Bibliographic record
Abstract
In this thesis we investigate nonlinear quantum effects and squeezing in cavity optomechanical systems, where light interacts with mechanical motion. In the first part of this thesis we analyze how to generate squeezed mechanical states and squeezed output light with state-of-the-art optomechanical setups via dissipation. We predict that arbitrary large steady-state bosonic squeezing can be generated. Furthermore, we show that our dissipative output light squeezing scheme can be used directly to enhance the intrinsic measurement sensitivity of an optomechanical cavity. In the second part, we explore the so-called “single-photon strong coupling regime” of optomechanics. In this regime, the nonlinear quantum nature of the optomechanical interaction becomes important. We work out the first signatures of this nonlinear quantum interaction. We also propose how to observe these signatures with near-future optomechanical experiments. In the following, we analyze how an even stronger quantum interaction between photons and phonons modifies the statistics of photons which are transmitted through an optomechanical system. In the last part of this thesis, we discuss how to verify energy quantization of a mechanical degree of freedom. We propose to make use of an optomechanical setup where the position squared of a mechanical degree of freedom is coupled to the light field. We predict that energy quantization could be observable e.g. with nanometer-sized dielectric spheres.
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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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".