Optimizing Measurements Sequences for Quantum State Verification

TL;DR

This paper investigates how the order of measurements affects the efficiency of quantum state verification and proposes strategies to optimize measurement sequences, significantly reducing the number of measurements needed.

Contribution

It introduces new algorithms for optimizing measurement sequences in quantum state verification, including adaptive methods that improve efficiency over traditional approaches.

Findings

Optimized measurement sequences reduce verification measurements.

Adaptive protocols outperform non-adaptive methods in faulty state assessment.

Numerical simulations demonstrate significant efficiency gains.

Abstract

We consider the problem of deciding whether a given state preparation, i.e., a source of quantum states, is accurate, namely produces states close to a target one within a prescribed threshold. We show that, when multiple measurements need to be used, the order of measurements is critical for quickly assessing accuracy. We propose and compare different strategies to compute optimal or suboptimal measurement sequences either relying solely on a priori information, i.e., the target state for state preparation, or actively adapting the sequence to the previously obtained measurements. Numerical simulations show that the proposed algorithms reduce significantly the number of measurements needed for verification, and indicate an advantage for the adaptive protocol especially assessing faulty preparations.