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We investigate the adoption of Machine Learning techniques for piston sensing in the context of segmented primary mirror telescopes by the means of numerical simulations. Considering a Natural Guide Star Wavefront Sensor, composed by one high order modes sensor plus a second sensor dedicated to the differential piston modes, we focus on the latter and tackle the problem of providing an accurate estimation for the piston modes coefficients from a defocused image of the system PSF.
We consider as a baseline algorithm a customized version of LIFT (which is based on a Maximum Likelihood Estimation) and compare its performance with a Deep Neural Network (DNN) regression. After considering several DNN architectures, we designed a simple one and performed some degree of hyperparameter optimization on it to obtain the final DNN version.
The code we developed is written in Python and relies on the Tensorflow4 library and its numerical backend JAX3.
The Deformable Mirror Simulator (DMS) is an optical device reproducing the F/13 beam from the adaptive secondary mirror of the Very Large Telescope UT4. The system has been designed and integrated as a test tool for the calibration and functional verification of the WaveFront sensor module of the ERIS instrument (or ERIS-AO). To this purpose the DSMSim includes a high order deformable mirror and two sources to mimic the laser and natural asterisms and illuminate the WFS optics.
In this paper we report the design of the DSMSim, the integration, verification and alignment procedure with the ERIS-AO; in the end we outline a roadmap for future improvements of the system. This work is intended to be a reference for future instrumentation projects (e.g. MAVIS-AO) for the VLT.
SHARK-NIR is an instrument which provides direct imaging, coronagraphic imaging, dual band imaging and low resolution spectroscopy in Y, J and H bands, taking advantage of the outstanding performance of the Large Binocular Telescope AO systems. Binocular observations will be provided used in combination with SHARK-VIS (operating in V band) and LMIRCam of LBTI (operating from K to M bands), in a way to exploit coronagraphic simultaneous observations in three different wavelengths.
A wide variety of coronagraphic techniques have been implemented in SHARK-NIR, ranging from conventional ones such as the Gaussian Lyot, to others quite robust to misalignments such as the Shaped Pupil, to eventually techniques more demanding in term of stability during the observation, as the Four Quadrant; the latter is giving in theory and simulations outstanding contrast, and it is supported in term of stability by the SHARK-NIR internal fast tip-tilt loop and local NCPA correction, which should ensure the necessary stability allowing this technique to operate at its best.
The main science case is of course exoplanets search and characterization and young stellar systems, jets and disks characterization, although the LBT AO extreme performance, allowing to reach excellent correction even at very faint magnitudes, may open to science previously difficult to be achieved, as for example AGN and QSO morphological studies.
The institutes participating to the SHARK-NIR consortium which designed and built the instrument are Istituto Nazionale di Astro Fisica (INAF, Italy), the Max Planck Institute for Astronomy (MPIA, Heidelberg, Germany) and University of Arizona/Steward Observatory (UoA/SO, Tucson, Az, USA). We report here about the SHARK-NIR status, that should achieve first light at LBT before the end of 2022.
Demonstrating the sub-nanometer sensitivity of a pyramid WaveFrontSensor for active space telescopes
We present the error budget of an astronomical single conjugated adaptive optics system with a pyramid wavefront sensor. The chosen approach is semianalytical to take into account the full response characteristics of this kind of sensor, and, in addition to these characteristics, it includes the closed-loop dynamics and all the main error sources: fitting, temporal, measurement, and aliasing error. This error budget has been made to complement more complex numerical simulators in the system design process, to rapidly explore a huge range of system parameters and to assess the critical components. Its reliability is demonstrated with a comparison with Monte Carlo numerical simulations on a reference system, the Single Conjugated Adaptive Optics Upgrade for Large Binocular Telescope.
Initially proposed as an instrument covering also the K-band, the current design foresees a camera working from Y to H bands, exploiting in this way the synergy with other LBT instruments such as LBTI, which is actually covering wavelengths greater than L' band, and it will be soon upgraded to work also in K band. SHARK-NIR has been undergoing the conceptual design review at the end of 2015 and it has been approved to proceed to the final design phase, receiving the green light for successive construction and installation at LBT.
The current design is significantly more flexible than the previous one, having an additional intermediate pupil plane that will allow the usage of coronagraphic techniques very efficient in term of contrast and vicinity to the star, increasing the instrument coronagraphic performance. The latter is necessary to properly exploit the search of giant exo-planets, which is the main science case and the driver for the technical choices of SHARK-NIR. We also emphasize that the LBT AO SOUL upgrade will further improve the AO performance, making possible to extend the exo-planet search to target fainter than normally achieved by other 8-m class telescopes, and opening in this way to other very interesting scientific scenarios, such as the characterization of AGN and Quasars (normally too faint to be observed) and increasing considerably the sample of disks and jets to be studied.
Finally, we emphasize that SHARK-NIR will offer XAO direct imaging capability on a FoV of about 15"x15", and a simple coronagraphic spectroscopic mode offering spectral resolution ranging from few hundreds to few thousands. This article presents the current instrument design, together with the milestones for its installation at LBT.
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