We develop and evaluate a new approach to phase estimation for observational astronomy that can be used for accurate point spread function reconstruction. Phase estimation is required where a terrestrial observatory uses an adaptive optics (AO) system to assist astronomers in acquiring sharp, high-contrast images of faint and distant objects. Our approach is to train a conditional adversarial artificial neural network architecture to predict phase using the wavefront sensor data from a closed-loop AO system. We present a detailed simulation study under different turbulent conditions, using the retrieved residual phase to obtain the point spread function of the simulated instrument. Compared to the state-of-the-art model-based approach in astronomy, our approach is not explicitly limited by modeling assumptions, e.g., independence between terms, such as bandwidth and anisoplanatism—and is conceptually simple and flexible. We use the open-source COMPASS tool for end-to-end simulations. On key quality metrics, specifically the Strehl ratio and Halo distribution in our application domain, our approach achieves results better than the model-based baseline.
Real-time segment phasing is non-trivial in giant segmented mirror telescopes, as slope-based wavefront sensing methods are blind to segment piston if the gaps between segments are sufficiently large. In the GMT, this is certainly the case, and many solutions have been proposed which require additional wavefront sensing hardware and added optomechanical complexity. We propose a novel sequential phase-diversity method which requires only a time-sequence of closed-loop tip-tilt wavefront sensor images.
It is common practice in adaptive optics to use CCD detectors with global shutter readout for wavefront sensing. sCMOS detectors with rolling shutter readout are often not considered due to image distortion when the object is moving at high speed. However, sCMOS detectors have the potential to achieve lower readout noise, larger format, and lower cost. Therefore, we investigate the effect of rolling shutter readout in the context of the laser guide star wavefront sensors of ULTIMATE-Subaru, a Ground Layer Adaptive Optics project at the Subaru telescope. In the case of a laser guide star wavefront sensor, the wavefront tip-tilt component is filtered out in the measurement due to the tip-tilt indetermination effect. With the rolling shutter readout, the tip-tilt component can alias onto the higher-order wavefront components, it becomes a problem for the wavefront measurement. Firstly, we identify the particular modes that are aliased onto, as well as the frequency response of this aliasing. As a result, it is confirmed that when the oscillation frequency of tip-tilt is faster than about 10% of the sampling frequency of the detector, it is partially measured as higher-order components such as coma and trefoil. We also conduct a wavefront measurement experiment using the ORCA-Flash4.0 v2 sCMOS detector manufactured by Hamamatsu Photonics. The experiment with the optical system shows consistent results as the simulation. Finally, we estimate the effect of aliasing from the tip-tilt components of the atmospheric turbulence, telescope vibration, and laser guide star jitter using a end-to-end adaptive optics simulation.
The MCAO Assisted Visible Imager and Spectrograph (MAVIS) is currently in preliminary design for the ESO VLT in Chile, and is set to deliver diffraction limited science in V-band over a wide (30”x30”) field of view. In order for MAVIS to capitalise on its high angular resolution over a large science field, a sensitive astrometric calibration process will be employed. The stringent requirements on this calibration process require the development of an astrometric calibration technique which is insensitive to manufacturing errors in the calibration mask, while still able to detect a broad range of distortions present in the MAVIS optical path. We derive one such calibration method along with simulations in the MAVIS context, using the open-source MAVISIM tool with realistic errors present.
We develop and evaluate a new approach to phase estimation for observational astronomy that can be used for accurate point spread function reconstruction. Phase estimation is required where a terrestrial observatory uses an Adaptive Optics (AO) system to assist astronomers in acquiring sharp, high-contrast images of faint and distant objects. Our approach is to train a conditional adversarial artificial neural network architecture to predict phase using the wavefront sensor data from a closed-loop AO system. We present a detailed simulation study under different turbulent conditions, using the retrieved residual phase to obtain the point spread function of the simulated instrument. Compared to the state-of-the-art model-based approach in astronomy, our approach is not explicitly limited by modelling assumptions—e.g. independence between terms, such as bandwidth and anisoplanatism—and is conceptually simple and flexible. We use the open source COMPASS tool for end-to-end simulations. On key quality metrics, specifically the Strehl ratio and Halo distribution in our application domain, our approach achieves results better than the model-based baseline.
The MCAO Assisted Visible Imager and Spectrograph (MAVIS) is currently in preliminary design for the ESO VLT. The instrument will provide multi-conjugate adaptive optics correction over a wide field of 30”x30”, feeding the visible part of the spectrum (from 370 to 1000nm) to an imager and a spectrograph. The Adaptive Optics Module (AOM) of MAVIS implements two deformable mirrors, composed by more than 2000 actuators each, and includes a Laser Guide Star (LGS) and a Natural Guide Star (NGS) wavefront sensor for the tomographic reconstruction and correction of the atmospheric turbulence. Moreover, it provides other key functionalities like atmospheric dispersion compensation and field de-rotation, delivering a corrected diffraction-limited 30”x30” focal plane to three output ports: one for the imager, one for the spectrograph and one for visiting instruments. In this paper we describe the current optical configuration of the AOM, and we report the results of the analyses conducted to evaluate the expected optical performance of the system. The analyses include simulations for the manufacturing and alignment tolerances, sensitivity to mid-spatial frequency figure errors and their impact to astrometry.
