Wednesday, June 12, 2019
4:00 PM - 5:00 PM
Annenberg 105

Special Seminar in CMS

Wavefront sensing and control for high-contrast imaging in space
He Sun, Ph.D. student, Mechanical and Aerospace Engineering, Princeton University,
Speaker's Bio:
He Sun is a Ph.D. student in Mechanical and Aerospace Engineering at Princeton University. His research interests lie in optics, signal processing, and control systems, with a particular focus on their applications in astronomical telescopes and instruments. His research has been recognized through the IEEE Aerospace Conference best paper award on observation technologies and systems. He is also a recipient of the Harari Fellowship and the Princeton School of Engineering and Applied Science (SEAS) Award for Excellence. Before coming to Princeton, He received his B.Eng. in Engineering Mechanics and B.A. in Economics from Peking University, China, in 2014.

One of the most important scientific goals of the next generation of large space telescopes is the imaging and characterization of earth-like exoplanets, which are a billion times fainter than their host stars. This requires that telescopes be equipped with high-contrast instruments, such as coronagraphs, to suppress the star light, and wavefront sensing and control systems to cancel the aberrations induced by imperfect telescope optics. Early successes of such a system in ground-based telescopes, employing what is known as extreme adaptive optics, have revealed the potential for future high-contrast imaging in space. The first space-based coronagraph and wavefront sensing and control system will soon fly with NASA’s Wide Field Infra-Red Survey Telescope (WFIRST) in the mid 2020s.

In this talk, I will introduce a new treatment of wavefront sensing and control as a stochastic optimal control problem: it first estimates the aberrated light field based on the sensing commands and images, and then it controls the deformable mirrors to correct the estimated wavefront aberrations. I will also present our recent contributions focusing on fast and efficient wavefront sensing and control algorithms. First, I will discuss the application of variational Bayesian methods to improve the accuracy of system state space modeling. Then, I will introduce approaches to efficiently collect wavefront sensing commands and images based on optimal experiment design theory. Experiments on prototype systems and simulations of real telescopes will be reported to demonstrate these new algorithms. The talk will end with a further discussion of the challenges and opportunities ahead, including but not limited to, multi-wavelength wavefront sensing, control, and image processing using an integral field spectrograph.

For more information, please contact Diane Goodfellow by email at diane@cms..caltech.edu