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Record W2888997864 · doi:10.1021/acsphotonics.8b01519

Swept-Frequency Drumhead Optomechanical Resonators

2019· article· en· W2888997864 on OpenAlexafffund
Raphaël St-Gelais, Simon Bernard, Christoph Reinhardt, Jack C. Sankey

Bibliographic record

VenueACS Photonics · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMechanical and Optical Resonators
Canadian institutionsMcGill UniversityUniversity of Ottawa
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for InnovationAlfred P. Sloan Foundation
KeywordsOptomechanicsResonatorFinesseAccelerationNoise (video)OpticsMechanical resonancePhysicsOptoelectronicsDisplacement (psychology)Octave (electronics)DissipationCoupling (piping)Materials scienceLaserAcousticsVibrationFabry–Pérot interferometer

Abstract

fetched live from OpenAlex

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).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.361
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.004

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.

Opus teacher head0.007
GPT teacher head0.241
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations26
Published2019
Admission routes2
Has abstractyes

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