Quantum Computing Classification for Amino Acids Based on Photoacoustic Signals Features

Quantum computing technique is used to study the photoacoustic (PA) signals of amino acids. Amino acids are important molecules to make proteins for constructing all living things. The research searches the amino acid photoacoustic signal features by using wavelet signal processing, and then build a quantum circuit to predict the category of amino acids by using the loss function to optimize the feedback of the quantum circuit. In addition, the correlation among PA features, the electron-ion interaction pseudopotential (EIIP) values and Van der Waals volume (Vvdw) are observed.