Quantum Bayesian Inference: An Exploration

This paper introduces a framework for performing Bayesian inference using quantum computation. It presents a proof-of-concept quantum algorithm that performs posterior sampling. We provide an accessible introduction to quantum computation for economists and a practical demonstration of quantum-based posterior sampling for Bayesian estimation. Our key contribution is the preparation of a quantum state whose measurement yields samples from a discretized posterior distribution. While the proposed approach does not yet offer computational speedups over classical techniques such as Markov Chain Monte Carlo, it highlights both the conceptual promise and practical challenges in integrating quantum computation into the econometrician’s toolbox.