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01-modeling-and-emsolver.ipynb		01-modeling-and-emsolver.ipynb
02-autograd-and-optimization-jax.ipynb		02-autograd-and-optimization-jax.ipynb
02-autograd-and-optimization-pytorch.ipynb		02-autograd-and-optimization-pytorch.ipynb
03-device-and-datatype-jax.ipynb		03-device-and-datatype-jax.ipynb
03-device-and-datatype-torch.ipynb		03-device-and-datatype-torch.ipynb
README.md		README.md

README.md

Tutorials

Modeling and Electromagnetic simulation

Modeling and EMsolver
- modeling and Electromagnetic simulation(Meent uses RCWA).

Autograd and Optimization

Autograd and Optimization on JAX or Autograd and Optimization on PyTorch
- gradient and optimization with the help of Automatic Differentiation(a.k.a. backprop).
- separately written for JAX and PyTorch backends for user convenience.

Device and Precision

Device and Precision on JAX or Device and Precision on PyTorch
- setting device(CPU or GPU)
- setting precision(64bit or 32bit)
- separately written for JAX and PyTorch backends for user convenience.