附加模块
Luceda Circuit Analyzer
Gain deeper insights into your designs with Luceda Circuit Analyzer. Leverage advanced circuit analysis capabilities to assess circuit performance under real-world conditions, evaluate design tolerances, and estimate yield.
About this module
The Luceda Circuit Analyzer is a powerful module, offering advanced tools for analyzing photonic integrated circuits (PICs) and optimizing designs to improve yield and reliability. Luceda Circuit Analyzer provides advanced circuit analysis methodologies:
- Tracer Analysis
- Corner Analysis
- Monte Carlo Analysis
- Layout-aware Monte Carlo Analysis
PIC designer benefits
- Simulate the effect of process and environmental variations on your designs.
- Understand the critical process parameters.
- Identify critical components in the design.
- Make more yield estimations.
- Optimize your design layout considering spatial correlations of the variation on individual components.
Discover Luceda Circuit Analyzer Features
PIC Tracer Analysis
With Tracer Analysis, you can track the propagation of light through the circuit in a layout view. This feature helps you identify critical components in the design and develop a more intuitive understanding of how the PIC works.
Corner Analysis
Corner Analysis enables you to define process and design corners to evaluate circuit performance under a discrete set of varying conditions. You can start with your own set of assumptions based on your measurement outcomes or use foundry-provided specifications to perform worst-case and best-case design simulations.
Monte Carlo Analysis
Monte Carlo Analysis enables you to quantify the distribution of circuit-level figures of merit based on statistical behavioral models of individual components.
- Precisely define component specifications based on circuit-level yield requirements.
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Accurately q
uantified yield predictions using validated statistical component models from foundries.
Layout-Aware Variability Analysis
Layout-Aware Variability Analysis allows you to take into account spatial correlation of the variation of individual based on wafer maps. This approach provides more precise yield predictions and enables layout optimizations to reduce variation, improving overall performance.
