AI 中文总结
针对NISQ设备，提出稀疏量子体素编码将分子重建转化为计算基支撑恢复，实验在IBM Kingston设备上以少量采样实现了高召回率的分子几何重建，提升了读出效率。
AI 中文摘要
我们提出了一种分子几何结构的稀疏计算基编码方案，该方案将分子重建问题从全态层析转化为基于计算基采样的支撑恢复问题。为实现该编码方案，我们将分子空间离散化为三维网格，每个原子的位置和化学种类被映射到单个计算基态。这种离散化在体素分辨率尺度上引入了空间量化，随后分子被编码为该稀疏占据态集合上的等叠加态，我们假设存在合适的态制备方法。与需要约$\mathcal{O}(3^n \times 10^{2\text{--}3})$次测量采样次数（$n$为量子比特数）的全态层析不同，我们提出的编码方案可简化为计算基下的礼券收集者采样问题。在无噪声硬件上，完整重建含$A$个原子的分子需要$\mathcal{O}(A\log A)$次采样；在有噪声硬件上，所需采样次数会增加。我们在156量子比特的IBM Kingston设备上，使用8量子比特电路对10原子乙胺分子的离散几何结构进行重建，尽管存在显著硬件噪声，仅用$\mathcal{O}(10^2)$次采样就实现了较高的平均重建召回率。这些结果表明，我们提出的编码方案是适用于近期设备的、实用且具备高效读出能力的分子几何结构表示方法。
英文摘要
We propose a sparse computational-basis encoding of voxelized molecular geometries that converts molecular reconstruction from full-state tomography into support recovery by computational-basis sampling. To realize the encoding scheme, the molecular space is discretized into a 3D grid, and each atom's position and chemical species is mapped to a single computational basis state. This discretization introduces spatial quantization at the voxel-resolution scale. The molecule is then encoded as an equal superposition over this sparse set of occupied states, where we assume that a suitable state preparation method exists. In contrast to full state tomography, which requires on the order of $\mathcal{O}(3^n \times 10^{2\text{--}3})$ measurement shots, where $n$ is the number of qubits, our proposed encoding scheme reduces to a coupon-collector sampling problem in the computational basis. Complete recovery of an $A$-atom molecule requires $\mathcal{O}(A\log A)$ shots on noise-free hardware. On noisy hardware, the required number of shots increases. We demonstrate the method on the 156-qubit IBM Kingston device using 8-qubit circuits to reconstruct the discretized geometry of a 10-atom ethylamine molecule with high mean reconstruction recall using only $\mathcal{O}(10^2)$ shots despite substantial hardware noise. These results demonstrate that our proposed encoding scheme is a practical, readout-efficient representation for molecular geometries on near-term devices.
