Latency in the control loop of adaptive optics (AO) systems can severely limit performance. Under the frozen flow hypothesis linear predictive control techniques can overcome this; however, identification and tracking of relevant turbulent parameters (such as wind speeds) is required for such parametric techniques. This can complicate practical implementations and introduce stability issues when encountering variable conditions. Here, we present a non-linear wavefront predictor using a long short-term memory (LSTM) artificial neural network (ANN) that assumes no prior knowledge of the atmosphere and thus requires no user input. The ANN is designed to predict the open-loop wavefront slope measurements of a Shack–Hartmann wavefront sensor (SH-WFS) one frame in advance to compensate for a single-frame delay in a simulated 7 × 7 single-conjugate adaptive optics system operating at 150 Hz. We describe how the training regime of the LSTM ANN affects prediction performance and show how the performance of the predictor varies under various guide star magnitudes. We show that the prediction remains stable when both wind speed and direction are varying. We then extend our approach to a more realistic two-frame latency system. AO system performance when using the LSTM predictor is enhanced for all simulated conditions with prediction errors within 19.9–40.0 nm RMS of a latency-free system operating under the same conditions compared to a bandwidth error of 78.3 ± 4.4 nm RMS.

We present the first on-sky results of a four-telescope integrated optics discrete beam combiner (DBC) tested at the 4.2 m William Herschel Telescope. The device consists of a four-input pupil remapper followed by a DBC and a 23-output reformatter. The whole device was written monolithically in a single alumino-borosilicate substrate using ultrafast laser inscription. The device was operated at astronomical H-band (1.6 µm), and a deformable mirror along with a microlens array was used to inject stellar photons into the device. We report the measured visibility amplitudes and closure phases obtained on Vega and Altair that are retrieved using the calibrated transfer matrix of the device. While the coherence function can be reconstructed, the on-sky results show significant dispersion from the expected values. Based on the analysis of comparable simulations, we find that such dispersion is largely caused by the limited signal-to-noise ratio of our observations. This constitutes a first step toward an improved validation of the DBC as a possible beam combination scheme for long-baseline interferometry.

Dedicated tip-tilt loops are commonly implemented on adaptive optics (AO) systems. In addition, a number of recent high-performance systems feature tip-tilt controllers which are more efficient than the integral action controller. In this context, Linear Quadratic Gaussian (LQG) tip-tilt regulators based on stochastic models identified from AO telemetry have demonstrated their capacity to effectively compensate for the cumulated effects of atmospheric disturbance, windshake and vibrations. These tip-tilt LQG regulators can also be periodically re-tuned during AO operations, thus allowing to track changes in the disturbances’ temporal dynamics. This paper investigates the potential benefit of extending the number of low-order modes to be controlled using models identified from AO telemetry. The global stochastic dynamical model of a chosen number of turbulent low-order modes is identified through data-driven modelling from wavefront sensor measurements. The remaining higher modes are modelled using priors with autoregressive models of order 2. The loop is then globally controlled using the optimal LQG regulator build from all these models. Our control strategy allows for combining a dedicated tip-tilt loop with a deformable mirror that corrects for the remaining low-order modes and for the higher orders altogether, without resorting to mode decoupling. Performance results are obtained through evaluation of the Strehl ratio computed on H-band images from the scientific camera, or in replay mode using on-sky AO telemetry recorded in July 2019 on the CANARY instrument.

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