TensorCircuit Documentation#


Welcome and congratulations! You have found TensorCircuit. 👏


TensorCircuit is an open-source high-performance quantum computing software framework in Python.

  • It is built for humans. 👽

  • It is designed for speed, flexibility and elegance. 🚀

  • It is empowered by advanced tensor network simulator engine. 🔋

  • It is ready for quantum hardware access with CPU/GPU/QPU (local/cloud) hybrid solutions. 🖥

  • It is implemented with industry-standard machine learning frameworks: TensorFlow, JAX, and PyTorch. 🤖

  • It is compatible with machine learning engineering paradigms: automatic differentiation, just-in-time compilation, vectorized parallelism and GPU acceleration. 🛠

With the help of TensorCircuit, now get ready to efficiently and elegantly solve interesting and challenging quantum computing problems: from academic research prototype to industry application deployment.

Unified Quantum Programming#

TensorCircuit is unifying infrastructures and interfaces for quantum computing.

Unified Backends


Unified Devices


Unified Providers

QPUs from different vendors

Unified Resources


Unified Interfaces

numerical sim/hardware exp

Unified Engines

ideal/noisy/approximate simulation

Unified Representations


Unified Pipelines

stateless functional programming/stateful ML models

Reference Documentation#

The following documentation sections briefly introduce TensorCircuit to the users and developpers.


The following documentation sections include integrated examples in the form of Jupyter Notebook.

API References#

Indices and Tables#