Phase estimation with randomized Hamiltonians

Understand

Iterative phase estimation has long been used in quantum computing to estimate Hamiltonian eigenvalues.

• This is done by applying many repetitions of the same fundamental simulation circuit to an initial state, and using statistical inference to glean estimates of the eigenvalues from the resulting data.
• Here, we show a generalization of this framework where each of the steps in the simulation uses a different Hamiltonian.
• This allows the precision of the Hamiltonian to be changed as the phase estimation precision increases.