NMR quantum computing: applying theoretical methods to designing enhanced systems
Bibliographic record
Abstract
Density functional theory results for chemical shifts and spin-spin coupling constants are presented for compounds currently used in NMR quantum computing experiments. Specific design criteria were examined and numerical guidelines were assessed. Using a field strength of 7.0 T, protons require a coupling constant of 4 Hz with a chemical shift separation of 0.3 ppm, whereas carbon needs a coupling constant of 25 Hz for a chemical shift difference of 10 ppm, based on the minimal coupling approximation. Using these guidelines, it was determined that 2,3-dibromothiophene is limited to only two qubits; the three qubit system bromotrifluoroethene could be expanded to five qubits and the three qubit system 2,3-dibromopropanoic acid could also be used as a six qubit system. An examination of substituent effects showed that judiciously choosing specific groups could increase the number of available qubits by removing rotational degeneracies in addition to introducing specific conformational preferences that could increase (or decrease) the magnitude of the couplings. The introduction of one site of unsaturation can lead to a marked improvement in spectroscopic properties, even increasing the number of active nuclei.
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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 | 0.002 | 0.003 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".