Asymptotically Optimal Adversarial Strategies for the Probability Estimation Framework

Entropy (Basel). 2023 Sep 2;25(9):1291. doi: 10.3390/e25091291.

Abstract

The probability estimation framework involves direct estimation of the probability of occurrences of outcomes conditioned on measurement settings and side information. It is a powerful tool for certifying randomness in quantum nonlocality experiments. In this paper, we present a self-contained proof of the asymptotic optimality of the method. Our approach refines earlier results to allow a better characterisation of optimal adversarial attacks on the protocol. We apply these results to the (2,2,2) Bell scenario, obtaining an analytic characterisation of the optimal adversarial attacks bound by no-signalling principles, while also demonstrating the asymptotic robustness of the PEF method to deviations from expected experimental behaviour. We also study extensions of the analysis to quantum-limited adversaries in the (2,2,2) Bell scenario and no-signalling adversaries in higher (n,m,k) Bell scenarios.

Keywords: Bell inequalities; asymptotic equipartition property; device-independent quantum random number generation; min-entropy; quantum nonlocality.