Progress in the measurement and reduction of thermal noise in optical coatings for gravitational-wave detectors Article Swipe

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M. Granata , A. Amato , G. Cagnoli , M. Coulon , J. Degallaix , Danièle Forest , L. Mereni , C. Michel , L. Pinard , B. Sassolas , Julien Teillon ·

YOU? · · 2019 · Open Access · · DOI: https://doi.org/10.1364/oic.2019.fa.1

Coating thermal noise is a fundamental limit for experiments involving optical and quantum transducers. We report on the latest research activity on low-noise coatings at the Laboratoire des Matériaux Avancés, from updated values for the current Ta₂O₅, Ta₂O₅-TiO₂ and SiO₂ coatings of the Advanced LIGO, Advanced Virgo and KAGRA detectors to recent results from sputtered Nb₂O₅, TiO₂-Nb₂O₅, Ta₂O₅-ZrO₂, MgF₂, AlF₃ and Si₃N₄ coatings. Some alternative options, like amorphous-silicon and AlGaAs crystalline coatings among others, are also briefly discussed.

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LIGO Detector Materials science Coating Optoelectronics Noise (video) Optical coating Silicon Amorphous solid Thermal Optics Nanotechnology Physics Computer science Artificial intelligence Image (mathematics) Meteorology Organic chemistry Chemistry

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Type: article
Language: en
Landing Page: https://doi.org/10.1364/oic.2019.fa.1
PDF: https://opg.optica.org/viewmedia.cfm?uri=OIC-2019-FA.1&seq=0
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Cited By: 3
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DOI: https://doi.org/10.1364/oic.2019.fa.1

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Title: Progress in the measurement and reduction of thermal noise in optical coatings for gravitational-wave detectors

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Language: en

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Publication year: 2019

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Authors: M. Granata, A. Amato, G. Cagnoli, M. Coulon, J. Degallaix, Danièle Forest, L. Mereni, C. Michel, L. Pinard, B. Sassolas, Julien Teillon

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Landing page: https://doi.org/10.1364/oic.2019.fa.1

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Concepts: LIGO, Detector, Materials science, Coating, Optoelectronics, Noise (video), Optical coating, Silicon, Amorphous solid, Thermal, Optics, Nanotechnology, Physics, Computer science, Artificial intelligence, Image (mathematics), Meteorology, Organic chemistry, Chemistry

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Cited by: 3

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citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	False