Ground-based gravitational-wave (GW) detectors, such as LIGO, Virgo, and KAGRA, are among the most precise instruments ever built. Since the first detection in 2015, they have opened a new window on the Universe through the direct observation of GWs. Continued efforts focus on improving their sensitivity, which requires identifying and suppressing numerous noise sources. Stray light is one such source, as it can spoil control loops and manifest as excess strain noise in the low- and min-frequency band. This thesis investigates stray light arising from particulate contamination. Even in the clean environments of the interferometers, dust can deposit on surfaces and become a source of scattered light. To quantify this effect, I present a systematic dust-monitoring campaign carried out in Virgo, combining automated imaging procedures with particle recognition on exposed witness samples. From these measurements, I derive quantitative estimates of dust-induced stray light and assess its impact. Furthermore, I compare dust-scattering measurements with numerical models and characterize the optical and surface properties of candidate materials for the next-generation Einstein Telescope (ET), including beam-pipe steel and baffle coatings. I also establish cleanliness requirements for the ET arms by linking constraints on scattered light to limits on dust contamination of the optical baffles. In addition, I develop a theoretical model for strain noise induced by dust particles crossing the beam when falling within the interferometer arms, and numerically evaluate its amplitude under different cleanliness conditions. Together, these studies provide an extensive assessment of dust-induced stray light in GW detectors, quantifying the impact of dust contamination in Virgo, characterizing the optical properties of candidate materials, and establishing cleanliness requirements for the construction and operation of the Einstein Telescope.
Stray Light from Particle Contamination in the Virgo and Einstein Telescope Gravitational Waves Detectors
MOSCATELLO, ANDREA
2026
Abstract
Ground-based gravitational-wave (GW) detectors, such as LIGO, Virgo, and KAGRA, are among the most precise instruments ever built. Since the first detection in 2015, they have opened a new window on the Universe through the direct observation of GWs. Continued efforts focus on improving their sensitivity, which requires identifying and suppressing numerous noise sources. Stray light is one such source, as it can spoil control loops and manifest as excess strain noise in the low- and min-frequency band. This thesis investigates stray light arising from particulate contamination. Even in the clean environments of the interferometers, dust can deposit on surfaces and become a source of scattered light. To quantify this effect, I present a systematic dust-monitoring campaign carried out in Virgo, combining automated imaging procedures with particle recognition on exposed witness samples. From these measurements, I derive quantitative estimates of dust-induced stray light and assess its impact. Furthermore, I compare dust-scattering measurements with numerical models and characterize the optical and surface properties of candidate materials for the next-generation Einstein Telescope (ET), including beam-pipe steel and baffle coatings. I also establish cleanliness requirements for the ET arms by linking constraints on scattered light to limits on dust contamination of the optical baffles. In addition, I develop a theoretical model for strain noise induced by dust particles crossing the beam when falling within the interferometer arms, and numerically evaluate its amplitude under different cleanliness conditions. Together, these studies provide an extensive assessment of dust-induced stray light in GW detectors, quantifying the impact of dust contamination in Virgo, characterizing the optical properties of candidate materials, and establishing cleanliness requirements for the construction and operation of the Einstein Telescope.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/358094
URN:NBN:IT:UNIPD-358094