AI 中文总结
该研究无需模型与先验归属，利用图论结合千赫兹精度腔增强光谱仪，重构水光谱的158个能级，精度较文献值高两个数量级，为多原子分子精密光谱学开辟新路径。
AI 中文摘要
将高分辨率分子光谱的谱线归属到量子态需要哈密顿模型和大量专家干预，因此较大分子的光谱会积累大量未归属谱线。本文展示了可仅利用图论直接从原始未归属的跃迁频率中重构分子能级，无需模型和先验归属。该逆图构建利用重复频率差和四周期闭合以千赫兹精度组装能级网络，所需的密集宽带光谱由腔增强光谱仪（SCALS）生成，该仪器可在数十太赫兹范围内连续扫描，兼具宽带覆盖、高灵敏度和高精度，为单一自动化设备。将其应用于1537-1605 nm范围内的水吸收光谱，在无归属的情况下获得了686个水的兰姆凹陷，该方法重构了158个能级，其精度大多比对应文献值高两个数量级。通过消除归属障碍，该方法为无需跃迁频率先验知识的多原子分子探索性精密光谱学开辟了途径。
英文摘要
Assigning the lines of high-resolution molecular spectra to quantum states requires a Hamiltonian model and substantial expert intervention, so the spectra of larger molecules accumulate vast numbers of unassigned lines. Here we show that molecular energy levels can instead be reconstructed directly from the raw, unassigned transition frequencies, using graph theory alone with no model and no prior assignment. Our inverse graph construction exploits recurring frequency differences and four-cycle closures to assemble an energy-level network at kilohertz precision. The dense, broadband spectra this requires are produced by a cavity-enhanced spectrometer (SCALS) that scans continuously across tens of terahertz at kilohertz accuracy, combining broadband coverage, high sensitivity, and high precision in a single automated instrument. Applied to the water absorption spectrum in the range of 1537--1605~nm, 686 Lamb dips of water were obtained without assignments, and the method reconstructs 158 energy levels that are mostly two orders of magnitude more precise than the corresponding literature values. By removing the assignment barrier, this approach opens a route to exploratory precision spectroscopy of polyatomic molecules without a priori knowledge of transition frequencies.
