EXPERIMENTAL GRAVITATIONAL & COSMOLOGICAL PHYSICS
THE RICHARDSON LAB
Research
The Richardson group is developing and employing new technologies aimed at overcoming fundamental limitations in gravitational-wave detection, as well as contributing to the commissioning of the current generation of U.S.-based detectors, Advanced LIGO.
Our current research focus is on overcoming the quantum sensing limit in gravitational-wave detection. Quantum fluctuations of light are the limiting source of instrumental noise across most of the frequency band accessible to ground-based detectors (100 Hz and above). We are developing new laser wavefront control technology to significantly reduce optical losses inside the detectors. This will enable detectors to achieve higher levels of stored laser power and more efficiently utilize entangled photons, or "squeezed" light, for greater quantum noise reduction. We are also conducting experimental design studies aimed at reducing the susceptibility of squeezed light to quantum decoherence inside the detector, employing an algorithmic approach to optical systems design that promises to achieve superior error tolerance.
Higher-Order Active Wavefront Control
To support higher levels of squeezing and laser power in LIGO and future facilities, we are developing a new class of adaptive optic capable of dynamically correcting higher-order optical aberrations inside gravitational-wave detectors.
The maximum operating power of Advanced LIGO is now limited by higher-order aberrations induced by small, absorptive defects in the mirror coatings ("point absorbers"). These present a major source of internal loss, and one for which the current thermal compensation system has no corrective capability. By extending active optical correction to a finer spatial scale, our work will (1) directly extend the astrophysical range of the detectors, increasing detection rates, and (2) produce higher-fidelity measurements of individual waveforms, enabling precision tests of fundamental physics. Our technology will also have broad application to other fields benefiting from ultra low-loss laser cavities, from AMO to optical quantum computing.
Optimal Detector Design for Squeezed Light
To achieve greater quantum noise reduction with squeezed light, we are developing optical models embedded within machine learning simulations aimed at identifying maximally error-tolerant gravitational-wave detector designs.
Future detectors, from LIGO A+ to third-generation facilities, will rely on greater levels of squeezed-light enhancement, with an ultimate goal of 10 dB of quantum noise reduction. Even as squeezing technology matures, the internal losses of the LIGO detectors themselves remain too large to support such high levels of squeezing. Our approach targets the largest source of internal loss, mode-mismatch between the coupled laser cavities, which arises from limitations in the manufacturing and positioning of the optics. Preliminary results suggest that by minimizing sensitivity to the most common fabrication and installation errors, an optimally error-tolerant design can achieve considerably greater quantum noise reduction, for the same level of injected squeezing.
Image credit: LIGO/Caltech/MIT
Origins of Nonlinear Noise
In addition to the main strain channel, where gravitational waves are observed, each LIGO detector has over 10,000 channels which monitor the operation of different subsystems as well as the seismic, acoustic, and electromagnetic environment. This treasure trove of data presents a unique and largely untapped opportunity: How can we best leverage these vast amounts of data to improve our understanding of noise processes in LIGO, and ultimately improve our ability to detect gravitational waves?
In collaboration with Prof. Vagelis Papalexakis of the Department of Computer Science & Engineering, we are developing novel, largely unsupervised, machine learning and data science techniques to model and analyze the vast amounts of data recorded in the LIGO detectors. Our goal is to identify major contributing sources of nonlinear noise and gain insight into the physical nature of their couplings, leading to actionable information to guide the detector commissioning and directly improve the science data.