Single Conjugate Adaptive Optics System Research Articles

Non-modulated pyramid wavefront sensor

Context. The diffusion of adaptive optics systems in astronomical instrumentation for large ground-based telescopes is rapidly increasing and the pyramid wavefront sensor is replacing the Shack–Hartmann as the standard solution for single conjugate adaptive optics systems. The pyramid wavefront sensor is typically used with a tip-tilt modulation to increase the linearity range of the sensor, but the non-modulated case is interesting because it maximizes the sensor sensitivity. The latter case is generally avoided for the reduced linearity range that prevents robust operation in the presence of atmospheric turbulence. Aims. We aim to solve part of the issues of the non-modulated pyramid wavefront sensor by reducing the model error in the interaction matrix. We linearize the sensor response in the working conditions without extending the sensor linearity range. Methods. We developed a new calibration approach to model the response of pyramid wave front sensor in partial correction, whereby the working conditions in the presence of residual turbulence are considered. Results. We use in simulations to show how the new calibration approach allows for the pyramid wave front sensor without modulation to be used to sense and correct atmospheric turbulence and we discuss when this case is preferable over the modulated case.

Off-axis point spread function reconstruction forsingle conjugate adaptive optics.

Modern giant segmented mirror telescopes (GSMTs) such as the Extremely Large Telescope, which is currently under construction, depend heavily on adaptive optics (AO) systems to correct for atmospheric distortions. However, a residual blur always remains in the astronomical images corrected by single conjugate AO (SCAO) systems due to fitting and bandwidth errors, which can mathematically be described by a convolution of the true image with a point spread function (PSF). Due to the nature of the turbulent atmosphere and its correction, the PSF is spatially varying, which is known as an anisoplanatic effect. The PSF serves, e.g.,as a quality measure for science images and therefore needs to be known as accurately as possible. In this paper, we present an algorithm for PSF reconstruction from pupil-plane data in directions apart from the guide star direction in an SCAO system. Our algorithm is adapted to the needs of GSMTs focused on estimating the contribution of the anisoplanatic and generalized fitting error to the PSF. Results obtained in an end-to-end simulation tool show a qualitatively good reconstruction of the PSF compared to the PSF calculated directly from the simulated incoming wavefront as well as stable performance with respect to imprecise knowledge of atmospheric parameters.

Advances in control of a pyramid single conjugate adaptive optics system

ABSTRACT Adaptive optics systems are an essential technology for the modern astronomy for ground-based telescopes. One of the most recent revolution in the field is the introduction of the pyramid wavefront sensor. The higher performance of this device is paid with increased complexity in the control. In this work, we report about advances in the adaptive optics (AO) system control obtained with SOUL at the Large Binocular Telescope. The first is an improved Tip/Tilt temporal control able to recover the nominal correction even in presence of high temporal frequency resonances. The second one is a modal gain optimization that has been successfully tested on sky for the first time. Pyramid wavefront sensors are the key technology for the first light AO systems of all Extremely Large Telescopes and the reported advances can be relevant contributions for such systems.

Pyramid wavefront sensor optical gains compensation using a convolutional model

Context. Extremely large telescopes are overwhelmingly equipped with pyramid wavefront sensors (PyWFS) over the more widely used Shack–Hartmann wavefront sensor to perform their single-conjugate adaptive optics (SCAO) mode. The PyWFS, a sensor based on Fourier filtering, has proven to be highly successful in many astronomy applications. However, this sensor exhibits non-linear behaviours that lead to a reduction of the sensitivity of the instrument when working with non-zero residual wavefronts. This so-called optical gains (OG) effect, degrades the closed-loop performance of SCAO systems and prevents accurate correction of non-common path aberrations (NCPA). Aims. In this paper, we aim to compute the OG using a fast and agile strategy to control PyWFS measurements in adaptive optics closed-loop systems. Methods. Using a novel theoretical description of PyWFS, which is based on a convolutional model, we are able to analytically predict the behaviour of the PyWFS in closed-loop operation. This model enables us to explore the impact of residual wavefront errors on particular aspects such as sensitivity and associated OG. The proposed method relies on the knowledge of the residual wavefront statistics and enables automatic estimation of the current OG. End-to-end numerical simulations are used to validate our predictions and test the relevance of our approach. Results. We demonstrate, using on non-invasive strategy, that our method provides an accurate estimation of the OG. The model itself only requires adaptive optics telemetry data to derive statistical information on atmospheric turbulence. Furthermore, we show that by only using an estimation of the current Fried parameter r0 and the basic system-level characteristics, OGs can be estimated with an accuracy of less than 10%. Finally, we highlight the importance of OG estimation in the case of NCPA compensation. The proposed method is applied to the PyWFS. However, it remains valid for any wavefront sensor based on Fourier filtering subject from OG variations.

