Quantum Machine Learning is an emerging field of research which tries to combine the two cutting edge research areas of twenty first century, Machine Learning and Quantum Computation. Machine learning refers to those approaches in which the machine learns itself from its experiences and makes predictions upon entirely new similar surroundings. Quantum computation and quantum information science utilizes the soul of quantum mechanics like principle of superposition of quantum states and quantum entanglement to achieve immense computational speedup that overthrow classical computers. Several classical machine learning techniques such as k-means clustering, neural networks have being transcribed to quantum language. The research is at its premature state. Here we have studied the centroid distance based supervised cluster assignment algorithm on number of data sets. We have implemented those algorithm on IBMQ quantum computer using QISKIT-SDK python. We used the real device backend IBMQX4 with five qubits. Further an approach have been carried out to cast the basic Rosenblat's Neuron structure to the quantum neuron.
Quantum Bit (Qubit)
A bit is the most fundamental unit of information in classical computation which a classical computer can manipulate. Quantum computers works on Quantum Bits or shortly qubits. A classical bit can exist in well defined states either zero(0) or one(1), whereas a qubit can exist in superposition of states $\Ket{0}$ and $\Ket{1}$. Any real quantum system having two distinct states can be used to realize a qubit. The challenge of quantum computation is on achieving the transitions between these states in a controlled manner. Because perfectly isolated systems only exists in textbooks and every real system is interacting with its surroundings.
Mathematically a two dimensional Hilbert space can be used to represent the state of a qubit. Any two orthonormal eigenstate say $\Ket{0}$ and $\Ket{1}$ can be chosen as the basis vectors for describing the state, and the generic state of any qubit can be written as,
$\ket{\psi} = \alpha \ket{0} + \beta \ket{1} $
where $\alpha$ and $\beta$ are complex numbers and they are constrained by the normalization condition
{$|\alpha|}^2 + {|\beta|}^2 = 1$
If we perform a measurement on state of a qubit in the computational basis, we get state $\Ket{0}$ with probability $|\alpha|^2$ and $\Ket{1}$ with probability $|\beta|^2$. Once we perform the measurement the system collapses to either $\Ket{0}$ or $\Ket{1}$. Thus an infinitely many number of measurements on identically prepared systems are required to find out $\alpha$ and $\beta$.
The Bloch sphere representation of state of a qubit
It is much more helpful in thinking about qubits through Bloch sphere representation since it provides a geometric picture of the qubit and of the transformations carried out on them.
The generic state of a qubit can be rewritten in Bloch sphere notation,
