Ensemble Engineering to Overcome Destructive Cancellation in Quantum Measurements
arXiv:2605.03729
The paper proposes engineering the sampling distribution of quantum ensembles directly into the prepared state to reduce destructive cancellation in expectation‑value measurements on NISQ devices, demonstrating the method with amplitude‑amplification and shallow circuits on up to 20 qubits.
Abstract
On noisy intermediate-scale quantum (NISQ) devices, expectation values of many observables are obtained through sampling-based approximations to trace-like quantities. A central limitation of this approach is destructive cancellation under near-uniform ensembles, which can render physically relevant signals effectively unresolvable. Here we show that this limitation is not simply statistical, but reflects a structural mismatch between ensemble weights and the operator-dependent sign structure of the measured correlator. We introduce a general framework for mitigating this effect through quantum ensemble engineering, in which the sampling distribution is encoded directly in the prepared quantum state. By reformulating correlators in a basis-resolved representation, we make the origin of cancellation explicit and derive strategies for aligning ensemble weights with operator structure. We realize this approach using two complementary circuit constructions: a Grover-type amplitude amplification protocol that provides a structure-aligned benchmark, and an oracle-free shallow circuit designed for near-term hardware constraints. Using the infinite-temperature correlation function as a representative setting, we combine noiseless numerical simulations with demonstrations on IBM Quantum hardware using circuits with up to 20 qubits, showing that engineered ensembles expose operator-resolved contributions that are strongly suppressed under uniform averaging. We identify a practical tradeoff between amplification strength and noise robustness, extend the framework to multi-qubit diagonal observables, and outline a path toward non-diagonal generalizations. These results position ensemble engineering as a new tool for improving measurement efficiency in near-term quantum algorithms.
22 pages, 13 figures