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Welcome to the Ace-TN Documentation
===================================


.. sidebar::
   :class: sphinxsidebar

   .. image:: source/png/ace_tensors.png
      :alt: An image in a sidebar
      :width: 175px

Ace-TN is a framework for simulating infinite projected entangled-pair states (iPEPS) with a focus on
GPU acceleration. We follow a simple pythonic design philosophy with PyTorch tensors as the primary 
tensor-network building blocks, allowing users to quickly setup and manage iPEPS calculations on GPUs.

See our preprint at `https://arxiv.org/abs/2503.13900 <https://arxiv.org/abs/2503.13900>`_.

Features
--------

- Fast iPEPS ground-state calculations using GPUs.
- Flexible interface for custom model hamiltonian design.
- Modular and extensible design enabling quick integration of new iPEPS algorithms in a multi-GPU setting.

Code Example
-------------

The basic workflow of an iPEPS ground-state calculation with Ace-TN can be executed with

.. code-block:: python

    from acetn.ipeps import Ipeps
    ipeps = Ipeps(config)
    ipeps.evolve(dtau=0.01, steps=500)
    measurements = ipeps.measure()

Please see the `User Guide <source/user_guide.html>`_ for more info on usage and getting started.

Citation
--------
If you found Ace-TN useful for your research, please cite:

.. code-block::

   @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}, 
   }

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   :maxdepth: 1
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   source/user_guide
   source/modules