Multicone Diamond Waveguides for Nanoscale Quantum Sensing
Bibliographic record
Abstract
The long-lived electronic spin of the nitrogen-vacancy (NV) center in diamonds is a promising quantum sensor for detecting nanoscopic magnetic and electric fields in various environments. However, the poor signal-to-noise ratio (SNR) of prevalent optical spin-readout techniques presents a critical challenge in improving measurement sensitivity. Here, we address this limitation by coupling individual NVs to optimized diamond nanopillars, thereby enhancing the collection efficiency of fluorescence. Guided by near-field optical simulations, we predict improved performance for tall (≥5 μm) pillars with tapered sidewalls. This is subsequently verified by fabricating and characterizing a representative set of structures using a newly developed nanofabrication process. We observe increased SNR for optimized devices, owing to improved emission collimation and directionality. Promisingly, these devices are compatible with low-numerical-aperture collection optics and a reduced tip radius, reducing experimental overhead and facilitating improved spatial resolution for scanning 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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".