Zoned Neutral Atom Quantum Architectures

• Zoned neutral atom quantum architectures are systems that spatially segment qubits into dedicated zones for storage, entanglement, and measurement.
• They leverage optical trap technologies such as SLMs and AODs to reconfigure and mobilize atoms with high fidelity and parallelism.
• Compiler heuristics and SMT-based scheduling optimize qubit movement and gate execution, enhancing error mitigation and scalability in large circuits.

Zoned neutral atom quantum architectures refer to spatially partitioned quantum computing platforms in which distinct hardware regions—termed “zones”—are engineered for specific operational roles such as memory (storage), entangling gates (processing), and measurement (readout). The core principle is to exploit the physical reconfigurability and mobility of neutral atom qubits via optical trap technologies (spatial light modulators (SLMs), acousto-optic deflectors (AODs)), enabling enhanced error mitigation, parallelism, and efficient circuit execution at scale. Recent advances incorporate compiler frameworks and zone-aware resource scheduling to optimize the fidelity and scalability of quantum algorithms on these platforms (Huang et al., 21 Nov 2024, Lin et al., 18 Nov 2024, Chen et al., 19 May 2025, Bluvstein et al., 2023, Decker, 10 May 2024, Stade et al., 28 May 2025, Stade et al., 15 Dec 2025).

1. Zone Definitions and Physical Realization

Zoned architectures are physically realized on a grid of optically trapped atoms, with the plane or 3D volume subdivided into at least two, often three, regions:

• Storage Zone (StoZ): Large SLM-generated arrays hold “idle” qubits at trap spacings (e.g. 3–6 μm), providing shielding from entangling laser fields and suppressing unwanted decoherence. Storage traps support parallel single-qubit rotations with minimal cross-talk.
• Entanglement (Interaction, Execution) Zone (EntZ/EZ/Z_C): AOD trap arrays or mobile tweezers spatially rearrange selected atoms into proximity (< Rydberg blockade radius, e.g. 4–10 μm) for simultaneous multi-qubit Rydberg gates (CZ, CPhase, etc.). This zone can dynamically compress, stretch, and mobilize qubit positions to maximize gate parallelism.
• Measurement (Readout) Zone (OutZ/RZ): Dedicated imaging regions are spatially separated to minimize laser-induced decoherence during fluorescence-based mid-circuit or final-state measurement.

Zone separation distances are hardware-dependent (e.g. 12–30 μm between storage and entangling zone); atom shuttles are engineered to maintain fidelity >99.9% per transfer, with typical inter-zone transfer times of 10–20 μs (Huang et al., 21 Nov 2024, Lin et al., 18 Nov 2024, Ruan et al., 19 Nov 2024, Farouk et al., 2023).

2. Gate Scheduling, Qubit Movement, and Resource Partitioning

Circuit execution requires loading appropriate qubits from storage into the entanglement zone, scheduling gate rounds, and returning qubits upon completion. Key scheduling primitives include:

• Stage Partitioning: Circuits are partitioned into ASAP (as soon as possible) rounds where all two-qubit gates on disjoint pairs are executed in parallel in EntZ (or Z_C). Reuse analysis identifies qubits that can remain in EntZ across adjacent rounds, minimizing unnecessary shuttling (Huang et al., 21 Nov 2024, Lin et al., 18 Nov 2024, Stade et al., 15 Dec 2025).
• Movement Constraints: AOD-based rearrangement operations obey strict non-crossing and order-preserving constraints; only entire rows or columns may be mobilized, and mobile-trap motions must avoid ghost spots and collisions. Compatible movements are grouped into maximal parallel rearrangement steps to minimize overhead (Stade et al., 28 May 2025, Stade et al., 15 Dec 2025).
• Compiler Heuristics: Routing-aware placement (A*) and Iterative Diving Search (IDS) integrate distance, parallel movement, and lookahead cost functions, enabling scalable compilation and up to 49% reduction in rearrangement overhead (Stade et al., 15 Dec 2025).
• Circuit/Array Partitioning: Physics-aware hardware plane decomposition partitions the device into independent zones (e.g., two N/2 × N/2 AOD subarrays and associated SLM buffers). Improved Kernighan-Lin algorithm optimizes circuit division to maximize per-zone parallel execution and minimize cross-zone “global” gates, with formal loss function incorporating qubit activity and inter-zone communication cost (Chen et al., 19 May 2025). Qubits without further cross-zone gates are parked in SLM sites post-local phase (Chen et al., 19 May 2025).

3. Algorithms, Intermediate Representations, and Scheduling Optimization

Zoned architectures mandate specialized compilation strategies:

• Max-Cut and Cross-Minimization: Qubit mapping for layer assignments leverages weighted max-cut to maximize vertical parallel movement, followed by bi-layer crossing minimization using GRASP heuristics, enabling circuit stacking and trade-offs between array width and algorithmic parallelism (Decker, 10 May 2024).
• ZAIR Specification: The intermediate representation for zoned platforms describes zones, SLM/AOD arrays, and “rearrangeJob” operations, including explicit trap assignments and detailed movement instructions, supporting both hardware abstraction and low-level pulse scheduling (Lin et al., 18 Nov 2024).
• Preemptive Gate Scheduling and Mantra: Gate reordering (e.g., fountain CZ chains and in-zone ZZ interactions) reduces inter-zone crossings by 68%, physical gate counts by 35%, and improves fidelities by 17% (Jang et al., 4 Mar 2025). Schedules are optimized to execute maximal contiguous same-zone gate sequences prior to any zone switch.
• SMT-Based Scheduling: Satisfiability modulo theories (SMT) solvers produce minimal-stage schedules for logical state preparation by explicit encoding of trap occupancy, movement ordering, AOD activation flags, and entanglement-zone shielding. ASP (approximate success probability) is maximized by minimizing idle time and Rydberg pulse count (Stade et al., 14 Nov 2024).

