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Benchmarking the algorithmic performance of near-term neutral atom processors

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arxiv 2402.02127 v1 pith:Y2CURDYU submitted 2024-02-03 quant-ph

classification quant-ph
keywords quantumalgorithmatomqubitprocessorsqubitsalgorithmicancilla
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

Neutral atom quantum processors provide a viable route to scalable quantum computing, with recent demonstrations of high-fidelity and parallel gate operations and initial implementation of quantum algorithms using both physical and logical qubit encodings. In this work we present a characterization of the algorithmic performance of near term Rydberg atom quantum computers through device simulation to enable comparison against competing architectures. We consider three different quantum algorithm related tests, exploiting the ability to dynamically update qubit connectivity and multi-qubit gates. We calculate a quantum volume of $\mathbf{\mathit{V_{Q}}=2^{9}}$ for 9 qubit devices with realistic parameters, which is the maximum achievable value for this device size and establishes a lower bound for larger systems. We also simulate highly efficient implementations of both the Bernstein-Vazirani algorithm with >0.95 success probability for 9 data qubits and 1 ancilla qubit without loss correction, and Grover's search algorithm with a loss-corrected success probability of 0.97 for an implementation of the algorithm using 6 data qubits and 3 ancilla qubits using native multi-qubit $\mathbf{CCZ}$ gates. Our results indicate Rydberg atom processors are a highly competitive near-term platform which, bolstered by the potential for further scalability, can pave the way toward useful quantum computation.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Quantum Walks on Arbitrary Spatial Networks with Rydberg Atoms

    quant-ph 2025-07 conditional novelty 6.0 of 10

    A Rydberg-atom implementation of staggered quantum walks on spatial networks, with a new tessellation-cover algorithm, is proposed and numerically shown to achieve O(√N) spatial search time.

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