Real-time control (RTC) is pivotal for any Adaptive Optics (AO) system, including high-contrast imaging of exoplanets and circumstellar environments. It is the brain of the AO system, and what wavefront sensing and control (WFS&C) techniques need to work with to achieve unprecedented image quality and contrast, ultimately advancing our understanding of exoplanetary systems in the context of high contrast imaging (HCI). Developing WFS&C algorithms first happens in simulation or a lab before deployment on-sky. The transition to on-sky testing is often challenging due to the different RTCs used. Sharing common RTC standards across labs and telescope instruments would considerably simplify this process. A data architecture based on the interprocess communication method known as shared memory is ideally suited for this purpose. The CACAO package, an example of RTC based on shared memory, was initially developed for the Subaru- SCExAO instrument and now deployed on several benches and instruments. This proceeding discusses the challenges, requirements, implementation strategies, and performance evaluations associated with integrating a shared memory-based RTC. The Santa Cruz Extreme AO Laboratory (SEAL) bench is a platform for WFS&C development for large groundbased segmented telescopes. Currently, SEAL offers the user a non-real-time version of CACAO, a shared-memory based RTC package initially developed for the Subaru-SCExAO instrument, and now deployed on several benches and instruments. We show here the example of the SEAL RTC upgrade as a precursor to both RTC upgrade at the 3-m Shane telescopes at Lick Observatory (Shane-AO) and a future development platform for the Keck II AO. This paper is aimed at specialists in AO, astronomers, and WFS&C scientists seeking a deeper introduction to the world of RTCs.
Exoplanet direct imaging using adaptive optics (AO) is often limited by non-common path aberrations (NCPAs) and aberrations that are invisible to traditional pupil-plane wavefront sensors (WFSs). This can be remedied by focal-plane (FP) WFSs that characterize aberrations directly from a final science image. Photonic lanterns (PLs) can act as low-order FPWFSs with the ability to direct some light to downstream science instruments. Using a PL on the SEAL (Santa Cruz Extreme AO Laboratory) high-contrast imaging testbed, we demonstrate (1) linear ranges and (2) closed-loop control. Additionally, we simulate the use of the PL in a multi-wavefront sensor AO system, in which multiple WFSs feed back to the same common-path deformable mirror. Building on previous multi-WFS AO demonstrations on SEAL, we simulate a modulated pyramid WFS to sense aberrations of high spatial order and large amplitude, and the PL to sense low order aberrations including NCPAs. We assess adaptive optics performance in this setting using three different PL wavefront reconstruction algorithms. We also provide a new method to experimentally identify the propagation matrix of a PL, making advanced model-based algorithms practical. This work demonstrates the role of photonic technologies and multi-stage wavefront sensing in the context of extreme AO and high contrast imaging.
The use of a photonic lantern as focal plane wavefront sensor has seen recent widespread interest – it can remove non-common-path aberrations, accurately sense low-wind-effect and petal modes, and provide wavelength resolution. It encodes both the PSFs phase and amplitude into the intensities of its single-mode-fibre outputs, from which the wavefront is reconstructed (by neural network or other algorithm). It also offers exciting potential as an imager to resolve structure at and beyond the telescope diffraction limit, filling in a coronagraphs IWA blind spot. This can utilise interferometric techniques, or an oversampled photonic lantern, having sufficient measurement dimensions that the amplitude, phase and spatial coherence of the science field can be entirely constrained by the output fluxes, and so the wavefront-error-induced components can be disambiguated from the source spatial structure. Other applications such as fibre nulling, optimal single-mode fibre injection, spectroastrometry, and others are also in development. Here, a brief overview of the photonic lantern sensor and these various applications will be given, along with key references.
Astrophotonics, with its potential for creating low-cost, mass-producible devices, offers a path to dramatically reduce the cost of future astronomical spectrographs. However, coupling the light from large astronomical telescopes into small, photonic chip-based instruments remains a challenge. Photonic lanterns offer a potential solution. Photonic lanterns predictably decompose the inherently multimode light from a ground-based telescope into a series of single-mode outputs, thus eliminating the need for exotic optical elements or extreme AO to achieve high efficiency. We have built a custom assembly for the AO system at Lick Observatory’s 3m Shane Telescope to test photonic lantern behavior on-sky. Here we report on multiple nights of observations over the past year using a lantern with a design wavelength of 1550 nm. Our data reveals the lantern’s basic performance over a 605–1000 nm band and its time domain response to turbulent PSFs with AO correction residuals. These measurements are important for determining the efficacy of future efforts to preferentially select or combine output modes in “real-world” scenarios across scientifically useful bandwidths.
We present the results of testing optimal linear-quadratic-Gaussian (LQG) control for tip and tilt Zernike wavefront modes on the SEAL (Santa cruz Extreme AO Lab) testbed. The controller employs a physics model conditioned by the expected tip/tilt power spectrum and vibration peaks. The model builds on similar implementations, such as that of the Gemini Planet Imager, by considering the effects of loop delays and the response of the control hardware. Tests are being performed on SEAL using the Fast Atmospheric Self-coherent camera Technique (FAST), and being executed using a custom Python library to align optics, generate interaction matrices, and perform real-time control by combining controllers with simulated disturbance signals to be corrected. We have carried out open-loop data collection, characterizing the natural bench dynamics, and have shown a reduction in RMS wavefront error due to integrator control and LQG control.
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