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Capturing high resolution imagery of the Earth's surface often calls for a telescope of considerable size, even from Low Earth Orbits (LEO). A large aperture often requires large and expensive platforms. For instance, achieving a resolution of 1m at visible wavelengths from LEO typically requires an aperture diameter of at least 30cm. Additionally, ensuring high revisit times often prompts the use of multiple satellites. In light of these challenges, a small, segmented, deployable CubeSat telescope was recently proposed creating the additional need of phasing the telescope's mirrors. Phasing methods on compact platforms are constrained by the limited volume and power available, excluding solutions that rely on dedicated hardware or demand substantial computational resources. Neural Network (NN) are known for their computationally efficient inference and reduced on board requirements. Therefore we developed a NN based method to measure co phasing errors inherent to a deployable telescope. The proposed technique demonstrates its ability to detect phasing error at the targeted performance level (typically a wavefront error (WFE) below 15 nm RMS for a visible imager operating at the diffraction limit) using a point source. The robustness of the NN method is verified in presence of high order aberrations or noise and the results are compared against existing state of the art techniques. The developed NN model ensures its feasibility and provides a realistic pathway towards achieving diffraction limited images.

The amount of Adaptive Optics (AO) telemetry generated by VIS/NIR ground-based observatories is ever greater, leading to a growing need for a standardised data exchange format to support performance analysis and AO research and development activities that involve large-scale telemetry mining, processing, and curation. This paper introduces the Adaptive Optics Telemetry (AOT) data exchange format as a standard for sharing AO telemetry from visible/infrared ground-based observatories. AOT is based on the Flexible Image Transport System (FITS) and aims to provide unambiguous and consistent data access across various systems and configurations, including natural and single/multiple laser guide-star AO systems. We designed AOT focused on two key use cases: atmospheric turbulence parameter estimation and point-spread function reconstruction (PSF-R). We prototyped and tested the design using existing AO telemetry datasets from multiple systems: single conjugate with natural and laser guide stars, tomographic systems with multi-channel wavefront sensors, single and multi wavefront correctors in systems featuring either a Shack-Hartmann or Pyramid as main wavefront sensors. The AOT file structure has been thoroughly defined, specifying data fields, descriptions, data types, units, and expected dimensions. To support this format, we have developed a Python package that enables data conversion, reading, writing and exploration of AOT files, which has been made publicly available and compatible with a general-purpose Python package manager. We demonstrate the flexibility of the AOT format by packaging data from five different instruments, installed on different telescopes.

The development of the Keck All sky Precision Adaptive optics (KAPA) project was initiated in September 2018 to upgrade the Keck I adaptive optics (AO) system to enable laser tomography adaptive optics (LTAO) with a four laser guide star (LGS) asterism. The project includes the replacement of the existing LMCT laser with a Toptica laser, the implementation of a new real-time controller (RTC) and wavefront sensor optics and camera, and a new daytime calibration and test platform to provide the required infrastructure for laser tomography. The work presented here describes the new daytime calibration infrastructure to test the performance for the KAPA tomographic algorithms. This paper outlines the hardware infrastructure for daytime calibration and performance assessment of tomographic algorithms. This includes the implementation of an asterism simulator having fiber-coupled light sources simulating four Laser Guide Stars (LGS) and two Natural Guide Stars (NGS) at the AO bench focus, as well as the upgrade of the existing TelSim on the AO bench to simulate focal anisoplanatism and wind driven atmospheric turbulence. A phase screen, that can be adjusted in effective altitude, is used to simulate wind speeds up to 10 m/s for a duration of upto 3 s., Comment: 15 pages, 13 figures. Publishd as part of SPIE Astronomical telescopes + Instrumentation 2022 proceedings

