Towards Sub-Diffraction Mapping of NV Center Positions via Electrostatic Raster Scanning
Bibliographic record
Abstract
We present a theoretical method for the nanometric position mapping of single nitrogen-vacancy (NV) centers in diamond using electric-field-induced Stark shifts. A tunable saddle point in the electric field is generated by four symmetrically arranged electrodes and scanned across a defined area. As the saddle point moves, local field variations produce measurable shifts in the NV center's optically detected magnetic resonance (ODMR) spectrum. An analytical model was developed to calculate the voltage configurations needed to position the saddle point with nanometer scale precision. The spin Hamiltonian of the NV center is used to simulate its response under realistic field conditions. Results showed a linear relation between electric field amplitude and resonance frequency shift, with approximately 200 Hz per$15 ~\mathrm{V} / \text{cm}$. These shifts are well within ODMR detection limits, and prior experiments confirm detectability down to 14 V/cm. This method enables sub-10 nanometer localization without optical imaging, offering a scalable solution for integrating NV centers into quantum devices.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".