The convergence of gradient descent, GPUs, and Python has revolutionized the field of artificial intelligence, and now, these same technologies are opening new frontiers in photonics. GPUs boost electromagnetic simulation speed by a factor of 100, adjoint-based gradient descent enables efficient exploration of the design space, and Python can automate complex workflows. When combined, they unlock unprecedented potential for accelerating photonic innovation.
This seminar will introduce new developments in Tidy3D, the next-generation photonic optimization tool designed to be the "PyTorch" of the photonics world. We will showcase the magic of automated design by demonstrating how to perform adjoint optimization with just a few lines of code on any Tidy3D simulation. Tidy3D empowers you to push the boundaries of possibility—whether working on ultra-large or long-duration simulations for 2D materials, topological photonics, interconnect circuits, or Lidar chips
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