TensorCircuit Next Generation =========================================================== .. image:: https://github.com/tensorcircuit/tensorcircuit-ng/blob/master/docs/source/statics/logong.png?raw=true :target: https://github.com/tensorcircuit/tensorcircuit-ng **Welcome and congratulations! You have found TensorCircuit: the Next Generation.** 👏 Introduction --------------- `TensorCircuit-NG `_ is an industrial-grade, open-source high-performance quantum software framework in Python. It is designed for researchers and engineers who demand **Speed, Flexibility, and Elegance**. .. grid:: 1 1 2 3 :gutter: 3 .. grid-item-card:: 🧬 Built for Humans :shadow: md Intuitive API that feels like natural quantum physics. Focus on your research, not the boilerplate. .. grid-item-card:: 🚀 Extreme Performance :shadow: md Achieve **10-100x GPU speedup**. Powered by JIT compilation and optimized tensor engines. .. grid-item-card:: 🤖 Deep ML Fusion :shadow: md Native integration with **JAX, TensorFlow, and PyTorch**. Seamlessly combine AD with quantum kernels. .. grid-item-card:: ⛓️ Advanced Engines :shadow: md State-of-the-art support for **Noisy, Analog, Approximate and Stabilizer** simulations. .. grid-item-card:: ☁️ Hardware Agnostic :shadow: md Run your code anywhere: from local CPUs to distributed GPUs/TPUs and **QPU providers** via a unified interface. .. grid-item-card:: 🛠 Industrial Strength :shadow: md Committed to stability and performance. **Long-term support** and proven by extensive research and industrial applications. .. important:: Please cite our published `whitepaper `_ when using TensorCircuit or TensorCircuit-NG in your research. The bibtex information is provided by ``tc.cite()``. .. note:: TensorCircuit-NG is the active continuation of TensorCircuit project. We recommend upgrading to TensorCircuit-NG for the latest features and improvements. You can upgrade by running the following command: ``pip uninstall tensorcircuit && pip install tensorcircuit-ng`` Get Started in Seconds ----------------------- Install with one line: .. code-block:: bash pip install tensorcircuit-ng Simulate your first circuit: .. code-block:: python import tensorcircuit as tc c = tc.Circuit(2) c.h(0) c.cnot(0, 1) print(c.state()) # Ideal Bell state: [0.707, 0, 0, 0.707] print(c.expectation_ps(z=[0, 1])) # ZZ expectation: 1.0 Useful Links -------------------- TensorCircuit is created and now maintained as `TensorCircuit-NG `_ by `Shi-Xin Zhang `_. The current core authors of TensorCircuit-NG are `Shi-Xin Zhang `_ and `Yu-Qin Chen `_. We also thank `contributions `_ from the open source community. If you have any further questions or collaboration ideas, please use the issue tracker or forum below, or send email to shixinzhang#iphy.ac.cn .. card-carousel:: 2 .. card:: Source code :link: https://github.com/tensorcircuit/tensorcircuit-ng :shadow: md GitHub .. card:: PyPI :link: https://pypi.org/project/tensorcircuit-ng :shadow: md ``pip install tensorcircuit-ng`` .. card:: Documentation :link: https://tensorcircuit-ng.readthedocs.io :shadow: md Readthedocs .. card:: Whitepaper :link: https://quantum-journal.org/papers/q-2023-02-02-912/ :shadow: md *Quantum* journal .. card:: Issue Tracker :link: https://github.com/tensorcircuit/tensorcircuit-ng/issues :shadow: md GitHub Issues .. card:: Forum :link: https://github.com/tensorcircuit/tensorcircuit-ng/discussions :shadow: md GitHub Discussions .. card:: DockerHub :link: https://hub.docker.com/repository/docker/tensorcircuit/tensorcircuit :shadow: md ``docker pull`` .. card:: Application :link: https://github.com/tensorcircuit/tensorcircuit-ng#research-and-applications :shadow: md Research using TC Unified Quantum Programming ------------------------------ TensorCircuit-NG is building the future of unified quantum computing infrastructures. .. grid:: 1 2 4 4 :margin: 0 :padding: 0 :gutter: 3 .. grid-item-card:: 🛠 Unified Backends :columns: 12 6 3 3 :shadow: md JAX, TensorFlow, PyTorch, Numpy, Cupy .. grid-item-card:: 💻 Unified Devices :columns: 12 6 3 3 :shadow: md CPU, GPU, and TPU support .. grid-item-card:: 🏛 Unified Providers :columns: 12 6 3 3 :shadow: md QPUs from major vendors .. grid-item-card:: 🌐 Unified Resources :columns: 12 6 3 3 :shadow: md Local, Cloud, and HPC environments .. grid:: 1 2 4 4 :margin: 0 :padding: 0 :gutter: 3 .. grid-item-card:: 🎛 Unified Interfaces :columns: 12 6 3 3 :shadow: md Numerical sim and hardware experiments .. grid-item-card:: ⚙️ Unified Engines :columns: 12 6 3 3 :shadow: md Ideal, Noisy, Analog, and Stabilizer .. grid-item-card:: 📝 Unified Representations :columns: 12 6 3 3 :shadow: md Qiskit, OpenQASM, Cirq, and IR .. grid-item-card:: 🧊 Unified Objects :columns: 12 6 3 3 :shadow: md Neural Nets, Tensor Nets, and Circuits Reference Documentation ---------------------------- The following documentation sections briefly introduce TensorCircuit-NG to the users and developpers. .. toctree:: :maxdepth: 2 quickstart.rst agentic.rst advance.rst faq.rst sharpbits.rst infras.rst contribution.rst Tutorials --------------------- The following documentation sections include integrated examples in the form of Jupyter Notebook. .. toctree-filt:: :maxdepth: 2 :zh:tutorial.rst :zh:whitepapertoc.rst :en:tutorial_cn.rst :en:whitepapertoc_cn.rst :en:textbooktoc.rst API References ======================= .. toctree:: :maxdepth: 2 modules.rst Indices and Tables ================== * :ref:`genindex` * :ref:`modindex` * :ref:`search` Join the Community ================== We are always looking for contributors and collaborators! * Check out our `GitHub Discussions `_ for questions and show-and-tell. * Report bugs or request features via `GitHub Issues `_. * Star the repository to stay updated! ⭐