Classical and quantum regression analysis for the optoelectronic performance of NTCDA/p-Si UV photodiode

This paper details the performance of a fabricated Au/NTCDA/p-Si/Al photodiode. We evaluate three classical algorithms (KNN, ANN, GP) and a Quantum Neural Network (QNN) to predict the behavior of the fabricated device. The Continuous-Variable (CV) QNN, utilizing only one Qumode, was employed for the first time to model the photodiode performance, yielding acceptable results with the lowest parameter set.