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Reconfigurable nonlinear optical element using tunable couplers and inverse-designed structure
Vahid Nikkhah1, Mario Junior Mencagli2, Nader Engheta1
1Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA.
Nanophotonics (Berlin, Germany)
|December 5, 2024
Summary
This study introduces a novel wave-based analog computing approach using engineered structures for ultra-fast signal processing. It presents a reconfigurable nonlinear optical architecture for advanced wave-based computing.
Area of Science:
- Physics
- Electrical Engineering
- Materials Science
Background:
- Wave-based analog computing offers ultra-fast and power-efficient signal processing.
- Current proposals primarily focus on linear operations due to challenges with nonlinear materials.
- There is a need for efficient methods to perform nonlinear operations in wave-based computing.
Purpose of the Study:
- To propose a novel three-port device for power-dependent transmission using linear and nonlinear materials.
- To develop a reconfigurable nonlinear optical architecture for implementing diverse nonlinear signal functions.
- To advance wave-based analog computing by integrating nonlinear capabilities.
Main Methods:
- Utilizing the method of inverse design to create a three-port device.
- Combining linear and Kerr nonlinear materials within the device.
- Integrating the proposed devices with Mach-Zehnder interferometers (MZIs) to form a reconfigurable architecture.
Main Results:
- A three-port device with tunable power-dependent transmission properties was successfully designed.
- A reconfigurable nonlinear optical architecture capable of implementing various nonlinear functions was proposed.
- The architecture demonstrates potential for advanced wave-based signal processing.
Conclusions:
- The proposed device and architecture enable controllable nonlinear operations in wave-based systems.
- This work paves the way for reconfigurable nonlinear signal processing integrated with linear networks.
- The findings contribute to the development of full-fledged wave-based analog computing.

