PWFSs on GMCAO: a different approach to the non-linearity issue

Viotto, Valentina; Bergomi, Maria; Dima, Marco; Farinato, Jacopo; Greggio, Davide; Magrin, Demetrio; Portaluri, Elisa; Ragazzoni, Roberto; Esposito, Simone; Pinna, Enrico

doi:10.1117/12.2232834

Cited by 4 publications

(7 citation statements)

References 1 publication

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“…Moreover, the modal control is associated with the necessity to identify and correct on the fly the so-called modal optical gains. 8,27,[99][100][101][102][103] Furthermore, the modal basis is not as well-suited for pupils with spiders as the zonal approach, which allows significantly more degrees of freedom in the representation of wavefront. 49,69,[104][105][106][107] An alternative-decoupled-approach to AO loop control considers the two steps: wavefront reconstruction and DM fitting, separately and independently.…”

Section: Coupled and Decoupled Controlmentioning

confidence: 99%

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Review on methods for wavefront reconstruction from pyramid wavefront sensor data

Shatokhina

Hutterer

Ramlau

2020

J. Astron. Telesc. Instrum. Syst.

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Pyramid wavefront sensors are planned to be a part of many instruments that are currently under development for the extremely large telescopes (ELT). The unprecedented scales of the upcoming ELT-era instruments are inevitably connected with serious challenges for wavefront reconstruction and control algorithms. Apart from the huge number of correcting elements to be controlled in real-time, real-life features such as the segmentation of the telescope pupil, the low wind effect, the nonlinearity of the pyramid sensor, and the noncommon path aberrations will have a significantly larger impact on the imaging quality in the ELT framework than they ever had before. We summarize various kinds of wavefront reconstruction algorithms for the pyramid wavefront sensor. Based on several forward models, different algorithms were developed in the last decades for linear and nonlinear wavefront correction. The core ideas of the algorithms are presented, and a detailed comparison of the presented methods with respect to underlying pyramid sensor models, computational complexities, and reconstruction qualities is given. In addition, we review the existing and possible solutions for the above-named real-life phenomena. At the same time, directions for further investigations are sketched.

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Section: Coupled and Decoupled Controlmentioning

confidence: 99%

“…A similar but slightly different approach for recovering the mode-dependent nonlinearity factors was described in Ref. 99. The authors suggest injecting a dither signal in an additional local loop with a dedicated low-order DM.…”

Section: Sensor's Nonlinearitymentioning

confidence: 99%

Review on methods for wavefront reconstruction from pyramid wavefront sensor data

Shatokhina

Hutterer

Ramlau

2020

J. Astron. Telesc. Instrum. Syst.

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“…(17) and considering the steps needed to derive the equations corresponding to Eqs. (19) through (21). In contrast, the PolarPixel and ReImPixel representations have N = 2K (instead of N = K), but otherwise have similar computational complexity to the PhasePixel representation.…”

Section: B Detector Intensity and Its Derivativesmentioning

confidence: 99%

“…The needed derivatives of the intensity are shown in Eqs. (19) through (21) for the PhasePixel representation. Since each element of the N × N Hessian of the cost function requires a sum over L pixels, calculation of this Hessian requires the determination of (N 2 + N)L/2 quantities.…”

Section: Nonlinear Least-squaresmentioning

confidence: 99%

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Efficient, nonlinear phase estimation with the nonmodulated pyramid wavefront sensor

Frazin

2018

J. Opt. Soc. Am. A

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The sensitivity of the pyramid wavefront sensor (PyWFS) has made it a popular choice for astronomical adaptive optics (AAO) systems. The PyWFS is at its most sensitive when it is used without modulation of the input beam. In nonmodulated mode, the device is highly nonlinear. Hence, all PyWFS implementations on current AAO systems employ modulation to make the device more linear. The upcoming era of 30-m class telescopes and the demand for ultra-precise wavefront control stemming from science objectives that include direct imaging of exoplanets make using the PyWFS without modulation desirable. This article argues that nonlinear estimation based on Newton's method for nonlinear optimization can be useful for mitigating the effects of nonlinearity in the nonmodulated PyWFS. The proposed approach requires all optical modeling to be pre-computed, which has the advantage of avoiding real-time simulations of beam propagation. Further, the required real-time calculations are amenable to massively parallel computation. Numerical experiments simulate a PyWFS with faces sloped 3.7° to the horizontal, operating at a wavelength of 0.85 μm, and with an index of refraction of 1.45. A singular value analysis shows that the common practice of calculating two "slope" images from the four PyWFS pupil images discards critical information and is unsuitable for the nonmodulated PyWFS simulated here. Instead, this article advocates estimators that use the raw pixel values not only from the four geometrical images of the pupil, but from surrounding pixels as well. The simulations indicate that nonlinear estimation can be effective when the Strehl ratio of the input beam is greater than 0.3, and the improvement relative to linear estimation tends to increase at larger Strehl ratios. At Strehl ratios less than about 0.5, the performances of both the nonlinear and linear estimators are relatively insensitive to noise since they are dominated by nonlinearity error.

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Real-time adaptive optics with pyramid wavefront sensors: part I. A theoretical analysis of the pyramid sensor model

2019

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We consider the mathematical background of the wavefront sensor type that is widely used in Adaptive Optics systems for astronomy, microscopy, and ophthalmology. The theoretical analysis of the pyramid sensor forward operators presented in this paper is aimed at a subsequent development of fast and stable algorithms for wavefront reconstruction from data of this sensor type. In our analysis we allow the sensor to be utilized in both the modulated and non-modulated fashion. We derive detailed mathematical models for the pyramid sensor and the physically simpler roof wavefront sensor as well as their various approximations. Additionally, we calculate adjoint operators which build preliminaries for the application of several iterative mathematical approaches for solving inverse problems such as gradient based algorithms, Landweber iteration or Kaczmarz methods.

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PWFSs on GMCAO: a different approach to the non-linearity issue

Cited by 4 publications

References 1 publication

Review on methods for wavefront reconstruction from pyramid wavefront sensor data

Review on methods for wavefront reconstruction from pyramid wavefront sensor data

Efficient, nonlinear phase estimation with the nonmodulated pyramid wavefront sensor

Real-time adaptive optics with pyramid wavefront sensors: part I. A theoretical analysis of the pyramid sensor model

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