Computing excited OH stretch states of water dimer in 12-D using contracted intermolecular and intramolecular basis functions
Bibliographic record
Abstract
Due to the ubiquity and importance of water, water dimer has been intensively studied. Computing the (ro-)vibrational spectrum of water dimer is challenging. The potential has 8 wells separated by low barriers which makes harmonic approximations of limited utility. A variational approach is imperative, but difficult because there are 12 coupled vibrational coordinate. In this paper, we use a product contracted basis, whose functions are products of intramolecular and intermolecular functions computed using an iterative eigensolver. An intermediate matrix $\bs{F}$ facilitates calculating matrix elements. Using $\bs{F}$, it is possible to do calculations on a general potential without storing the potential on the full quadrature grid. We find that surprisingly many intermolecular functions are required. This is due to the importance of coupling between inter- and intra-molecular coordinates. The full $G_{16}$ symmetry of water dimer is exploited. We calculate, for the first time, monomer excited stretch states and compare $P(1)$ transition frequencies with their experimental counterparts. We also compare with experimental vibrational shifts and tunnelling splittings. Surprisingly, we find that the the largest tunnelling splitting, which does not involve interchange of the two monomers, is smaller in the asymmetric stretch excited state than in the ground state. Differences between levels we compute and those obtained with a [6+6] adiabatic approximation [Leforestier et al. J. Chem. Phys. {\bf{137}} 014305 (2012) ] are $\sim 0.6$ cm$^{-1}$ for states without monomer excitation, $\sim 4$ cm$^{-1}$ for monomer excited bend states, and as large as $\sim 10$ cm$^{-1}$ for monomer excited stretch states.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".