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Register a new userAnisoCADO: a python package for analytically generating adaptive optics point spread functions for the Extremely Large Telescope
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Kieran Leschinski
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AnisoCADO is a Python package for generating images of the point spread function (PSF) for the european extremely large telescope (ELT). The code allows the user to set many of the most important atmospheric and observational parameters that influence the shape and strehl ratio of the resulting PSF, including but not limited to: the atmospheric turbulence profile, the guide star position for a single conjugate adaptive optics (SCAO) solution, differential telescope pupil transmission, etc. Documentation can be found at https://anisocado.readthedocs.io/en/latest/
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An explanation for the origin of asymmetry along the preferential axis of the PSF of an AO system is developed. When phase errors from high altitude turbulence scintillate due to Fresnel propagation, wavefront amplitude errors may be spatially offset from residual phase errors. These correlated errors appear as asymmetry in the image plane under the Fraunhofer condition. In an analytic model with an open-loop AO system, the strength of the asymmetry is calculated for a single mode of phase aberration, which generalizes to two dimensions under a Fourier decomposition of the complex illumination. Other parameters included are the spatial offset of the AO correction, which is the wind velocity in the frozen flow regime multiplied by the effective AO time delay, and propagation distance or altitude of the turbulent layer. In this model, the asymmetry is strongest when the wind is slow and nearest to the coronagraphic mask when the turbulent layer is far away, such as when the telescope is pointing low towards the horizon. A great emphasis is made about the fact that the brighter asymmetric lobe of the PSF points in the opposite direction as the wind, which is consistent analytically with the clarification that the image plane electric field distribution is actually the inverse Fourier transform of the aperture plane. Validation of this understanding is made with observations taken from the Gemini Planet Imager, as well as being reproducible in end-to-end AO simulations.
The performance of a wide-field adaptive optics system depends on input design parameters. Here we investigate the performance of a multi-conjugate adaptive optics system design for the European Extremely Large Telescope, using an end-to-end Monte-Carlo adaptive optics simulation tool, DASP. We consider parameters such as the number of laser guide stars, sodium layer depth, wavefront sensor pixel scale, number of deformable mirrors, mirror conjugation and actuator pitch. We provide potential areas where costs savings can be made, and investigate trade-offs between performance and cost. We conclude that a 6 laser guide star system using 3 DMs seems to be a sweet spot for performance and cost compromise.
The performance of a wide-field adaptive optics system depends on input design parameters. Here we investigate the performance of a multi-object adaptive optics system design for the European Extremely Large Telescope, using an end-to-end Monte-Carlo adaptive optics simulation tool, DASP, with relevance for proposed instruments such as MOSAIC. We consider parameters such as the number of laser guide stars, sodium layer depth, wavefront sensor pixel scale, actuator pitch and natural guide star availability. We provide potential areas where costs savings can be made, and investigate trade-offs between performance and cost, and provide solutions that would enable such an instrument to be built with currently available technology. Our key recommendations include a trade-off for laser guide star wavefront sensor pixel scale of about 0.7 arcseconds per pixel, and a field of view of at least 7 arcseconds, that EMCCD technology should be used for natural guide star wavefront sensors even if reduced frame rate is necessary, and that sky coverage can be improved by a slight reduction in natural guide star sub-aperture count without significantly affecting tomographic performance. We find that adaptive optics correction can be maintained across a wide field of view, up to 7 arcminutes in diameter. We also recommend the use of at least 4 laser guide stars, and include ground-layer and multi-object adaptive optics performance estimates.
A multi-object spectrograph on the forthcoming European Extremely Large Telescope will be required to operate with good sky coverage. Many of the interesting deep cosmological fields were deliberately chosen to be free of bright foreground stars, and therefore are potentially challenging for adaptive optics (AO) systems. Here we investigate multi-object AO performance using sub-fields chosen at random from within the Great Observatories Origins Deep Survey (GOODS)-S field, which is the worst case scenario for five deep fields used extensively in studies of high-redshift galaxies. Our AO system model is based on that of the proposed MOSAIC instrument but our findings are equally applicable to plans for multi-object spectroscopy on any of the planned Extremely Large Telescopes. Potential guide stars within these sub-fields are identified and used for simulations of AO correction. We achieve ensquared energies within 75~mas of between 25-35% depending on the sub-field, which is sufficient to probe sub-kpc scales in high-redshift galaxies. We also investigate the effect of detector readout noise on AO system performance, and consider cases where natural guide stars are used for both high-order and tip-tilt-only AO correction. We also consider how performance scales with ensquared energy box size. In summary, the expected AO performance is sufficient for a MOSAIC-like instrument, even within deep fields characterised by a lack of bright foreground stars.
Context. The knowledge of the point-spread function compensated by adaptive optics is of prime importance in several image restoration techniques such as deconvolution and astrometric/photometric algorithms. Wavefront-related data from the adaptive optics real-time computer can be used to accurately estimate the point-spread function in adaptive optics observations. The only point-spread function reconstruction algorithm implemented on astronomical adaptive optics system makes use of particular functions, named $U_{ij}$. These $U_{ij}$ functions are derived from the mirror modes, and their number is proportional to the square number of these mirror modes. Aims. We present here two new algorithms for point-spread function reconstruction that aim at suppressing the use of these $U_{ij}$ functions to avoid the storage of a large amount of data and to shorten the computation time of this PSF reconstruction. Methods. Both algorithms take advantage of the eigen decomposition of the residual parallel phase covariance matrix. In the first algorithm, the use of a basis in which the latter matrix is diagonal reduces the number of $U_{ij}$ functions to the number of mirror modes. In the second algorithm, this eigen decomposition is used to compute phase screens that follow the same statistics as the residual parallel phase covariance matrix, and thus suppress the need for these $U_{ij}$ functions. Results. Our algorithms dramatically reduce the number of $U_{ij}$ functions to be computed for the point-spread function reconstruction. Adaptive optics simulations show the good accuracy of both algorithms to reconstruct the point-spread function.
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