Characterization of Disturbances in Systems of Coupled Micro-Resonator Arrays
Bibliographic record
Abstract
This paper describes a method for processing signals from an array of coupled resonators to detect perturbations due to external stimuli. This method is based on simultaneous monitoring of the relative changes in all eigenvalues of the characteristic equation and processing this information to quantify the amount of perturbations and to determine the resonators whose properties have changed. Since the method is based on the relative movements of eigenvalues, the variations in the absolute values of the eigenfrequencies do not strongly affect its accuracy. It will be shown that this technique is capable of detecting perturbations even if direct signals from some of the coupled resonators are not available. The role of coupling strength on the sensitivity of the system is also discussed. It is shown that it is possible to increase the sensitivity of the sensor system to perturbations by a large factor through proper selection of the coupling coefficient between the resonators. The proposed model is experimentally verified using an array of coupled micro-cantilever resonators fabricated in a standard micro-fabrication process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".