Quantum Pattern Recognition for Local Sequence Alignment

Abstract

Over the last two decades, there have been some challenging proposals on the field of pattern recognition by means of quantum technology. The application of them is considered for a popular branch of bioinformatics which analyzes massive amounts of sequence data for genes and proteins. More specific, the Smith-Waterman algorithm is studied under the more general term of local sequence alignment. The steps of this algorithm are totally reformed and powered by the quantum mechanics computing theory. The proposed method is based on R. Schützhold's pattern recognition quantum algorithm. A binary and unstructured data set is formed after the comparison of the sequences under alignment which is used by R. Schützhold's algorithm to identify and locate potential patterns. It is achieved with the aid of a spatial light modulator. The adopted quantum algorithm exhibits an exponential speed-up in comparison with its classical counterparts.