https://github.com/ace-tn/ace-tn
Library for GPU-accelerated simulation of infinite projected entangled-pair states (iPEPS)
https://github.com/ace-tn/ace-tn
ctmrg ipeps quantum simulation tensor-network
Last synced: 7 days ago
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Library for GPU-accelerated simulation of infinite projected entangled-pair states (iPEPS)
- Host: GitHub
- URL: https://github.com/ace-tn/ace-tn
- Owner: ace-tn
- License: apache-2.0
- Created: 2025-03-14T23:29:40.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2026-01-15T22:15:48.000Z (8 days ago)
- Last Synced: 2026-01-16T01:49:32.754Z (8 days ago)
- Topics: ctmrg, ipeps, quantum, simulation, tensor-network
- Language: Python
- Homepage: https://ace-tn.github.io/ace-tn/
- Size: 6.55 MB
- Stars: 10
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 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](https://arxiv.org/abs/2503.13900).
## Getting Started
### Installation
To install Ace-TN, use:
```bash
pip install acetn
```
### Quickstart
After installation, a simple example calculation can be run by using `python3 script.py` for the following `script.py`:
```bash
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](https://ace-tn.github.io/ace-tn/) 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.