A. G. Basden

Open-loop tomography with artificial neural networks on CANARY: on-sky results

We present recent results from the initial testing of an artificial neural network (ANN)-based tomographic reconstructor Complex Atmospheric Reconstructor based on Machine lEarNing (CARMEN) on CANARY, an adaptive optics demonstrator operated on the 4.2m William Herschel Telescope, La Palma. The reconstructor was compared with contemporaneous data using the Learn and Apply (L&A) tomographic reconstructor. We find that the fully optimized L&A tomographic reconstructor outperforms CARMEN by approximately 5percent in Strehl ratio or 15nm rms in wavefront error. We also present results for CANARY in Ground Layer Adaptive Optics mode to show that the reconstructors are tomographic. The results are comparable and this small deficit is attributed to limitations in the training data used to build the ANN. Laboratory bench tests show that the ANN can outperform L&A under certain conditions, e.g. if the higher layer of a model two layer atmosphere was to change in altitude by ∼300m (equivalent to a shift of approximately one tenth of a subaperture).

Comparative Study of Neural Network Frameworks for the Next Generation of Adaptive Optics Systems

Many of the next generation of adaptive optics systems on large and extremely large telescopes require tomographic techniques in order to correct for atmospheric turbulence over a large field of view. Multi-object adaptive optics is one such technique. In this paper, different implementations of a tomographic reconstructor based on a machine learning architecture named “CARMEN” are presented. Basic concepts of adaptive optics are introduced first, with a short explanation of three different control systems used on real telescopes and the sensors utilised. The operation of the reconstructor, along with the three neural network frameworks used, and the developed CUDA code are detailed. Changes to the size of the reconstructor influence the training and execution time of the neural network. The native CUDA code turns out to be the best choice for all the systems, although some of the other frameworks offer good performance under certain circumstances.

Science Case and Requirements for the MOSAIC Concept for a Multi-Object Spectrograph for the European Extremely Large Telescope

Over the past 18 months we have revisited the science requirements for a multi-object spectrograph (MOS) for the European Extremely Large Telescope (E-ELT). These efforts span the full range of E-ELT science and include input from a broad cross-section of astronomers across the ESO partner countries. In this contribution we summarise the key cases relating to studies of high-redshift galaxies, galaxy evolution, and stellar populations, with a more expansive presentation of a new case relating to detection of exoplanets in stellar clusters. A general requirement is the need for two observational modes to best exploit the large (≥40 arcmin2) patrol field of the E-ELT. The first mode (‘high multiplex’) requires integrated-light (or coarsely resolved) optical/near-IR spectroscopy of >100 objects simultaneously. The second (‘high definition’), enabled by wide-field adaptive optics, requires spatially-resolved, near-IR of >10 objects/sub-fields. Within the context of the conceptual study for an ELT-MOS called MOSAIC, we summarise the toplevel requirements from each case and introduce the next steps in the design process.

Wave-front error breakdown in laser guide star multi-object adaptive optics validated on-sky by Canary

Context. Canary is the multi-object adaptive optics (MOAO) on-sky pathfinder developed in the perspective of multi-object spectrograph on extremely large telescopes (ELTs). In 2013, Canary was operated on-sky at the William Herschel telescope (WHT), using three off-axis natural guide stars (NGS) and four off-axis Rayleigh laser guide stars (LGS), in open-loop, with the on-axis compensated turbulence observed with a H -band imaging camera and a Truth wave-front sensor (TS) for diagnostic purposes. Aims. Our purpose is to establish a reliable and accurate wave-front error breakdown for LGS MOAO. This will enable a comprehensive analysis of Canary on-sky results and provide tools for validating simulations of MOAO systems for ELTs. Methods. To evaluate the MOAO performance, we compared the Canary on-sky results running in MOAO, in single conjugated adaptive optics (SCAO) and in ground layer adaptive optics (GLAO) modes, over a large set of data acquired in 2013. We provide a statistical study of the seeing. We also evaluated the wave-front error breakdown from both analytic computations, one based on a MOAO system modelling and the other on the measurements from the Canary TS. We have focussed especially on the tomographic error and we detail its vertical error decomposition. Results. We show that Canary obtained 30.1%, 21.4% and 17.1% H -band Strehl ratios in SCAO, MOAO and GLAO respectively, for median seeing conditions with 0.66′′ of total seeing including 0.59′′ at the ground. Moreover, we get 99% of correlation over 4500 samples, for any AO modes, between two analytic computations of residual phase variance. Based on these variances, we obtain a reasonable Strehl-ratio (SR) estimation when compared to the measured IR image SR. We evaluate the gain in compensation for the altitude turbulence brought by MOAO when compared to GLAO.

First on-sky results of a neural network based tomographic reconstructor: Carmen on Canary

We present on-sky results obtained with Carmen, an artificial neural network tomographic reconstructor. It was tested during two nights in July 2013 on Canary, an AO demonstrator on the William Hershel Telescope. Carmen is trained during the day on the Canary calibration bench. This training regime ensures that Carmen is entirely flexible in terms of atmospheric turbulence profile, negating any need to re-optimise the reconstructor in changing atmospheric conditions. Carmen was run in short bursts, interlaced with an optimised Learn and Apply reconstructor. We found the performance of Carmen to be approximately 5% lower than that of Learn and Apply.

