Neutral Atom Quantum Processors

• Neutral atom quantum processors are architectures using individually trapped neutral atoms as qubits, enabling scalable quantum simulation and computation.
• They employ tunable Rydberg interactions and optical control techniques to implement high-fidelity entangling gates and dynamic reconfiguration.
• Advances in readout fidelity, atomic retention, and co-designed compilation strategies drive improved throughput and integration with quantum networks.

Neutral atom quantum processors utilize arrays of individually trapped neutral atoms, typically alkali or alkaline-earth(-like) species, as quantum bits (qubits). These architectures leverage strong, tunable Rydberg–Rydberg interactions for native, high-fidelity entangling gates and exhibit exceptional promise for scalable, high-throughput quantum information processing, quantum simulation, and networked computation. Recent advances include system-level modeling of the fundamental trade-offs between readout fidelity and atom survival, circuit throughput metrics, and the optimization of information extraction strategies necessary for practical deployment at scale (Chen et al., 15 Jan 2026).

1. Physical Principles and System Architecture

Neutral atom processors confine single atoms—such as $^{87}$Rb or $^{171}$Yb—in programmable arrays of optical tweezers or static optical lattices. Qubit encoding generally employs two hyperfine ground states with long $T_1$ and $T_2$ times. Optical access enables both global and site-selective control of single- and multi-qubit rotations via microwave, Raman, or Rydberg-coupling laser fields. The Rydberg excited state, with large principal quantum number $n$, gives rise to strong van der Waals interactions $V_{ij} = C_6/|r_i-r_j|^6$, setting the foundational physics of the Rydberg blockade (Henriet et al., 2020, Dalyac et al., 2024). Electronic excitation from the ground $|g\rangle$ to Rydberg $|r\rangle$ implements fast, native CZ and CCZ gates and enables programmable many-body Hamiltonians for simulation (McInroy et al., 2024).

System architecture scales from a few qubits to arrays ($N\gtrsim1000$) with defect-free loading ensured by real-time imaging and dynamic rearrangement. Two major design patterns are now routine:

• Static, globally addressed arrays: All qubits controlled simultaneously by global pulses with programmable detunings.
• Dynamic, individually addressed arrays: Site-specific optical addressing yields local gates and rapid reconfiguration, minimizing routing overhead and maximizing connectivity (Radnaev et al., 2024).

The trapping, cooling, and decoherence parameters—trap depth ($T_{\mathrm{trap}}$), initial atom temperature ($^{171}$0), collection efficiency ($^{171}$1), Rabi frequencies ($^{171}$2), and interaction strengths ($^{171}$3)—are experimentally tunable in the range required for scalable, high-fidelity quantum operations (Rava et al., 28 Nov 2025, Chen et al., 15 Jan 2026).

2. Readout Strategies, Atomic Retention, and Throughput

A key challenge in neutral atom quantum processors is balancing the readout fidelity ($^{171}$4) and atomic retention probability ($^{171}$5) to maximize usable system throughput. Readout protocols are fundamentally limited by photon scattering: each scattered photon imparts a recoil $^{171}$6, increasing the atomic temperature and the probability of trap escape (Chen et al., 15 Jan 2026). The atomic loss probability formalism integrates the tail of the Maxwell–Boltzmann energy distribution above the trap threshold, yielding

$^{171}$7

Readout is performed by discrimination between "dark" ($^{171}$8) and "bright" ($^{171}$9) states via photon counting, with noise statistics governed by the detector choice:

• Single-photon detector (SPD): Poissonian statistics with background dark counts ($T_1$0).
• qCMOS camera: Gaussian noise readout, with mean/variance ($T_1$1, $T_1$2), plus Poissonian fluorescence (Chen et al., 15 Jan 2026).

The readout duration $T_1$3 sets the trade-off: longer $T_1$4 yields higher $T_1$5 but reduced $T_1$6 due to increased heating. The quantum circuit iteration rate (qCIR),

$T_1$7

parametrizes average circuits per second, correctly capturing non-destructive and destructive readout as limiting cases.

