Classifying quantum states based on Bayesian approach

Quantum computing mainly deals with the interaction and manipulation of the most fundamental parts of matter, namely the atom, in order to aid the computations and increase the parallelism and hence the efficiency. This paper mainly deals with classifying the states that the atom can possess and finds out an algorithm for the same using a Bayesian approach based on posterior probabilities. Even though this paper does not deal with a comprehensive treatment of skills and techniques required to design and implement a quantum computer, but it suggests a probability-based Bayesian approach for classifying the quantum states of an atom. The Bayes decision rule for minimum cost is used to classify the states.