Implementation of renormalized excitonic method at <i>ab initio</i> level
Bibliographic record
Abstract
The renormalized excitonic method [Hajj et al., Phys Rev B 2005, 72, 224412], in which the excited state of the whole system may be described as a linear combination of local excitations, has been implemented at ab initio level. Its performance is tested on the ionization potential and the energy gap between singlet ground state and lowest triplet for linear molecular hydrogen chains and more realistic systems, such as polyenes and polysilenes, using full configuration interaction (FCI) wave functions with a minimal basis set. The influence of different block sizes and the extent of interblock interactions are investigated. It has been demonstrated that satisfactory results can be obtained if the near degeneracies between the model space and the outer space are avoided and if interactions between the next-nearest neighbor blocks are considered. The method can be used with larger basis sets and other accurate enough ab initio evaluations (instead of FCI) of local excited states, from blocks, or from dimers or trimers of blocks. It provides a new possibility to accurately and economically describe the low-lying delocalized excited states of large systems, even inhomogeneous ones.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".