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Suspended optics in gravitational wave (GW) observatories are susceptible to alignment perturbations, particularly slow drifts over time, due to variations in temperature and seismic levels. Such misalignments affect the coupling of the…
We describe an optical simulation program that models a complete, coupled-cavity interferometer like those used by the Laser Interferometer Gravitational-Wave Observatory (LIGO) Project. A wide variety of interferometer deformations can be…
The detection of gravitational waves has inaugurated the era of gravitational astronomy and opened new avenues for the multimessenger study of cosmic sources. Thanks to their sensitivity, the Advanced LIGO and Advanced Virgo interferometers…
Estimating the state of a dynamical system from a series of noise-corrupted observations is fundamental in many areas of science and engineering. The most well-known method, the Kalman smoother (and the related Kalman filter), relies on…
The goal of the Laser Interferometric Gravitational-Wave Observatory (LIGO) is to detect and study gravitational waves of astrophysical origin. Direct detection of gravitational waves holds the promise of testing general relativity in the…
This paper considers the problem of controlling a dynamical system when the state cannot be directly measured and the control performance metrics are unknown or partially known. In particular, we focus on the design of data-driven…
In the last decade, the Laser Interferometer Gravitational-Wave Observatory (LIGO) and the European Virgo observatory have opened a new observational window on the universe. These cavity-enhanced laser interferometers sense spacetime…
Using a network of seismometers and sets of optimal filters, we implemented a feed-forward control technique to minimize the seismic contribution to multiple interferometric degrees of freedom of the LIGO interferometers. The filters are…
This work presents a scalable control framework based on nonlinear Model Predictive Control for high-dimensional dynamical systems. The proposed approach addresses the key challenges of model scalability and partial observability by…
The unprecedented sensitivity of the Laser Interferometer Gravitational-Wave Observatory, which enables the detection of distant astrophysical sources, also renders the detectors highly susceptible to low-frequency ground motion. Persistent…
This paper proposes a Koopman-based framework for modeling, prediction, and control of unknown nonlinear time-varying systems. We present a novel Koopman-based learning method for predicting the state of unknown nonlinear time-varying…
Machine learning has become an effective tool for processing the extensive data sets produced by large physics experiments. Gravitational-wave detectors are now listening to the universe with quantum-enhanced sensitivity, accomplished with…
This article provides an overview of the current state of machine learning in gravitational-wave research with interferometric detectors. Such applications are often still in their early days, but have reached sufficient popularity to…
With the advent of gravitational-wave astronomy and the discovery of more compact binary coalescences, data quality improvement techniques are desired to handle the complex and overwhelming noise in gravitational wave (GW) observational…
Long-horizon dynamical prediction is fundamental in robotics and control, underpinning canonical methods like model predictive control. Yet, many systems and disturbance phenomena are difficult to model due to effects like nonlinearity,…
The operation of an interferometer for gravitational waves detection requires sophisticated feedback controls in many parts of the apparatus. The aim of this lecture is to introduce the types of problems to be faced in this line of…
Based on the prior O1-O2 observing runs, about 30% of the data collected by Advanced LIGO and Virgo in the next observing runs are expected to be single-interferometer data, i.e., they will be collected at times when only one detector in…
In this paper, we propose a non-parametric method for state estimation of high-dimensional nonlinear stochastic dynamical systems, which evolve according to gradient flows with isotropic diffusion. We combine diffusion maps, a manifold…
As we aim to control complex systems, use of a simulator in model-based reinforcement learning is becoming more common. However, it has been challenging to overcome the Reality Gap, which comes from nonlinear model bias and susceptibility…
Gravitational waves (GWs) can be distorted by intervening mass distributions while propagating, leading to frequency-dependent modulations that imprint a distinct signature on the observed waveforms. Bayesian inference for GW lensing with…