The Zernike wavefront sensor (ZWFS) is a concept belonging to the wide class Fourier-filtering wavefront sensor (FFWFS). The ZWFS is known for its extremely high sensitivity while having a low dynamic range, which makes it a unique sensor for second
stage adaptive optics (AO) systems or quasi-static aberrations calibration sensor. This sensor is composed of a focal plane mask made of a phase shifting dot fully described by two parameters: its diameter and depth. In this letter, we aim to improve the performance of this sensor by changing the diameter of its phase shifting dot. We begin with a general theoretical framework providing an analytical description of the FFWFS properties, then we predict the expected ZWFS sensitivity for different configurations of dot diameters and depths. The analytical predictions are then validated with end-to-end simulations. From this, we propose a variation of the classical ZWFS shape which exhibits extremely appealing properties. We show that the ZWFS sensitivity can be optimized by modifying the dot diameter and even reach the optimal theoretical limit, with a trade-off for low spatial frequencies sensitivity. As an example, we show that a ZWFS with a 2{lambda}/D dot diameter (where {lambda} is the sensing wavelength and D the telescope diameter), hereafter called Z2WFS, exhibits a sensitivity twice higher than the classical 1.06{lambda}/D ZWFS for all the phase spatial components except for tip-tilt modes. Furthermore, this gain in sensitivity does not impact the dynamic range of the sensor, and the Z2WFS exhibits a similar dynamical range as the classical 1.06{lambda}/D ZWFS. This study opens the path to the conception of diameter-optimized ZWFS.
With its high sensitivity, the Pyramid wavefront sensor (PyWFS) is becoming an advantageous sensor for astronomical adaptive optics (AO) systems. However, this sensor exhibits significant non-linear behaviours leading to challenging AO control issues
. In order to mitigate these effects, we propose to use, in addition to the classical pyramid sensor, a focal plane image combined with a convolutive description of the sensor to perform a fast tracking of the PyWFS non-linearities, the so-called optical gains (OG). We show that this additional focal plane imaging path only requires a small fraction of the total flux, while representing a robust solution to estimate the PyWFS OG. Finally, we demonstrate the gain brought by our method with the specific examples of bootstrap and Non-Common Path Aberrations (NCPA) handling.
Extremely Large Telescopes have overwhelmingly opted for the Pyramid wavefront sensor (PyWFS) over the more widely used Shack-Hartmann WaveFront Sensor (SHWFS) to perform their Single Conjugate Adaptive Optics (SCAO) mode. The PyWFS, a sensor based o
n Fourier filtering, has proven to be highly successful in many astronomy applications. However, it exhibits non-linearity behaviors that lead to a reduction of its sensitivity when working with non-zero residual wavefronts. This so-called Optical Gains (OG) effect, degrades the close loop performance of SCAO systems and prevents accurate correction of Non-Common Path Aberrations (NCPA). In this paper, we aim at computing the OG using a fast and agile strategy in order to control the PyWFS measurements in adaptive optics closed loop systems. Using a novel theoretical description of the PyFWS, which is based on a convolutional model, we are able to analytically predict the behavior of the PyWFS in closed-loop operation. This model enables us to explore the impact of residual wavefront error 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. We demonstrate, using on non-invasive strategy, that our method provides an accurate estimation of the OG. The model itself only requires AO telemetry data to derive statistical information on atmospheric turbulence. Furthermore, we show that by only using an estimation of the current Fried parameter r_0 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.
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 PWF
S 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 $lambda/D$).
In this paper, we describe Fourier-based Wave Front Sensors (WFS) as linear integral operators, characterized by their Kernel. In a first part, we derive the dependency of this quantity with respect to the WFSs optical parameters: pupil geometry, fil
tering mask, tip/tilt modulation. In a second part we focus the study on the special case of convolutional Kernels. The assumptions required to be in such a regime are described. We then show that these convolutional kernels allow to drastically simplify the WFSs model by summarizing its behavior in a concise and comprehensive quantity called the WFSs Impulse Response. We explain in particular how it allows to compute the sensors sensitivity with respect to the spatial frequencies. Such an approach therefore provides a fast diagnostic tool to compare and optimize Fourier-based WFSs. In a third part, we develop the impact of the residual phases on the sensors impulse response, and show that the convolutional model remains valid. Finally, a section dedicated to the Pyramid WFS concludes this work, and illustrates how the slopes maps are easily handled by the convolutional model.
We introduce in this article a general formalism for Fourier based wave front sensing. To do so, we consider the filtering mask as a free parameter. Such an approach allows to unify sensors like the Pyramid Wave Front Sensor (PWFS) and the Zernike Wa
ve Front Sensor (ZWFS). In particular, we take the opportunity to generalize this two sensors in terms of sensors class where optical quantities as, for instance, the apex angle for the PWFS or the depth of the Zernike mask for the ZWFS become free parameters. In order to compare all the generated sensors of this two classes thanks to common performance criteria, we firstly define a general phase-linear quantity that we call meta-intensity. Analytical developments allow then to split the perfectly phase-linear behavior of a WFS from the non-linear contributions making robust and analytic definitions of the sensitivity and the linearity range possible. Moreover, we define a new quantity called the SD factor which characterizes the trade-off between these two antagonist quantities. These developments are generalized for modulation device and polychromatic light. A non-exhaustive study is finally led on the two classes allowing to retrieve the usual results and also make explicit the influence of the optical parameters introduced above.
In this article, we compare a set of Wave Front Sensors (WFS) based on Fourier filtering technique. In particular, this study explores the class of pyramidal WFS defined as the 4 faces pyramid WFS, all its recent variations (6, 8 faces, the flattened
PWFS, etc.) and also some new WFSs as the flattened cone WFS or the 3 faces pyramid WFS. In the first part, we describe such a sensors class thanks to the optical parameters of the Fourier filtering mask and the modulation parameters. In the second part, we use the unified formalism to create a set of performance criteria: size of the signal on the detector, efficiency of incoming flux, sensitivity, linear range and chromaticity. In the third part, we show the influence of the previous optical and modulation parameters on these performance criteria. This exhaustive study allows to know how to optimize the sensor regarding to performance specifications. We show in particular that the number of faces has influence on the number of pixels required to do the wave front sensing but no influence on the sensitivity and linearity range. To modify these criteria, we show that the modulation radius and the apex angle are much more relevant. Moreover we observe that the time spent on edges or faces during a modulation cycle allows to adjust the trade-off between sensitivity and linearity range.
