发表机构
IBM Research; ExxonMobil Technology and Engineering Company（IBM研究院; 埃克森美孚技术与工程公司）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究采用基于采样的量子对角化框架计算多炔分子的非简谐振动光谱，结合量子采样与子空间对角化，在多达104量子比特下揭示红外强度随基组演化的现象，并指出多态恢复等扩展挑战。
AI 中文摘要
预测非简谐振动光谱是一项复杂的计算任务，随着分子尺寸和振动基函数数量的增加，该任务迅速变得不可行，导致底层希尔伯特空间呈指数增长。在此，我们采用基于采样的量子对角化（SQD）框架来计算非简谐振动能量和光谱。该方法将量子态制备与采样、构型恢复、在基构型子空间中对哈密顿量进行投影对角化以及跃迁偶极矩的计算相结合，以获得振动能量和红外光谱。我们研究了两种采样方法，即vib-LUCJ和vib-SqDRIFT，并将该方法应用于研究多炔分子C$_2$H$_2$和C$_4$H$_2$，达到了需要多达104个量子比特的表示。除能量外，跃迁偶极计算表明，即使低能特征值看似收敛，红外强度和激发态组成仍会通过非简谐混合和强度再分配随基组大小继续演化。这些结果表明，基于采样的量子子空间方法可以在远超完全对角化范围的振动空间中捕获光谱信息。此外，我们的模拟确定了多态恢复和可扩展的投影空间处理是进一步扩展基于采样方法的核心挑战。
英文摘要
Predicting anharmonic vibrational spectra is a complex computational task, which becomes quickly infeasible as molecular size and the number of vibrational basis functions increase, leading to an exponential growth of the underlying Hilbert space. Here, we employ a sample-based quantum diagonalization (SQD) framework to compute anharmonic vibrational energies and spectra. The approach combines quantum state preparation and sampling with configuration recovery, diagonalization of the Hamiltonian projected in a subspace of basis configurations, and calculation of transition-dipole moments to obtain both vibrational energies and infrared spectra. We investigate two approaches for sampling, namely, vib-LUCJ and vib-SqDRIFT and apply the method to study the polyyne molecules C$_2$H$_2$ and C$_4$H$_2$, reaching representations requiring up to 104 qubits. Beyond energies, transition-dipole calculations reveal that infrared intensities and excited-state composition continue to evolve with basis size through anharmonic mixing and intensity redistribution, even when low-energy eigenvalues appear converged. These results show that sample-based quantum subspace methods can capture spectroscopic information in vibrational spaces far beyond the regime of full diagonalization. Moreover, our simulation identify multi-state recovery and scalable projected-space treatment as central challenges for further scaling sample-based approaches.
Comments19 pages, 9 figures
