Data for "Zero-field identification and control of hydrogen-related electron-nuclear spin registers in diamond"
Bibliographic record
Abstract
Spin defects in diamond serve as powerful building blocks for quantum technologies, especially for applications in quantum sensing and quantum networking. Electron-nuclear defects formed in the environment of optically active spins, such as the nitrogen-vacancy (NV) center, provide a resource for multi-qubit quantum registers. However, many of these defects have yet to be characterized, limiting their control and integration in quantum devices. Here, we apply two hybrid electron-nuclear spin control schemes to self-consistently characterize unknown spin defects at the single-spin level. We perform double electron-electron resonance at zero field (ZF-DEER) to extract hyperfine components and introduce a nuclear-electron-electron triple resonance (NEETR) protocol to control and identify the nuclear spin through the stronger electronic spin interaction. These results provide a guide to resolving the defect structures using ab initio calculations, leading to the identification of a new hydrogen-related defect structure as well as an accurate match to a previously identified nitrogen-related defect. We further apply our NEETR protocol to demonstrate initialization, unitary control, and long-lived coherence of the hydrogen nuclear spin qubit with $T_2 = 1.0(3)\,\mathrm{ms}$. Together, these characterization and control tools establish a framework to harness previously unknown electron-nuclear defects for quantum register applications.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".