A unified figure of merit, the normalized quantum Fisher information,

$T_1$8

integrates information gain per second over both retention and fidelity. Experimentally, optimal $T_1$9 is realized at intermediate $T_2$0 maximizing this product. For $T_2$1Rb, cycle and reloading times of $T_2$2 and $T_2$3, and detectors with

• SPD: $T_2$4, $T_2$5, $T_2$6, $T_2$7.
• qCMOS: $T_2$8, $T_2$9, $n$0, $n$1,

illustrate the operational efficiency and regime-specific trade-offs (Chen et al., 15 Jan 2026).

3. Large-Scale Computation and Algorithmic Performance

Scalable neutral atom processors are benchmarked using both analog and digital quantum algorithms. Platforms such as QuEra Aquila and Pasqal Fresnel have demonstrated quantum adiabatic algorithm (QAA) and quantum approximate optimization algorithm (QAOA) solution of NP-hard Maximum Independent Set (MIS) problems on unit-disk graphs at scales up to $n$2 with $n$3 approximation ratios for subhundred qubit registers (Rava et al., 28 Nov 2025). Transfer learning and parameter re-use enable robust QAOA performance (approximate ratio $n$4 for $n$5). Performance scaling is limited by cumulative atom loss ($n$6 per run) and decoherence (both spontaneous decay and Doppler dephasing), with error mitigation via post-selection, SPAM calibration, and parameter pre-optimization (Rava et al., 28 Nov 2025). Ancilla recycling and mid-circuit measurement support further improvements in circuit depth and logical qubit protocols (Muniz et al., 11 Jun 2025).

Quantum volume $n$7 has been achieved with nine-qubit devices using reconfigurable connectivities (McInroy et al., 2024), matching or exceeding superconducting and trapped-ion platforms for small benchmarks. Gate fidelities surpass $n$8 for single- and two-qubit gates and $n$9 for native three-qubit CCZ implementations. These protocols enable loss-corrected algorithmic success probabilities of $V_{ij} = C_6/|r_i-r_j|^6$0 for Grover search on $V_{ij} = C_6/|r_i-r_j|^6$1 data qubits plus three ancilla (McInroy et al., 2024).

4. Compiler Design, Reconfigurability, and Optimization

The dynamical, field-programmable nature of neutral atom arrays is a principal advantage for circuit compilation and resource optimization. Architectures supporting dynamically field-programmable qubit arrays (DPQA) feature both stationary (SLM) and mobile (AOD) tweezer traps. Qubit transport, by rigid row/column movements, allows arbitrary two- and multi-qubit gates to be scheduled at minimal depth overhead with hardware-aware constraint satisfaction (using, e.g., SMT solvers) (Tan et al., 2023). Greedy heuristics and hybrid approaches, including iterative peeling protocols, yield $V_{ij} = C_6/|r_i-r_j|^6$2–$V_{ij} = C_6/|r_i-r_j|^6$3 gate count reductions over traditional grid architectures for circuits up to 90 qubits.

Hardware and compilation co-design includes explicit modeling of Rydberg blockade radius, crosstalk constraints, shuttling latencies, and mid-circuit atom replacement. Cost functions can incorporate gate fidelity, idle time, and erasure probability, supporting a transition from NISQ-optimized workflows to fault-tolerance-centric compilation (Schmid et al., 2023).