4. Fidelity, Parallelism, and Scaling Benchmarks

Empirical results consistently demonstrate that zoning yields substantial gains in circuit fidelity, gate parallelism, and compilation efficiency:

• Fidelity Improvements: Zoned architectures equipped with reuse-aware compilers achieve up to 22× fidelity over monolithic architectures, and maintain only a 10% gap to optimal movement+placement+reuse (Lin et al., 18 Nov 2024). A 5.4× increase in fidelity is found versus previous architectures with 100 qubits (Huang et al., 21 Nov 2024), and multi-qubit gates and mid-circuit readout can achieve >99% in tens of μs (Zhang et al., 21 Mar 2025).
• Resource Efficiency and Scalability: The standard cell approach enables linear-time resource estimation, with circuit compilation and scheduling scaling efficiently to thousands of qubits by leveraging zone-specific parallelism and movement packing (Dobbs et al., 2022, Stade et al., 15 Dec 2025, Chen et al., 19 May 2025).
• Experimental Compilation Times: Physics-aware compilation exhibits up to 78.5× speedup relative to previous methods on a 16×16 array, with near-constant circuit depth and further improvement as system scales (Chen et al., 19 May 2025).
• Gate Parallelism: Zoned architectures maximize two-qubit parallelism within EntZ, with benchmark circuits (Shor, QFT, QAOA, BV, Ising, Cat) showing layer depths and parallel gate counts directly correlated to zone-packing and routing-aware placement (Huang et al., 21 Nov 2024, Stade et al., 28 May 2025).

5. Extension to Logical Encoding, Error Correction, and Advanced Zone Topologies

Zoned neutral-atom processors are engineered to support error-corrected computation:

• Logical Qubits and Block Codes: Surface codes, color codes, Steane [[7,1,3]], [[8,3,2]], and hypercube block-connectivity are all achieved with physical and logical qubits mapped to zone-distinct Trap arrays, with transversal gates orchestrated by zone-aware AOD movement and Raman control (Bluvstein et al., 2023, Stade et al., 13 May 2024).
• Syndrome Extraction and Measurement: Ensemble-assisted architectures and heteronuclear platforms enable rapid non-demolition syndrome extraction, measurement-based logical state preparation in shallow schedule depth, and block-wise code scaling (Zhang et al., 21 Mar 2025, Farouk et al., 2023, Bluvstein et al., 2023).
• Dynamic and Multi-Zone Architectures: Compiler research investigates multi-layer zoning, dynamic zone shapes, 2.5D and 3D tilings, and dual-type/dual-element array architectures to further decouple error pathways, increase T₂, and enable scalable error-correction benchmarks (Zhang et al., 21 Mar 2025, Decker, 10 May 2024).

6. Limitations, Research Challenges, and Future Directions

Zoned neutral atom quantum architectures face several constraints and open questions:

• Hardware Constraints: AOD-based motion is subject to channel non-crossing, no atom overlap, and finite acceleration; perfect parallelism is limited by zone size and the inability to move atoms individually within a row or column.
• Dense Circuit Limitation: Algorithms with all qubits active in every stage (e.g., dense Ising models) derive less fidelity benefit from zoning due to minimal “idle shielding” opportunity (Huang et al., 21 Nov 2024).
• Compiler Scaling and Optimality: SMT-based scheduling can time out for the largest codes (non-optimal schedules may result), and heuristic approaches strive for tighter optimality guarantees in multi-zone or 3D layouts (Stade et al., 14 Nov 2024, Stade et al., 28 May 2025).
• Ongoing Research: Future improvements are anticipated in multi-zone scheduling, machine-learned placement, real-time hardware feedback, zone co-design, and hybrid logical-movement optimization frameworks. Efforts also target generalized syndrome extraction, adaptive zoning geometries, and dynamic integration of measurement scheduling with hardware movement primitives (Chen et al., 19 May 2025, Huang et al., 21 Nov 2024, Lin et al., 18 Nov 2024, Stade et al., 15 Dec 2025).

7. Comparative Summary Table: Fidelity and Efficiency Metrics

Compiler / Method	Fidelity Gain	Rearrangement Reduction	Compilation Speedup
ZAC (Lin et al., 18 Nov 2024)	22× vs. Enola	4× vs. NALAC	—
Zap (Huang et al., 21 Nov 2024)	5.4× vs. Enola	60–80% vs. prior	—
Routing-Aware (Stade et al., 28 May 2025)	—	17–49% vs. baseline	Seconds for 200 qubits
IDS + Relaxed (Stade et al., 15 Dec 2025)	—	28.1% avg. vs. A*	≤11min up to 5000q.
PAC (Chen et al., 19 May 2025)	—	—	78.5× vs. DPQA

These results confirm the foundational role of zoning in realizing practical, high-fidelity, large-scale quantum computation with neutral atoms.