Real-time Adaptive Optics Research Articles

Dual-conjugate adaptive optics for wide-field high-resolution retinal imaging

We present analysis and preliminary laboratory testing of a real-time dual-conjugate adaptive optics (DCAO) instrument for ophthalmology that will enable wide-field high resolution imaging of the retina in vivo. The setup comprises five retinal guide stars (GS) and two deformable mirrors (DM), one conjugate to the pupil and one conjugate to a plane close to the retina. The DCAO instrument has a closed-loop wavefront sensing wavelength of 834 nm and an imaging wavelength of 575 nm. It incorporates an array of collimator lenses to spatially filter the light from all guide stars using one adjustable iris, and images the Hartmann patterns of multiple reference sources on a single detector. Zemax simulations were performed at 834 nm and 575 nm with the Navarro 99 and the Liou- Brennan eye models. Two correction alternatives were evaluated; conventional single conjugate AO (SCAO, using one GS and a pupil DM) and DCAO (using multiple GS and two DM). Zemax simulations at 575 nm based on the Navarro 99 eye model show that the diameter of the corrected field of view for diffraction-limited imaging (Strehl >or= 0.8) increases from 1.5 deg with SCAO to 6.5 deg using DCAO. The increase for the less stringent condition of a wavefront error of 1 rad or less (Strehl >or= 0.37) is from 3 deg with SCAO to approximately 7.4 deg using DCAO. Corresponding results for the Liou-Brennan eye model are 3.1 deg (SCAO) and 8.2 deg (DCAO) for Strehl >or= 0.8, and 4.8 deg (SCAO) and 9.6 deg (DCAO) for Strehl >or= 0.37. Potential gain in corrected field of view with DCAO is confirmed both by laboratory experiments on a model eye and by preliminary in vivo imaging of a human eye.

Modal Fourier wavefront reconstruction using graphics processing units

Large degree-of-freedom, real-time adaptive optics control requires reconstruction algorithms that are computationally efficient and readily parallelized for hardware implementation. Poyneer et al. [J. Opt. Soc. Am. A 19, 2100–2111 (2002)] have shown that the wavefront reconstruction with the use of the fast Fourier transform (FFT) and spatial filtering is computationally tractable and sufficiently accurate for its use in large Shack–Hartmann-based adaptive optics systems (up to 10,000 actuators). We show here that by the use of graphical processing units (GPUs), a specialized hardware capable of performing FFTs on big sequences almost 5 times faster than a high-end CPU, a problem of up to 50,000 actuators can already be done within a 6-ms limit. We give the method to adapt the FFT in an efficient way for the underlying architecture of GPUs.

Fast wave-front reconstruction by solving the Sylvester equation with the alternating direction implicit method

Large degree-of-freedom real-time adaptive optics (AO) control requires reconstruction algorithms that are computationally efficient and readily parallelized for hardware implementation. In particular, we find the wave-front reconstruction for the Hudgin and Fried geometry can be cast into a form of the well-known Sylvester equation using the Kronecker product properties of matrices. We derive the filters and inverse filtering formulas for wave-front reconstruction in two-dimensional (2-D) Discrete Cosine Transform (DCT) domain for these two geometries using the Hadamard product concept of matrices and the principle of separable variables. We introduce a recursive filtering (RF) method for the wave-front reconstruction on an annular aperture, in which, an imbedding step is used to convert an annular-aperture wave-front reconstruction into a squareaperture wave-front reconstruction, and then solving the Hudgin geometry problem on the square aperture. We apply the Alternating Direction Implicit (ADI) method to this imbedding step of the RF algorithm, to efficiently solve the annular-aperture wave-front reconstruction problem at cost of order of the number of degrees of freedom, O(n). Moreover, the ADI method is better suited for parallel implementation and we describe a practical real-time implementation for AO systems of order 3,000 actuators.

Real-time Adaptive Optics with a Twisted Nematic Liquid Crystal Light Modulator Controlled by the Wave Front Reconstruction Sensor

We propose adaptive optics constructed with a new principle. In this system, numerical phase reconstruction algorithm is incorporated with the Hartmann wave front sensor and the phase compensator is driven to the conjugate of the input phase distortion at each time step. The computer simulation shows a sufficient robustness and swiftness of the wave front reconstruction sensor. Then, the experimental system is configured putting special emphasis on the simplicity and feasibility of the system. A small 2-dimensional grid mask is used in the Hartmann sensor, and a twisted nematic phase modulator with a response time of 30 ms is used as the phase compensator. The control system has a simple open loop setup using a phase reconstruction algorithm. This experimental system was effective not only for static phase distortion, but also for the dynamic phase perturbation induced by a thermal convection.

Curvature Wavefront Sensor For Solar Adaptive Optics

Active or adaptive optics often require the ability to characterize wavefront aberrations using natural extended sources. The task becomes especially challenging when dealing with widely extended sources such as the solar granulation. We propose a new approach based on the processing of oppositely defocused images. This method, which is a generalization of a technique known as curvature sensing, derives the wavefront curvature from the difference between two oppositely defocused images and determines the second momenta of the point spread function. The proposed method measures the wavefront aberration from the images themselves, requires little computational resources, is fast enough to be used in a real-time adaptive optics system and is particularly adapted to random patterns such as solar granulation or spot penumbras whose morphology evolves during the observation. We envision the application of the method to real-time seeing compensation in solar astronomical telescopes, and to the correction of optical system aberrations in remote sensing instrumentation. This effort is directed towards building a curvature sensor for the real-time applications.

Some computational problems arising in adaptive optics imaging systems

Recently there has been growing interest and progress in using numerical linear algebra techniques in adaptive optics imaging control computations. Real-time adaptive optics is a means for enhancing the resolution of ground based, optical telescopes beyond the limits previously imposed by the turbulent atmosphere. An adaptive optics system automatically corrects for light distortions caused by the medium of transmission. The system measures the characteristics of the phase of the arriving wavefront and corrects for the degradations by means of one or more deformable mirrors controlled by special purpose computers. No attempt is made in this paper to give a comprehensive survey of recent numerical linear applications in optical imaging. Rather, two fairly representative applications are discussed in some detail. The following research topics in the area of adaptive optics control systems, each involving the formulation and numerical solution of difficult problems in numerical linear algebra, are described: (1) Jacobi-like eigenvalue computations for multiple bandwidth deformable mirror control methods, and (2) covariance matrix computations for performance modeling of adaptive optics systems using fast Hankel transforms.

A real-time closed-loop liquid crystal adaptive optics system: first results

We present the first results from a real-time closed-loop adaptive optics system incorporating a liquid crystal based corrector device and a Shack-Hartmann wavefront sensor. The system is designed to operate at a bandwidth which would be useful in astronomical applications. Here we show results of the system correcting laboratory simulated Kolmogorov-like turbulence.