The pyramid wavefront sensor (PWS) was initially proposed by astronomers to measure aberrations introduced
by the atmosphere. More recently it has been used to measure aberrations of the human eye, and has been
successfully incorporated into an adaptive optics loop to correct those aberrations. The raw sensor signal can
be used as feedback to control a wavefront correcting device, or with appropriate scaling, to reconstruct the
wavefront map in the pupil. In practice, use of dynamic modulation allows one to tune the sensitivity and range
of the sensor to best suit the particular application. We describe a PWS primarily designed to perform in-vivo
measurements of human eyes. The sensor is calibrated over a wide range of settings allowing one to choose those
best suited to a specific task. For example, enhanced-sensitivity measurements of very small aberrations require
small range (closed loop adaptive optics). Alternatively, if one wants to measure the aberrations of the eye
without any correction, the range required is subject-dependent and can be large; the price paid is in reduced
sensitivity . We present in-vivo measurements of human eyes taken at a number of experimental settings and
compare the performance of the PWS at each.
A performance comparison is made using a number of commercially available Deformable Mirrors(DM) in fitting
both ocular and atmospheric wavefronts. Least squares phase fitting simulations are performed for five mirrors
using experimentally obtained mirror influence functions. The DMs used cover a range of DM technologies with
varying size and cost. The phase fitting performance of these mirrors is found to be a function of influence
function shape, actuator density and available mirror stroke.
MEMS is one of several emerging technologies for fabricating wavefront correctors for use in adaptive optics systems. Each technology has its own advantages and disadvantages. In order to compare devices, it is useful to define a task and make a comparison based upon the effectiveness of each device for this task. Such an approach implies, of course, that device A might be better suited for task X whereas device B is better suited for task Y. In adaptive optics, this situation is already known: deformable mirrors that are relatively effective at compensating for atmospheric turbulence are not necessarily the mirrors that one would choose for correction of the aberrations of the eye. This is essentially because the statistical modal distribution of the aberrated wavefronts in each case are different. In this talk, we shall present a method for systematically evaluating the effectiveness of different mirror (or transmissive) technologies in adaptive optics in the eye. It uses a model for the aberrations of the eye (such as that developed by Thibos et al1) and a least squares fitting procedure. Results will be presented for at least 4 mirrors, including a 12x12 MEMS device. The key point is that it is the effectiveness of each actuator signal that is important, not the raw number of actuators.
A key component of any adaptive optics system (AO) for the correction of wavefront aberrations, is the wavefront sensor(WFS). Many systems operate in a mode where a WFS measures the aberrations present in the incoming beam. The required corrections are determined and applied by the wavefront corrector - often a deformable mirror (DM). We wish to develop a wavefront sensor-less correcting system, as derived from the original adaptive optics system of Muller and Buffington. In this experiment we employ a method in which a correcting element with adjustable segments is driven to maximise some function of the image. We employ search algorithms to find the optimal combination of actuator voltages to maximise a certain sharpness metric. The “sharpness” is based on intensity measurements taken with a CCD camera. Results have been achieved using a Nelder-Mead variation of the Simplex algorithm. Preliminary results show that the Simplex algorithm can minimise the aberrations and restore the Airy rings of the imaged point source. Good correction is achieved within 50-100 iterations of the Simplex algorithm. The results are repeatable and so-called “blind” correction of the aberrations is achieved. The correction achieved using various sharpness algorithms laid out by Muller and Buffington are evaluated and presented.
Typical applications of ultra-high-power femtosecond lasers include precision drilling and surface micro-machining of metals, and micro-structuring of transparent materials. However, high peak-power pulsed lasers are difficult to focus close to the diffraction limit because of aberrations that induce deviations from a perfect spatial wave-front. The sources of these aberrations include thermally induced and nonlinear optical distortions, as well as static distortions such as those introduced by gratings used in chirped-pulse amplification (CPA). A spatially clean beam is desirable to achieve the highest possible intensity on-target, and to minimize the energy deposited outside the central focus. One way to achieve this is to correct the wave-front using an adaptive optical element such as a deformable mirror, a more cost-effective solution than increasing peak intensity by providing further pulse amplification. The wave-front of the femtosecond system is measured using a Hartmann-Shack wave-front sensor, and corrected with a 37-channel deformable membrane mirror used slightly off-axis. The deformable mirror has been tested with a FISBA OPTIK μPhase HR digital interferometer, which is also used to calibrate the performance of the wave-front sensor. The influence of fluctuations of the laser on the measurement is minimised by averaging the centroid positions obtained from several consecutive frames. The distorted wave-front is compared to a reference flat wave-front which is obtained from a collimated laser diode operating at the same wavelength as the femtosecond system. The voltages on the deformable mirror actuators are then set to minimise the difference between the measured and reference wave-fronts using a simple least squares approach. Wave-front sensor and correction software is implemented in Matlab.