Diffraction-based nonlinear model for the design of broadband adiabatic up-conversion imaging.

Area of Science:

• Nonlinear Optics
• Optical Imaging
• Computational Photonics

Background:

• Mid-infrared (MIR) parametric upconversion imaging converts MIR light to visible images.
• Existing models struggle with long, aperiodic poled crystals and broadband adiabatic frequency upconversion.
• Accurate modeling is crucial for advancing MIR imaging in fields like biomedical sensing and remote detection.

Purpose of the Study:

• Introduce a generalized diffraction-based numerical simulation framework for nonlinear image/signal generation.
• Address limitations in modeling upconversion imaging for both periodic and aperiodic poled crystals.
• Provide a tool for interpreting experimental results in nonlinear optical imaging.

Main Methods:

• Developed a diffraction-based numerical simulation framework.
• The model accommodates both periodically and aperiodically poled nonlinear crystals.
• Incorporated analysis of varying image magnification in upconversion imaging.

Main Results:

• The framework accurately predicts nonlinear image/signal evolution in upconversion imaging systems.
• Simulations were validated against experimental measurements of broadband MIR to visible-NIR upconversion.
• The model captures image magnification effects from multiwavelength objects at Fourier planes.

Conclusions:

• The new numerical framework enables accurate prediction of nonlinear image generation in upconversion imaging.
• It supports both periodic and aperiodic crystal designs, expanding modeling capabilities.
• This tool will facilitate the interpretation and optimization of experimental upconversion imaging.