This package is a library for quantum computing that uses Qiskit Terra to build out, compile and run quantum circuits. It allows create quantum channels, easy move it through qubits and make tomography. Also, it has ui interface for quick change different backends.

For example, consider Hadamard transformation. Built the channel and make tomography (using mask you can place it on different qubit without channel code changing)

from qchannels.channels.abstract import AbstractChannelCircuit
from qchannels.core.manage_parameters import set_parameters
from qchannels.core.launcher import Launcher

import numpy as np


class Hadamard(AbstractChannelCircuit):
    REL_SYSTEM_QUBITS = [0]  # It is require only one qubit

    def create_circuit(self, q_regs, c_regs):
        self.h(q_regs[0])

    @staticmethod
    def get_theory_channel():
        H = np.array([[1, 1], [1, -1]]) / np.sqrt(2)
        return lambda rho: H@rho@H


parameters = set_parameters('Test Hadamard transformation')

mask = {0: 3}  # It's optional. It change a qubit in channel, more detail in AbstractChannelCircuit
channel = Hadamard(backend_name=parameters['backend_name'], mask=mask)
launcher = Launcher(token=parameters['token'], backend_name=parameters['backend_name'],
                    shots=parameters['shots'])
print(launcher.run(channel, meas_qubits=channel.system_qubits)[0])

You can execute this file and get density matrix:

$ python examples/hadamard.py
[[0.50073241+0.j         0.49999289-0.00256344j]
 [0.49999289+0.00256344j 0.49926759+0.j        ]]

In order to run it on real computer, you just have to put it in arguments

$ python examples/hadamard.py -b ibmqx4

More information about arguments:

$ python examples/hadamard.py --help

Also you can measure fidelity of the channel. Just add:

rho = launcher.run(channel, meas_qubits=channel.system_qubits)[0]
print(fidelity(rho, channel.get_theory_channel()(
    get_density_matrix_from_state(get_state(0, dim=2))
)))

Dependencies

At least Python 3.6 or later is needed

Setup your environment

We recommend using python virtual environments to improve your experience. Refer to our Environment Setup documentation for more information.

Installation

We encourage installing this package via the PIP tool (a python package manager):

pip install .

or

pip install package_directory/

Instructions

Add your IBM token to Qconfig.py.example, rename to Qconfig.py and move it to a directory with the executable file.