T. Butterley

MOAO first on-sky demonstration with CANARY

Context. A new challenging adaptive optics (AO) system, called multi-object adaptive optics (MOAO), has been successfully demonstrated on-sky for the first time at the 4.2 m William Herschel Telescope, Canary Islands, Spain, at the end of September 2010. Aims. This system, called CANARY, is aimed at demonstrating the feasibility of MOAO in preparation of a future multi-object near infra-red (IR) integral field unit spectrograph to equip extremely large telescopes for analysing the morphology and dynamics of high-z galaxies. Methods. CANARY compensates for the atmospheric turbulence with a deformable mirror driven in open-loop and controlled through a tomographic reconstruction by three widely separated off-axis natural guide star (NGS) wavefront sensors, which are in open loop too. We compared the performance of conventional closed-loop AO, MOAO, and ground-layer adaptive optics (GLAO) by analysing both IR images and simultaneous wave-front measurements. Results. In H-band, Strehl ratios of 0.20 are measured with MOAO while achieving 0.25 with closed-loop AO in fairly similar seeing conditions (r 0 ≈ 15 cm at 0.5 μm). As expected, MOAO has performed at an intermediate level between GLAO and closed-loop AO.

Durham extremely large telescope adaptive optics simulation platform

Adaptive optics systems are essential on all large telescopes for which image quality is important. These are complex systems with many design parameters requiring optimization before good performance can be achieved. The simulation of adaptive optics systems is therefore necessary to categorize the expected performance. We describe an adaptive optics simulation platform, developed at Durham University, which can be used to simulate adaptive optics systems on the largest proposed future extremely large telescopes as well as on current systems. This platform is modular, object oriented, and has the benefit of hardware application acceleration that can be used to improve the simulation performance, essential for ensuring that the run time of a given simulation is acceptable. The simulation platform described here can be highly parallelized using parallelization techniques suited for adaptive optics simulation, while still offering the user complete control while the simulation is running. The results from the simulation of a ground layer adaptive optics system are provided as an example to demonstrate the flexibility of this simulation platform.

Stereo-SCIDAR : optical turbulence profiling with high sensitivity using a modified SCIDAR instrument.

The next generation of adaptive optics systems will require tomographic reconstruction techniques to map the optical refractive index fluctuations, generated by the atmospheric turbulence, along the line of sight to the astronomical target. These systems can be enhanced with data from an external atmospheric profiler. This is important for Extremely Large Telescope scale tomography. Here we propose a new instrument which utilizes the generalized Scintillation Detection And Ranging (SCIDAR) technique to allow high sensitivity vertical profiles of the atmospheric optical turbulence and wind velocity profile above astronomical observatories. The new approach, which we refer to as ‘stereo-SCIDAR’, uses a stereoscopic system with the scintillation pattern from each star of a double-star target incident on a separate detector. Separating the pupil images for each star has several advantages including increased magnitude difference tolerance for the target stars; negating the need for re-calibration due to the normalization errors usually associated with SCIDAR; an increase of at least a factor of 2 in the signal-to-noise ratio of the cross-covariance function and hence the profile for equal magnitude target stars and up to a factor of 16 improvement for targets of 3 mag difference and easier real-time reconstruction of the wind-velocity profile. Theoretical response functions are calculated for the instrument, and the performance is investigated using a Monte Carlo simulation. The technique is demonstrated using data recorded at the 2.5-m Nordic Optical Telescope and the 1.0-m Jacobus Kapteyn Telescope, both on La Palma.

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).

Using artificial neural networks for open-loop tomography

Modern adaptive optics (AO) systems for large telescopes require tomographic techniques to reconstruct the phase aberrations induced by the turbulent atmosphere along a line of sight to a target which is angularly separated from the guide sources that are used to sample the atmosphere. Multi-object adaptive optics (MOAO) is one such technique. Here, we present a method which uses an artificial neural network (ANN) to reconstruct the target phase given off-axis references sources. We compare our ANN method with a standard least squares type matrix multiplication method and to the learn and apply method developed for the CANARY MOAO instrument. The ANN is trained with a large range of possible turbulent layer positions and therefore does not require any input of the optical turbulence profile. It is therefore less susceptible to changing conditions than some existing methods. We also exploit the non-linear response of the ANN to make it more robust to noisy centroid measurements than other linear techniques.

