用量子算法提升复杂环境下的导航决策与目标追踪效率
QANTIS: A Hardware-Validated Quantum Platform for POMDP Planning and Multi-Target Data Association
- 结合量子幅值放大与QUBO优化，实现高效信念更新和多目标数据关联
- 硬件实验显示罕见观测概率提升5.1倍，后验分布误差仅0.0015
- 首次在超导硬件上实现闭环量子-经典混合POMDP系统，适合当前量子设备
不确定性下的自主导航需解决部分可观测马尔可夫决策过程（POMDP）规划与多目标数据关联（MTDA）问题。两者在大规模下计算负担重：信念更新代价为$\mathcal{O}(P(e)^{-1})$，MTDA为NP难。量子幅值放大可将查询复杂度降至$\mathcal{O}(P(e)^{-1/2})$，QUBO重构使MTDA适用于量子及类量子优化。我们提出QANTIS平台，集成量子信念更新（Grover幅值放大与BIQAE）、FPC-QAOA的QUBO数据关联及可组合误差缓解，并在三台IBM Heron后端进行45次硬件实验。实测中，对Tiger信念算子应用一次Grover迭代，将罕见观测概率从0.179提升至0.907（5.1倍；ISA 18），后验分布保持良好（Hellinger 0.0015），可用样本数从1,463增至7,429。这验证了$\mathcal{O}(P(e)^{-1/2})$机制在$k=1$时的有效性，而非时序优势。我们首次在超导硬件上实现闭环混合量子-经典Tiger POMDP（$T=8$，最大Hellinger < 0.015），并实证刻画了NISQ可行性边界：基于零噪声外推（ZNE）的误差缓解在ISA ≈ 100以下有益，高于1,000则有害；FPC-QAOA在≤15个QUBO变量（ISA ≤ 450）时有效。结果界定当前超导硬件的实际可行操作范围，而非今日规模下的时序量子优势。
原文摘要 · Abstract (English)
Autonomous navigation under uncertainty requires solving partially observable Markov decision processes (POMDPs) for planning and assigning sensor measurements to tracked targets--a task known as multi-target data association (MTDA). Both problems become computationally demanding at scale: belief conditioning costs $\mathcal{O}(P(e)^{-1})$ per node under rare evidence, while MTDA is NP-hard. Quantum amplitude amplification can quadratically reduce the belief-update query cost to $\mathcal{O}(P(e)^{-1/2})$, while QUBO reformulations expose MTDA to quantum and quantum-inspired optimisation heuristics. We present QANTIS, a modular platform that integrates quantum belief update (Grover amplitude amplification and BIQAE), QUBO-based data association via FPC-QAOA, and composable error mitigation, and we report a 45-experiment hardware study on three IBM Heron backends. On hardware, a single Grover iterate applied to a Tiger belief oracle amplifies a rare observation probability from $0.179$ to $0.907$ ($5.1\times$; ISA 18) while preserving the Bayesian posterior (Hellinger $0.0015$), increasing usable-shot yield from 1,463 to 7,429. We interpret this as a hardware validation of the quadratic query-complexity mechanism at $k=1$ with posterior preservation, rather than a wall-clock advantage claim. We further demonstrate, to our knowledge, the first closed-loop hybrid quantum-classical Tiger POMDP on superconducting hardware ($T=8$, max Hellinger below $0.015$), and empirically characterise NISQ feasibility boundaries: ZNE-based error mitigation is beneficial below ISA $\approx 100$ and harmful above ISA $\gtrsim 1{,}000$; FPC-QAOA is meaningful at $\leq 15$ QUBO variables (ISA $\lesssim 450$). These results characterise practical operating regimes on current superconducting hardware rather than wall-clock quantum advantage at today's problem scales.
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