A new temporal control approach for SCAO systems

Adaptive optics (AO) systems for ground-based telescopes use deformable mirrors to physically correct wavefront distortions induced by atmospheric turbulence. Due to time delays caused by different parts of the AO system, the process of turbulence correction becomes even more difficult since the earth’s atmosphere changes continuously. In this paper we propose a new temporal control approach for the computation of optimal mirror configurations based on the solution of a sequence of inverse problems for the wavefront sensor operator. Our mathematical formulation of the underlying problem allows the incorporation of computationally efficient wavefront reconstruction methods and a wavefront prediction step. Based on the frozen flow assumption, the prediction of a future wavefront relies on a suitable shift of the reconstructed wavefront. The performance of our temporal control algorithm is demonstrated in the context of a single conjugate adaptive optics system on a 37 meter telescope using a Shack–Hartmann wavefront sensor. Numerical results of the proposed control method are provided using OCTOPUS, the official end-to-end simulation tool of the European Southern Observatory.

A telescope-ready approach for modal compensation of pyramid wavefront sensor optical gain

The pyramid wavefront sensor (PWFS) is the currently preferred design for high-sensitivity adaptive optics (AO) systems for extremely large telescopes (ELTs). Yet, nonlinearities of the signal retrieved from the PWFS pose a significant problem for achieving the full correction potential using this sensor, a problem that will only worsen with the increasing dimension of telescopes. This paper investigates the so-called optical gain (OG) phenomenon, a sensitivity reduction and an overall modification of the sensor response induced by the residual wavefront itself, with considerable effects in standard observation conditions for ELT-sized AO systems. Through extensive numerical analysis, this work proposes a formalism to measure and minimize the first-order nonlinearity error caused by optical gain variation, which uses a modal compensation technique of the calibrated reconstructor; this enables a notable increase in performance in faint guide stars or important seeing scenarios, for example from 16 to 30% H-band Strehl ratio for a sixteenth magnitude star in r0 = 13 cm turbulence. Beyond the performance demonstrated by this compensation, a complete algorithm for realistic operation conditions is designed, which from dithering a few deformable mirror modes retrieves the optimal gains and updates the command matrix accordingly. The performance of this self-updating technique – which successfully allows automatic OG compensation regardless of the turbulent conditions, and its minimal interference with the scientific instrument are demonstrated through extensive end-to-end numerical simulations, all at the scale of an ELT instrument single-conjugate AO system.

A Multiplatform CPU-Based Architecture for Cost-Effective Adaptive Optics Systems

An adaptive optics (AO) system is composed of three key elements: a wave-front sensor (WFS) that detects the aberrations, a deformable mirror (DM) that provides the wavefront correction, and a closed-loop control system that elaborates the measurements acquired by the sensor and sends commands to the mirror. The control system can be implemented on a dedicated platform (e.g., field programmable gate array) or on general-purpose platforms (e.g., central processing unit (CPU), graphics processing unit). Dedicated hardware guarantees high performance but needs more development time and programming skills than general-purpose hardware, leading to a less maintainable system for the end user. The proposed solution aims to be a cost-effective multiplatform CPU-based flexible framework. The software, developed in C++ and using Eigen and Qt libraries, provides the tools to tune and control the AO system from wavefront measurement settings to controller parameters. A logging feature allows in-depth offline data analysis, while scripting enables execution of batch experiments. The AO system is tuned and evaluated by interfacing the WFS and DM with our software architecture. The results show that the proposed solution is able to correct the aberrations of a low- to medium-size single conjugate AO system, with a control frequency up to $\text{500}\,{\text{Hz}}$ and computational latency of $\text{40}\,\mu {\text{s}}$ , using a consumer-grade notebook.

Tensor-based predictive control for extremely large-scale single conjugate adaptive optics.

In this paper we propose a data-driven predictive control algorithm for large-scale single conjugate adaptive optics systems. At each time sample, the Shack-Hartmann wavefront sensor signal sampled on a spatial grid of size N×N is reshuffled into a d-dimensional tensor. Its spatial-temporal dynamics are modeled with a d-dimensional autoregressive model of temporal order p, where each tensor storing past data undergoes a multilinear transformation by factor matrices of small sizes. Equivalently, the vector form of this autoregressive model features coefficient matrices parametrized with a sum of Kronecker products between d-factor matrices. We propose an Alternating Least Squares algorithm for identifying the factor matrices from open-loop sensor data. When modeling each coefficient matrix with a sum of r terms, the computational complexity for updating the sensor prediction online reduces from O(pN4) in the unstructured matrix case to O(prd N2(d+1)d). Most importantly, this model structure breaks away from assuming any prior spatial-temporal coupling as it is discovered from the data. The algorithm is validated on a laboratory testbed that demonstrates the ability to accurately decompose the coefficient matrices of large-scale autoregressive models with a tensor-based representation, hence achieving high data compression rates and reducing the temporal error especially for a large Greenwood per sample frequency ratio.

层向多层共轭自适应光学系统的模拟

The adaptive optics (AO) system in which one turbulence layer is corrected has a good compensation performance only over small field of view. The technology of multi-conjugate adaptive optics (MCAO) can overcome the limitation. The elementary structure and working principle of layer oriented multi-conjugate adaptive optics (LOMCAO) system was presented. Simulation method of LOMCAO system was investigated, including how to generate dynamic turbulence wavefront data, wavefront reconstruction algorithm of pyramid wavefront sensor and close-loop modal control procedure of deformable mirror. Simulations for single layer-conjugate and two layer-conjugate AO systems were carried out. The simulation results show that LOMCAO system has better correction performance over a larger field of view than single-conjugate AO system due to the face that much more guide stars are used and two layer turbulence are compensated in LOMCAO system.