Experience with wavefront sensor and deformable mirror interfaces for wide-field adaptive optics systems

Recent advances in adaptive optics (AO) have led to the implementation of wide field-of-view AO systems. A number of wide-field AO systems are also planned for the forthcoming Extremely Large Telescopes. Such systems have multiple wavefront sensors of different types, and usually multiple deformable mirrors (DMs). Here, we report on our experience integrating cameras and DMs with the real-time control systems of two wide-field AO systems. These are CANARY, which has been operating on-sky since 2010, and DRAGON, which is a laboratory AO real-time demonstrator instrument. We detail the issues and difficulties that arose, along with the solutions we developed. We also provide recommendations for consideration when developing future wide-field AO systems.

Considerations for EAGLE from Monte Carlo adaptive optics simulation

The EAGLE instrument for the European Extremely Large Telescope is a multi-object integral field unit spectrograph that uses a multi-object adaptive optics (AO) system for wavefront correction of interesting lines of sight. We present a Monte Carlo AO simulation package that has been used to model the performance of EAGLE, and provide results, including comparisons with an analytical code. These results include an investigation of the performance of compressed reconstructor representations that have the potential to significantly reduce the complexity of a real-time control system when implemented.

LOLAS: an optical turbulence profiler in the atmospheric boundary layer with extreme altitude resolution

We report the development and first results of an instrument called Low Layer SCIDAR (Scintillation Detection and Ranging) (LOLAS) which is aimed at the measurement of optical-turbulence profiles in the atmospheric boundary layer with high altitude resolution. The method is based on the Generalized SCIDAR (GS) concept, but unlike the GS instruments which need a 1-m or larger telescope, LOLAS is implemented on a dedicated 40-cm telescope, making it an independent instrument. The system is designed for widely separated double-star targets, which enables the high altitude resolution. Using a 200-arcsec-separation double star, we have obtained turbulence profiles with unprecedented 12-m resolution. The system incorporates necessary novel algorithms for autoguiding, autofocus and image stabilization. The results presented here were obtained at Mauna Kea Observatory. They show LOLAS capabilities but cannot be considered as representative of the site. A forthcoming paper will be devoted to the site characterization. The instrument was built as part of the Ground Layer Turbulence Monitoring Campaign on Mauna Kea for Gemini Observatory.

Acceleration of adaptive optics simulations using programmable logic

Numerical simulation is an essential part of the design and optimization of astronomical adaptive optics (AO) systems. Simulations of AO are computationally expensive and the problem scales rapidly with telescope aperture size, as the required spatial order of the correcting system increases. Practical realistic simulations of AO systems for extremely large telescopes are beyond the capabilities of all but the largest of modern parallel supercomputers. Here, we describe a more cost-effective approach through the use of hardware acceleration using field programmable gate arrays. By transferring key parts of the simulation into programmable logic, large increases in computational bandwidth can be expected. We show that the calculation of wavefront sensor image centroids can be accelerated by a factor of 4 by transferring the algorithm into hardware. Implementing more demanding parts of the AO simulation in hardware will lead to much greater performance improvements of up to 1000 times. Ke yw ords: instrumentation: adaptive optics ‐ methods: numerical ‐ techniques: miscellaneous ‐ telescopes ‐ instrumentation: high angular resolution.

Total eclipse of the heart: the AM CVn Gaia14aae/ASSASN-14cn

We report the discovery and characterization of a deeply eclipsing AM CVn-system, Gaia14aae (=ASSASN-14cn). Gaia14aae was identified independently by the All-Sky Automated Survey for Supernovae (ASAS-SN; Shappee et al.) and by the Gaia Science Alerts project, during two separate outbursts. A third outburst is seen in archival Pan-STARRS-1 (PS1; Schlafly et al.; Tonry et al.; Magnier et al.) and ASAS-SN data. Spectroscopy reveals a hot, hydrogen-deficient spectrum with clear double-peaked emission lines, consistent with an accreting double-degenerate classification. We use follow-up photometry to constrain the orbital parameters of the system. We find an orbital period of 49.71 min, which places Gaia14aae at the long period extremum of the outbursting AM CVn period distribution. Gaia14aae is dominated by the light from its accreting white dwarf (WD). Assuming an orbital inclination of 90° for the binary system, the contact phases of the WD lead to lower limits of 0.78 and 0.015 M⊙ on the masses of the accretor and donor, respectively, and a lower limit on the mass ratio of 0.019. Gaia14aae is only the third eclipsing AM CVn star known, and the first in which the WD is totally eclipsed. Using a helium WD model, we estimate the accretors effective temperature to be 12 900 ± 200 K. The three outburst events occurred within four months of each other, while no other outburst activity is seen in the previous 8 yr of Catalina Real-time Transient Survey (CRTS; Drake et al.), Pan-STARRS-1 and ASAS-SN data. This suggests that these events might be rebrightenings of the first outburst rather than individual events.