Introduction
Large-scale, reliable photonic integrated circuits (PICs) have arrived. Governments, academia, and industry recognize that photonic integration is critical for applications like communications, sensing, and computing. Photonic design automation (PDA) tools will be as important for PIC success as electronic design automation (EDA) was for integrated circuits. This white paper examines modeling differences between PICs and electronics and explains pSim’s simulation approach for PICs.
Simulation of Electronic Circuits
Since the 1970s, SPICE and SPICE-like simulators have enabled time- and frequency-domain analysis of analog circuits composed of basic components like transistors, resistors, and capacitors. Some optoelectronic devices can also be modeled with equivalent circuits, like VCSELs.
Simulation of Photonic Circuits
Photonic circuits involve closed optical paths due to rings, modulators, etc. Performance depends on multi-directional signal interactions including reflection, transmission, and multi-path interference. Unlike electrical signals in SPICE, optical signals require accounting for polarization, phase, mode profiles, and wavelengths.
Photonic System Simulation
A tailored approach to modeling devices in PICs with diverse geometries and materials is neither seamless nor efficient. Therefore, a SPICE-like photonic system modeling approach is more suitable.
The pSim Approach
pSim enables time- and frequency-domain simulation of linear and nonlinear PICs. Each device is a compact model, and circuits comprise multiple models, like the examples below:
Compact models can be based on analytical solutions, responses from device simulations, Python syntax, or foundry PDK elements. pSim supports co-simulation with popular Spice simulators for electronic circuit simulation, and users can choose their preferred Spice simulator. pSim also supports importing S-parameters based on measurements.
Benefits of pSim
Accuracy: Bi-directional propagation naturally accounts for reflection, transmission, and multi-path interference.
Speed and Efficiency: Compact models enable fast simulation of complex linear and nonlinear PICs.
Flexibility and Ease of Use: Python co-simulation offers unlimited model expansion. PDK and layout tool interfaces simplify fabrication. pSim integration enables system-level PIC optimization. Hierarchical components allow scaling.
In summary, pSim provides a proven approach to efficiently simulate real-world PIC performance and behavior. pSim’s accuracy, flexibility, and scalability make it an indispensable tool for overcoming PIC complexity and enabling next-generation photonic innovation.
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