Deformable mirrors based on magnetic liquids
Bibliographic record
Abstract
The trend towards ever larger telescopes and more advanced adaptive optics systems such as multi-conjugate adaptive optics is driving the need for deformable mirrors with a large number of low cost actuators. Other applications require strokes larger than those readily available from conventional mirrors. Magnetically deformable liquid mirrors are a potential solution to both these problems. Depositing a thin silver colloid known as a metal liquid-like film (MELLF) on the ferrofluid surface solves the problem of low reflectivity of pure ferrofluids. This combination provides a liquid optical surface that can be precisely shaped in a magnetic field. We have demonstrated a reflective coating that is stable for more than 30 days with a reflectivity of 50% in the near infrared. Additional experiments indicate that MELLF coatings can provide near infrared reflectivity values in excess of 80%. We also report on recent response time measurements of liquid deformable mirrors. We have demonstrated liquid mirror actuators with slew rates of 800 μm/s, corresponding to an actuator bandwidth of approximately 40 Hz and 80 Hz for strokes of 10 μm and 5 μm respectively.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".