MAVIS will be part of the next generation of VLT instrumentation and it will include a visible imager and a spectrograph, both fed by a common Adaptive Optics Module. The AOM consists in a MCAO system, whose challenge is to provide a 30” AO-corrected FoV in the visible domain, with good performance in a 50% sky coverage at the Galactic Pole. To reach the required performance, the current AOM scheme includes the use of up to 11 reference sources at the same time (8 LGSs + 3 NGSs) to drive more than 5000 actuators, divided into 3 deformable mirrors (one of them being UT4 secondary mirror). The system also includes some auxiliary loops, that are meant to compensate for internal instabilities (including WFSs focus signal, LGS tip-tilt signal and pupil position) so to push the stability of the main AO loop and the overall performance. Here we present the Preliminary Design of the AOM, which evolved, since the previous phase, as the result of further trade-offs and optimizations. We also introduce the main calibration strategy for the loops and sub-systems, including NCPA calibration approach. Finally, we present a summary of the main results of the performance and stability analyses performed for the current design phase, in order to show compliance to the performance requirements.
The MCAO Assisted Visible Imager and Spectrograph (MAVIS) is a new visible instrument for ESO Very Large Telescope (VLT). Its Adaptive Optics Module (AOM) must provide extreme adaptive optics correction level at low galactic latitude and high sky coverage at the galactic pole on the FoV of 30arcsec of its 4k × 4k optical imager and on its monolithic Integral Field Unit, thanks to 3 deformable mirrors (DM), 8 Laser Guide Stars (LGS), up to 3 Natural Guide Stars (NGS) and 11 Wave Front Sensors (WFS). A careful performance estimation is required to drive the design of this module and to assess the fulfillment of the system and subsystems requirements. Here we present the work done on this topic during the last year: we updated the system parameters to account for the phase B design and for more realistic conditions, and we produced a set of results from analytical and end-to-end simulations that should give a as complete as possible view on the performance of the system.
MAVIS (the MCAO Assisted Visible Imager & Spectrograph) will be driven by a high performance real-time control (RTC) system relying on cutting edge hardware and software technologies, including the hard real-time pipeline as well as the supervisory and tightly coupled telemetry sub-systems. To meet the extremely challenging requirements of a complex instrument like MAVIS, this forward looking implementation of the COSMIC platform is designed to support, end-to-end, a wide range of control schemes, from classical model-based approaches up to modern data-driven methodologies. In this paper, we will review the design and prototyping activities being led during phase B of the project.
KEYWORDS: Visible radiation, James Webb Space Telescope, Observatories, Adaptive optics, Large telescopes, Spectrographs, Spatial resolution, Hubble Space Telescope, Telescopes
A consortium of several Australian and European institutes – together with the European Southern Observatory (ESO) – has initiated the design of MAVIS, a Multi-Conjugate Adaptive Optics (MCAO) system for the ground- based 8-m Very Large Telescope (VLT). MAVIS (MCAO-assisted Visible Imager and Spectrograph) will deliver visible images and integral field spectrograph data with 2-3x better angular resolution than the Hubble Space Telescope, making it a powerful complement at visible wavelengths to future facilities like the space-based James Webb Space Telescope and the 30 to 40m-class ground-based telescopes currently under construction, which are all targeting science at near-infrared wavelengths. MAVIS successfully passed its Phase A in May 2020. We present the motivations, requirements, principal design choices, conceptual design, expected performance and an overview of the exciting science enabled by MAVIS.
The Adaptive Optics Module of MAVIS is a self-contained MCAO module, which delivers a corrected FoV to the postfocal scientific instruments, in the visible. The module aims to exploit the full potential of the ESO VLT UT4 Adaptive Optics Facility, which is composed of the high spatial frequency deformable secondary mirror and the laser guide stars launching and control systems. During the MAVIS Phase A, we evaluated, with the support of simulations and analysis at different levels, the main terms of the error budgets aiming at estimating the realistic AOM performance. After introducing the current opto-mechanical design and AO scheme of the AOM, we here present the standard wavefront error budget and the other budgets, including manufacturing, alignment of the module, thermal behavior and noncommon path aberrations, together with the contribution of the upstream telescope system.
