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Department of Chemistry, University of Copenhagen, DK-2100 Copenhagen, Denmark.
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Quantum hardware can now directly compute nuclear gradients and Hessians, but the trade-offs in error mitigation reveal significant challenges for larger molecules.
HRPA(D) and SOPPA(CCSD) outperform traditional methods in accuracy while revealing that RPA excels for aromatic molecules due to its unique electronic excitation energy overestimation.
Exact Hamiltonian transformations can halve the computational cost of operator selection in fermionic ADAPT-VQE, making it nearly as efficient as gradient-based methods.