PathWave device modeling (IC-CAP) Software

Keysight EDA 2026 for Device Modeling

Elevate your design intelligence with Python automation and AI / ML. MBP 2026 includes a new Machine Learning Toolkit and Python automation framework to assist engineers in creating fully automated flow runs in a few minutes instead of hours for the typical manual corner tweaking process. IC-CAP 2025 integrates AI technology to significantly enhance the automation and accuracy of device modeling extraction, reducing flow complexity and improving consistency.

Highlights

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IC-CAP 2025

Highlights:

  • New Keysight ML Optimizer - enables AI for device modeling
  • New Model Generator QA - facilitate Model QA during the extraction
  • New Model Generator Utility tools - easily create Suites and Model Templates
  • Model Generator examples BSIM-BULK, BSIM-CMG and BSIM4
  • Enhanced CMC GaN RF packages – now includes ASM-HEMT ANN Hybrid model
  • Python 3.12 upgrade - new packages available
  • Support for new OS: RHEL8, RHEL9, and SUSE 15

The new ML Optimizer is part of the existing W7010E IC-CAP Analysis, and the W7008E Model Generator Advanced Tools add-on now includes the Model Generator QA and Model Re-centering. 

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Machine-Learning-Based-Automatic-Parameter-Extraction

SPICE Model Verification in IC-CAP Model Generator

Self-heating and trapping enhancements in GaN HEMT models

Model Generator Re-Centering Tool in IC-CAP

IC-CAP 2025 integrates AI technology to enhance the automation and accuracy of device modeling extraction significantly. The new Keysight Machine Learning (ML) Optimizer successfully extracts numerous parameters from extensive data, reducing flow complexity and improving consistency. Additionally, new features such as the Model Generator QA and the Utilities Toolkit facilitate the management and organization of modeling extraction projects. The IC-CAP Model Generator framework streamlines data import, organization, and filtering and adds parameter extraction steps with tuners/optimizers or Python scripts.

IC-CAP Model Recentering

IC-CAP Demo Videos

Model Builder Pro 2026

MBP 2026 includes the following new features and major enhancements:

  • New Machine Learning Toolkit
    • Machine Learning(ML) optimizer
    • Example auto-extraction flows: BSIM4, Gummel-Poon
    • Python APIs and Related Utilities: Parameter range analysis
  • Library support enhancements
  • Python API/MBP Script enhancements
  • MBP GUI enhancements
  • BSIM-CMG 112.0 support

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Accelerating Compact Model Parameter Extraction with the Machine-Learning Optimizer

MQA

Model Quality Assurance 2026

MQA 2026 includes the following new features and major enhancements:

  • New Aging Model QA Rule
  • Supports OMI Model QA
  • Supports the new rule of MOSRA analysis
  • Upgraded BSIM-CMG default rule
  • Enhanced the MQA plot data table to highlight the errors

WaferPro 2025

Highlights:

  • Python 3.12.11
  • WaferPro/A-LFNA Remote Control
  • Support for the latest E4727B A-LFNA 1/f Noise System software (A-LFNA 2026)
  • New instrument drivers for Keysight PZ2100A Precision SMU, NA520xA PNA-X Pro, E5080B ENA, E5081A ENA-X, and Streamline Series VNA
  • MPI driver now supports MPI's fully automated probers and thermal chucks
  • Compressed HDF5 file saving

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Remote Controlling E4727B for Automated LF Noise Measurements

Advanced Low-Frequency Noise Analyzer (A-LFNA) 2026

Highlights:

  • External software can now control A-LFNA using the new WaferPro/A-LFNA Remote-Control Python or C++ APIs. This includes cross-platform control from a LINUX system.
  • Support for Stress Bias Test for FET
  • Dramatic reduction in time to process and display large-size RTNoise data
  • Support for User Parameter's x-axis for Overlay>Analysis plot
  • Vth, delta-Vth, and delta-Id plot for FET RTNoise are now supported
  • Added factor for Theoretical Thermal Noise of FET, 4 kT gm * Factor

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How to Determine the Low-Frequency Noise Source in Cryogenic Operation

Remote Controlling E4727B for Automated LF Noise Measurements

LF Noise Measurement  Before and After Stress Biasing with E4727B

Device Modeling and Characterization Software and Hardware

Featured Resources

White Papers 2025.12.16

Accelerating Semiconductor Innovation through Machine Learning-Driven Modeling

This white paper highlights how AI and ML revolutionize semiconductor device modeling and parameter extraction. It introduces neural network-based and hybrid approaches, ML-driven workflows, and benchmarks that demonstrate faster, more accurate, and scalable modeling—enabling quicker PDK delivery, improved DTCO, and competitive advantage in advanced semiconductor design.

2025.12.16

Application Notes 2025.10.30

Remote Controlling E4727B for Automated LF Noise Measurements

In this application note, we measure LF noise on several NMOS devices remotely with different measurement groups using A-LFNA remote control and carry out data post-processing on a local computer.

2025.10.30

Application Notes 2025.10.21

LF Noise Measurement Before and After Stress Biasing with E4727B

Application of the low-frequency noise measurement system (Keysight E4727B) for the stress biasing and aging test.

2025.10.21

Application Notes 2025.08.28

Hybrid ANN Approach for Enhanced Device Modeling Accuracy

This application note helps users understand the advantages of using hybrid ANN to improve modeling accuracy in a short time, and demonstrates how to apply this approach with the IC-CAP ANN Toolkit.

2025.08.28

Application Notes 2025.11.12

Accelerating Compact Model Parameter Extraction with the Machine Learning Optimizer

This application note introduces the Machine Learning (ML) Optimizer in Device Modeling MBP 2026, a next-generation optimization tool that simplifies and automates compact model parameter extraction.

2025.11.12

Application Notes 2024.09.27

Machine Learning-Based Automatic Parameter Extraction

The new ML optimizer in IC-CAP can enhance device modeling efficiency and boost productivity, reducing the time required from days to hours. The robust device modeling capability is demonstrated through the use case of model re-centering and BSIM4 modeling. With the Model Generator, users can seamlessly import target data and create scaling plots for tuning or optimization. The new ML optimizer enables fully automatic parameter extraction by simply selecting the desired targets for adjustment and choosing the associated model parameters in a single step, as opposed to a series of optimizations with the old optimizers. This results in a substantial enhancement of modeling efficiency within a short timeframe.

2024.09.27

Brochures 2025.10.09

Keysight EDA Solutions for Semiconductor Foundries

In this brochure, we explore the critical factors foundries must consider at each stage of the device modeling and PDK development flow. By showcasing Keysight EDA's comprehensive solutions, we demonstrate how it becomes a key enabler in driving the evolution of ICs beyond Moore’s Law.

2025.10.09

Application Notes 2024.09.25

SPICE Model Verification in IC-CAP Model Generator

IC-CAP Model Generator QA provides a new tool for quick simulation QA on Model Generator. It allows you to extend simulation conditions, compare with two simulators, and automatically generate reports. This application note introduces the usefulness of those features.

2024.09.25

Case Studies 2024.04.09

Determined the Low-Frequency Noise Source in Cryogenic Operation

Japan's National Institute of Advanced Industrial Science and Technology (AIST) successfully the measurements of random telegraph noise (RTN) in short-channel MOSFETs at cryogenic temperatures using the Keysight E4727B Advanced Low-Frequency Noise Analyzer is expanding the understanding of noise sources in quantum computing, paving the way for faster machines moving forward.

2024.04.09

Application Notes 2024.01.31

Model Generator Re-Centering Tool in IC-CAP

This is an application note for the new IC-CAP feature: Recentering Tool

2024.01.31

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