Application of Quantum Information Processing Algorithms to Advanced Reactor Informatics

We are investigating application of quantum information (QI) algorithms to communication and data analytics of advanced nuclear reactors (ARs). The AR's, which are currently under development as part of energy de-carbonization initiative, are intended as highly automated replacements to existing fleet of aging nuclear reactors. Integration of QI into AR control and monitoring systems is one potentially promising approach to achieving AR autonomous operation. The first part of this work explores quantum key distribution (QKD) for secure wireless communications with a nuclear facility. This is investigated through computer simulations with SeQUeNCe (Simulator of QUantum Network Communication) software package developed for modeling of quantum networks. The second part of this work involves investigating performance of Quantum Principal Component Analysis (Q-PCA), using data sets from a thermal hydraulic flow loop, which are relevant to nuclear facility operation. Classical PCA is a frequently used unsupervised machine learning algorithm for data dimensionality reduction and analysis. Performance of Q-PCA, which is implemented using IBM Qiskit software package, is benchmarked relative to that of classical PCA.