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Software framework for experimenting with Operator Learning Renormalization Group (OLRG)

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Teal

A Python Package for Operator Learning Renromalization Group.

Warning: This package is currently at its early stages of development. It is not yet ready for serious use. All the APIs are subject to change. No unit tests are available yet. However the implementation has been tested in private projects and is expected to work.

This package contains the implementation for paper Operator Learning Renormalization Group, arXiv:2403.03199 as paper-v1 release.

Installation

This package is currently at its early stages of development. Thus it is not yet available on PyPI. We use rye for package management. To install it from source, clone the repository and run:

rye sync

To setup CUDA environment, please refer to jax documents.

Examples

Running HEM example

python examples/hem.py --wandb=False\
  --n-iterations=5000\
  --ham=TFIM\
  --n-start=2\
  --n-final=6\
  --enlarge-by=1\
  --final-time=0.1\
  --order=2\
  --n-batch=1\
  --depth=4\
  --width=4\
  --order-factor=one\
  --n-samples=20

Running OMM example

Warning: This may require a GPU to run.

python examples/omm.py --wandb=False --n-iterations=5000 --ham=TFIM --n-start=4 --n-final=10 --enlarge-by=1 --final-time=0.1 --order=2 --n-batch=5 --depth=8 --order-factor=one --n-samples=20

License

Apache License 2.0

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Software framework for experimenting with Operator Learning Renormalization Group (OLRG)

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