Efficient Bayesian phase estimation using mixed priors

Understand

We describe an efficient implementation of Bayesian quantum phase estimation in the presence of noise and multiple eigenstates.

• The main contribution of this work is the dynamic switching between different representations of the phase distributions, namely truncated Fourier series and normal distributions.
• The Fourier-series representation has the advantage of being exact in many cases, but suffers from increasing complexity with each update of the prior.
• This necessitates truncation of the series, which eventually causes the distribution to become unstable.