发表机构
Indian Institute of Technology Bombay; Centre of Excellence in Quantum Information, Computing, Science & Technology, Indian Institute of Technology Bombay（印度理工学院孟买分校; 印度理工学院孟买分校量子信息、计算、科学与技术卓越中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出Q-WAVE混合方法，结合SqDRIFT采样与CISD行列式及β退火VAE生成新主导行列式，增强量子波函数，在H₂O、N₂、乙烯及Cr₂体系上实现亚毫哈特里或化学精度。
AI 中文摘要
基于样本的量子对角化（SQD）已成为量子中心超计算的一条有前景的途径，它依赖于在硬件采样的行列式子空间内对分子哈密顿量进行经典对角化。然而，在强关联区域，其精度会下降，因为相关的行列式空间超出了有限次采样所能捕获的范围。在这项工作中，我们引入了基于变分自编码器的量子波函数增强（Q-WAVE），这是一种混合方法，将通过SqDRIFT Krylov电路采样的行列式与组态相互作用单双激发（CISD）行列式以及生成式机器学习相结合。使用自定义的β退火变分自编码器（VAE）模型，Q-WAVE迭代地将该基组扩展至变分基态。VAE在连续潜空间中从组合的硬件和CISD种子学习波函数的主要支撑结构，生成超越任何固定激发层次的新主导行列式。由此产生的紧凑波函数超越了仅从原始硬件样本中提取的结果。我们展示了与全组态相互作用相比，对于H₂O和N₂解离，达到了亚毫哈特里精度。最后，我们验证了Q-WAVE在52量子比特乙烯系统上的可扩展性（相对于CCSD(T)达到亚毫哈特里精度），以及一个高度关联的60量子比特Cr₂应力测试，该测试在最终微扰修正后达到了化学精度。
英文摘要
Sample-based quantum diagonalization (SQD) has emerged as a promising route for quantum-centric supercomputing, relying on classical diagonalization of the molecular Hamiltonian within a hardware-sampled determinant subspace. However, its accuracy degrades in strongly correlated regimes where the relevant determinant space exceeds what finite-shot sampling can capture. In this work, we introduce Quantum Wavefunction Augmentation via Variational Autoencoders (Q-WAVE), a hybrid method that combines determinants sampled via SqDRIFT Krylov circuits and configuration interaction singles and doubles (CISD) determinants with generative machine learning. Using a custom $β$-annealed variational autoencoder (VAE) model, Q-WAVE iteratively expands this basis toward the variational ground state. The VAE learns the wavefunction's primary support structure from the combined hardware and CISD seed in a continuous latent space, generating new dominant determinants beyond any fixed excitation hierarchy. The resulting compact wavefunction exceeds what can be extracted from raw hardware samples alone. We demonstrate sub-millihartree accuracy compared to full configuration interaction for $\text{H}_2\text{O}$ and $\text{N}_2$ dissociation. Finally, we establish Q-WAVE's scalability on a 52-qubit ethylene system (achieving sub-millihartree accuracy versus CCSD(T)) and a highly correlated 60-qubit $\text{Cr}_2$ stress test that attains chemical accuracy upon a final perturbative correction.
Comments20 pages, 8 figures
