Efficient partitioning technique for computing the dynamics of intramolecular processes: Radiationless transitions in pyrazine
Bibliographic record
Abstract
An efficient QP partitioning algorithm to compute the eigenvalues, eigenvectors, and the dynamics of large molecular systems of a particular type is presented. Compared to straightforward diagonalization, the algorithm displays favorable scaling (proportional to N(T)2) as a function of N(T), the size of the Hamiltonian matrix. In addition, the algorithm is trivially parallelizable, necessitating no "cross-talk" between nodes, thus enjoying the full linear speedup of parallelization. Moreover, the method requires very modest storage space, even for extremely large matrices. The method has also been enhanced through the development of a coarse-grained approximation, enabling an increase of the basis set size to unprecedented levels (10(8)-10(10) in the current application). The QP algorithm is applied to the dynamics of electronic internal conversion in a 24 vibrational-mode model of pyrazine. A performance comparison with other dynamical methods is presented, along with results for the decay dynamics of pyrazine and a discussion of resonance line shapes.
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".