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Record W4394623595 · doi:10.1088/1361-6382/ad3c8c

Optical properties of germania and titania at 1064 nm and at 1550 nm

2024· article· en· W4394623595 on OpenAlexafffund
D Diksha, A. Amato, V. Spagnuolo, G. I. McGhee, M. Chicoine, Caspar Clark, Stephen Hill, J. Hough, G. R. Johns, R. Keil, N Mavridi, S. Reid, Sheila Rowan, T Schapals, F. Schiettekatte, S. C. Tait, I. W. Martin, J. Steinlechner

Bibliographic record

VenueClassical and Quantum Gravity · 2024
Typearticle
Languageen
FieldEngineering
TopicChalcogenide Semiconductor Thin Films
Canadian institutionsUniversité de Montréal
FundersFonds de recherche du Québec – Nature et technologiesInterreg Vlaanderen-NederlandInterregScience and Technology Facilities CouncilNatural Sciences and Engineering Research Council of CanadaVlaamse regeringNederlandse Organisatie voor Wetenschappelijk OnderzoekUniversity of GlasgowScottish Universities Physics AllianceCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaRoyal Society
KeywordsPhysicsOptics

Abstract

fetched live from OpenAlex

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, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mrow> <mml:msub> <mml:mi>Ta</mml:mi> <mml:mn>2</mml:mn> </mml:msub> <mml:msub> <mml:mi mathvariant="normal">O</mml:mi> <mml:mn>5</mml:mn> </mml:msub> </mml:mrow> </mml:mrow> </mml:math> mixed with <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mrow> <mml:msub> <mml:mi>TiO</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:mrow> </mml:math> . For upgrades to room-temperature detectors, a mixture of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mrow> <mml:msub> <mml:mi>GeO</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:mrow> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mrow> <mml:msub> <mml:mi>TiO</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:mrow> </mml:math> is an interesting alternative candidate coating material. While the rather low refractive index of GeO 2 increases with increasing <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mrow> <mml:msub> <mml:mi>TiO</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:mrow> </mml:math> content, a higher <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mrow> <mml:msub> <mml:mi>TiO</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:mrow> </mml:math> 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 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mrow> <mml:msub> <mml:mi>TiO</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:mrow> </mml:math> content is beneficial as the TiO 2 suppresses the low-temperature mechanical loss peak of GeO 2 . In this paper, we present the optical properties of coatings—produced by plasma-assisted ion-beam evaporation—with high TiO 2 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 GeO 2 was also measured. Furthermore, results at the currently-used wavelength of 1064 nm are presented.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.426
Threshold uncertainty score0.578

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)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.207
Teacher spread0.188 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations4
Published2024
Admission routes2
Has abstractyes

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