Measuring peptide mass spectrum correlation using the quantum Grover algorithm

We investigated the use of the quantum Grover algorithm in the mass-spectrometry-based protein identification process. The approach coded the mass spectra on a quantum register and uses the Grover search algorithm for searching multiple solutions to find matches from a database. Measurement of the fidelity between the input and final states was used to quantify the similarity between the experimental and theoretical spectra. The optimal number of iteration is proven to be pi/4sqrt[N/k] , where k refers to the number of marked states. We found that one iteration is sufficient for the search if we let more that 62% of the N states be marked states. By measuring the fidelity after only one iteration of Grover search, we discovered that it resembles that of the correlation-based measurement used in the existing protein identification software. We concluded that the quantum Grover algorithm can be adapted for a correlation-based mass spectra database search, provided that decoherence can be kept to a minimum.