Advanced AO systems will likely utilise Pyramid wave-front sensors (PWFS) over the traditional Shack-Hartmann sensor in the quest for increased sensitivity, peak performance and ultimate contrast. Here, we wish to bring knowledge and quantify the PWFS theoretical limits as a means to highlight its properties and use cases. We explore forward models for the PWFS in the spatial-frequency domain for they prove quite useful since a) they emanate directly from physical-optics (Fourier) diffraction theory; b) provide a straightforward path to meaningful error breakdowns, c) allow for reconstruction algorithms with $O (n\,log(n))$ complexity for large-scale systems and d) tie in seamlessly with decoupled (distributed) optimal predictive dynamic control for performance and contrast optimisation. All these aspects are dealt with here. We focus on recent analytical PWFS developments and demonstrate the performance using both analytic and end-to-end simulations. We anchor our estimates with observed on-sky contrast on existing systems and then show very good agreement between analytical and Monte-Carlo estimates for the PWFS. For a potential upgrade of existing high-contrast imagers on 10\,m-class telescopes with visible or near-infrared PWFS, we show under median conditions at Paranal a contrast improvement (limited by chromatic and scintillation effects) of 2x-5x by replacing the wave-front sensor alone at large separations close to the AO control radius where aliasing dominates, and factors in excess of 10x by coupling distributed control with the PWFS over most of the AO control region, from small separations starting with the Inner Working Angle of typically 1-2 $\lambda/D$ to the AO correction edge (here 20 $\lambda/D$)., Comment: 12 pages, 13 figures

Wavefront sensors encode phase information of an incoming wavefront into an intensity pattern that can be measured on a camera. Several kinds of wavefront sensors (WFS) are used in astronomical adaptive optics. Amongst them, Fourier-based wavefront sensors perform a filtering operation on the wavefront in the focal plane. The most well known example of a WFS of this kind is the Zernike wavefront sensor, and the pyramid wavefront sensor (PWFS) also belongs to this class. Based on this same principle, new WFSs can be proposed such as the n-faced pyramid (which ultimately becomes an axicone) or the flattened pyramid, depending on whether the image formation is incoherent or coherent. In order to test such novel concepts, the LOOPS adaptive optics testbed hosted at the Laboratoire d'Astrophysique de Marseille has been upgraded by adding a Spatial Light Modulator (SLM). This device, placed in a focal plane produces high-definition phase masks that mimic otherwise bulk optic devices. In this paper, we first present the optical design and upgrades made to the experimental setup of the LOOPS bench. Then, we focus on the generation of the phase masks with the SLM and the implications of having such a device in a focal plane. Finally, we present the first closed-loop results in either static or dynamic mode with different WFS applied on the SLM., Comment: 14 pages, 9 figures, submitted to JATIS

Atmospheric profiling is a requirement for controlling wide-field Adaptive Optics (AO) instruments, analyzing the AO performance with respect to the observing conditions and predicting the Point Spread Function (PSF) spatial variations. We present PEPITO, a new concept for profiling atmospheric turbulence from {\em post~facto} tip-tilt (TT) corrected short-exposure images. PEPITO utilizes the anisokinetism effect in the images between several stars separated from a reference star, and then produces the profile estimation using a model-fitting methodology, by fitting to the long exposure TT-corrected PSF. PEPITO has a high sensitivity to both $C_n^2(h)$ and $L_0(h)$ by relying on the full telescope aperture and a large field of view. It then obtains a high vertical resolution (1\,m-400\,m) configurable by the camera pixel scale, taking advantage of fast statistical convergence (of order of tens of seconds). With only a short exposure-capable large format detector and a numerical complexity independent of the telescope diameter, PEPITO perfectly suits accurate profiling for night optical turbulence site characterization or adaptive optics instruments operations. We demonstrate, in simulation, that the $C_n^2(h)$ and $L_0(h)$ can be estimated to better than 1\% accuracy, from fitted PSFs of magnitude V=11 on a D=0.5\,m telescope with a 10 arcmin field of view., Comment: 11 pages, 14 figures, accepted 2019 April 04, submitted 2019 January 29

Geared by the increasing need for enhanced performance, both optical and computational, new dynamic control laws have been researched in recent years for next generation adaptive optics systems on current 10 m-class and extremely large telescopes up to 40 m. We provide an overview of these developments and point out prospects to making such controllers drive actual systems on-sky., Comment: 11 pages, 2 colour figures

