Wavefront sensing and control in space-based coronagraph instruments using Zernike's phase-contrast method
Garreth Ruane, J. Kent Wallace, John Steeves, Camilo Mejia Prada,, Byoung-Joon Seo, Eduardo Bendek, Carl Coker, Pin Chen, Brendan Crill, Jeff, Jewell, Brian Kern, David Marx, Phillip K. Poon, David Redding, A J Eldorado, Riggs, Nicholas Siegler, Robert Zimmer

TL;DR
This paper demonstrates the effectiveness of a Zernike wavefront sensor in space-based coronagraph instruments, achieving picometer sensitivity and closed-loop control, crucial for future high-contrast space telescopes like HabEx and LUVOIR.
Contribution
The study experimentally validates Zernike's phase-contrast method for wavefront sensing in space telescopes, showing high sensitivity and control capabilities relevant for future missions.
Findings
ZWFS measures low- and mid-spatial frequency aberrations with 1 pm sensitivity.
Closed-loop control resolves individual deformable mirror actuators.
Predicted performance indicates ~1 hour integration for picometer sensitivity with natural starlight.
Abstract
Future space telescopes with coronagraph instruments will use a wavefront sensor (WFS) to measure and correct for phase errors and stabilize the stellar intensity in high-contrast images. The HabEx and LUVOIR mission concepts baseline a Zernike wavefront sensor (ZWFS), which uses Zernike's phase contrast method to convert phase in the pupil into intensity at the WFS detector. In preparation for these potential future missions, we experimentally demonstrate a ZWFS in a coronagraph instrument on the Decadal Survey Testbed in the High Contrast Imaging Testbed facility at NASA's Jet Propulsion Laboratory. We validate that the ZWFS can measure low- and mid-spatial frequency aberrations up to the control limit of the deformable mirror, with surface height sensitivity as small as 1 pm, using a configuration similar to the HabEx and LUVOIR concepts. Furthermore, we demonstrate closed-loop…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
