Symmetry-tailored and parallel-readout variants of adaptive quantum gradient estimation cut the state-preparation query count for fermionic k-RDM estimation, giving a quadratic speedup over prior QGE methods at fixed particle number.
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Faster Quantum Algorithm for Multiple Observables Estimation in Fermionic Problems
Symmetry-tailored and parallel-readout variants of adaptive quantum gradient estimation cut the state-preparation query count for fermionic k-RDM estimation, giving a quadratic speedup over prior QGE methods at fixed particle number.