The estimation of atmospheric turbulence parameters is of relevance for: a) site evaluation & characterisation; b) prediction of the point spread function; c) live assessment of error budgets and optimisation of adaptive optics performance; d) optimisation of fringe trackers for long baseline optical interferometry. The ubiquitous deployment of Shack-Hartmann wavefront sensors in large telescopes makes them central for atmospheric turbulence parameter estimation via adaptive optics telemetry. Several methods for the estimation of the Fried parameter and outer scale have been developed, most of which are based on the fitting of Zernike polynomial coefficients variances reconstructed from the telemetry. The non-orthogonality of Zernike polynomial derivatives introduces modal cross coupling, which affects the variances. Furthermore, the finite resolution of the sensor introduces aliasing. In this article the impact of these effects on atmospheric turbulence parameter estimation is addressed with simulations. It is found that cross coupling is the dominant bias. An iterative algorithm to overcome it is presented. Simulations are conducted for typical ranges of the outer scale (4 to 32m), Fried parameter (10 cm) and noise in the variances (signal-to-noise ratio of 10 and above). It is found that, using the algorithm, both parameters are recovered with sub-percent accuracy., Comment: Accepted for publication by MNRAS

Throughout the last decade, the Advanced Telecommunications Computing Architecture (ATCA) solidified its position as one of the main switched-based crate standards for advanced Physics instrumentation, offering not only highly performant characteristics in data throughput, channel density or power supply/dissipation capabilities, but also special features for high availability (HA), required for latest and upcoming large-scale endeavours, as is the case of ITER. Hot Swap is one of the main HA features in ATCA, allowing for Boards to be replaced in a crate (Shelf), without powering off the whole system. Platforms using the Peripheral Component Interconnect Express (PCIe) protocol on the Fabric Interface must be complemented, at the software level, with the PCIe Hot Plug native feature, currently not specified for the ATCA form-factor. From a customised Hot Plug support implementation for ATCA Node Boards, the paper presents an implementation extension for Hub Boards, allowing Hot Plug of PCIe switching devices, without causing bus enumeration problems. This paper further addresses the main issues concerning an eventual standardization of PCIe Hot Plug support in ATCA, such as the implementability of Hot Plug Elements and the generation and management of Hot Plug Events, aiming to stimulate the discussion within the PICMG community towards a long overdue standardized solution for Hot Plug in ATCA., Comment: 4 pages, 3 figures, 21st IEEE Real Time Conference - Colonial Williamsburg 9-15 June 2018 Woodlands Conference Center

The main role of the ITER Radial Neutron Camera (RNC) diagnostic is to measure in real-time the plasma neutron emissivity profile at high peak count rates for a time duration up to 500 s. Due to the unprecedented high performance conditions and after the identification of critical problems, a set of activities have been selected, focused on the development of high priority prototypes, capable to deliver answers to those problems before the final RNC design. This paper presents one of the selected activities: the design, development and testing of a dedicated FPGA code for the RNC Data Acquisition prototype. The FPGA code aims to acquire, process and store in real-time the neutron and gamma pulses from the detectors located in collimated lines of sight viewing a poloidal plasma section from the ITER Equatorial Port Plug 1. The hardware platform used was an evaluation board from Xilinx (KC705) carrying an IPFN FPGA Mezzanine Card (FMC-AD2-1600) with 2 digitizer channels of 12-bit resolution sampling up to 1.6 GSamples/s. The code performs the proper input signal conditioning using a down-sampled configuration to 400 MSamples/s, apply dedicated algorithms for pulse detection, filtering and pileup detection, and includes two distinct data paths operating simultaneously: i) the event-based data-path for pulse storage; and ii) the real-time processing, with dedicated algorithms for pulse shape discrimination and pulse height spectra. For continuous data throughput both data-paths are streamed to the host through two distinct PCIe x8 Direct Memory Access (DMA) channels., Comment: 6 pages, 10 figures, 21st IEEE Real Time Conference (RT-2018), Colonial Williamsburg, 9-15 June 2018

