(Invited) Isolating an Individual Ion Emitter and Light-Induced Tunneling Upconversion
Bibliographic record
Abstract
This talk will review two recent discoveries made in my group. Single Photon Emitters: Intrigued by the promise of single-photon quantum technologies, many have studied the properties of single ion defect emitters, particularly lanthanides in a crystal matrix (including praseodymium, cerium, and erbium). I will report on a way of reliably isolating individual erbium ion emitters in nanocrystals with the potential for 100% individual emitter yield in post-selection. We used a nanoplasmonic (metal nanostructure) aperture optical tweezer to reliably isolate individual erbium ion emitters in individually trapped NaYF4 nanocrystals. The nanoplasmonic aperture solved two major problems: (1) it enhanced the emission rate so that single ions could be detected reliably in a short time, and (2) it isolated the single Er containing nanocrystal from the other nanocrystals in solution. This new demonstration follows our recently published work showing 400× increased emission using the nanoapertures. Light-Induced Upconversion Emission: Upconverted light from nanostructured metal surfaces can be produced by harmonic generation and multi-photon luminescence; however, these are very weak processes and require extremely high field intensities to produce a measurable signal. Here we report on bright emission, 5 orders of magnitude greater than harmonic generation, that can be seen from metal tunnel junctions due to light-induced inelastic tunneling. Like inelastic tunneling light emission, which was recently reported to have 2% conversion efficiency per tunneling event, the emission wavelength recorded varies with the local electric field applied; however, here the field is from a 1560 nm femtosecond pulsed laser source. Finite-difference time-domain simulations of the experimental conditions show the local field is sufficient to generate tunneling-based inelastic light emission in the visible regime. This phenomenon is promising for producing ultrafast upconverted light emission with higher efficiency than conventional nonlinear processes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.007 |
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".