Estimating Phosphorescent Emission Energies in Ir<sup>III</sup> Complexes Using Large‐Scale Quantum Computing Simulations**
Bibliographic record
Abstract
transition energies in nine phosphorescent iridium complexes using the iterative qubit coupled cluster (iQCC) method to determine if quantum simulations have any advantages over classical methods. These simulations would require a gate-based quantum computer with at least 72 fully-connected logical qubits. Since such devices do not yet exist, we demonstrate the iQCC method using a purpose-built quantum simulator on classical hardware. The results are compared to a selection of common DFT functionals, ab initio methods, and empirical data. iQCC is found to match the accuracy of the best DFT functionals, but with a better correlation coefficient, demonstrating that it is better at predicting the structure-property relationship. Results indicate that the iQCC method has the required accuracy to design organometallic complexes when deployed on emerging quantum hardware and sets an industrially relevant target for demonstrating quantum advantage.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".