English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Most adaptive optics (AO) systems using pyramid wavefront sensors (PyWFS) toestimate the phase of the pupil field use mechanical modulation of the beam inorder to increase the dynamic range in low-order modes so the PyWFS canusefully operate at low Strehl ratio. The tradeoff for this approach is reducedsensitivity, which, in turn, makes it difficult to attain a high Strehl ratioonce the loop has been closed. We propose an algorithm that increases thedynamic range of the PyWFS without modulation. The proposed algorithm achievesthis in two ways: 1) it allows the PyWFS to be treated with any desired opticalmodeling algorithms, and 2) it employs Newton's method for nonlinearoptimization to create an estimator that is more accurate than thecorresponding linear estimator. Numerical simulations show that nonlinearoptimization can make more accurate estimates of the phase of the wavefrontthan the corresponding linear estimator for Strehl ratios of the input beamthat are greater than about 0.2. As the input Strehl ratio increases, so doesthe advantage of the nonlinear estimator over the linear one. For example, whenthe input beam had a Strehl ratio of 0.4 (corresponding to a standard deviationof the phase of about 0.96 radians), the linear estimator error had a standarddeviation of about 0.65 radians, while the nonlinear estimator error had astandard deviation of about 0.27 radians (this depends only weakly on the noiselevel, assuming there is enough signal for the PyWFS to work in the linearregime). The new algorithm can be implemented in massively parallel modes,since the required calculations have almost no inter-dependencies. It issuggested that the required computations can be performed quickly enough forthe purposes of AO on modern computer systems.

Fast, Nonlinear Phase Estimation with the Non-Modulated Pyramid Wavefront Sensor at Low Strehl Ratio