Quantum Regression Model for the Prediction of Surface Plasmon Resonance Sensor Behaviour

Abstract

In this paper, we made a pioneering effort for the first time to implement Quantum Neural Network regressor model to predict the sensing behavior of Surface plasmon resonance (SPR) sensor and compared the performance of the proposed model with two traditional algorithms namely Support Vector Regressor (SVR) and Artificial Neural Network (ANN) regressor. The proposed trained quantum regressor model is crucial and efficient enough as it could be used to predict the trend of the target value that is confinement loss of the SPR biosensor.