LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Long-distance pattern projection through an unfixed multimode fiber with natural evolution strategy-based wavefront shaping.

Photo from wikipedia

Focusing light into an arbitrary pattern through complex media is desired in energy delivery-related scenarios and has been demonstrated feasible with the assistance of wavefront shaping. However, it still encounters… Click to show full abstract

Focusing light into an arbitrary pattern through complex media is desired in energy delivery-related scenarios and has been demonstrated feasible with the assistance of wavefront shaping. However, it still encounters challenges in terms of pattern fidelity and focusing contrast, especially in a noisy and perturbed environment. In this work, we show that the strategy relying on natural gradient ascent-based parameter optimization can help to resist noise and disturbance, enabling rapid wavefront optimization towards high-quality pattern projection through complex media. It is revealed that faster convergence and better robustness can be achieved compared with existing phase control algorithms. Meanwhile, a new fitness function based on cosine similarity is adopted for the algorithm, leading to higher focusing contrast without sacrificing similarity to the target pattern. As a result, long-distance projection of an arbitrary pattern can be accomplished with considerably enhanced performance through a 15-meter multimode fiber that is not fixed and susceptible to perturbation. With further engineering, the approach may find special interests for many biomedical applications, such as deep-tissue photon therapy and optogenetics, where free-space localized optical delivery encounters challenges.

Keywords: multimode fiber; projection; pattern projection; long distance; wavefront shaping

Journal Title: Optics express
Year Published: 2022

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.