Ultrafast ultrasound imaging by optical polymer microring resonator array and a dual optical frequency comb: a theoretical concept
Bibliographic record
Abstract
Ultrasound imaging is typically based on the use of arrays of piezoelectric transducers that can both emit and receive ultrasound. It has recently been shown that on-chip optical microresonator transducers can achieve massive improvements in minimizing footprint and increasing both ultrasound sensitivity and bandwidth; however, the construction of practical arrays remains an open problem. We study the feasibility of making an array of optical microresonators for ultrafast imaging. As a proof of concept, we propose the design of a linear array of polymer microring resonators with equally spaced resonance frequencies. Optical dual-comb setup simultaneously interrogates the whole array’s ultrasound perturbation by assigning each microring to a single comb tooth. Using an optical frequency comb for detection provides an efficient way of sampling a large array of transducers while using only a single balanced heterodyne detection scheme per branch.
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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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".