Dresden 2026 – scientific programme

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QI: Fachverband Quanteninformation

QI 1: Quantum Computing and Algorithms I

QI 1.10: Talk

Monday, March 9, 2026, 12:15–12:30, BEY/0137

Adaptive, efficient and provable energy estimation on noisy intermediate-scale quantum computers — •Bruno Murta¹, Alexander Gresch², and Martin Kliesch¹ — ¹TUHH - Hamburg University of Technology — ²eleQtron GmbH

Estimating the energy of a prepared quantum state from measurements is a central subroutine in quantum simulation algorithms. In a noisy intermediate-scale quantum (NISQ) setting, this estimation must be carried out with shallow readout circuits. In this work, we introduce an energy estimation framework that both tightens theoretical guarantees and reduces the cost of measuring molecular and solid-state Hamiltonians on NISQ devices. Our protocol exploits empirical (co)variance information gathered during measurement collection to adapt the estimation to the specific state, interpolates between qubit-wise and global commutativity to provide a trade-off between circuit depth and shot efficiency, and is supported by rigorous error bounds. Numerical benchmarks on molecular and lattice models indicate that the resulting scheme achieves a significant suppression of shot noise for a fixed measurement budget, while keeping quantum resources compatible with current NISQ hardware.

Keywords: Quantum energy estimation; Noisy intermediate-scale quantum (NISQ) hardware; Quantum many-body simulation; Adaptive measurement protocols; Observable grouping strategies