Diffractive optical elements 75 years on: from micro-optics to metasurfaces
Bibliographic record
Abstract
Diffractive optical elements (DOEs) are intricately designed devices with the purpose of manipulating light fields by precisely modifying their wavefronts. The concept of DOEs has its origins dating back to 1948 when D. Gabor first introduced holography. Subsequently, researchers introduced binary optical elements (BOEs), including computer-generated holograms (CGHs), as a distinct category within the realm of DOEs. This was the first revolution in optical devices. The next major breakthrough in light field manipulation occurred during the early 21st century, marked by the advent of metamaterials and metasurfaces. Metasurfaces are particularly appealing due to their ultra-thin, ultra-compact properties and their capacity to exert precise control over virtually every aspect of light fields, including amplitude, phase, polarization, wavelength/frequency, angular momentum, etc. The advancement of light field manipulation with micro/nano-structures has also enabled various applications in fields such as information acquisition, transmission, storage, processing, and display. In this review, we cover the fundamental science, cuttingedge technologies, and wide-ranging applications associated with micro/nano-scale optical devices for regulating light fields. We also delve into the prevailing challenges in the pursuit of developing viable technology for real-world applications. Furthermore, we offer insights into potential future research trends and directions within the realm of light field manipulation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".