Ace-TN: Simple and Efficient iPEPS Simulation
About
Ace-TN is an efficient and easy-to-use library for simulating infinite projected entangled-pair states (iPEPS) using the corner-transfer matrix renormalization group (CTMRG) method.
- GPU Acceleration: Supports GPU computations, offering a significant performance boost for larger and more complex iPEPS simulations.
- Multi-GPU Support: Can utilize multiple GPUs, allowing users to scale calculations to the largest possible system sizes.
- Flexible and Easy to Use: Easy and straightforward API, providing easy management of tensors and flexible model Hamiltonian construction.
See our preprint at https://arxiv.org/abs/2503.13900.
Getting Started
Installation
To install Ace-TN, use:
pip install acetn
Quickstart
After installation, a simple example calculation can be run by using python3 script.py for the following script.py:
from acetn.ipeps import Ipeps
# Set simulation options in the config
config = {
"TN":{
"nx": 2,
"ny": 2,
"dims": {"phys": 2, "bond": 2, "chi": 20},
},
"model":{
"name": "heisenberg",
"params": {"J": 1.0},
},
}
# Initialize an iPEPS
ipeps = Ipeps(config)
# Perform imaginary-time evolution steps
ipeps.evolve(dtau=0.01, steps=100)
# Measure observables
measurements = ipeps.measure()
For more details on usage, see the project documentation or try some of the example scripts in the samples directory.
Multi-GPU Usage
Run a script script.py in multi-GPU mode using N processes and N GPUs with
torchrun --nproc_per_node=N script.py
Citing
If you found Ace-TN useful for your research, please cite:
@misc{AceTN_2025,
title={Ace-TN: GPU-Accelerated Corner-Transfer-Matrix Renormalization of Infinite Projected Entangled-Pair States},
author={Addison D. S. Richards and Erik S. Sørensen},
year={2025},
eprint={2503.13900},
archivePrefix={arXiv},
primaryClass={cond-mat.str-el},
url={https://arxiv.org/abs/2503.13900},
}
License
Ace-TN is licensed under the Apache-2.0 License. See the LICENSE file for more details.
Metadata
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