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Methods of processing quantum data become more important as quantum computingdevices improve their quality towards fault tolerant universal quantumcomputers. These methods include discrimination and filtering of quantum statesgiven as an input to the device that may find numerous applications in quantuminformation technologies. In the present paper, we address a scheme of aclassification of input states, which is nondestructive and deterministic forcertain inputs, while probabilistic, in general case. This can be achieved byincorporating phase estimation algorithm into the hybrid quantum-classicalcomputation scheme, where quantum block is trained classically. We performproof-of-principle implementation of this idea using superconducting quantumprocessor of IBM Quantum Experience. Another aspect we are interested in is amitigation of errors occurring due to the quantum device imperfections. Weapply a series of heuristic tricks at the stage of classical postprocessing inorder to improve raw experimental data and to recognize patterns in them. Theseideas may find applications in other realization of hybrid quantum-classicalcomputations with noisy quantum machines.

Nondestructive classification of quantum states using an algorithmic quantum computer