Quantum Inference Protocol : from origination to application - Ho, Matthew Shu Hui (Nanyang Technological University, 2021)
We are at the interface of two hot research areas – modelling of stochastic processes with causal models in quantitative science, and quantum simulation on real quantum devices. Classical causal models first made its appearance in 1989 with the aim of extracting a stochastic process’ underlying dynamics in order to do statistically faithful predictions. Research into causal models expanded into the quantum regime where it was shown that quantum models could outperform classical models; quantum models had equal predictive capabilities but had less memory requirement. This kickstarted the exploratory research into building more optimal quantum models with lower memory requirements. However, all quantum models required prior knowledge of classical causal models. Errors that occurred in classical models due to finite-length stochastic processes were automatically inherited by quantum models.