Swept-Frequency Drumhead Optomechanical Resonators
Bibliographic record
Abstract
We demonstrate a high-Q (>5 × 106) swept-frequency membrane mechanical resonator achieving resonance tuning over more than one octave via a simple integrated electrical heater. Throughout this tuning range, the membrane displacement noise remains dominated by fundamental thermo-mechanical fluctuations. Such high Q-factor and low displacement noise make the device especially promising for acceleration sensing. The inferred acceleration noise floor of the device is below 1 μg Hz–1/2, an unprecedented level of performances for acceleration sensors operating at frequencies above 50 kHz. The device can also be mechanically stabilized (or driven) via bolometric optomechanics, and we demonstrate laser cooling from room temperature to 10 K using a low finesse optical cavity. This method of frequency tuning is also well-suited to fundamental studies of mechanical dissipation; in particular, we recover the dissipation spectra of many modes, identifying material damping, and coupling to substrate resonances as the dominant loss mechanisms. The device is compatible with established batch fabrication techniques, and its optical readout is compatible with low-coherence light sources (e.g., a monochromatic light-emitting diode).
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".