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Published January 19, 2023 | public
Journal Article

High-accuracy numerical models of Brownian thermal noise in thin mirror coatings

Abstract

Brownian coating thermal noise in detector test masses is limiting the sensitivity of current gravitational-wave detectors on Earth. Therefore, accurate numerical models can inform the ongoing effort to minimize Brownian coating thermal noise in current and future gravitational-wave detectors. Such numerical models typically require significant computational resources and time, and often involve closed-source commercial codes. In contrast, open-source codes give complete visibility and control of the simulated physics, enable direct assessment of the numerical accuracy, and support the reproducibility of results. In this article, we use the open-source SpECTRE numerical relativity code and adopt a novel discontinuous Galerkin numerical method to model Brownian coating thermal noise. We demonstrate that SpECTRE achieves significantly higher accuracy than a previous approach at a fraction of the computational cost. Furthermore, we numerically model Brownian coating thermal noise in multiple sub-wavelength crystalline coating layers for the first time. Our new numerical method has the potential to enable fast exploration of realistic mirror configurations, and hence to guide the search for optimal mirror geometries, beam shapes and coating materials for gravitational-wave detectors.

Additional Information

The authors thank Josh Smith for helpful discussions. Computations were performed with the SpECTRE [9] and deal.ii [16, 17] codes on the Minerva cluster at the Max Planck Institute for Gravitational Physics and on the Ocean cluster at Fullerton. The figures in this article were produced with dgpy [22], matplotlib [23, 24], TikZ [25] and ParaView [26]. This work was supported in part by the Sherman Fairchild Foundation, by NSF Grant Nos. PHY-1654359 and AST-1559694 at Cal State Fullerton, by NSF Grant Nos. PHY-2011961, PHY-2011968 and OAC-1931266 at Caltech and by NSF Grant Nos. PHY-1912081 and OAC-1931280 at Cornell.

Additional details

Created:
August 22, 2023
Modified:
October 24, 2023