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unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ctmrg","ipeps","quantum","simulation","tensor-network"],"created_at":"2026-01-16T18:31:10.143Z","updated_at":"2026-01-16T18:31:10.234Z","avatar_url":"https://github.com/ace-tn.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Ace-TN: Simple and Efficient iPEPS Simulation\n## About\nAce-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.\n\n- **GPU Acceleration**: Supports GPU computations, offering a significant performance boost for larger and more complex iPEPS simulations.\n- **Multi-GPU Support**: Can utilize multiple GPUs, allowing users to scale calculations to the largest possible system sizes.\n- **Flexible and Easy to Use**: Easy and straightforward API, providing easy management of tensors and flexible model Hamiltonian construction.\n\nSee our preprint at [https://arxiv.org/abs/2503.13900](https://arxiv.org/abs/2503.13900).\n\n## Getting Started\n### Installation\nTo install Ace-TN, use:\n```bash\npip install acetn\n```\n### Quickstart\nAfter installation, a simple example calculation can be run by using `python3 script.py` for the following `script.py`:\n```bash\nfrom acetn.ipeps import Ipeps\n\n# Set simulation options in the config\nconfig = {\n    \"TN\":{\n        \"nx\": 2,\n        \"ny\": 2,\n        \"dims\": {\"phys\": 2, \"bond\": 2, \"chi\": 20},\n    },\n    \"model\":{\n        \"name\": \"heisenberg\",\n        \"params\": {\"J\": 1.0},\n    },\n}\n\n# Initialize an iPEPS\nipeps = Ipeps(config)\n\n# Perform imaginary-time evolution steps\nipeps.evolve(dtau=0.01, steps=100)\n\n# Measure observables\nmeasurements = ipeps.measure()\n```\nFor 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.\n\n## Multi-GPU Usage\nRun a script `script.py` in multi-GPU mode using `N` processes and `N` GPUs with\n```\ntorchrun --nproc_per_node=N script.py\n```\n\n## Citing\nIf you found Ace-TN useful for your research, please cite:\n```\n@misc{AceTN_2025,\n      title={Ace-TN: GPU-Accelerated Corner-Transfer-Matrix Renormalization of Infinite Projected Entangled-Pair States}, \n      author={Addison D. S. Richards and Erik S. Sørensen},\n      year={2025},\n      eprint={2503.13900},\n      archivePrefix={arXiv},\n      primaryClass={cond-mat.str-el},\n      url={https://arxiv.org/abs/2503.13900}, \n}\n```\n\n## License\nAce-TN is licensed under the Apache-2.0 License. See the `LICENSE` file for more details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Face-tn%2Face-tn","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Face-tn%2Face-tn","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Face-tn%2Face-tn/lists"}