AI 中文总结
研究将CUDA-Q原生管道耦合GQE与QSCI应用于EUV光刻胶化学，通过GPT-2策略等实现能量变分上限，电路深度是扩展关键，在多方面取得成果，40量子比特结果受支持限制，经典子空间扩展有进展。
AI 中文摘要
我们扩展了一个原生CUDA-Q管道，该管道将生成量子本征求解器（GQE）与量子选择配置相互作用（QSCI）耦合，应用于14至44个量子比特的活性空间，用于单烷基锡氧氢氧化物的极紫外光刻胶化学。GPT-2策略生成UCCSD算符序列，采样比特串成为行列式并进行经典对角化，交叉电路广义特征值细化使每个报告的GQE+QSCI能量成为变分上限。从14到40个量子比特的每个层级都有精确的CASCI或FCI参考，32个量子比特的SnO有多达1.66亿个行列式。该管道在化学上是精确的，在最高层级的最佳种子上，对于三氢氧化甲基锡通过30个量子比特，对于SnO通过32个量子比特，误差低于1.6 mHa。电路深度而非训练长度是扩展的关键因素；精炼子空间随算符数量近乎线性增长，同时在行列式空间中占比极小，在32个量子比特的SnO层级为0.017%。它还可以在54个量子比特的IQM Emerald处理器上运行，在其路由的双量子比特门允许的浅深度下，对于14个量子比特的SnO，从CCSD振幅排序池前缀可达+0.330 mHa，对于22个量子比特的工业正丁基锡配体，在逐电路读出自校准下，从深度截断训练电路可达+3.92 mHa，占活性空间相关性的81%；在这些数量上的经典配置恢复将22个量子比特的结果收紧到+0.18至0.21 mHa。对于甲基抗蚀剂，电离使经典UCCSD(T) Sn-C键解离能从72.6降至21.2 kcal/mol，这是曝光时翻转溶解度的开关。相比之下，40个量子比特的结果在22.8 mHa时受支持限制，硬件上完整训练的假设等待更高的保真度，并且经典子空间扩展在没有量子采样器的情况下达到32至40个量子比特空间，因此该边界被映射而非突破。
英文摘要
We scale a CUDA-Q-native pipeline coupling a generative quantum eigensolver (GQE) to quantum-selected configuration interaction (QSCI) across active spaces of 14 to 44 qubits, applied to the extreme-ultraviolet (EUV) photoresist chemistry of monoalkyltin oxo-hydroxides. A GPT-2 policy emits UCCSD operator sequences; sampled bitstrings become determinants, diagonalised classically, and a cross-circuit generalised-eigenvalue refinement makes every reported GQE+QSCI energy a variational upper bound. Every rung from 14 to 40 qubits carries an exact CASCI or FCI reference, up to 166 million determinants for SnO at 32 qubits. The pipeline is chemically accurate, below 1.6 mHa, through 30 qubits on methyltin trihydroxide and through 32 on SnO, on the best seed at the top rungs. Circuit depth rather than training length is the scaling lever; the refined subspace grows near-linearly with the operator count while staying a vanishing fraction of the determinant space, 0.017% at the 32-qubit SnO rung. It also runs on the 54-qubit IQM Emerald processor, at the shallow depths its routed two-qubit gates allow, reaching +0.330 mHa for SnO at 14 qubits from a CCSD-amplitude-ordered pool prefix and +3.92 mHa for the industrial n-butyltin ligand at 22 qubits from depth-truncated trained circuits under per-circuit readout self-calibration, 81% of the active-space correlation; classical configuration recovery on those counts tightens the 22-qubit result to +0.18 to 0.21 mHa. For the methyl resist, ionisation collapses the classical UCCSD(T) Sn-C bond dissociation energy from 72.6 to 21.2 kcal/mol, the switch that flips solubility on exposure. Against that, the 40-qubit result is support-limited at 22.8 mHa, the full trained ansatz on hardware awaits better fidelities, and classical subspace expansion reaches the 32 to 40-qubit spaces with no quantum sampler, so that boundary is mapped, not beaten.
Comments12 pages, 4 figures, 6 tables. Code and persisted hardware counts: https://github.com/KarimElgammal/gqe-qsci-euv-photoresists
