PennyLane-Qulacs Plugin




The PennyLane-Qulacs plugin integrates the Qulacs quantum computing framework with PennyLane’s quantum machine learning capabilities.

PennyLane is a cross-platform Python library for quantum machine learning, automatic differentiation, and optimization of hybrid quantum-classical computations.

Qulacs is a software library for quantum computing, written in C++ and with GPU support.

Once PennyLane-Qulacs is installed, the provided Qulacs devices can be accessed straight away in PennyLane, without the need to import any additional packages.


Currently, PennyLane-Qulacs provides one Qulacs device for PennyLane:


We ran a 100 executions of 4 layer quantum neural network strongly entangling layer and compared the runtimes between CPU and GPU.


To see the PennyLane-Qulacs plugin in action, you can use any of the qubit based demos from the PennyLane documentation, for example the tutorial on qubit rotation, and simply replace 'default.qubit' with the 'qulacs.simulator' device:

dev = qml.device('qulacs.simulator', wires=XXX)