Investigation of the molecular mechanisms of electronic decoherence within a quinone cofactor
Bibliographic record
Abstract
The notion of decoherence is particularly adapted to discuss the quantum-to-classical transition in the context of chemical reactions. Decoherence can be modeled by computing the time evolution of nuclear wave packets evolving on distinct potential energy surfaces, here using density functional theory (DFT) and Born–Oppenheimer molecular dynamics simulations. We investigate a redox cofactor of biological interest (tryptophan tryptophylquinone, TTQ) found in the enzyme methylamine dehydrogenase. We also report the first systematic comparison of semi-empirical DFT (tight-binding DFT) and classical force field approaches for estimating decoherence in molecular systems. In the TTQ cofactor, we find that decoherence combines structural and dynamical aspects: it is initiated by the divergent motions of few atoms and then propagates dynamically to the remaining atoms. It is the mass effect of all the atoms that leads to decoherence within a few femtosecond.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".