Development of an efficient photonic device for the reformatting of celestial light

The advent of 30 m class Extremely Large Telescopes will require spectrographs of unprecedented spectral resolution in order to meet ambitious science goals, such as detecting Earth-like exoplanets via the radial velocity technique. The consequent increase in the size of the spectrograph makes it challenging to ensure their optimal environmental stabilization and precise spectral calibration. The multimode optical fibers used to transport light from the telescope focal plane to the separately housed environmentally stabilized spectrograph introduces modal noise. This phenomena manifests as variations in the light pattern at the output of the fiber as the input coupling and/or fiber position changes which degrades the spectrograph line profile, reducing the instrument precision. The photonic lantern is a guided wave transition that efficiently couples a multimode point spread function into an array of single modes. If arranged in a linear array at the input of the spectrograph these single modes can in principle provide a diffraction-limited mode noise free spectra in the dispersion axis. In this paper we describe the fabrication and throughput performance of the hybrid reformatter. This device combines the proven low-loss performance of a multicore fiber-based photonic lantern with an ultrafast laser inscribed three-dimensional waveguide interconnect that performs the reformatting function to a diffraction-limited pseudo-slit. The device provided an in laboratory throughput of 65 ± 2% at 1550 ± 20 nm and an on-sky throughput of 53 ± 4% at 1530 ± 80 nm using the CANARY adaptive optics system at the William Herschel Telescope.

Final two-stage MOAO on-sky demonstration with CANARY

CANARY is an on-sky Laser Guide Star (LGS) tomographic AO demonstrator in operation at the 4.2m William Herschel Telescope (WHT) in La Palma. From the early demonstration of open-loop tomography on a single deformable mirror using natural guide stars in 2010, CANARY has been progressively upgraded each year to reach its final goal in July 2015. It is now a two-stage system that mimics the future E-ELT: a GLAO-driven woofer based on 4 laser guide stars delivers a ground-layer compensated field to a figure sensor locked tweeter DM, that achieves the final on-axis tomographic compensation. We present the overall system, the control strategy and an overview of its on-sky performance.

Tomography for Astronomical Adaptive Optics using the CANARY On-Sky Demonstrator

CANARY is an on-sky demonstrator instrument for the investigation of novel forms of tomographic Adaptive Optics (AO) which are required by the prospective European Extremely Large Telescope (E-ELT). CANARY is deployed on the 4.2m William Herschel Telescope in the Canary Islands, Spain. In its most evolved variant (Phase C2), CANARY employs four Laser Guide Star (LGS) Wavefront Sensors (WFS) and three Natural Guide Star (NGS) WFS to perform tomography on the turbulent atmospheric volume above the telescope. The projected wavefront phase error for a particular line of sight is then corrected by two Deformable Mirrors (DMs), and the resultant residual wavefront error is monitored by a further NGS WFS and an image recording camera. We outline the CANARY design, and present the most recent results obtained with a novel open/closed loop control approach designed to mimic the E-ELT.

Proposal for a field experiment of elongated Na LGS wave-front sensing in the perspective of the E-ELT

Wavefront (WF) sensing using Sodium (Na) Laser Guide Stars (LGS) is a key concern for the design of a number of first generation Extremely Large Telescope (ELT) Adaptive Optics (AO) modules. One of the main challenges is the mitigation of the effects induced by extreme LGS spot elongation on the WF measurements. Before the final design studies of the E-ELT instruments, a Na LGS WF sensing on-sky experiment at the E-ELT scale is mandatory to achieve the full validation of the proposed mitigation strategies and their performance. This experiment will provide unique spatial and temporal WF measurements on a true Na LGS, perturbed by the atmospheric turbulence and mesospheric variability. The fine comparative analysis of such data with synchronously acquired WF measurements on at least one natural guide star (NGS) will be fundamental to test a number of algorithms, configurations for spot sampling and truncation and WF reconstruction schemes including multi-LGS configurations. A global error budget for the whole experiment will be derived with time to feed into the numerical simulation and the design of subsequent E-ELT LGS-AO modules. The data produced will be made available to the E-ELT community. We propose to use CANARY, the Multi-Object AO demonstrator installed at the 4.2m WHT which is a modular AO platform, equipped with several NGS WF Sensor (WFS) and Rayleigh multi-LGS unit and WFS. The transportable 20W Sodium laser unit (WLGSU), developed at ESO, will be positioned at a varying distance from the WHT to provide off-axis launching (up to 40m), simulating the whole range of LGS spot elongations obtained on the E-ELT. In such a case, the WHT pupil will represent an off-axis sub-pupil of the main E-ELT pupil. In addition, this experiment will include a Na layer profiler and the capability for open and closed loop operations. The experiment is scheduled before the end of 2016.

First demo science with MOAO: observations of distant merging galaxies with CANARY

During phase B, CANARY, the MOAO demonstrator, has been coupled to a dedicated, high sensitivity, near-IR camera based on a science grade NICMOS detector: CAMICAz. Using this combination, we have observed two distant merging systems at H and K in July 2013, with a resolution better than 150 mas over long exposures (< 1h). In this paper, we present this unique demo science data set, detail the performance achieved in terms of resolution and sensitivity and the first scientific results. Additionally, we provide a comparative study of the scientific output of MOAO with respect to classical LGS AO and HST.