5. Quantum Networking and Distributed Architectures

Neutral atom quantum processors are suited for integration into modular quantum networks. Architectures employ species-resolved communication and memory zones (e.g., dual-species with $V_{ij} = C_6/|r_i-r_j|^6$4Rb for photonic links and $V_{ij} = C_6/|r_i-r_j|^6$5Cs for local gates), or twisted-cavity modules supporting array-scale loading with in-situ cooling (Li et al., 2024, Young et al., 2022). Both high-NA free-space and near-concentric optical cavities have been benchmarked for photonic coupling efficiency ($V_{ij} = C_6/|r_i-r_j|^6$6), supporting remote entanglement rates $V_{ij} = C_6/|r_i-r_j|^6$7 per channel and Bell-pair fidelities $V_{ij} = C_6/|r_i-r_j|^6$8 (Young et al., 2022, Li et al., 2024).

Photon collection enhancements via cavity Purcell factors, active cooling, and rapid cycling permit single-shot entanglement establishment in $V_{ij} = C_6/|r_i-r_j|^6$9 per attempt. Timing-correlated error tagging enables error-diagnosis incorporating "soft information" in decoders, facilitating logic-gate-level intermodule operations and scalable surface code implementation across modules (Li et al., 2024).

6. Directions in Fault-Tolerance, Error-Correction, and System Integration

Recent demonstrations of loss- and error-corrected logical qubits leverage neutral atom advantages in erasure conversion: gate or measurement-induced leakage presents as atom loss, which is natively detected and flagged in imaging. Distance-2 and -3 codes (e.g., [[4,2,2]], [[9,1,3]]) have been implemented with threshold scaling $|g\rangle$0 and logical error rates lower than the physical baseline (Reichardt et al., 2024). Ancilla replacement via rapid reservoir loading and mid-circuit atom manipulation supports repeated syndrome extraction over $|g\rangle$1 rounds (Muniz et al., 11 Jun 2025). System-level integration with fast, non-destructive readout (loss $|g\rangle$2, per-call error $|g\rangle$3) and high-fidelity gates moves neutral atom platforms into a regime compatible with surface code thresholds (Radnaev et al., 2024, Reichardt et al., 2024).

Digital twin frameworks (e.g., AtomTwin.jl) now model full mixed quantum/classical dynamics, including motional dephasing, noise, and schedule-specific effects, providing quantitative end-to-end validation for circuit design and optimization (Whitlock, 20 Apr 2026).

Continued increases in collection efficiency, atom replacement rates, and gate/measurement speeds (currently achieving circuit rates $|g\rangle$4 Hz for non-destructive readout (Chen et al., 15 Jan 2026)) will extend the depth and complexity of feasible algorithms, facilitating quantum advantage in NISQ regimes and supporting the transition to practical, error-corrected neutral atom quantum computation.

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References

• (Chen et al., 15 Jan 2026) Optimized readout strategies for neutral atom quantum processors
• (Tan et al., 2023) Compiling Quantum Circuits for Dynamically Field-Programmable Neutral Atoms Array Processors
• (Rava et al., 28 Nov 2025) Benchmarking neutral atom-based quantum processors at scale
• (McInroy et al., 2024) Benchmarking the algorithmic performance of near-term neutral atom processors
• (Radnaev et al., 2024) A universal neutral-atom quantum computer with individual optical addressing and non-destructive readout
• (Young et al., 2022) An architecture for quantum networking of neutral atom processors
• (Reichardt et al., 2024) Fault-tolerant quantum computation with a neutral atom processor
• (Muniz et al., 11 Jun 2025) Repeated ancilla reuse for logical computation on a neutral atom quantum computer
• (Li et al., 18 Jun 2025) Fast, continuous and coherent atom replacement in a neutral atom qubit array
• (Whitlock, 20 Apr 2026) AtomTwin.jl: a physics-native digital twin framework for neutral-atom quantum processors
• (Li et al., 2024) High-rate and high-fidelity modular interconnects between neutral atom quantum processors
• (Schmid et al., 2023) Computational Capabilities and Compiler Development for Neutral Atom Quantum Processors: Connecting Tool Developers and Hardware Experts
• (Henriet et al., 2020) Quantum computing with neutral atoms
• (Dalyac et al., 2024) Graph Algorithms with Neutral Atom Quantum Processors