Can We Avoid the Intruder-State Problems in the State-Universal Coupled-Cluster Approaches While Preserving Size Extensivity?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Following the analysis of principal bottlenecks in the extension of the single-reference (SR) coupled-cluster (CC) methodology to the multireference (MR) case, we review and discuss some recent developments that facilitate the use of general model spaces (GMSs) within the state universal (SU) or Hilbert space MR CC formalism. The use of a GMS improves our ability to avoid the intruder state problems. This feature is further enhanced by generalizing the idea of the externally corrected (ec) SR CC formalism to the MR situations. In this latter approach we employ the cluster analysis to extract the most important higher-than-pair cluster amplitudes from a suitable set of known wave functions. Similarly to the SR case, the most convenient external source is represented by wave functions that are obtained via a modest size MR configuration interaction (CI), which employs an N -dimensional reference space. The resulting higher-than-pair cluster amplitudes are subsequently used in the SU CCSD method that is based on an M -dimensional GMS avoiding intruders. We discuss general aspects of these developments from various viewpoints and provide selective illustrations of the key concepts and ideas.
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.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it