Visualization of electronic and vibrational polarizabilities and hyperpolarizabilities
Bibliographic record
Abstract
At the molecular level of any observed nonlinear optical behavior, one finds the polarizability and hyperpolarizability tensors. These quantities are nowadays easily calculated for small- to intermediate-sized molecules. However, to gain further insight into these properties, pictorial approaches are valuable. Here we extend the work of Chopra et al. [J. Phys. Chem., 93, 7120 (1989)] to obtain a method that may be used in order to understand how average (hyper)polarizabilities are distributed over the molecular frame. The pictures obtained represent (hyper)polarizability moments and give a description of local contributions to the total electric property. Furthermore, the formal foundations of the proposed method are developed to be used to represent both the electronic and the vibrational components of the (hyper)polarizabilities. The theory is applied to a series of push–pull polyenes. One important conclusion is the lack of any similarity between the electronic and vibrational pictorializations of either the polarizability or the first hyperpolarizability. © 2000 John Wiley & Sons, Inc. Int J Quant Chem 78: 348–377, 2000
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".