Wavefront reconstruction for extremely large telescopes via CuRe with domain decomposition

The Cumulative Reconstructor is an accurate, extremely fast reconstruction algorithm for Shack-Hartmann wavefront sensor data. But it has shown an unacceptable high noise propagation for large apertures. Therefore, in this paper we describe a domain decomposition approach to deal with this drawback. We show that this adaptation of the algorithm gives the same reconstruction quality as the original algorithm and leads to a significant improvement with respect to noise propagation. The method is combined with an integral control and compared to the classical matrix vector multiplication algorithm on an end-to-end simulation of a single conjugate adaptive optics system. The reconstruction time is 20n (number of subapertures), and the method is parallelizable.

Computational performance comparison of wavefront reconstruction algorithms for the European Extremely Large Telescope on multi-CPU architecture

The European Southern Observatory (ESO) is studying the next generation giant telescope, called the European Extremely Large Telescope (E-ELT). With a 42 m diameter primary mirror, it is a significant step from currently existing telescopes. Therefore, the E-ELT with its instruments poses new challenges in terms of cost and computational complexity for the control system, including its adaptive optics (AO). Since the conventional matrix-vector multiplication (MVM) method successfully used so far for AO wavefront reconstruction cannot be efficiently scaled to the size of the AO systems on the E-ELT, faster algorithms are needed. Among those recently developed wavefront reconstruction algorithms, three are studied in this paper from the point of view of design, implementation, and absolute speed on three multicore multi-CPU platforms. We focus on a single-conjugate AO system for the E-ELT. The algorithms are the MVM, the Fourier transform reconstructor (FTR), and the fractal iterative method (FRiM). This study enhances the scaling of these algorithms with an increasing number of CPUs involved in the computation. We discuss implementation strategies, depending on various CPU architecture constraints, and we present the first quantitative execution times so far at the E-ELT scale. MVM suffers from a large computational burden, making the current computing platform undersized to reach timings short enough for AO wavefront reconstruction. In our study, the FTR provides currently the fastest reconstruction. FRiM is a recently developed algorithm, and several strategies are investigated and presented here in order to implement it for real-time AO wavefront reconstruction, and to optimize its execution time. The difficulty to parallelize the algorithm in such architecture is enhanced. We also show that FRiM can provide interesting scalability using a sparse matrix approach.

Extreme adaptive optics in the mid-IR: The METIS AO system

METIS, the Mid-infrared ELT Imager and Spectrograph, is currently in its phase A study as one of the candidate first-light instruments for the European Extremely Large Telescope. METIS will feature several observational modes, ranging from diffraction limited imaging in L, M and N-bands to high-resolution Integral Field spectroscopy for the L and M-bands. METIS in its current design gives sensitivities similar to Spitzer in imaging and low-resolution spectroscopy and with its high-resolution spectrograph will provide unprecedented line sensitivity. The design of METIS is optimized for both galactic science cases (e.g. conditions in the early solar system, formation and evolution of proto-planetary disks and properties of exoplanets) and extragalactic science cases (e.g. the growth of Supermassive Black Holes). METIS will require a high-order adaptive optics (AO) system to meet its scientific goals, both to provide correction for atmospheric turbulence as well as reduce the impact of wind shake, leading to a residual image motion of 3 - 5 mas rms. METIS is expected to feature both an internal Single Conjugate AO system as well as an external Laser Tomography AO system. The challenges for the METIS AO system are mainly in the broad correction range, an excellent image stability required for coronagraphy and in providing a high sky coverage to be available for as many science targets as possible. An additional challenge for METIS is the need to compensate for composition turbulence, mainly in the form of fast fluctuations in water vapor concentration. Water vapor fluctuations impact the performance of METIS in several ways: Atmospheric dispersion causes a broadening of the point-spread function, both in the science channel and the wavefront channel, but can be corrected using a Atmospheric Dispersion Corrector. Variations in the water vapor composition cannot be corrected this way and are currently estimated to give a residual image motion of ≤10 mas rms. This effect can, especially for coronagraphy, not be neglected. Chromatic optical path difference errors, caused by changes in the index of refraction along the path through the atmosphere were found to be negligible in the case of METIS due to attenuation by the outer scale (at typical values of 25 m). Chromatic anisoplanatism is the effect that the light at different wavelengths travels through a slightly different light path through the atmosphere and can be–at least partly–corrected. The last effect is composition turbulence, mainly caused by fast (> 1 Hz) fluctuations in the water vapor content. Based on data for ALMA and radiometer probes, this leads to a maximum loss in Strehl ratio between 5 and 10%. This mainly has an impact on coronagraphy and the METIS AO team is actively investigating ways to compensate also water vapor turbulence. The main challenge is currently obtaining reliable data on the distribution and magnitude of precipitable water vapor fluctuations.