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We propose genetic algorithms, which are robust optimization techniques inspired by natural selection, to enhance the versatility of digital quantum simulations.
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Cited in the paper.
Notice that a global phase in the unitary W j W_{j} does not affect the evolution but it affects the value of R j R_{j} , so we should consider inf ϕ ‖ U j − e i ϕ W j ‖ \inf_{\phi}||U_{j}-e^{i\phi}W_{j}|| . As we normally have access to the initial state of the evolution, the evaluation function R j = | ⟨ Ψ | U j † W j | Ψ ⟩ | 2 R_{j}=|\langle\Psi|U_{j}^{\dagger}W_{j}|\Psi\rangle|^{2} , in which the global phase is irrelevant, can be chosen
Cited in the paper.
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