CO Dimer: New Potential Energy Surface and Rovibrational Calculations
Bibliographic record
Abstract
The spectrum of CO dimer was investigated by solving the rovibrational Schrödinger equation on a new potential energy surface constructed from coupled-cluster ab initio points. The Schrödinger equation was solved with a Lanczos algorithm. Several 4D (rigid monomer) global ab initio potential energy surfaces (PESs) were made using a previously reported interpolating moving least-squares (IMLS) fitting procedure specialized to describe the interaction of two linear fragments. The potential has two nonpolar minima giving rise to a complicated set of energy level stacks, which are very sensitive to the shapes and relative depths of the two wells. Although the CO dimer has defied previous attempts at an accurate purely ab initio description our best surface yields results in good agreement with experiment. Root-mean-square (rms) fitting errors of less than 0.1 cm(-1) were obtained for each of the fits using 2226 ab initio data at different levels. This allowed direct assessment of the quality of various levels of ab initio theory for prediction of spectra. Our tests indicate that standard CCSD(T) is slow to converge the interaction energy even when sextuple zeta bases as large as ACV6Z are used. The explicitly correlated CCSD(T)-F12b method was found to recover significantly more correlation energy (from singles and doubles) at the CBS limit. Correlation of the core-electrons was found to be important for this system. The best PES was obtained by extrapolation of calculations at the CCSD(T)(AE)-F12b/CVnZ-F12 (n = 3,4) levels. The calculated energy levels were compared to 105 J ≤ 10 levels from experiment. The rms error for 68 levels with J ≤ 6 is only 0.29 cm(-1). The calculated energy levels were assigned stack labels using several tools. New stacks were found. One of them, stack y1, has an energy lower than many previously known stacks and may be observable.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".