This is a Python tool which takes a unitary matrix and returns a quantum circuit implementing it as Q# code, Cirq circuit, or Qiskit circuit.
pip install quantum-decomp
>>> import numpy, quantum_decomp
>>> SWAP = numpy.array([[1,0,0,0],[0,0,1,0],[0,1,0,0], [0,0,0,1]])
>>> print(quantum_decomp.matrix_to_qsharp(SWAP, op_name='Swap'))
operation Swap (qs : Qubit[]) : Unit {
CNOT(qs[1], qs[0]);
CNOT(qs[0], qs[1]);
CNOT(qs[1], qs[0]);
}
>>> print(quantum_decomp.matrix_to_cirq_circuit(SWAP))
0: ───@───X───@───
│ │ │
1: ───X───@───X───
>>> print(quantum_decomp.matrix_to_qiskit_circuit(SWAP))
┌───┐ ┌───┐
q_0: ┤ X ├──■──┤ X ├
└─┬─┘┌─┴─┐└─┬─┘
q_1: ──■──┤ X ├──■──
└───┘
See example.ipynb for more examples and instructions how to use this tool.
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This tool was inspired by Microsoft Q# Coding Contest and was implemented as part of online course "Applications of Quantum Mechanics" at MIT.
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See this paper for detailed description of the algorithm and further references to papers with algorithms.
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Blog post about the tool.