Automation API

Enables Lumerical tools to interact with each other, third-party applications, and a rich set of Python content

The Automation API, which is accessible via Python, enables users to perform powerful custom analyses, undertake enhanced optimization and visualization, produce publication-quality plots, and automate complex workflows​

Python-Driven Interoperability

  • Build, run, and control simulations across multiple Lumerical tools​, or interface Lumerical tools with third-party applications
  • Use a single file to run optical, thermal, and electrical simulations before post-processing the data in Python
  • Take advantage of the rich open-source projects available within the Python photonics community

Indispensable for the Photonics Python Community

Take advantage of the many benefits of using Python:​

  • Make use of an extensive set of Python libraries in the fields of numerical analysis, visualization, optimization and more
  • Leverage special, purpose built applications for photonic designers
  • Use the well-known Python language to build your own in-house integrations and applications

Automation Enables Inverse Design

Take advantage of Inverse Design, a new capability made possible via Lumerical’s Automation API:​

  • Based on an open-source implementation of the Adjoint Method​ packaged within FDTD Solutions, available on GitHub
  • Automatically discover optimal geometries for a desired target performance​

"[Lumerical] heard that I was developing this open source capability, they reached out to me, and were very supportive in providing their Python API, along with guidance and testing that hardened my open source PID implementation to be production-worthy” Christopher Lalau-Keraly, lumopt author

“For us, it is very important that the eventual tool flow of future photonic designers in enterprise companies is more reliable because all of the pieces having commercial-grade support, combined with the flexibility of Python support” Thomas Van Vaerenbergh, HPE

“We use Lumerical’s Python API in my edX silicon photonics course to have KLayout communicate with INTERCONNECT to perform PIC simulations, and with FDTD to simulate passive silicon photonic components and to create S-Parameter compact models to automatically populate a compact model library (SiEPIC-EBeam-PDK)” Prof. Lukas Chrostowski, University of British Columbia

"[Lumerical] heard that I was developing this open source capability, they reached out to me, and were very supportive in providing their Python API, along with guidance and testing that hardened my open source PID implementation to be production-worthy” Christopher Lalau-Keraly, lumopt author

“For us, it is very important that the eventual tool flow of future photonic designers in enterprise companies is more reliable because all of the pieces having commercial-grade support, combined with the flexibility of Python support” Thomas Van Vaerenbergh, HPE

“We use Lumerical’s Python API in my edX silicon photonics course to have KLayout communicate with INTERCONNECT to perform PIC simulations, and with FDTD to simulate passive silicon photonic components and to create S-Parameter compact models to automatically populate a compact model library (SiEPIC-EBeam-PDK)” Prof. Lukas Chrostowski, University of British Columbia

Video: Efficient Automation with Lumerical's Python API

The first resource for anyone looking for an understanding of using Python with the Automation API

Watch the video (requires Log-in)

Knowledge Base: Using Lumerical Tools with Python

Your guide for using the Automation API to drive Lumerical Simulations

Knowledge Base

Inverse Design of a Waveguide Crossing

Use the Automation API to explore Parametric Optimization

Application Gallery

Try the Automation API today!

Contact our experts