All-Optical Phase Conjugation Using Diffractive Wavefront Processing
November 08, 2023 Β· Declared Dead Β· π Nature Communications
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Che-Yung Shen, Jingxi Li, Tianyi Gan, Mona Jarrahi, Aydogan Ozcan
arXiv ID
2311.04473
Category
physics.optics
Cross-listed
cs.CV,
physics.app-ph
Citations
18
Venue
Nature Communications
Last Checked
1 month ago
Abstract
Optical phase conjugation (OPC) is a nonlinear technique used for counteracting wavefront distortions, with various applications ranging from imaging to beam focusing. Here, we present the design of a diffractive wavefront processor to approximate all-optical phase conjugation operation for input fields with phase aberrations. Leveraging deep learning, a set of passive diffractive layers was optimized to all-optically process an arbitrary phase-aberrated coherent field from an input aperture, producing an output field with a phase distribution that is the conjugate of the input wave. We experimentally validated the efficacy of this wavefront processor by 3D fabricating diffractive layers trained using deep learning and performing OPC on phase distortions never seen by the diffractive processor during its training. Employing terahertz radiation, our physical diffractive processor successfully performed the OPC task through a shallow spatially-engineered volume that axially spans tens of wavelengths. In addition to this transmissive OPC configuration, we also created a diffractive phase-conjugate mirror by combining deep learning-optimized diffractive layers with a standard mirror. Given its compact, passive and scalable nature, our diffractive wavefront processor can be used for diverse OPC-related applications, e.g., turbidity suppression and aberration correction, and is also adaptable to different parts of the electromagnetic spectrum, especially those where cost-effective wavefront engineering solutions do not exist.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β physics.optics
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Training of photonic neural networks through in situ backpropagation
R.I.P.
π»
Ghosted
Experimental robustness of Fourier Ptychography phase retrieval algorithms
R.I.P.
π»
Ghosted
The physics of optical computing
R.I.P.
π»
Ghosted
Freeform Diffractive Metagrating Design Based on Generative Adversarial Networks
R.I.P.
π»
Ghosted
Scalable Optical Learning Operator
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Language Models are Few-Shot Learners
R.I.P.
π»
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
π»
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
π»
Ghosted