A fast Newton method for entropy maximization in statistical phase estimation

A fast Newton method is presented for solving the entropy maximization problem in the Bayesian statistical approach to phase estimation. The method requires only instead of standard floating point operations per iteration, while converging in the same rate as the standard Newton method. The method is described and related computational issues are discussed. Numerical results on simple test cases are also presented to demonstrate the behavior of the method.