Alignment of three mirror anastigmat telescopes using a multilayered stochastic parallel gradient descent algorithm

TL;DR

This paper introduces a stochastic parallel-gradient-descent algorithm for early-stage alignment of three mirror anastigmat telescopes, enabling the telescope to reach diffraction-limited imaging before fine adaptive optics correction.

Contribution

It proposes a novel on-sky coarse alignment method using SPGD to improve initial telescope setup for better wavefront quality.

Findings

SPGD effectively reduces wavefront error to acceptable levels

The method achieves diffraction-limited imaging in early alignment stages

Wavefront peak-to-valley errors are minimized successfully

Abstract

When a telescope doesn't reach a reasonable point spread function on the detector or detectable wavefront quality after initial assembly, a coarse phase alignment on-sky is crucial. Before utilizing a closed loop adaptive optics system, the observatory needs a strategy to actively align the telescope sufficiently for fine wavefront sensing. This paper presents a method of early-stage alignment using a stochastic parallel-gradient-descent (SPGD) algorithm which performs random perturbations to the optics of a three mirror anastigmat telescope design. The SPGD algorithm will drive the telescope until the wavefront error is below the acceptable range of the fine adaptive optics system to hand the telescope over. The focused spot size over the field of view is adopted as a feed parameter to the SPGD algorithm and wavefront peak-to-valley error values are monitored to directly compare our mechanical capabilities to our alignment goal of diffraction limited imaging and fine wavefront sensing.