Shack-Hartmann wavefront sensing relies on accurate spot centre measurement. Several algorithms were developed with this aim, mostly focused on precision, i.e. minimizing random errors. In the solar and extended scene community, the importance of the accuracy (bias error due to peak-locking, quantisation or sampling) of the centroid determination was identified and solutions proposed. But these solutions only allow partial bias corrections. To date, no systematic study of the bias error was conducted. This article bridges the gap by quantifying the bias error for different correlation peak-finding algorithms and types of sub-aperture images and by proposing a practical solution to minimize its effects. Four classes of sub-aperture images (point source, elongated laser guide star, crowded field and solar extended scene) together with five types of peak-finding algorithms (1D parabola, the centre of gravity, Gaussian, 2D quadratic polynomial and pyramid) are considered, in a variety of signal-to-noise conditions. The best performing peak-finding algorithm depends on the sub-aperture image type, but none is satisfactory to both bias and random errors. A practical solution is proposed that relies on the anti-symmetric response of the bias to the sub-pixel position of the true centre. The solution decreases the bias by a factor of ~7 to values of < 0.02 pix. The computational cost is typically twice of current cross-correlation algorithms., Comment: 8 pages, 6 figures. Accepted for publication in MNRAS

We build on a long-standing tradition in astronomical adaptive optics (AO) of specifying performance metrics and error budgets using linear systems modeling in the spatial-frequency domain. Our goal is to provide a comprehensive tool for the calculation of error budgets in terms of residual temporally filtered phase power spectral densities and variances. In addition, the fast simulation of AO-corrected point spread functions (PSFs) provided by this method can be used as inputs for simulations of science observations with next-generation instruments and telescopes, in particular to predict post-coronagraphic contrast improvements for planet finder systems. We extend the previous results and propose the synthesis of a distributed Kalman filter to mitigate both aniso-servo-lag and aliasing errors whilst minimizing the overall residual variance. We discuss applications to (i) analytic AO-corrected PSF modeling in the spatial-frequency domain, (ii) post-coronagraphic contrast enhancement, (iii) filter optimization for real-time wavefront reconstruction, and (iv) PSF reconstruction from system telemetry. Under perfect knowledge of wind velocities, we show that $\sim$60 nm rms error reduction can be achieved with the distributed Kalman filter embodying anti- aliasing reconstructors on 10 m class high-order AO systems, leading to contrast improvement factors of up to three orders of magnitude at few ${\lambda}/D$ separations ($\sim1-5{\lambda}/D$) for a 0 magnitude star and reaching close to one order of magnitude for a 12 magnitude star., Comment: 15 pages, 8 figures

The use of Fourier methods in wave-front reconstruction can significantly reduce the computation time for large telescopes with a high number of degrees of freedom. However, Fourier algorithms for discrete data require a rectangular data set which conform to specific boundary requirements, whereas wave-front sensor data is typically defined over a circular domain (the telescope pupil). Here we present an iterative Gerchberg routine modified for the purposes of discrete wave-front reconstruction which adapts the measurement data (wave-front sensor slopes) for Fourier analysis, fulfilling the requirements of the Fast Fourier Transform (FFT) and providing accurate reconstruction. The routine is used in the adaptation step only and can be coupled to any other Wiener-like or least-squares method. We compare simulations using this method with previous Fourier methods and show an increase in performance in terms of Strehl ratio and a reduction in noise propagation for a 40x40 SPHERE-like adaptive optics system. For closed loop operation with minimal iterations the Gerchberg method provides an improvement in Strehl, from 95.4% to 96.9% in K-band. This corresponds to ~40 nm improvement in rms, and avoids the high spatial frequency errors present in other methods, providing an increase in contrast towards the edge of the correctable band.

