Systems and methods for quantum bayesian networks

This invention describes a method for using quantum computers to solve complex problems, particularly those represented as Bayesian networks, which are common in artificial intelligence. It works by converting these directed Bayesian networks into undirected Markov networks, which are better suited for the physical structure of current quantum processors. The quantum computer then processes this converted problem to find approximate solutions. The claims specifically detail methods for this conversion, such as 'moralization' or adapting the network to the quantum processor's physical layout.