qiskit is an open-source compilation framework capable of targeting various types of hardware and a high-performance quantum computer simulator with emulation capabilities, and various compiler plug-ins.
This library sports some useful algorithms for quantum computers using qiskit as a basis.
- Multi Qubit Quantum Fourier Transform
- Draper adder
- Uniform Rotations
- State Preparation
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_algorithmsTo test that the algorithms are working correctly you can run
$ make testYou can use the state preparation as follows
from dc_qiskit_algorithms.MottonenStatePrep 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 .
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.
Carsten Blank
- 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.
The data cybernetics qiskit algorithms plugin is free and open source, released under the Apache License, Version 2.0.