
Quantum computing architectures based on neutral atoms offer large scales and high-fidelity operations. They can be heterogeneous, with different zones for storage, entangling operations, and readout. Zoned architectures improve computation fidelity by shielding idling qubits in storage from side-effect noise, unlike monolithic architectures where all operations occur in a single zone. However, supporting these flexible architectures with efficient compilation remains challenging. In this paper, we propose ZAC, a scalable compiler for zoned architectures. ZAC minimizes data movement overhead between zones with qubit reuse, i.e., keeping them in the entanglement zone if an immediate entangling operation is pending. Other innovations include novel data placement and instruction scheduling strategies in ZAC, a flexible specification of zoned architectures, and an intermediate representation for zoned architectures, ZAIR. Our evaluation shows that zoned architectures equipped with ZAC achieve a 22x improvement in fidelity compared to monolithic architectures. Moreover, ZAC is shown to have a 10% fidelity gap on average compared to the ideal solution. This significant performance enhancement enables more efficient and reliable quantum circuit execution, enabling advancements in quantum algorithms and applications. ZAC is open source at https://github.com/UCLAVAST/ZAC
The scalability of neutral-atom quantum computing is increasingly limited by a compiler–architecture challenge: logical circuits must be mapped onto dynamically reconfigurable atom arrays while controlling crosstalk, transport overhead, and hardware constraints. To address this problem, we present ZAP, a co-designed zoned architecture and deterministic compiler for field-programmable atom arrays. ZAP partitions the array into storage and entanglement zones and combines hardware-aware ASAP-separate scheduling, look-ahead placement, and conflict-aware routing in a single-pass compilation flow, thereby avoiding the repeated global search used in prior approaches. Evaluated on structured quantum benchmarks and random 3-regular circuits, ZAP consistently delivers multi-order-of-magnitude compilation speedups while maintaining competitive or superior execution quality. Relative to ZAC and PowerMove, ZAP typically reduces compilation time from tens of seconds to below 0.1 s and achieves speedups exceeding 1,000×; relative to Enola, the speedup exceeds 10,000× on the evaluated suite. ZAP's fidelity gains are most pronounced on structured workloads with irregular connectivity and nonuniform qubit reuse, where its scheduling and placement decisions more effectively suppress crosstalk and limit transport-related loss, while on random circuits it remains competitive and preserves the same scalability advantage. These results show that hardware-structured, non-iterative compilation provides a practical path toward fast, scalable, and noise-aware neutral-atom quantum computing.
Quantum computing promises to solve previously intractable problems, with neutral atoms emerging as a promising technology. Zoned neutral atom architectures allow for immense parallelism and higher coherence times by shielding idling atoms from interference with laser beams. However, in addition to hardware, successful quantum computation requires sophisticated software support, particularly compilers that optimize quantum algorithms for hardware execution. In the compilation flow for zoned neutral atom architectures, the effective interplay of the placement and routing stages decides the overhead caused by rearranging the atoms during the quantum computation. Suboptimal placements can lead to unnecessary serialization of the rearrangements in the subsequent routing stage. Despite this, all existing compilers treat placement and routing independently thus far—focusing solely on minimizing travel distances. This work introduces the first routing-aware placement method to address this shortcoming. It groups compatible movements into parallel rearrangement steps to minimize both rearrangement steps and travel distances. The implementation utilizing the A* algorithm reduces the rearrangement time by 17% on average and by 49% in the best case compared to the state-of-the-art. The complete code is publicly available in open-source as part of the Munich Quantum Toolkit (MQT) at https://github.com/cda-tum/mqt-qmap.
Zoned neutral atom architectures are emerging as a promising platform for large-scale quantum computing. Their growing scale, however, creates a critical need for efficient and automated compilation solutions. Yet, existing methods fail to scale to the thousands of qubits these devices promise. State-of-the-art compilers, in particular, suffer from immense memory requirements that limit them to small-scale problems. This work proposes a scalable compilation strategy that "searches smarter, not harder". We introduce Iterative Diving Search (IDS), a goal-directed search algorithm that avoids the memory issues of previous methods, and relaxed routing, an optimization to mitigate atom rearrangement overhead. Our evaluation confirms that this approach compiles circuits with thousands of qubits and, in addition, even reduces rearrangement overhead by 28.1% on average. The complete code is publicly available in open-source as part of the Munich Quantum Toolkit (MQT) at https://github.com/munich-quantum-toolkit/qmap.
Neutral atom quantum computers (NAQCs) have emerged as promising candidates for scalable quantum computing, thanks to their advanced hardware capabilities, particularly qubit movement and the Zoned Architecture (ZA). However, fully harnessing these features presents significant compilation challenges, requiring careful coordination across gate scheduling, qubit positioning, atom movement, and inter-zone communication. In this paper, we propose PowerMove, an efficient compiler for NAQCs that unlocks new optimization opportunities, significantly improving qubit movement strategies while seamlessly integrating ZA. Our evaluation demonstrates orders-of-magnitude fidelity improvements over state-of-the-art methods, with execution time reduced by up to 3.76× and compilation time accelerated by up to 216.9× across various NISQ applications. Furthermore, PowerMove extends naturally to the fault-tolerant quantum computing (FTQC) setting, where physical qubits are replaced by logical qubits encoded in QEC codes, achieving a 4.78× reduction in execution time. These results highlight PowerMove's impact on both near-term NISQ applications and long-term FTQC implementations. We have open-sourced our codes at https://github.com/Scarlett0815/PowerMove to facilitate further research and collaboration within the community.
Quantum computing promises to solve problems previously deemed infeasible. However, high error rates necessitate quantum error correction for practical applications. Seminal experiments with zoned neutral atom architectures have shown remarkable potential for fault-tolerant quantum computing. To fully harness their potential, efficient software solutions are vital. A key aspect of quantum error correction is the initialization of physical qubits representing a logical qubit in a highly entangled state. This process, known as state preparation, is the foundation of most quantum error correction codes and, hence, a crucial step towards fault-tolerant quantum computing. Generating a schedule of target-specific instructions to perform the state preparation is highly complex. First software tools exist but are not suitable for the zoned neutral atom architectures. This work addresses this gap by leveraging the computational power of SMT solvers and generating minimal schedules for the state preparation of logical arrays. Experimental evaluations demonstrate that actively utilizing zones to shield idling qubits consistently results in higher fidelities than solutions disregarding these zones. The complete code is publicly available in open-source as part of the Munich Quantum Toolkit (MQT) at https://github.com/cdatum/mqt-qmap.
Neutral atom quantum computers (NAQC) are emerging as a promising, scalable quantum computing platform because of their long qubit coherence, flexible qubit arrangement, and multiqubit gate capabilities. However, circuit execution often requires physically moving qubits, making compilation a critical optimization challenge. We propose a circuit independent mathematical framework built on graph-theoretic combinatorial optimization that determines the minimal number of required qubit transfers. This model captures spatial constraints specific to NAQC platforms with zone-limited gate operations and multi-qubit gates. From this framework, we encode the qubit mapping problem as a nonlinear integer program and solve it using a genetic algorithm, enabling trade-offs between minimizing the total traveled distance and the number of parallel transfer operations. Compared to the state-of-the-art scalable compiler for zoned architectures, our approach consistently finds fewer transfers. Depending on the optimization focus, our method produces shorter traveled distances or fewer parallel transfer operations. This work provides both theoretical guaranties and a practical tool for efficient, architecture-aware quantum circuit compilation. As a result, practitioners can generate hardware-aware mappings that reduce movement-induced errors and better exploit atom transfer parallelism, directly improving execution efficiency on NAQC devices.