Adaptive Wavefront Estimation Algorithms for High-Contrast Imaging of Exoplanets

The direct imaging of exoplanets orbiting stars outside our solar system remains one of the crucial tools we have available to answer whether there exists life beyond Earth. The light from an Earth-like exoplanet is approximately ten orders of magnitude dimmer than its host star and hence the imaging system of the telescope observing the exoplanet must be able to suppress the starlight to achieve a “contrast” of 10−10 in the image. This is typically achieved using a coronagraph, which blocks the light from the star while allowing the light from the planet to pass through. However, some starlight that leaks through the coronagraph needs to be further removed in the search region for the exoplanet; this region is referred to as the dark hole or dark zone (DZ). Creating a DZ requires the use of focal plane wavefront sensing and control techniques, which estimates the electric field of the starlight in the focal plane of the telescope using a camera and then informs the deformable mirrors (DMs) located upstream of the coronagraph to null these electric fields. Once the DZ is created with a desired contrast, there are still slow, high-order drifts in the optical system that cause the contrast to degrade over the long observation times of the science target. High-order wavefront sensing and control (HOWFSC) techniques are required to maintain the contrast in the DZ while observing a science target. Dark Zone Maintenance (DZM) is a technique that has demonstrated the ability to maintain the contrast in the DZ over long observation times. This algorithm utilizes an Extended Kalman Filter (EKF) to estimate the open-loop electric field at every pixel in the DZ and use this information to inform the control algorithm. The achievable contrast and contrast stability of DZM are determined by several key parameters: the optical system’s drift rate, the photon flux and associated shot noise in the measurement images, and the probe magnitude applied to the DMs for the estimation algorithm. This work quantifies the impact of the drift rate, photon rate, and probe magnitude on the performance of DZM by performing a parameter scan on high-contrast imaging testbeds. The parameter scan was performed on both the in-air High-contrast imager for Complex Aperture Telescopes (HiCAT) testbed at the Space Telescope Science Institute (STScI) and the in-vacuum Decadal Survey Testbed (DST) at the Jet Propulsion Laboratory (JPL). The parameter scan was run in both simulation and on the physical testbed using the contrast in the DZ as a performance metric, and evaluated relative to the photon-noise theoretical bounds to assess the efficacy of the DZM algorithm. The substantial difference between the theoretical bounds and experimental results, on average 70 times worse on HiCAT, motivated the development and implementation of a new DZM algorithm that utilized a separate EKF to estimate the modes of wavefront error derived from the DMs and use that information to correct for the aberrations. This new modal EKF algorithm was tested with a similar parameter scan on the HiCAT simulator demonstrating a nearly 5 times level of improvement relative to the original DZM algorithm simulation performance. The results of this work will inform the design of future algorithms to maintain high contrast during observations for upcoming space telescope missions such as the Habitable Worlds Observatory (HWO).

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Aeronautics and Astronautics

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2025

Author dc:creator

• Manojkumar, Saikrishna

Advisor dc:contributor.advisor

• Cahoy, Kerri

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/162978

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/162978