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Quantum Computing made easy with PyTorch on CPU/GPU

Construct, simulate and train quantum circuit the same as constructing a normal PyTorch Model

Dynamic Computation Graph

Easily obtain the intermediate data and perform debugging.

Automatic Gradient Computation

Obtain gradients on circuit parameters with back-propagation

Gate & Pulse Level Support

Simulation support across different levels.

Batch Mode Processing

Simulating a batch of quantum circuit, fully leverage the parallel computing power on GPUs/CPUs

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All the operations are implemented with PyTorch native operations

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Build the quantum circuit model by specifcy the quantum gates in the __init__ function and then specify the circuit structure in the forward function

Partners

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