School of Engineering & IT
Multiple object adaptive optic
Large Field of View telescopes observe celestial objects through regions of atmosphere that are different and temporally changing.
Large Field of View telescopes observe celestial objects through regions of atmosphere that are different and temporally changing.
Program Code: 1643
Objectives:
Large Field of View telescopes observe celestial objects through regions of atmosphere that are different and temporally changing. Traditional adaptive optics (AO) techniques involving single mirror correction will only correct a small region of this atmospheric effect, and typically destroy imagery outside this region. It is possible to assign different correcting elements to each region, but the logistical difficulty and light loss in determining the distortion at each region and the actual shape taken by the corrector, mean that other techniques must be investigated to predict the turbulent structure and evolution across the whole field of view from a limited set of measurements. Non-optical methods must also be designed to determine the state of each corrector. This project will involve design of correctors, wavefront sensors, and control algorithm design to address MOAO implementations.
Description of Work:
Investigate commercial and custom designed deformable mirrors; Determine non-optical methods for determining their shape;
Develop algorithms for the prediction of turbulence evolution both spatially and temporally from limited observations of optical wavefronts;
Design control algorithms within embedded FPGA hardware for the manipulation of wavefront sensed data to control an array of deformable mirrors; Implementation of such a system on a small wide-field of view telescope as a proof-of-principle suitable for adoption of large telescope instrumentation.
The project will involve laboratory work, materials science, simulation and algorithm development, astronomical observation, and development of high-speed digital and analog electronics.
Contact:
Dr Andrew Lambert a.lambert@adfa.edu.au
School of Engineering & IT