Optical properties of germania and titania at 1064 nm and at 1550 nm
Bibliographic record
Abstract
Abstract One of the main noise sources in current gravitational-wave detectors is the thermal noise of the high-reflectivity coatings on the main interferometer optics. Coating thermal noise is dominated by the mechanical loss of the high-refractive index material within the coating stacks, Ta 2 O 5 mixed with TiO 2 . For upgrades to room-temperature detectors, a mixture of GeO 2 and TiO 2 is an interesting alternative candidate coating material. While the rather low refractive index of GeO2 increases with increasing TiO 2 content, a higher TiO 2 content results in a lower threshold temperature before heat treatment leads to crystallisation, and potentially to a degradation of optical properties. For future cryogenic detectors, on the other hand, a higher TiO 2 content is beneficial as the TiO2 suppresses the low-temperature mechanical loss peak of GeO2. In this paper, we present the optical properties of coatings—produced by plasma-assisted ion-beam evaporation—with high TiO2 content at 1550 nm, a laser wavelength considered for cryogenic gravitational-wave detectors, as a function of heat-treatment temperature. For comparison, the absorption of pure GeO2 was also measured. Furthermore, results at the currently-used wavelength of 1064 nm are presented.
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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 | 0.001 | 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) | 0.003 | 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".