Prior statistical knowledge of the atmospheric turbulence is essential for designing, optimizing and evaluating tomographic adaptive optics systems. We present the statistics of the vertical profiles of $C_N^2$ and the outer scale at Maunakea estimated using a Slope Detection And Ranging (SLODAR) method from on-sky telemetry taken by RAVEN, which is a MOAO demonstrator in the Subaru telescope. In our SLODAR method, the profiles are estimated by a fit of the theoretical auto- and cross-correlation of measurements from multiple Shack-Haltmann wavefront sensors to the observed correlations via the non-linear Levenberg-Marquardt Algorithm (LMA), and the analytic derivatives of the spatial phase structure function with respect to its parameters for the LMA are also developed. The estimated profile has the median total seeing of 0.460$^{\prime\prime}$ and large $C_N^2$ fraction of the ground layer of 54.3%. The $C_N^2$ profile has a good agreement with the result from literatures, except for the ground layer. The median value of the outer scale is 25.5m and the outer scale is larger at higher altitudes, and these trends of the outer scale are consistent with findings in literatures., Comment: 11 pages, 10 figures, submitted to MNRAS

Sky-coverage in laser-assisted AO observations largely depends on the system's capability to guide on the faintest natural guide-stars possible. Here we give an up-to-date status of our natural guide-star processing tailored to the European-ELT's visible and near-infrared (0.47 to 2.45 {\mu}m) integral field spectrograph - Harmoni. We tour the processing of both the isoplanatic and anisoplanatic tilt modes using the spatio-angular approach whereby the wave-front is estimated directly in the pupil plane avoiding a cumbersome explicit layered estimation on the 35-layer profiles we're currently using. Taking the case of Harmoni, we cover the choice of wave-front sensors, the number and field location of guide-stars, the optimised algorithms to beat down angular anisoplanatism and the performance obtained with different temporal controllers under split high-order/low-order tomography or joint tomography. We consider both atmospheric and far greater telescope wind buffeting disturbances. In addition we provide the sky-coverage estimates thus obtained., Comment: To appear at the SPIE Adaptive Telescopes and Instrumentation Conference proceedings, paper no 9909-180; 13 pages, 12 figures

Multi-object astronomical adaptive-optics (MOAO) is now a mature wide-field observation mode to enlarge the adaptive-optics-corrected field in a few specific locations over tens of arc-minutes. The work-scope provided by open-loop tomography and pupil conjugation is amenable to a spatio-angular Linear-Quadratic Gaussian (SA-LQG) formulation aiming to provide enhanced correction across the field with improved performance over static reconstruction methods and less stringent computational complexity scaling laws. Starting from our previous work [1], we use stochastic time-progression models coupled to approximate sparse measurement operators to outline a suitable SA-LQG formulation capable of delivering near optimal correction. Under the spatio-angular framework the wave-fronts are never explicitly estimated in the volume,providing considerable computational savings on 10m-class telescopes and beyond. We find that for Raven, a 10m-class MOAO system with two science channels, the SA-LQG improves the limiting magnitude by two stellar magnitudes when both Strehl-ratio and Ensquared-energy are used as figures of merit. The sky-coverage is therefore improved by a factor of 5., Comment: 30 pages, 7 figures, submitted to Applied Optics

Computationally-efficient wave-front reconstruction techniques for astronomical adaptive optics systems have seen a great development in the past decade. Algorithms developed in the spatial-frequency (Fourier) domain have gathered large attention specially for high-contrast imaging systems. In this paper we present the Wiener filter (resulting in the maximization of the Strehl-ratio) and further develop formulae for the anti-aliasing Wiener filter that optimally takes into account high-order wave-front terms folded in-band during the sensing (i.e. discrete sampling) process. We employ a continuous spatial-frequency representation for the forward measurement operators and derive the Wiener filter when aliasing is explicitly taken into account. We further investigate and compare to classical estimates using least-squares filters the reconstructed wave-front, measurement noise and aliasing propagation coefficients as a function of the system order. Regarding high-contrast systems, we provide achievable performance results as a function of an ensemble of for ward models for the Shack-Hartmann wave-front sensor (using sparse and non-sparse representations) and compute point-spread function raw intensities. We find that for a 32x32 single-conjugated adaptive optics system the aliasing propagation coefficient is roughly 60% of the least-squares filters whereas the noise propagation is around 80%. Contrast improvements of factors of up to 2 are achievable across the field in H-band. For current and next generation high-contrast imagers, despite better aliasing mitigation, anti-aliasing Wiener filtering cannot be used as a stand-alone method and must therefore be used in combination with optical spatial filters deployed before image formation takes actual place., Comment: Accepted for publication on JOSA-A