Expanded horizons for generating and exploring optical angular momentum in vortex structures
Bibliographic record
Abstract
Spin provides for a well-known extension to the information capacity of nanometer-scale electronic devices. Spin transfer can be effected with high fidelity between quantum dots, this type of emission being primarily associated with emission dipoles. However, in seeking to extend the more common spectroscopic connection of dipole transitions with orbital angular momentum, it has been shown impossible to securely transmit information on any other multipolar basis – partly because point detectors are confined to polarization measurement. Standard polarization methods in optics provide for only two independent degrees of freedom, such as the circular states of opposing handedness associated with photon spin. Complex light beams with structured wave-fronts or vector polarization do, however, offer a basis for additional degrees of freedom, enabling individual photons to convey far more information content. A familiar example is afforded by Laguerre-Gaussian modes, whose helically twisted wave-front and vortex fields are associated with orbital angular momentum. Each individual photon in such a beam has been shown to carry the entire spatial helical-mode information, supporting an experimental basis for sorting beams of different angular momentum content. One very recent development is a scheme for such optical vortices to be directly generated through electronic relaxation processes in structured molecular chromophore arrays.
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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 | 0.003 | 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 | 0.002 | 0.006 |
| Scholarly communication | 0.003 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 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".