dc-qiskit-algorithms 0.0.14

Features

• Multi Qubit Quantum Fourier Transform

• Draper adder

• Uniform Rotations

• State Preparation

Installation

This library requires Python version 3.5 and above, as well as qiskit. Installation of this plugin, as well as all dependencies, can be done using pip:

$ python -m pip install dc_qiskit_algorithms

To test that the algorithms are working correctly you can run

$ make test

Getting started

You can use the state preparation as follows

from dc_qiskit_algorithms.MöttönenStatePrep import state_prep_möttönen

vector = [-0.1, 0.2, -0.3, 0.4, -0.5, 0.6, -0.7, 0.8]
vector = numpy.asarray(vector)
vector = (1 / numpy.linalg.norm(vector)) * vector

qubits = int(numpy.log2(len(vector)))
reg = QuantumRegister(qubits, "reg")
c = ClassicalRegister(qubits, "c")
qc = QuantumCircuit(reg, c, name='state prep')
state_prep_möttönen(qc, vector, reg)

After this, the quantum circuit is prepared in the given state. All complex vectors are possible!

Please refer to the documentation of the dc qiskit algorithm Plugin .

Contributing

We welcome contributions - simply fork the repository of this plugin, and then make a pull request containing your contribution. All contributers to this plugin will be listed as authors on the releases.

We also encourage bug reports, suggestions for new features and enhancements, and even links to cool projects or applications built on PennyLane.

Authors

Carsten Blank

Support

• Source Code: https://github.com/carstenblank/qiskit-algorithms

• Issue Tracker: https://github.com/carstenblank/qiskit_algorithms/issues

If you are having issues, please let us know by posting the issue on our Github issue tracker.

License

The data cybernetics qiskit algorithms plugin is free and open source, released under the Apache License, Version 2.0.