arXiv subjects

Jim Warner

Publications and source records attributed to Jim Warner.

4 recordsLinked to original sources

arXiv2025

GEMINI: The First Underground Testbed for Seismic Isolation and Interplatform Control in Next-Generation Gravitational-Wave Detectors

GEMINI is an underground research and development facility dedicated to advancing seismic isolation and control technologies for future gravitational-wave observatories, including the Einstein Telescope (ET) and the Lunar Gravitational-Wave Antenna (LGWA). This paper presents the technical design and theoretical framework of GEMINI's active seismic isolation platforms, including detailed noise budget analyses, performance predictions, and residual platform motion evaluations. The GEMINI platforms are designed to achieve unprecedented vibration isolation, targeting motion suppression across the 10 mHz to 10 Hz frequency band, and with the goal to make them the quietest platforms of their kind. In the context of ET, GEMINI will enable the development and validation of inter-platform control strategies essential for the stabilization of auxiliary degrees of freedom of its interferometers. GEMINI will also support the testing of cryogenic payloads and ultra-sensitive inertial sensors required for LGWA. By integrating advanced cryogenic systems, precision inertial sensors, and state-of-the-art vibration isolation technologies, GEMINI will serve as a versatile testbed for next-generation ground-based gravitational-wave detectors and lunar seismometry missions.

physics.ins-det↗

arXiv2020

Particle swarming of sensor correction filters

Reducing the impact of seismic activity on the motion of suspended optics is essential for the operation of ground-based gravitational wave detectors. During periods of increased seismic activity, low-frequency ground translation and tilt cause the Advanced LIGO observatories to lose `lock', reducing their duty cycles. This paper applies modern global-optimisation algorithms to aid in the design of the `sensor correction' filter, used in the control of the active platforms. It is shown that a particle swarm algorithm that minimises a cost-function approximating the differential RMS velocity between platforms can produce control filters that perform better across most frequencies in the control bandwidth than those currently installed. These tests were conducted using training data from the LIGO Hanford Observatory seismic instruments and simulations of the HAM-ISI (Horizontal Access Module Internal Seismic Isolation) platforms. These results show that new methods of producing control filters are ready for use at LIGO. The filters were implemented at LIGO's Hanford Observatory, and use the resulting data to refine the cost function.

astro-ph.IM↗

arXiv2020

Towards windproofing LIGO: Reducing the effect of wind-driven floor tilt by using rotation sensors in active seismic isolation

Modern gravitational-wave observatories require robust low-frequency active seismic isolation in order to keep the interferometer at its ideal operating conditions. Seismometers are used to measure both the motion of the ground and isolated platform. These devices are susceptible to contamination from ground tilt at frequencies below 0.1 Hz, particularly arising from wind-pressure acting on building walls. Consequently, during LIGO's first observing run both observatories suffered significant downtime when wind-speeds were above 7 m/s. We describe the use of ground rotation sensors at the LIGO Hanford Observatory to correct nearby ground seismometers to produce tilt-free ground translation signals. The use of these signals for sensor correction control improved low-frequency seismic isolation and allowed the observatory to operate under wind speeds as high as $15-20$ m/s.

physics.ins-det↗

arXiv2019

Ground motion prediction at gravitational wave observatories using archival seismic data

Gravitational wave observatories have always been affected by tele-seismic earthquakes leading to a decrease in duty cycle and coincident observation time. In this analysis, we leverage the power of machine learning algorithms and archival seismic data to predict the ground motion and the state of the gravitational wave interferometer during the event of an earthquake. We demonstrate improvement from a factor of 5 to a factor of 2.5 in scatter of the error in the predicted ground velocity over a previous model fitting based approach. The level of accuracy achieved with this scheme makes it possible to switch control configuration during periods of excessive ground motion thus preventing the interferometer from losing lock. To further assess the accuracy and utility of our approach, we use IRIS seismic network data and obtain similar levels of agreement between the estimates and the measured amplitudes. The performance indicates that such an archival or prediction scheme can be extended beyond the realm of gravitational wave detector sites for hazard-based early warning alerts.

astro-ph.IM↗