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The Retina

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The retina is a layer of nervous tissue at the back of the eye that transduces light into neural signals. This process, called phototransduction, is carried out by rod and cone photoreceptor cells in the back of the retina.

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Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.

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Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

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Adaptive beam forming across temperature variation in optical phased array enabled with deep neural network.

Makoto Nakai, Isamu Takai, SungWon Chung

|June 11, 2024

Summary

A deep neural network (DNN) adaptively controls optical phased arrays (OPAs) to maintain beam patterns despite manufacturing variations and temperature shifts. This technology enables precise beam forming for advanced photonic applications.

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Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station

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Published on: April 1, 2020

Area of Science:

Photonics
Optical Engineering
Machine Learning

Background:

Integrated optical phased arrays (OPAs) require calibration due to channel mismatches.
OPA beam patterns are susceptible to distortion from temperature fluctuations.

Purpose of the Study:

To develop a deep neural network (DNN) for adaptive control of OPAs.
To compensate for process mismatches and temperature variations in OPA beam forming.

Main Methods:

Implemented a DNN to control phase modulator voltages in a 128-channel OPA.
Utilized a commercial silicon photonics (SiP) process for OPA fabrication.
Demonstrated adaptive beam forming and multi-peak beam generation.

Main Results:

Achieved accurate beam forming within a 50° field of view.
Demonstrated 0.025° accuracy with 0.1° beam sweeping at a fixed temperature.
Maintained beam integrity across a 20°C temperature range.

Conclusions:

DNN-based adaptive control effectively addresses OPA calibration and temperature stability issues.
The proposed method enables robust and precise beam steering for integrated photonic systems.