Gresch, AlexanderAlexanderGreschTepe, UğurUğurTepeKliesch, MartinMartinKliesch2025-09-022025-09-022025-08-12Journal of Chemical Theory and Computation 21 (15): 7352-7359 (2025)https://hdl.handle.net/11420/57204We consider the problem of estimating the energy of a quantum state preparation for a given Hamiltonian in Pauli decomposition. For various quantum algorithms, in particular, in the context of quantum chemistry, it is crucial to have energy estimates with error bounds, as captured by guarantees on the problem's sampling complexity. In particular, when limited to Pauli basis measurements, the smallest sampling complexity guarantee comes from a simple single-shot estimator via a straightforward argument based on Hoeffding's inequality. In this work, we construct an adaptive estimator using the state's actual variance. Technically, our estimation method is based on the empirical Bernstein stopping (EBS) algorithm and grouping schemes, and we provide a rigorous tail bound, which leverages the state's empirical variance. In a numerical benchmark of estimating ground-state energies of several Hamiltonians, we demonstrate that EBS consistently improves upon elementary readout guarantees up to 1 order of magnitude.en1549-9626Journal of chemical theory and computation20251573527359ACSTechnology::600: TechnologyReducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance informationJournal Article10.1021/acs.jctc.5c00370Journal Article