Neutral-atom quantum computers can now arrange atoms in three-dimensional tweezer arrays, yet every existing compiler assumes a flat geometry. We present Piqasso, a compiler that exploits the vertical axis by stacking storage, entanglement, and readout into distinct layers. Its pipeline pairs an analytical placement respecting axial-clearance optics with a router that brings gate partners together via short vertical hops---bypassing in-plane crossing conflicts through out-of-plane detours---and a multi-AOD scheduler that parallelizes transport across focal planes. On 34 circuits, Piqasso reduces atom transport distance by 2.1$\times$ over a state-of-the-art planar compiler, yielding up to 7.3$\times$ faster execution, 2.2$\times$ higher movement fidelity, and 1.8$\times$ fewer serialized transport rounds, with all gains widening at scale.
Neutral-atom quantum computers can now arrange atoms in three-dimensional tweezer arrays, yet every existing compiler assumes a flat geometry. We present Piqasso, a compiler that exploits the vertical axis by stacking storage, entanglement, and readout into distinct layers. Its pipeline pairs an analytical placement respecting axial-clearance optics with a router that brings gate partners together via short vertical hops---bypassing in-plane crossing conflicts through out-of-plane detours---and a multi-AOD scheduler that parallelizes transport across focal planes. On 34 circuits, Piqasso reduces atom transport distance by 2.1× over a state-of-the-art planar compiler, yielding up to 7.3× faster execution, 2.2× higher movement fidelity, and 1.8× fewer serialized transport rounds, with all gains widening at scale.
Neutral atom quantum systems offer a promising pathway to large-scale quantum computing due to high qubit uniformity and flexible connectivity. To exploit this architecture, compilers must coordinate dynamic atom transport alongside highly parallel entangling gates. As circuits scale, the interplay between these operations becomes a system bottleneck, introducing denser logical interactions and longer temporal dependencies. Compilers must simultaneously satisfy rigid spatial constraints and complex movement schedules. Existing joint spatiotemporal compilation methods face an exponentially expanding search space, incurring substantial overheads or compromising fidelity as circuit size grows.
In this work, we propose ARGON, a scalable compilation framework that introduces a spatiotemporal decoupling paradigm for neutral atom processors. Our key novelty is offloading static geometric conflict resolution to an offline phase, precomputing a library of hardware-certified, high-parallelism spatial layouts. To guide temporal routing, we deploy a Graph Neural Network (GNN) predictor to evaluate candidate layouts against deep temporal horizons, proactively evading downstream kinematic bottlenecks. Finally, a heuristic router translates the selected sequence into collision-free physical transport.
Evaluations show ARGON completes compilation in under 10 seconds, delivering up to a >10^4x and 600x average speedup over state-of-the-art baselines. ARGON also minimizes routing decoherence and reduces Rydberg stages, improving execution fidelity by up to 10^2x on dense circuits.
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.
The neutral atom array has gained prominence in quantum computing for its scalability and operation fidelity. Previous works focus on fixed atom arrays (FAAs) that require extensive SWAP operations for long-range interactions. This work explores a novel architecture reconfigurable atom arrays (RAAs), also known as field programmable qubit arrays (FPQAs), which allows for coherent atom movements during circuit execution under some constraints. Such atom movements, which are unique to this architecture, could reduce the cost of longrange interactions significantly if the atom movements could be scheduled strategically. In this work, we introduce Atomique, a compilation framework designed for qubit mapping, atom movement, and gate scheduling for RAA. Atomique contains a qubit-array mapper to decide the coarse-grained mapping of the qubits to arrays, leveraging MAX k-Cut on a constructed gate frequency graph to minimize SWAP overhead. Subsequently, a qubit-atom mapper determines the fine-grained mapping of qubits to specific atoms in the array and considers load balance to prevent hardware constraint violations. We further propose a router that identifies parallel gates, schedules them simultaneously, and reduces depth. We evaluate Atomique across 20+ diverse benchmarks, including generic circuits (arbitrary, QASMBench, SupermarQ), quantum simulation, and QAOA circuits. Atomique consistently outperforms IBM Superconducting, FAA with long-range gates, and FAA with rectangular and triangular topologies, achieving significant reductions in depth and the number of two-qubit gates.
Neutral-atom quantum computing (NAQC) offers distinct advantages such as dynamic qubit reconfigurability, long coherence times, and high gate fidelities, making it a promising platform for scalable quantum computing. Among existing implementations, the Dynamically Field-Programmable Qubit Array (DPQA) architecture has emerged as the most prominent NAQC platform, enabling large-scale, high-fidelity operations through dynamic atom rearrangement and global Rydberg excitation. Despite these strengths, efficiently implementing quantum circuits like the Quantum Fourier Transform (QFT) remains a significant challenge due to atom-movement overheads and connectivity constraints. This paper introduces optimal compilation strategies tailored to QFT circuits on the DPQA architecture, addressing these challenges for both linear and grid-like configurations. By minimizing atom movements, the proposed methods achieve theoretical lower bounds in movement counts while preserving high circuit fidelity. Comparative evaluations against state-of-the-art DPQA compilers demonstrate the superior performance of the proposed methods, which could serve as benchmarks for evaluating the performance of future DPQA compilers.
Among different quantum computing technologies, neutral atom quantum computers have several advantageous features, such as multi-qubit gates, application-specific topologies, movable qubits, homogenous qubits, and long-range interactions. However, existing compilation techniques for neutral atoms fall short of leveraging these advantages in a practical and scalable manner. This paper introduces PARALLAX, a zero-SWAP, scalable, and parallelizable compilation and atom movement scheduling method tailored for neutral atom systems, which reduces high-error operations by 25% and increases the success rate by 28% on average compared to the state-of-the-art technique.
Compiling arbitrary-connectivity NISQ circuits onto monolithic single-zone neutral-atom devices is constrained by a finite interaction range and a minimum separation between simultaneously addressable sites. Under the minimum-separation constraint, the SWAP-only configuration of our pipeline does not return a schedule within a practical time budget on a range of circuits, including circuits as small as nine qubits. We address this with hub traps, a small number of dynamically placed empty traps that serve as transit waypoints, together with a per-gate rule that chooses between SWAP-based routing and hub-mediated shuttling. We evaluate the compiler on seventeen benchmarks using analytic estimates of execution time and a per-layer fidelity proxy, comparing against a placement-matched baseline and against ablations of our own pipeline. Hub traps make these otherwise-unsolved circuits compile in seconds to minutes and remove SWAP gates entirely on every completed circuit, so their role is to enable routing rather than only to optimize fidelity. The benefit is concentrated on routing-dominated circuits and is absent on routing-free ones, which we separate by the structure of the interaction graph. On the most routing-dominated circuit the fidelity proxy improves by up to three orders of magnitude over the placement-matched baseline. The gain comes primarily from eliminating SWAP overhead, as the absolute fidelities there remain low.