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Please predict whether this patent is acceptable.PATENT ABSTRACT: Quantum methods for Bayesian inference represent prior or current posterior distributions with a series of qubits. A rotation gate defined by a rotation angle based on the prior or current posterior is applied to a selected qubit of the series. The selected qubit is measured, and if measurement is successful, the state of the series of qubits represents a posterior or updated posterior. If the measurement is unsuccessful, the representation of the prior or current posterior in the series of qubits, the rotation operation, and the measurement operations are repeated until success. A sinc2 based model distribution is obtained using a quantum Fourier transform (QFT), and, in some cases, a QFT is also used to implement convolution in a filtering operation for inference with time-dependent systems.