The Learn and Apply tomographic reconstructor coupled with the pseudo open-loop control scheme shows promising results in simulation for multi-conjugate adaptive optics systems. We motivate, derive, and demonstrate the inclusion of a predictive step in the Learn and Apply tomographic reconstructor based on frozen-flow turbulence assumption. The addition of this predictive step provides an additional gain in performance, especially at larger wave-front sensor exposure periods, with no increase of online computational burden. We provide results using end-to-end numerical simulations for a multi-conjugate adaptive optics system for an 8m telescope based on the MAVIS system design.
The MCAO Assisted Visible Imager and Spectrograph (MAVIS) is a facility-grade visible MCAO instrument, currently under development for the Adaptive Optics Facility at the VLT. The adaptive optics system will feed both an imager and an integral field spectrograph, with unprecedented sky coverage of 50% at the Galactic Pole. The imager will deliver diffraction-limited image quality in the V band, cover a 30" x 30" field of view, with imaging from U to z bands. The conceptual design for the spectrograph has a selectable field-of-view of 2.5" x 3.6", or 5" x 7.2", with a spatial sampling of 25 or 50 mas respectively. It will deliver a spectral resolving power of R=5,000 to R=15,000, covering a wavelength range from 380 - 950 nm. The combined angular resolution and sensitivity of MAVIS fill a unique parameter space at optical wavelengths, that is highly complementary to that of future next-generation facilities like JWST and ELTs, optimised for infrared wavelengths. MAVIS will facilitate a broad range of science, including monitoring solar system bodies in support of space missions; resolving protoplanetary- and accretion-disk mechanisms around stars; combining radial velocities and proper motions to detect intermediate-mass black holes; characterising resolved stellar populations in galaxies beyond the local group; resolving galaxies spectrally and spatially on parsec scales out to 50 Mpc; tracing the role of star clusters across cosmic time; and characterising the first globular clusters in formation via gravitational lensing. We describe the science cases and the concept designs for the imager and spectrograph.
The Learn and Apply reconstruction scheme uses the knowledge of atmospheric turbulence to generate a tomographic reconstructor, and its performance is enhanced by the real-time identification of the atmosphere and the wind profile. In this paper we propose a turbulence profiling method that is driven by the atmospheric model. The vertical intensity distribution of turbulence, wind speed and wind direction can be simultaneously estimated from the Laser Guide Star measurements. We introduce the implementation of such a method on a GPU accelerated non-linear least-squares solver, which significantly increases the computation efficiency. Finally, we present simulation results to demonstrate the convergence quality from numerically generated telemetry, the end-to-end Adaptive Optics simulation results, and a time-to-solution analysis, all based on the MAVIS system design.
"We present initial results from the Multi-conjugate Adaptive-optics Visible Imager-Spectrograph Image Simulator (MAVISIM) to explore the astrometric capabilities of the next generation instrument MAVIS. A core scientific and operational requirement of MAVIS will be to achieve highly accurate differential astrometry, with accuracies on the order that of the extremely large telescopes. To better understand the impact of known and anticipated astrometric error terms, we have created an initial astrometric budget which we present here to motivate the creation of MAVISIM. In this first version of MAVISIM we include three major astrometric error sources; point spread function (PSF) field variability due to high order aberrations, PSF degradation and field variability due to tip-tilt residual error, and field distortions due to non-common path aberrations in the AO module. An overview of MAVISIM is provided along with initial results from a study using MAVISIM to simulate an image of a Milky Way-like globular cluster. Astrometric accuracies are extracted using PSF-fitting photometry with encouraging results that suggest MAVIS will deliver accuracies of 150µas down to faint magnitudes."
This paper presents a preliminary analysis of the first results we have obtained from the adaptive optics systems built for EOS 1.8 m telescope at Mount Stromlo. This presentation focuses on the single-camera stereo-SCIDAR for monitoring the atmospheric seeing. We briefly summarize the system, describe its on-sky performance during commissioning, compare results to numerical simulations and evaluate the remaining challenges going into the future.
Space debris in low Earth orbit (LEO) below 1500 km is becoming an increasing threat to spacecrafts. To manage the threat, we are developing systems to improve the ground-based tracking and imaging of space debris and satellites. We also intend to demonstrate that it is possible to launch a high-power laser that modifies the orbits of the debris. However, atmospheric turbulence makes it necessary to use adaptive optics with such systems. When engaging with objects in LEO, the objects are available only a limited amount of time. During the observation window, the object has to be acquired and performance of all adaptive optics feedback loops optimised. We have implemented a high-level adaptive optics supervision tool to automatise time-consuming tasks related to calibration and performance monitoring. This paper describes in detail the current features of our software.
Adaptive Optics (AO) systems rely on atmospheric turbulence models in order to reduce the effect of wave-front aberrations on image quality. Due to the nature of turbulence, these models can exploit shift-invariant structures without a severe loss in generality. The resulting subset of possible state-matrices is efficiently characterised for identification using Quadratic Programming (QP). Additionally, the initial assumption of shift-invariance is relaxed in order to accommodate for the boundary effect of finite-pupils.
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