Dynamic response of ferrofluidic deformable mirrors
Bibliographic record
Abstract
Ferrofluids can be used to make deformable mirrors having highly interesting characteristics (e.g., extremely large strokes and low costs). Until recently, such mirrors were thought to be restricted to corrections of frequencies lower than 10 Hz, thus limiting their usefulness. We present counterintuitive results that demonstrate that the limiting operational frequency can be increased by increasing the viscosity of the ferrofluid. We tested the response of ferrofluids having viscosities as high as 494 cP, finding that they could allow an adaptive optics correction frequency as high as 900 Hz. We also demonstrate that we can counter the amplitude loss due to the high viscosity by overdriving the actuators. The overdriving technique combines high current, short duration pulses with ordinary driving step functions to deform the mirror. The integration of a FDM in a complete closed-loop adaptive optics system running at about 500 Hz thus appears to be a realistic goal in the near future.
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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 | 0.001 |
| 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) | 0.002 | 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".